Futures Auto Levels [NariCapitalTrading]Futures Auto Levels Indicator
Introduction
The "Futures Auto Levels" (FAL) indicator shows the previous day's levels, weekly open, high, low, and the Initial Balance Range (IBR).
Indicator Components
The FAL indicator comprises the following components:
Previous Day's Levels: These include the open, high, low, and close of the previous trading day. They are represented on the chart by lines and labels, helping to identify significant price levels from the prior session.
Weekly Open, High, Low: These levels represent the open, high, and low prices of the current trading week.
Initial Balance Range (IBR): The IBR is calculated based on the price range during the first 60 minutes of the trading day. It helps identify initial trading range and potential breakout levels.
How to Use the Indicator
1. Previous Day's Levels:
Monitor the previous day's open, high, low, and close to identify key support and resistance levels.
Use these levels to gauge market sentiment and potential price reversals.
2. Weekly Open, High, Low:
Pay attention to the weekly open, high, and low to understand the market's behavior within the weekly timeframe.
These levels can act as reference points for setting profit targets and stop-loss orders.
3. Initial Balance Range (IBR):
Watch for price movements within the IBR to identify potential trading opportunities.
Breakouts above or below the IBR may signal the beginning of a new trend or continuation of the current trend.
Suggested/Potential Strategies
Reversal Trading: Look for price reversals around previous day's levels, especially when they coincide with other technical indicators or significant support/resistance zones.
Trend Following: Follow the trend by trading breakouts above/below the IBR or weekly high/low levels. Use trailing stops to capture profits while the trend remains intact.
Range Trading: Trade within the IBR when the market is consolidating. Buy near the IBR low and sell near the IBR high, with tight stop-loss orders to manage risk.
Conclusion
The Futures Auto Levels indicator is designed to help incorporate levels into trading analysis and trading strategies to improve profitability and consistency.
在腳本中搜尋"profit"
BlackPika Supertrend Public v2Hello Reader!
What is Supertrend indicator ?
The Supertrend Indicator is a popular technical analysis tool designed to assist traders in identifying market trends.
The indicator combines the average true range (ATR) with a multiplier to calculate its value. This value is then added to or subtracted from the asset’s closing price to plot the supertrend line.
The Supertrend Indicator can help identify trends, manage risk, and confirm market tendencies.
The indicator is limited by its lagging nature, is not very flexible, and can send up false signals.
The Supertrend Indicator has become a staple for traders in stocks, currencies, and commodities for its ability to identify and follow market trends.
About this script:
This script is based on the SuperTrend. There are some extra things added to make it able to use more efficiently. They are listed below:
1. Pullback signals: These signals indicate a pull back after a trend reversal and are the most optimum places where you can add to your existing position. They also come with Alerts !
2. Trailing Stop Loss and Take Profit: These further help to reduce the draw-down and can help you to trail profits with more granularity thus securing gains. This are using RSI levels. RSI levels above 70 will indicate a partial take profit when long and RSI levels below 25 will indicate a take profit level when short.
How to use ?
----------------
Personally I use it on major pairs on cryptocurrencies like BTCUSD . Usually after the trend flips, there will be pullbacks, You can enter a part of the position when trend reversal is confirmed. (LONG signal)
Then add more when you get a pullback (PB_LONG signal).
To make life simpler, alerts are added for pullback signals as well. These can help acheive good entry price. Entering at pullback signals limits your losses to a great extent, as the trend will flip on the bar close if it goes against you.
You can trade manually or you can automate. All the signals have been provided with Alerts. some signals have been grouped, to reduce the number of the alerts if you wish to.
I wish you all the luck and please comment and Like if you have any doubts.
Luxmi AI Filtered Option Scalping Signals (INDEX)Introduction:
Luxmi AI Filtered Option Scalping Signals (INDEX) is an enhanced iteration of the Luxmi AI Directional Option Buying (Long Only) indicator. It's designed for use on index charts alongside the Luxmi AI Smart Sentimeter (INDEX) indicator to enhance performance. This indicator aims to provide refined signals for option scalping strategies, optimizing trading decisions within index markets.
Understanding directional bias is crucial when trading index and index options because it helps traders align their strategies with the expected movement of the underlying index.
The Luxmi AI Filtered Option Scalping Signals (INDEX) indicator aims to simplify and expedite decision-making through comprehensive technical analysis of various data points on a chart. By leveraging advanced analysis of data points, this indicator scrutinizes multiple factors simultaneously to offer traders clear and rapid insights into market dynamics.
The indicator is specifically designed for option scalping, a trading strategy that aims to profit from short-term price fluctuations. It prioritizes signals that are conducive to quick execution and capitalizes on rapid market movements typical of scalping strategies.
Major Features:
Trend Cloud:
Working Principle:
The script utilizes the Relative Strength Index (RSI) to assess market momentum, identifying bullish and bearish phases based on RSI readings. It calculates two boolean variables, bullmove and bearmove, which signal shifts in momentum direction by considering changes in the Exponential Moving Average (EMA) of the closing price. When RSI indicates bullish momentum and the closing price's EMA exhibits positive changes, bullmove is triggered, signifying the start of a bullish phase. Conversely, when RSI suggests bearish momentum and the closing price's EMA shows negative changes, bearmove is activated, marking the beginning of a bearish phase. This systematic approach helps in understanding the current trend of the price. The script visually emphasizes these phases on the chart using plot shape markers, providing traders with clear indications of trend shifts.
Benefits of Using Trend Cloud:
Comprehensive Momentum Assessment: The script offers a holistic view of market momentum by incorporating RSI readings and changes in the closing price's EMA, enabling traders to identify both bullish and bearish phases effectively.
Structured Trend Recognition: With the calculation of boolean variables, the script provides a structured approach to recognizing shifts in momentum direction, enhancing traders' ability to interpret market dynamics.
Visual Clarity: Plotshape markers visually highlight the start and end of bullish and bearish phases on the chart, facilitating easy identification of trend shifts and helping traders to stay informed.
Prompt Response: Traders can promptly react to changing market conditions as the script triggers alerts when bullish or bearish phases begin, allowing them to seize potential trading opportunities swiftly.
Informed Decision-Making: By integrating various indicators and visual cues, the script enables traders to make well-informed decisions and adapt their strategies according to prevailing market sentiment, ultimately enhancing their trading performance.
How to use this feature:
The most effective way to maximize the benefits of this feature is to use it in conjunction with other key indicators and visual cues. By combining the color-coded clouds, which indicate bullish and bearish sentiment, with other features such as IS candles, microtrend candles, volume candles, and sentimeter candles, traders can gain a comprehensive understanding of market dynamics. For instance, aligning the color of the clouds with the trend direction indicated by IS candles, microtrend candles, and sentimeter candles can provide confirmation of trend strength or potential reversals.
Furthermore, traders can leverage the trend cloud as a trailing stop-loss tool for long entries, enhancing risk management strategies. By adjusting the stop-loss level based on the color of the cloud, traders can trail their positions to capture potential profits while minimizing losses. For long entries, maintaining the position as long as the cloud remains green can help traders stay aligned with the prevailing bullish sentiment. Conversely, a shift in color from green to red serves as a signal to exit the position, indicating a potential reversal in market sentiment and minimizing potential losses. This integration of the trend cloud as a trailing stop-loss mechanism adds an additional layer of risk management to trading strategies, increasing the likelihood of successful trades while reducing exposure to adverse market movements.
Moreover, the red cloud serves as an indicator of decay in option premiums and potential theta effect, particularly relevant for options traders. When the cloud turns red, it suggests a decline in option prices and an increase in theta decay, highlighting the importance of managing options positions accordingly. Traders may consider adjusting their options strategies, such as rolling positions or closing out contracts, to mitigate the impact of theta decay and preserve capital. By incorporating this insight into options pricing dynamics, traders can make more informed decisions about their options trades.
Scalping Cloud:
The scalping cloud serves as a specialized component within the trend cloud feature, specifically designed to pinpoint potential long and short entry points within the overarching trend cloud. Here's how it works:
Trend Identification: The trend cloud feature typically highlights the prevailing trend direction based on various technical indicators, price action, or other criteria. It visually represents the momentum and direction of the market over a given period.
Refined Entry Signals: Within this broader trend context, the scalping cloud narrows its focus to identify shorter-term trading opportunities. It does this by analyzing more granular price movements and shorter timeframes, seeking out potential entry points that align with the larger trend.
Long and Short Entries: The scalping cloud distinguishes between potential long (buy) and short (sell) entry opportunities within the trend cloud. For instance, within an uptrend indicated by the trend cloud, the scalping cloud might identify brief retracements or pullbacks as potential long entry points. Conversely, in a downtrend, it may signal short entry opportunities during temporary upward corrections.
Risk Management: By identifying potential entry points within the context of the trend, the scalping cloud also aids in risk management. Traders can use these signals to place stop-loss orders and manage their positions effectively, reducing the risk of adverse price movements.
The scalping cloud operates by analyzing the crossover and crossunder events between two key indicators: the Double Exponential Moving Average (DEMA) and a Weighted Average. Here's how it works:
Double Exponential Moving Average (DEMA): DEMA is a type of moving average that seeks to reduce lag by applying a double smoothing technique to price data. It responds more quickly to price changes compared to traditional moving averages, making it suitable for identifying short-term trends and potential trading opportunities.
Weighted Average: The weighted average calculates the average price of an asset over a specified period. However, it incorporates a weighting scheme that assigns more significance to recent price data, resulting in a more responsive indicator that closely tracks current market trends.
CE and NO CE Signals:
CE signals typically represent a Long Scalping Opportunity, suggesting that conditions are favorable for entering a long position. These signals indicate a strong upward momentum in the market, which traders can exploit for short-term gains through scalping strategies.
On the other hand, when there are no CE signals present, it doesn't necessarily mean that the trend has reversed or turned bearish. Instead, it indicates that the trend is still bullish, but the market is experiencing an active pullback. During a pullback, prices may temporarily retreat from recent highs as traders take profits or reevaluate their positions. While the overall trend remains upward, the pullback introduces a degree of uncertainty, making it less favorable for entering new long positions.
In such a scenario, traders may opt to exercise caution and refrain from entering new long positions until the pullback phase has concluded. Instead, they might consider waiting for confirmation signals, such as the resumption of CE signals or other bullish indications, before reengaging in long positions.
PE and NO PE Signals:
PE signals typically indicate a Short Entry opportunity, signaling that market conditions are conducive to entering a short position.
Conversely, when there are no PE signals present, it signifies that while the trend remains bearish, the market is currently in an active phase of consolidation or pullback. During such periods, prices may temporarily rise from recent lows, reflecting a pause in the downward momentum. While the overall trend remains downward, the absence of PE signals suggests that it may not be an optimal time to enter new short positions.
In this context, traders may exercise caution and wait for clearer signals before initiating new short positions. They might monitor the market closely for signs of a resumption in bearish momentum, such as the emergence of PE signals or other bearish indications. Alternatively, traders may choose to wait on the sidelines until market conditions stabilize or provide clearer directional signals.
Working Principle Of CE and PE Signals:
The feature calculates candlestick values based on the open, high, low, and close prices of each bar. By comparing these derived candlestick values, it determines whether the current candlestick is bullish or bearish. Additionally, it signals when there is a change in the color (bullish or bearish) of the derived candlesticks compared to the previous bar, enabling traders to identify potential shifts in market sentiment.
Micro Trend Candles:
Working Principle:
This feature begins by initializing variables to determine trend channel width and track price movements. Average True Range (ATR) is then calculated to measure market volatility, influencing the channel's size. Highs and lows are identified within a specified range, and trends are assessed based on price breaches, with potential changes signaled accordingly. The price channel is continually updated to adapt to market shifts, and arrows are placed to indicate potential entry points. Colors are assigned to represent bullish and bearish trends, dynamically adjusting based on current market conditions. Finally, candles on the chart are colored to visually depict the identified micro trend, offering traders an intuitive way to interpret market sentiment and potential entry opportunities.
Benefits of using Micro Trend Candles:
Traders can use these identified micro trends to spot potential short-term trading opportunities. For example:
Trend Following: Traders may decide to enter trades aligned with the prevailing micro trend. If the candles are consistently colored in a certain direction, traders may consider entering positions in that direction.
Reversals: Conversely, if the script signals a potential reversal by changing the candle colors, traders may anticipate trend reversals and adjust their trading strategies accordingly. For instance, they might close existing positions or enter new positions in anticipation of a trend reversal.
It's important to note that these micro trends are short-term in nature and may not always align with broader market trends. Therefore, traders utilizing this script should consider their trading timeframes and adjust their strategies accordingly.
How to use this feature:
This feature assigns colors to candles to represent bullish and bearish trends, with adjustments made based on current market conditions. Green candles accompanied by a green trend cloud signal a potential long entry, while red candles suggest caution, indicating a bearish trend. This visual representation allows traders to interpret market sentiment intuitively, identifying optimal entry points and exercising caution during potential downtrends.
Scalping Candles (Inspired by Elliott Wave and Open Interest Concepts):
Working Principle:
This feature draws inspiration from the Elliot Wave method, utilizing technical analysis techniques to discern potential market trends and sentiment shifts. It begins by calculating the variance between two Exponential Moving Averages (EMAs) of closing prices, mimicking Elliot Wave's focus on wave and trend analysis. The shorter-term EMA captures immediate price momentum, while the longer-term EMA reflects broader market trends. A smoother Exponential Moving Average (EMA) line, derived from the difference between these EMAs, aids in identifying short-term trend shifts or momentum reversals.
Benefits of using Scalping Candles Inspired by Elliott Wave:
The Elliott Wave principle is a form of technical analysis that attempts to predict future price movements by identifying patterns in market charts. It suggests that markets move in repetitive waves or cycles, and traders can potentially profit by recognizing these patterns.
While this script does not explicitly analyze Elliot Wave patterns, it is inspired by the principle's emphasis on trend analysis and market sentiment. By calculating and visualizing the difference between EMAs and assigning colors to candles based on this analysis, the script aims to provide traders with insights into potential market sentiment shifts, which can align with the broader philosophy of Elliott Wave analysis.
How to use this feature:
Candlestick colors are assigned based on the relationship between the EMA line and the variance. When the variance is below or equal to the EMA line, candles are colored red, suggesting a bearish sentiment. Conversely, when the variance is above the EMA line, candles are tinted green, indicating a bullish outlook. Though not explicitly analyzing Elliot Wave patterns, the script aligns with its principles of trend analysis and market sentiment interpretation. By offering visual cues on sentiment shifts, it provides traders with insights into potential trading opportunities, echoing Elliot Wave's emphasis on pattern recognition and trend analysis.
Chart Timeframe Support and Resistance:
Working Principle:
This feature serves to identify and visualize support and resistance levels on the chart, primarily based on the chosen Chart Timeframe (CTF). It allows users to specify parameters such as the number of bars considered on the left and right sides of each pivot point, as well as line width and label color. Moreover, users have the option to enable or disable the display of these levels. By utilizing functions to calculate pivot highs and lows within the specified timeframe, the script determines the highest high and lowest low surrounding each pivot point.
Additionally, it defines functions to create lines and labels for each detected support and resistance level. Notably, this feature incorporates a trading method that emphasizes the concept of resistance turning into support after breakouts, thereby providing valuable insights for traders employing such strategies. These lines are drawn on the chart, with colors indicating whether the level is above or below the current close price, aiding traders in visualizing key levels and making informed trading decisions.
Benefits of Chart Timeframe Support and Resistance:
Identification of Price Levels: Support and resistance levels help traders identify significant price levels where buying (support) and selling (resistance) pressure may intensify. These levels are often formed based on historical price movements and are regarded as areas of interest for traders.
Decision Making: Support and resistance levels assist traders in making informed trading decisions. By observing price reactions near these levels, traders can gauge market sentiment and adjust their strategies accordingly. For example, traders may choose to enter or exit positions, set stop-loss orders, or take profit targets based on price behavior around these levels.
Risk Management: Support and resistance levels aid in risk management by providing reference points for setting stop-loss orders. Traders often place stop-loss orders below support levels for long positions and above resistance levels for short positions to limit potential losses if the market moves against them.
How to use this feature:
Planning Long Positions: When considering long positions, it's advantageous to strategize when the price is in proximity to a support level identified by the script. This suggests a potential area of buying interest where traders may expect a bounce or reversal in price. Additionally, confirm the bullish bias by ensuring that the trend cloud is green, indicating favorable market conditions for long trades.
Waiting for Breakout: If long signals are generated near resistance levels detected by the script, exercise patience and wait for a breakout above the resistance. A breakout above resistance signifies potential strength in the upward momentum and may present a more opportune moment to enter long positions. This approach aligns with trading methodologies that emphasize confirmation of bullish momentum before initiating trades.
StopLoss and Target Lines:
In addition to generating entry signals, this indicator also incorporates predefined stop-loss ray lines and configurable risk-reward (R:R) target lines to enhance risk management and profit-taking strategies. Here's how these features work:
Predefined Stop-loss Ray Lines: The indicator automatically plots stop-loss ray lines on the chart, serving as visual guidelines for setting stop-loss levels. These stop-loss lines are predetermined based on specific criteria, such as volatility levels, support and resistance zones, or predefined risk parameters. Traders can use these lines as reference points to place their stop-loss orders, aiming to limit potential losses if the market moves against their position.
Configurable Risk-Reward (R:R) Target Lines: In addition to stop-loss lines, the indicator allows traders to set configurable risk-reward (R:R) target lines on the chart. These target lines represent predefined price levels where traders intend to take profits based on their desired risk-reward ratio. By adjusting the placement of these lines, traders can customize their risk-reward ratios according to their trading preferences and risk tolerance.
Risk Management: The predefined stop-loss ray lines help traders manage risk by providing clear exit points if the trade goes against their expectations. By adhering to these predetermined stop-loss levels, traders can minimize potential losses and protect their trading capital, thereby enhancing overall risk management.
Profit-taking Strategy: On the other hand, the configurable R:R target lines assist traders in establishing profit-taking strategies. By setting target levels based on their desired risk-reward ratio, traders can aim to capture profits at predefined price levels that offer favorable risk-reward profiles. This allows traders to systematically take profits while ensuring that potential gains outweigh potential losses over the long term.
The stop-loss and target lines incorporated in this indicator are dynamic in nature, providing traders with the flexibility to utilize them as trailing stop-loss and extended take-profit targets. Here's how these dynamic features work:
Trailing Stop-loss: Traders can employ the stop-loss lines as trailing stop-loss levels, allowing them to adjust their stop-loss orders as the market moves in their favor. As the price continues to move in the desired direction, indicator can dynamically adjust the stop-loss line to lock in profits while still allowing room for potential further gains. This trailing stop-loss mechanism helps traders secure profits while allowing their winning trades to continue running as long as the market remains favorable.
Extended Take Profit Targets: Similarly, traders can utilize the target lines as extended take-profit targets, enabling them to capture additional profits beyond their initial profit targets. By adjusting the placement of these target lines based on evolving market conditions or technical signals, traders can extend their profit-taking strategy to capitalize on potential price extensions or trend continuations. This flexibility allows traders to maximize their profit potential by capturing larger price movements while managing their risk effectively.
Rangebound Bars:
When the Rangebound Bars feature is enabled, the indicator represents candles in a distinct purple color to visually denote periods of sideways or range-bound price action. This visual cue helps traders easily identify when the market is consolidating and lacking clear directional momentum. Here's how it works:
Purple Candle Color: When the Rangebound Bars feature is active, the indicator displays candlesticks in a purple color to highlight periods of sideways price movement. This color differentiation stands out against the usual colors used for bullish (e.g., green or white) and bearish (e.g., red or black) candles, making it easier for traders to recognize range-bound conditions at a glance.
Signaling Sideways Price Action: The purple coloration of candles indicates that price movements are confined within a relatively narrow range and lack a clear upward or downward trend. This may occur when the market is consolidating, experiencing indecision, or undergoing a period of accumulation or distribution.
Working Principle:
The Rangebound Bars feature of this indicator is designed to assist traders in identifying and navigating consolidating market conditions, where price movements are confined within a relatively narrow range. This feature utilizes Pivot levels and the Average True Range (ATR) concept to determine when the market is range-bound and provides signals to stay out of such price action. Here's how it works:
Pivot Levels: Pivot levels are key price levels derived from the previous period's high, low, and closing prices. They serve as potential support and resistance levels and are widely used by traders to identify significant price levels where price action may stall or reverse. The Rangebound Bars feature incorporates Pivot levels into its analysis to identify ranges where price tends to consolidate.
Average True Range (ATR): The Average True Range is a measure of market volatility that calculates the average range between the high and low prices over a specified period. It provides traders with insights into the level of price volatility and helps set appropriate stop-loss and take-profit levels. In the context of the Rangebound Bars feature, ATR is used to gauge the extent of price fluctuations within the identified range.
Trailing Management (Zeiierman)█ Overview
The Trailing Management (Zeiierman) indicator is designed for traders who seek an automated and dynamic approach to managing trailing stops. It helps traders make systematic decisions regarding when to enter and exit trades based on the calculated risk-reward ratio. By providing a clear visual representation of trailing stop levels and risk-reward metrics, the indicator is an essential tool for both novice and experienced traders aiming to enhance their trading discipline.
The Trailing Management (Zeiierman) indicator integrates a Break-Even Curve feature to enhance its utility in trailing stop management and risk-reward optimization. The Break-Even Curve illuminates the precise point at which a trade neither gains nor loses value, offering clarity on the risk-reward landscape. Furthermore, this precise point is calculated based on the required win rate and the risk/reward ratio. This calculation aids traders in understanding the type of strategy they need to employ at any given time to be profitable. In other words, traders can, at any given point, assess the kind of strategy they need to utilize to make money, depending on the price's position within the risk/reward box.
█ How It Works
The indicator operates by computing the highest high and the lowest low over a user-defined period and then applying this information to determine optimal trailing stop levels for both long and short positions.
Directional Bias:
It establishes the direction of the market trend by comparing the index of the highest high and the lowest low within the lookback period.
Bullish
Bearish
Trailing Stop Adjustment:
The trailing stops are adjusted using one of three methods: an automatic calculation based on the median of recent peak differences, pivot points, or a fixed percentage defined by the user.
The Break-Even Curve:
The Break-Even Curve, along with the risk/reward ratio, is determined through the trailing method. This approach utilizes the current closing price as a hypothetical entry point for trades. All calculations, including those for the curve, are based on this current closing price, ensuring real-time accuracy and relevance. As market conditions fluctuate, the curve dynamically adjusts, offering traders a visual benchmark that signifies the break-even point. This real-time adjustment provides traders with an invaluable tool, allowing them to visually track how shifts in the market could impact the point at which their trades neither gain nor lose value.
Example:
Let's say the price is at the midpoint of the risk/reward box; this means that the risk/reward ratio should be 1:1, and the minimum win rate is 50% to break even.
In this example, we can see that the price is near the stop-loss level. If you are about to take a trade in this area and would respect your stop, you only need to have a minimum win rate of 11% to earn money, given the risk/reward ratio, assuming that you hold the trade to the target.
In other words, traders can, at any given point, assess the kind of strategy they need to employ to make money based on the price's position within the risk/reward box.
█ How to Use
Market Bias:
When using the Auto Bias feature, the indicator calculates the underlying market bias and displays it as either bullish or bearish. This helps traders align their trades with the underlying market trend.
Risk Management:
By observing the plotted trailing stops and the risk-reward ratios, traders can make strategic decisions to enter or exit positions, effectively managing the risk.
Strategy selection:
The Break-Even Curve is a powerful tool for managing risk, allowing traders to visualize the relationship between their trailing stops and the market's price movements. By understanding where the break-even point lies, traders can adjust their strategies to either lock in profits or cut losses.
Based on the plotted risk/reward box and the location of the price within this box, traders can easily see the win rate required by their strategy to make money in the long run, given the risk/reward ratio.
Consider this example: The market is bullish, as indicated by the bias, and the indicator suggests looking into long trades. The price is near the top of the risk/reward box, which means entering the market right now carries a huge risk, and the potential reward is very low. To take this trade, traders must have a strategy with a win rate of at least 90%.
█ Settings
Trailing Method:
Auto: The indicator calculates the trailing stop dynamically based on market conditions.
Pivot: The trailing stop is adjusted to the highest high (long positions) or lowest low (short positions) identified within a specified lookback period. This method uses the pivotal points of the market to set the trailing stop.
Percentage: The trailing stop is set at a fixed percentage away from the peak high or low.
Trailing Size (prd):
This setting defines the lookback period for the highest high and lowest low, which affects the sensitivity of the trailing stop to price movements.
Percentage Step (perc):
If the 'Percentage' method is selected, this setting determines the fixed percentage for the trailing stop distance.
Set Bias (bias):
Allows users to set a market bias which can be Bullish, Bearish, or Auto, affecting how the trailing stop is adjusted in relation to the market trend.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
GKD-M Stepped Baseline Optimizer [Loxx]The Giga Kaleidoscope GKD-M Stepped Baseline Optimizer is a Metamorphosis module included in the "Giga Kaleidoscope Modularized Trading System."
█ Introduction
The GKD-M Stepped Baseline Optimizer is an advanced component of the Giga Kaleidoscope Modularized Trading System (GKD), designed to enhance trading strategy development by dynamically optimizing Baseline moving averages. This tool allows traders to evaluate over 65 moving averages, adjusting them across multiple periods to identify which settings yield the highest win rates for their trading strategies. The optimizer systematically tests these moving averages across specified timeframes and intervals, offering insights into net profit, total closed trades, win percentages, and other critical metrics for both long and short positions. Traders can define the initial period and incrementally adjust this value to explore a wide range of periods, thus fine-tuning their strategies with precision. What sets the GKD-M Stepped Baseline Optimizer apart is its unique capability to adapt the baseline moving average according to the highest win rates identified during backtesting, at each trading candle. This win-rate adaptive approach ensures that the trading system is always aligned with the most effective period settings for the selected moving average, enhancing the system's overall performance. Moreover, the 'stepped' aspect of this optimizer introduces a filtering process based ons, significantly reducing market noise and ensuring that identified trends are both significant and reliable. This feature is critical for traders looking to mitigate the risks associated with volatile market conditions and to capitalize on genuine market movements.In essence, the GKD-M Stepped Baseline Optimizer is tailored for traders who utilize the GKD trading system, offering a sophisticated tool to refine their baseline indicators dynamically, ensuring that their trading strategies are continuously optimized for maximum efficacy.
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolated per ticker and trading side, long or short**
█ Core Features
Stepped Baseline for Noise Reduction
One of the hallmark features of the GKD-M Stepped Baseline Optimizer is its stepped baseline capability. This advanced functionality employs volatility filters to refine the selection of moving averages, significantly reducing market noise. The optimizer ensures that only substantial and reliable trends are considered, eliminating the false signals often caused by minor price fluctuations. This stepped approach to baseline optimization is critical for traders aiming to develop strategies that are both resilient and responsive to genuine market movements.
Dynamic Win Rate Adaptive Capability
Another cornerstone feature is the optimizer’s dynamic win rate adaptive capability. This unique aspect allows the optimizer to adjust the moving average period settings in real-time, based on the highest win rates derived from backtesting over a predefined range. At every trading candle, the optimizer evaluates a comprehensive set of backtesting data to ascertain the optimal period settings for the moving average in use. To perform the backtesting, the trader selects an initial period input (default is 60) and a skip value that increments the initial period input up to seven times. For instance, if a skip value of 5 is chosen, the Baseline Optimizer will run the backtest for the selected moving average on periods such as 60, 65, 70, 75, and so on, up to 90. If the user selects an initial period input of 45 and a skip value of 2, the Baseline Optimizer will conduct backtests for the chosen moving average on periods like 45, 47, 49, 51, and so forth, up to 57. The GKD-M Stepped Baseline Optimizer then exports the baseline with the highest cumulative win rate per candle to any baseline-enabled GKD backtest. This ensures that the baseline indicator remains continually aligned with the most efficacious parameters, dynamically adapting to changing market conditions.
Comprehensive Moving Averages Evaluation
The optimizer’s ability to test over 65 different moving averages across multiple periods stands as a testament to its comprehensive analytical capability. Traders have the flexibility to explore a wide array of moving averages, from traditional ones like the Simple Moving Average (SMA) and Exponential Moving Average (EMA) to more complex types such as the Hull Moving Average (HMA) and Adaptive Moving Average (AMA). This extensive evaluation allows traders to pinpoint the moving average that best aligns with their trading strategy and market conditions, further enhancing the system’s adaptability and effectiveness.
Volatility Filtering and Ticker Volatility Types
Incorporating a wide range of volatility types, including the option to utilize external volatility tickers like the VIX for filtering, adds another layer of sophistication to the optimizer. This feature allows traders to calibrate their baseline according to externals, providing an additional dimension of customization. Whether using standard deviation, ATR, or external volatility indices, traders can fine-tune their strategies to be responsive to the broader market sentiment and volatility trends.
█ Key Inputs
Baseline Settings
• Baseline Source: Determines the price data (Open, High, Low, Close) used for moving average calculations.
• Baseline Period: The starting period for moving average calculation.
• Backtest Skip: Incremental steps for period adjustments in the optimization process.
• Baseline Filter Type: Selection from over 65 moving averages for baseline calculation.
Volatility and Filter Settings
• Price Filter Type & Moving Average Filter Type: Defines thement applied to the price or the moving average, enhancing filter specificity.
• Filter Options: Allows users to select the application area of the volatility filter (price, moving average, or both).
• Filter Multiplier & Period: Configures the intensity and temporal scope of the filter, fine-tuning sensitivity to market volatility.
Backtest Configuration
• Window Period: Specifies the length of the backtesting window in days.
• Backtest Type: Chooses between a fixed window or cumulative data approach for backtesting.
• Initial Capital, Order Size, & Type: Sets the financial parameters for backtesting, including starting equity and the scale of trades.
• Commission per Order: Accounts for trading costs within backtest profitability calculations.
Date and Time Range
• From/Thru Year/Month/Day: Defines the historical period for strategy testing.
• Entry Time: Specifies the time frame during which trades can be initiated, crucial for strategies sensitive to market timing.
Volatility Measurements for Goldie Locks Volatility Qualifiers
• Mean Type & Period: Chooses the moving average type and period for volatility assessment.
• Inner/Outer Volatility Qualifier Multipliers: Adjusts the boundaries for volatility-based trade qualification.
• Activate Qualifier Boundaries: Enables or disables the upper and lower volatility qualifiers.
Advanced Volatility Inputs
• Volatility Ticker Selection & Trading Days: Incorporates external volatility indices (e.g., VIX) into the strategy, adjusting for market volatility.
• Static Percent, MAD Internal Filter Period, etc.: Provides fixed or adaptive volatility thresholds for filtering.
UI Customization
• Baseline Width & Table Display Options: Customizes the visual representation of the baseline and the display of optimization results.
• Table Header/Content Color & Text Size: Enhances readability and user interface aesthetics.
Export Options
• Export Data: Selects the specific metric to be exported from the script, such as net profit or average profit per trade.
Moving Average Specific Parameters
Specific inputs tailored to the characteristics of selected moving averages (e.g., Fractal Adjusted (FRAMA), Least Squares Moving Average (LSMA), T3, etc.), allowing users to fine-tune the behavior of these averages based on unique formula requirements.
█ Indicator UI
• Long and Short Baselines: The optimizer differentiates trends through two distinct baselines: a green line for long (uptrend) baselines and a red line for short (downtrend) baselines. These baselines alternate activation based on the current trend direction as determined by the moving average plus length combination for the candle in view.
Ambiguity in market direction, when an uptrend and downtrend are concurrently indicated, is visually represented by yellow lines.
• Stepping Mechanism for Trend Visualization: Adjusting the source input and the moving average output based on volatility, the indicator exhibits a stepped appearance on the chart. This mechanism ensures that only substantial market movements, surpassing a specified volatility threshold, are recognized as trend changes.
Stepping Activated
• Goldilocks Zone: Beyond the long and short baselines, the Goldilocks zone introduces a distinct moving average that closely follows the selected price or source input, aiming to strike the perfect balance between not too much and not too little market movement for trading. The upper limit of the Goldilocks zone indicates a market stretch too far for advantageous trading (overextension), while the lower limit suggests inadequate market movement for entry (underextension). Trading within the Goldilocks zone is deemed optimal, as it signifies sufficient but not excessive volatility for entering trades, aligning with either the long or short baseline recommendations. Moreover, the mean of the Goldilocks zone serves as a critical indicator, offering a median reference point that aligns closely with the market's current state. This mean is pivotal for traders, as it represents a 'just right' condition for market entry, embodying the essence of the Goldilocks principle in financial trading strategies.
• Signal Indicators and Entry Points: The chart includes with green or red dots to signify valid price points within the Goldilocks zone, indicative of conducive trading conditions. Furthermore, small directional arrows at the chart's bottom highlight potential long or short entry points, validated by the Goldilocks zone's parameters.
• Data Table: A table presenting real-time statistics from the current candle backward through the chosen range offers insights into win rates and other relevant data, aiding in informed decision-making. This table adapts with each new candle, highlighting the most favorable win rates for both long and short positions.
█ Optimizing Strategy with Backtesting
Optimizing a trading strategy with backtesting involves rigorously testing the strategy on historical data to evaluate its performance and robustness before applying it in live markets. The GKD-M Stepped Baseline Optimizer incorporates advanced backtesting capabilities, offering both cumulative and rolling window types of backtests. Here's how each backtest type operates and the insights they provide for refining trading strategies:
Cumulative Backtest
• Overview: A cumulative backtest evaluates a strategy's performance over a continuous period without resetting the strategy parameters or the simulated trading capital at the beginning of each new period.
• Utility: This type is useful for understanding a strategy's long-term viability, assessing how it adapts to different market conditions over an extended timeframe.
• Interpreting Statistics: Cumulative backtest results often focus on overall return, drawdowns, win rate, and the Sharpe ratio. A strategy with consistent returns, manageable drawdowns, a high win rate, and a favorable Sharpe ratio is considered robust.
Rolling Window Backtest
• Overview: Unlike the cumulative approach, a rolling window backtest divides the historical data into smaller, overlapping or non-overlapping periods (windows), running the strategy separately on each. After each window, the strategy parameters and simulated trading capital are reset.
• Utility: This method is invaluable for assessing a strategy's consistency and adaptability to various market phases. It helps identify if the strategy's performance is dependent on specific market conditions.
• Interpreting Statistics: For rolling window backtests, consistency is key. Look for similar performance metrics (returns, drawdowns, win rate) across different windows. Variability in performance indicates sensitivity to market conditions, suggesting the need for strategy adjustments.
Strategy Refinement Through Backtest Statistics
• Net Profit and Loss: Measures the strategy’s overall effectiveness. Consistent profitability across different market conditions is a positive indicator.
• Win Rate and Profit Factor: High win rates and profit factors indicate a strategy's efficiency in capturing gains over losses.
• Average Profit per Trade: Understanding the strategy's ability to generate profit on a per-trade basis can highlight its operational efficiency.
• Average Number of Bars in Trade: This metric helps understand the strategy's market exposure and timing efficiency.
█ Exporting Data and Integration with GKD Backtests
The GKD-M Stepped Baseline Optimizer seamlessly integrates with the broader GKD trading system, allowing traders to export the optimization data and leverage it within the various GKD backtest modules. This feature allows users to forward the GKD-M Stepped Baseline Optimizer adaptive signals to a GKD backtest to be used as a Baseline component in a GKD trading system.
█ Moving Averages included in the Stepped Baseline Optimizer
The GKD-M Stepped Baseline Optimizer incorporates an extensive array of over 65 moving averages, each with unique characteristics and implications for trading strategy development. This comprehensive suite enables traders to conduct nuanced analysis and optimization, ensuring the selection of the most effective moving average for Baseline input into their GKD trading system.
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Coral
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Ehlers Optimal Tracking Filter - EOTF
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Geometric Mean Moving Average
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE/2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA (Least Squares Moving Average)
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Range Filter
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Regularized EMA - REMA
Simple Decycler - SDEC
Simple Loxx Moving Average - SLMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Tether Lines
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triangle Moving Average Generalized
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Ultimate Smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
█ Volatility Types and Filtering
The GKD-M Stepped Baseline Optimizer features a comprehensive selection of over 15 volatility types, each tailored to capture different aspects of market behavior and risk.
Volatility Ticker Selection: Enables direct incorporation of external volatility indicators like VIX and EUVIX into the script for market sentiment analysis, signal filtering enhancement, and real-time risk management adjustments.
Standard Deviation of Logarithmic Returns: Quantifies asset volatility using the standard deviation applied to logarithmic returns, capturing symmetric price movements and financial returns' compound nature.
Exponential Weighted Moving Average (EWMA) for Volatility: Focuses on recent market information by applying exponentially decreasing weights to squared logarithmic returns, offering a dynamic view of market volatility.
Roger-Satchell Volatility Measure: Estimates asset volatility by analyzing the high, low, open, and close prices, providing a nuanced view of intraday volatility and market dynamics.
Close-to-Close Volatility Measure: Calculates volatility based on the closing prices of stocks, offering a streamlined but limited perspective on market behavior.
Parkinson Volatility Measure: Enhances volatility estimation by including high and low prices of the trading day, capturing a more accurate reflection of intraday market movements.
Garman-Klass Volatility Measure: Incorporates open, high, low, and close prices for a comprehensive daily volatility measure, capturing significant price movements and market activity.
Yang-Zhang Volatility Measure: Offers an efficient estimation of stock market volatility by combining overnight and intraday price movements, capturing opening jumps and overall market dynamics.
Garman-Klass-Yang-Zhang Volatility Measure: Merges the benefits of Garman-Klass and Yang-Zhang measures, providing a fuller picture of market volatility including opening market reactions.
Pseudo GARCH(2,2) Volatility Model: Mimics a GARCH(2,2) process using exponential moving averages of squared returns, highlighting volatility shocks and their future impact.
ER-Adaptive Average True Range (ATR): Adjusts the ATR period length based on market efficiency, offering a volatility measure that adapts to changing market conditions.
Adaptive Deviation: Dynamically adjusts its calculation period to offer a nuanced measure of volatility that responds to the market's intrinsic rhythms.
Median Absolute Deviation (MAD): Provides a robust measure of statistical variability, focusing on deviations from the median price, offering resilience against outliers.
Mean Absolute Deviation (MAD): Measures the average magnitude of deviations from the mean price, facilitating a straightforward understanding of volatility.
ATR (Average True Range): Finds the average of true ranges over a specified period, indicating the expected price movement and market volatility.
True Range Double (TRD): Offers a nuanced view of volatility by considering a broader range of price movements, identifying significant market sentiment shifts.
Timeframe Accumulation Analyzer (by TradersTavern)Indicator Name: Timeframe Accumulation Analyzer (by TradersTavern)
Overview:
The "Timeframe Accumulation Analyzer" by TradersTavern offers traders a sophisticated tool for comprehensive market analysis. With its intuitive interface and powerful features, this indicator enables traders to gain deep insights into market dynamics across multiple timeframes.
Features:
Multi-Timeframe Analysis: The Timeframe Accumulation Analyzer allows traders to delve into market data across various time intervals simultaneously, uncovering hidden patterns and trends.
Customization Options: Traders can tailor the indicator to their preferences with customizable settings, including line length, timeframe selection, line width, label display settings, and visual offsets for labels.
Visual Clarity: The indicator's intuitive design provides clear visualization of accumulation areas, empowering traders to make informed decisions with ease.
Contextual Insights: Customizable labels offer additional context by displaying pertinent information about each timeframe's accumulation points, enhancing traders' understanding of market dynamics.
Example Strategies and Trade Plans:
Trend Confirmation Strategy:
Objective: Confirm the strength of prevailing trends across multiple timeframes.
Trade Plan: Analyze accumulation areas across different timeframes to validate the continuity of trends.
Risk Management: Implement stop-loss orders based on accumulation levels or support/resistance zones.
Take Profit: Utilize multiple take-profit targets or trail the stop-loss to capture trend extensions.
Reversal Detection Strategy:
Objective: Identify potential reversal points by analyzing accumulation patterns.
Trade Plan: Look for divergence between price action and accumulation levels as possible reversal signals.
Risk Management: Place stop-loss orders beyond recent accumulation areas or significant pivot points.
Take Profit: Set profit targets based on historical support/resistance levels or Fibonacci extensions.
Breakout Confirmation Strategy:
Objective: Identify accumulation areas preceding breakout movements for confirmation.
Trade Plan: Wait for price to break above the highest accumulation point on the shortest timeframe for confirmation.
Risk Management: Place stop-loss orders below the lowest accumulation point or recent swing low.
Take Profit: Set profit targets based on the range of the breakout or trail the stop-loss to capture extended moves.
[Options Strategies] Selling Covered Calls and Puts (TSO) This trading indicator assists with traditional covered options trading strategies like Covered Calls, Covered Puts, and Cash Secured Puts. It also offers advanced features for trading options intelligently by utilizing options specific levels, such as BE (Break Even) and Strike (all visually shown on chart) in combination with S&R (Support and Resistance), Trend Lines, and other technical analysis tools such as MA (Moving Averages) and ATR Average True Range, all integrated within the indicator.
* Covered options approach over trading shares or options separately offers distinct advantages:
- Reduced Risk and Flexibility : Covered options strategy provides a more conservative approach by combining stock ownership with options trading. It reduces risk exposure compared to buying options outright or trading shares alone. Additionally, it offers flexibility in various market conditions.
- Profitability in Sideways Markets: Covered options allow for profitability in scenarios where the stock price is either moving optimally or remaining sideways. In contrast, just holding stocks might not yield significant gains in a sideways market, and buying options can result in losses due to time decay.
- Protection Against Price Movements: In covered options, if the stock price goes against the trade, the loss is mitigated by the premium received from selling the options. This provides a level of protection compared to other trading strategies where losses can accumulate more rapidly.
==============================================================
Strategies / Visual Examples:
---------------------------------------------------------------------------
---------------------------------------------------------------------------
Up to 3 Symbols can be monitored at the same time with alerts for each Symbol and a Stats Table. To see Symbol's visuals (Date Range, Strike, BE, etc.) - the chart has to be loaded with that Symbol. Here is an example of trading multiple stocks at same layout on different charts trading AAPL, BAC and TSLA.
---------------------------------------------------------------------------
---------------------------------------------------------------------------
An example of a Smart Covered Calls trading SPY.
STRATEGY EXPLANATION:
* Trade Open Trigger (Bullish/Sideway)
>>> S&R (Support and Resistance) or Trend Line broken, bounced off or simply near (if price is near/slightly crossing S&R/Trend Line > a bounce often takes place)
>>> Confirmation by additional TA (Technical Analysis) tools.
>>> EXAMPLE: Broken Resistance combined with a Trend Line up-bounce, confirmed by bullish 200EMA.
* TP (Take-Profit)
>>> Contracts Expire at Expiration date: Premium received for selling contracts kept.
>>> Assignment: Premium received for selling contracts kept + stock assigned/sold at a higher price than it was purchased.
* BE/SL (Break Even Stop-Loss) |
>>> BE/SL hit: stock sold at a slight loss with options contracts bought out (BTC - Buy to Close) at a lower price than initially sold (since price went down and these are calls), so technically the loss is reduced by the partial Premium still kept from initially sold contracts at trade open.
>>> Increasing the BE/SL distance: for wider BE/SL > Bid Price needs to be increased:
- Set longer Expiration date.
- Set closer Strike price.
NOTE: With longer Expiration date and closer Strike, chances of assignment increase as well. It's best to find an optimal level, where BE/SL is behind a Support/Resistance level and/or an established trend line and/or Large Length Moving Average, yet not extremely far away.
---------------------------------------------------------------------------
---------------------------------------------------------------------------
An example of a Smart Covered Puts trading SPY.
STRATEGY EXPLANATION:
* Trade Open Trigger (Bearish/Sideway)
>>> S&R (Support and Resistance) or Trend Line broken, bounced off or simply near (if price is near/slightly crossing S&R/Trend Line > a bounce often takes place)
>>> Confirmation by additional TA (Technical Analysis) tools.
>>> EXAMPLE: Broken Resistance combined with a Trend Line down-bounce, confirmed by bearish 200EMA.
* TP (Take-Profit)
>>> Contracts Expire at Expiration date: Premium received for selling contracts kept.
>>> Assignment: Premium received for selling contracts kept + stock assigned/bought-to-cover at a lower price than it was shorted.
* BE/SL (Break Even Stop-Loss) |
>>> BE/SL hit: stock bought-to-cover at a slight loss with options contracts bought out (BTC - Buy to Close) at a lower price than initially sold (since price went up and these are puts), so technically the loss is reduced by the partial Premium still kept from initially sold contracts at trade open.
>>> Increasing the BE/SL distance: for wider BE/SL > Bid Price needs to be increased:
- Set longer Expiration date.
- Set closer Strike price.
NOTE: With longer Expiration date and closer Strike, chances of assignment increase as well. It's best to find an optimal level, where BE/SL is behind a Support/Resistance level and/or an established trend line and/or Large Length Moving Average, yet not extremely far away.
---------------------------------------------------------------------------
---------------------------------------------------------------------------
An example of a Smart Secured Cash Puts trading SPY.
STRATEGY EXPLANATION:
* Trade Open Trigger (Bullish/Sideway)
>>> Bullish steady trend.
>>> Confirmation by additional TA (Technical Analysis) tools.
>>> EXAMPLE: Slowly rising price action above 200EMA.
* TP (Take-Profit)
>>> Early BTC: BTC (Buy to Close) before Expiration date if options premium/contract price already reduced by at least 50-90% (the reduced price is the profit, if premium lost 90% - only 10% will need to be paid to buy options out to close the trade) and if the stock price is nearing Resistance, Trend Line or big length moving average (like 200EMA) as a bounce may happen or even a potential reverse of the trend. If there is no trend reversal or a small correction bounce occurs, with further trend continuation > another Cash Secured Puts trade can be opened with new Expiration date and Strike.
>>> Contracts Expire at Expiration date: Premium received for selling contracts kept, considering the Strike was never hit.
>>> Assignment with stock closing below Strike and above/near BE (Break Even): Premium received for selling contracts kept. NOTE: It is best to get rid of the stock ASAP to then open a new Cash Secured Puts trade with lower Strike and a new Expiration date.
* BE/SL (Break Even Stop-Loss) |
>>> BE/SL hit: contracts bought out (BTC - Buy to Close) at a higher price than initially sold (since price went down and these are puts), the amount/difference in current contract price is the loss (as premium received + contract price increase is the total cost, which will have to be paid to buy the countracts out).
>>> Increasing the BE/SL distance: for wider BE/SL > Bid Price needs to be increased:
- Set longer Expiration date.
- Set closer Strike price.
NOTE: With longer Expiration date and closer Strike, chances of assignment increase as well. It's best to find an optimal level, where BE/SL is behind a Support/Resistance level and/or an established trend line and/or Large Length Moving Average, yet not extremely far away.
---------------------------------------------------------------------------
---------------------------------------------------------------------------
An example of Options Wheel strategy trading TQQQ. See how Strike and BE (Break Even) hits are displayed every time they occur.
STRATEGY EXPLANATION:
* Trade Open Trigger (Bullish/Sideway)
>>> Options Wheel strategy combines Cash Secured Puts with Covered Calls, so a steady bullish trend is preferred with lower volatility.
>>> It's best to start with Cash Secured Puts until assignment hits (stocks purchased), then switch to Covered Calls until assignment hits (stocks sold) and so on.
* TP (Take-Profit)
>>> Contracts Expire at Expiration date: Premium received for selling contracts kept.
>>> Assignment: Premium received for selling contracts kept. Stock is assigned (purchased if Cash Secured Puts were sold | sold if Covered Calls were sold ).
* BE/SL (Break Even Stop-Loss)
>>> Assignment is the stop-loss for this strategy, which ends current trade and starts next one. It is not a direct loss, but could result a long unrealized losses if after stock purchase assignment it goes down for a while or even a complete loss if low-cap company is used and it goes out of business.
>>> BE/SL distance can still be increased/kept optimal: for wider BE/SL > Bid Price needs to be increased:
- Set longer Expiration date.
- Set closer Strike price.
NOTE: With longer Expiration date and closer Strike, chances of assignment increase as well. It's best to find an optimal level, where BE/SL is behind a Support/Resistance level and/or an established Trend Line and/or Large Length Moving Average, yet not extremely far away.
| 3.0_wheel_strategy_tqqq_example.png
===========================================================================
Trading open/close/TP/SL labels, plots and colors explanations:
---------------------------------------------------------------------------
There are 3 approaches: Cashed Secured Puts, Covered Puts, Covered Calls. Here is an example showing all 3 (the Strikes, Bid prices, Expirations were chosen realistically).
>>> There are 3 symbol templates, the color can be changed for each and each symbol template can be unchecked to be fully hidden or all 3 can be used.
>>> Strike: dashed horizontal line plotted at chosen Strike, if Strike is hit within the Date Range - there will be a label shown.
>>> BE (Break Even): dotted horizontal line plotted at calculated BE, if BE is hit within the Date Range - there will be a label shown.
>>> Stock Purchased: solid horizontal line plotted at input price at which the stock was purchased.
>>> Date Range (STO >>> Expiration ): vertical lines with arrows (arrows direction is based on the approach), which connect Strike, BE (Break Even) and Stock Purchased creating an square/rectangle of the whole trade, making it easy to see everything at once.
>>> Stats Table: shows all the necessary data for each symbol.
===========================================================================
GLOBAL SETTINGS ///////////////////////////////////////////////////////////
---------------------------------------------------------------------------
>>> Show: week divider vertical lines: Will show vertical divider lines separating each week.
>>> Show: Mondays and Fridays: Will show M - for Monday, F - for Friday, T - for Tuesday (Tuesday will be shown if there is a Holiday on Monday)
---------------------------------------------------------------------------
OPTIONS SETUP: SYMBOL0X /////////////////////////////////////////////////// | (identical for all 3 symbols)
---------------------------------------------------------------------------
>>> Symbol0X | Show Table: Turns on symbol01, all visuals on chart, calculations, etc. Table can be separately hidden if desired.
>>> Label Size: Size of the labels on chart showing Strike, BE (Break Even), etc.
>>> Label Color: Color for all symbol0X labels.
>>> Text Color: Text color for all symbol0X labels.
>>> Options Trading Style: 1)Covered Calls: Bullish-sideways market approach (need to own 100 shares of stock per each contract sold), Strike price has to be set above the current stock price | 2)Covered Puts: Bearish-sideways market approach (need to own 100 shares of stock per each contract sold), Strike price has to be set below the current stock price | 3)Cash Secured Puts: Bullish-sideways approach (need to have enough cash to acquire shares at Strike price if hit), Strike price has to be set below the current stock price.
>>> # of contracts sold (1 contract > 100shares): # of contracts sold per trade, for Covered Calls and Covered Puts, every contract must be backed up by 100shares of the underlying stock.
>>> Price per 1 contract (Bid): Premium received per each contract sold.
>>> Strike Price.
>>> Stock Purchase Price: Stock purchase price (NOTE: This is only for Covered Call and Covered Puts, for Secured Cash Puts - stock is only purchased if at Expiration it closes beyond Strike price).
>>> STO (Sell to Open) Date: date at which the contracts were sold and Premium received.
>>> Exp (Expiration) Date: date at which contracts expire, if price never breaks the Strike at Expiration - contracts become worthless!
>>> Alert/Label: Futures Expire Soon: With this setting turned on, an Alert will trigger and a Label will be shown at opening of the first candle bar on the Expiration date. It will certainly be before the end of the day, however depending on the chart TimeFrame during alert creation - it may trigger at a different time. For Example: On a Daily chart TimeFrame SPY (S&P500) will trigger such alert at 9:30AM ET. ||| NOTE: Due to difference in timezones - the solid lines representing the STO >>> Exp range may be off by 1 business day from the date input in the indicator Settings > Inputs, so double check and calibrate the date by setting it 1 day behind/ahead from actual dates so that Alert is received on the actual Expiration date.
>>> Strike price Broken - Style: 'Close': Show/Alert Strike price broken only once candle bar is closed | 'Live': Show/Alert Strike price broken immediately once it happens, before candle bar is closed.
>>> Show: Strike price Broken: will show a label near candle bar breaking the Strike price.
>>> Alert: Strike price Broken: will alert at price breaking the Strike price.
>>> BE (Break Even) price Broken - Alert Style: 'Close': Show/Alert BE (Break Even) price broken only once candle bar is closed | 'Live': Show/Alert BE (Break Even) price broken immediately once it happens, before candle bar is closed.
>>> Show: BE (Break Even) price Broken: will show a label near candle bar breaking the BE price.
>>> Alert: BE (Break Even) price Broken: will alert at price breaking the BE price.
---------------------------------------------------------------------------
TA: TREND LINES ///////////////////////////////////////////////////////////
---------------------------------------------------------------------------
>>> Trend Lines - Uptrend/downtrend colors
>>> Show: Trend Lines: Show/Hide trend lines
>>> Show: Trend Line Breaks: Show/Hide labels where trend lines were broken
>>> Alert: Trend Line Breaks: Alert when trend line is broken
>>> Trend Lines - Search - Left Bars / Trend Lines - Search - Right Bars: how many candle bars will be used to calculate Trend Lines, the bigger the number > the more precise and less amount of trend lines will be found
>>> Trend Lines - Extend Setting
---------------------------------------------------------------------------
TA: S&R (SUPPORT AND RESISTANCE) //////////////////////////////////////////
---------------------------------------------------------------------------
>>> S&R (Support and Resistance) - Support/Resistance colors.
>>> Show: S&R (Support and Resistance) Top/Bottom Levels.
>>> Show: S&R (Support and Resistance) Top/Bottom Level Breaks: Show/Hide labels where support/resistance levels were broken
>>> Alert: S&R (Support and Resistance) Top/Bottom Level Breaks: Alert when S&R (Support and Resistance) level is broken
>>> S&R (Support and Resistance) - Search - Left Bars / S&R (Support and Resistance) - Search - Right Bars: how many candle bars will be used to calculate S&R (Support & Resistance) Levels, the bigger the number > the more precise and less amount of support and resistance levels will be found.
>>> S&R Search - Custom Resolution: This is a custom timeframe setting specifically for S&R Search, it disregards current chart timeframe. This is great to use for scalping, for example: with main chart set to 1min and the custom timeframe set to 3min or 5min - there will be stronger support/resistance levels with more detailed price action.
---------------------------------------------------------------------------
TA: ADDITIONAL TOOLS //////////////////////////////////////////////////////
>>> Show - MA (Moving Average).
>>> Show - ATR (Average True Range).
---------------------------------------------------------------------------
---------------------------------------------------------------------------
STATS TABLE ///////////////////////////////////////////////////////////////
Stats Table displays all the necessary date about each options setup.
>>> Table positioning
---------------------------------------------------------------------------
===========================================================================
Adding Alerts in TradngView
---------------------------------------------------------------------------
-Add indicator to chart and make sure to check/uncheck which alerts are required, then simply create it.
-Right-click anywhere on the TradingView chart
-Click on Add alert
-Condition: Select this indicator by it’s name
-Immediately below, change it to "alert() function calls only"
-Expiration: Open-ended (that may require higher tier TradingView account, otherwise the alert will need to be occasionally re-triggered)
-Alert name: Whatever you desire
-Hit “Create”
-Note: If you change ANY Settings within the indicator – you must DELETE the current alert and create a new one per steps above, otherwise it will continue triggering alerts per old Settings!
===========================================================================
If you have any questions or issues with the indicator, please message me directly via TradingView.
---------------------------------------------------------------------------
Good Luck! (NOTE: Trading is very risky, past performance is not necessarily indicative of future results, so please trade responsibly!)
ROCE with 3-Year EMAThis Pine Script indicator, "3-Year EMA of Return on Capital Employed (ROCE)," is designed for investors and traders who incorporate both fundamental and technical analysis in their market approach. ROCE is a crucial metric for evaluating the efficiency and profitability of a company's capital employment. Our script enhances this analysis by overlaying a 3-year Exponential Moving Average (EMA) on the ROCE, allowing users to compare current performance against a longer-term trend.
Key Features:
ROCE Calculation: The script calculates the Return on Capital Employed (ROCE) using EBIT (Earnings Before Interest and Taxes) for the Trailing Twelve Months (TTM) and Capital Employed (Total Assets minus Short Term Debt) for the Fiscal Year (FY). This calculation provides a snapshot of how effectively a company is using its capital to generate profits.
3-Year EMA Overlay: The script features a 3-year EMA of the ROCE, providing a smoothed, long-term trend line. This EMA helps in identifying broader trends in a company's operational efficiency and profitability, making it easier to spot deviations from the historical norm.
Customizable for Different Data Frequencies: Whether your data is quarterly, monthly, or weekly, the script is adaptable. The length of the EMA is adjustable to suit the data frequency, ensuring accurate representation over a 3-year period.
Visualization: The ROCE and its 3-year EMA are plotted with distinct colors for easy comparison and analysis. This visual representation aids in quickly assessing the company's current performance against its historical trend.
Customization: Users can adjust the EMA length to match the frequency of their data (e.g., 12 for quarterly, 36 for monthly, 156 for weekly data).
Usage Tips:
Best used on companies with stable and consistent reporting.
Combine with other fundamental and technical indicators fo
r comprehensive analysis.
Disclaimer: This script is provided for informational and educational purposes only and should not be construed as investment advice.
Ichimoku Strategy - Easiest Backtest [A.R.]▓ INTRODUCTION
This indicator allows a new "sandbox" approach to the Ichimoku system allowing to combine several entry, confirmation and exit conditions, to add basic risk management, to be able to backtest the performance of the strategy using a table directly on chart, and automate entry and exit signals using alerts.
▓ DEFINITION
The Ichimoku strategy is a trading system based on technical analysis, using a set of graphical indicators to evaluate the trend, strength and support/resistance levels of a financial asset. It integrates components such as the conversion line (Tenkan), the baseline (Kijun), the cloud delimited by the Senkou Span A and the Senkou Span B (SSA - SSB - Kumo) and the lagging span (Chikou) to provide different trading signals.
▓ ADDED VALUE
Several indicators and strategies concerning Ichimoku are already available on Tradingview, we are publishing this indicator to make this strategy even more accessible, what makes it original:
▪️ Unique Settings Windows, easy-to-read. The settings categories are clearly separated. Some parameters are aligned to avoid having an endless list of parameters to modify. This makes the settings window easy to understand and pleasant to use.
▪️ Sandbox type settings, you can choose 1 or 2 Entry conditions, choose to add 1 Confirmation, choose to add between 1 and 3 Exit Conditions. Dozens of possible configurations.
▪️ Possibility of adding basic Risk Management (TP/SL)
▪️ Backtest table directly on chart that allow to get quickly the results (script execution <1 sec) which makes it practical, allowing dozens of different configurations to be tested in a short period of time
▪️ Monitoring historical and current trades on chart thanks to Boxes and Labels
▓ HOW TO USE
You can try the indicator with default settings but you can also modify backtesting settings and trade Entry conditions, Entry Confirmation, and Exit conditions, also you can decide to add a Stop Loss and/or a Take Profit. Then you can find the stats of the backtesting in a table directly in the top right corner of the chart. Finally you can automate the strategy using Alert conditions. You can find all the settings below:
Initial backtesting settings:
🔹Set up Side: Choose Long|Short, Long or Short
🔹Set up Investment: Choose an amount in $, it simulates the equity / funds on the trading account.
🔹Set up Position Size: Choose an amount in $, it simulates the amount of the position size of each trade. If you want to simulate leverage trading, you can put a Position Size superior to Investment. For exemple Investment = 10000 and Position Size = 20000 simulates a x2 leverage.
🔹Set up your Fee rate %: Each trade entry and trade exit, a % of position size will be deducted from the PnL stats. For example if you choose 0.04% with 10000 Position Size, 4$ will be deducted each trade entry and each trade exit = 8$ fees each trade.
🔹Set up the Start and End date: It allows to backtest the strategy over a period of time, for Example from 01-01-2021 to 01-12-2022. By default the end date is year 2050, the backtest will start to take into account data from Start Date to the current time.
Backtest the main Ichimoku sub-strategies choosing entry conditions:
🔸Cloud Breakouts trading: Choose this Entry condition to start a trade when Price crosses the Cloud Upside (Long) or Downside (Short)
🔸Tenkan x Kijun cross trading: Choose this Entry condition to start a trade when Tenkan (Red line) crosses Kijun (Blue line) Upside (Long) or Downside (Short)
* There is no repaint, a signal is validated after the condition is confirmed at the end of the previous candle. If a signal appears on the chart, it won't ever disappear.
Entry Confirmations:
✔️ Chikou Above or Below price: if you check this setting, Long entry signals will be confirmed only when the Chikou (White Line) is Above the current price and Short entry signals will be confirmed only when the Chikou (White Line) is below the current price. In the Ichimoku system the Chikou is often used to confirm all types of signals.
Exit Conditions:
❌ Cloud Reintegrations: When a trade is open (Long or Short), if the price goes back into the cloud the trade is closed
❌ Reverse Cloud Breakouts: When a Long trade is open, if the price breaks out of the cloud from below the trade is closed. When a Short trade is open, if the price breaks out of the cloud from above the trade is closed.
❌ Reverse Tenkan-Kijun Cross: When a Long trade is open, if the Tenkan crosses Downside the Kijun the trade is closed. When a Short trade is open, if the Tenkan crosses Upside the Kijun the trade is closed.
Basic Risk Management:
⛔️ SL: Choose to set up a Stop Loss
✅ 1 single TP: Choose to set up a Take Profit
Signals:
🔔 Entry/Exit Alerts available: 4 types of alert conditions are available ENTRY LONG, ENTRY SHORT, EXIT LONG, EXIT SHORT. The entry conditions trigger at the beginning of the candle, choose alert frequence = once per bar.
👉 Tips: Easier to find profitable configurations in High Timeframe above H4.
▓ BACKTESTING SYSTEM
The Backtesting system integrated into the script tracks each trade. It allows you to test the strategy over a fixed period between a start date and an end date. It also allows to quickly and directly display on the chart the most important data to determine if a configuration is profitable such as the % PnL, the Max Drawdown, the amount of fees, the risk-reward ratio. It has been designed to be easy and quick to use even for a beginner.
═════════════════════════════════════════════════════════════════════════
The information published here on TradingView is not prohibited, doesn't constitute investment advice, and isn't created solely for qualified investors.
Important to note: The source code of this indicator is not accessible because it benefits from the code of our backtesting system present in other non-public indicators that we protect. Our indicators with the same backtesting system are published in separate publications because putting them together in a single script would considerably slow down the execution of the script.
Forex Master Pattern Screener 2Overview
The Forex Master Pattern Screener 2 is based on the Master Pattern, which includes contraction, expansion, and trend phases. This indicator is designed to identify and visualize market volatility, market phases, multi-timeframe contractions, liquidity points, and pivot calculations. It provides a clear image of the market's expansion and contraction phases. It's based on an alternative form of technical analysis that reveals the psychological patterns of financial markets through three phases.
Unlike the other master pattern indicators that just use highs and lows and aren't as accurate for finding contractions, this one uses actual measures of volatility to find extremely low levels of volatility and has customizable parameters depending on what you want to do.
What is the Forex Master Pattern?
The Forex Master Pattern is a framework that revolves around understanding market cycles, comprising the three main phases: contraction, expansion, and trend.
Contraction Phase: During this phase, the market has low volatility and is consolidating within a narrow range. Institutional volume tends to be low, and it's suggested to avoid trade entries during this period.
Expansion Phase: Volatility starts to increase, and there start to be bigger moves in price. Institutional traders start accumulating positions in this phase, and they might manipulate prices to draw in retail traders, creating liquidity for their own buying or selling goals.
Trend Phase: This final phase completes the market cycle. Institutional traders begin taking profits, leading to a reversal. This triggers panic among retail traders, resulting in liquidations and stops. This generates liquidity for institutional traders to profit, leaving retail traders with overvalued positions.
Value Line:
The "value line" acts as the fair value zone or the neutral belief zone where buyers and sellers agree on fair value. It can be likened to the center of gravity and is created during contraction zones.
Applications:
Identifying these phases and understanding the value lines can help traders determine the market's general direction and make better trading decisions.
This isn't a strategy but a concept explaining market behavior, allowing traders to develop various strategies based on these principles
The contractions, which are based on volatility calculations, can help you find out when big moves will occur, known as expansions.
How traders can use this indicator
1. Identifying Market Phases:
Contraction Phase: Look for periods where the market has low volatility and is contracting, indicated by a narrow range and highlighted by the contraction box. During this phase, traders prepare for a breakout but usually avoid making new trades until a clearer trend emerges.
Expansion Phase: When the indicator signals an expansion, it suggests that the market is moving out of consolidation and may be beginning a new trend. Traders might look for entry points here, anticipating a continuation of the trend.
Trend Phase: As the market enters this phase, traders look for signs of sustained movement in one direction and consider positions that benefit from this trend.
2. Multi-Timeframe Analysis:
By looking at multiple timeframes, traders can get a broader view of the market. For instance, a contraction phase in a shorter timeframe within an expansion phase in a longer timeframe might suggest a pullback in an overall uptrend. This indicator comes with a MTF contraction screener that is customizable.
2. Fair Value Lines:
The fair value acts like a "center of gravity.". Traders could use this as a reference point for understanding market sentiment and potential reversal points. This indicator shows these values in the middle of the contraction boxes.
3. Volatility Analysis:
This indicator's volatility settings can help traders understand the market's current volatility state. High volatility indicates a more active market with larger, faster moves, while low volatility might suggest caution and tighter stop-losses or take-profits. If volatility is contracting, then an expansion is imminent. This indicator shows the volatility with percentile ranks in 0-100 values and also alerts you when volatility is contracting, aka the contraction phase.
Volatility Calculations:
This indicator uses a geometric standard deviation to measure volatility based on historical price data. This metric quantifies the variability of price changes over a specified lookback period and then computes a percentile rank within a defined sample period. This percentile calculation helps evaluate the current volatility compared to historical levels.
Based on the percentile rank, the indicator sets thresholds to determine whether the current volatility is within a range considered "contraction" or not. For example, if there are really low levels of volatility on the percentile rank, then there is currently a contraction phase. The indicator also compares the volatility value against a moving average, where values above the current moving average value signal the expansion phase.
Multi-Timeframe Analysis (MTF):
This indicator comes with a multi-timeframe table that shows contractions for 5 different timeframes, and the table is customizable.
Bands:
This indicator comes with bands that are constructed based on the statistical calculations of the standard deviation applied to the log-transformed closing prices. It is commonly assumed that the distribution of prices fits some type of right-skewed distribution. To remove most of the skewness, you can use a log transformation , which makes the distribution more symmetrical and easier to analyze, thus the use of these bands . These bands are in the 2 standard deviation range. You can use these bands to trade at extreme levels. The band parameter is based on the contraction volatility lookback, which is in the Volatility Model Settings tab.
Ways the bands could be used with the contractions:
1. Identifying Breakout trades:
Contraction Zones: These zones indicate periods of low volatility where the market is consolidating. There are usually narrow price ranges, which are considered a build-up phase before a significant price move in any direction.
Bands: When the contraction zone occurs, you might notice the bands tightening around the price on smaller lookback periods, reflecting the decreased volatility. A continuous widening of the bands could then signal the beginning of an expansion phase, indicating a potential breakout opportunity.
2. Enhancing Trade Timing:
Before the Breakout: During the contraction phase, the bands might move closer together, reflecting the lower volatility. You can monitor this phase closely and prepare for a potential expansion. The bands can provide additional confirmation; for instance, a price move toward one of the bands might show an extreme occurrence and might show what the direction of the breakout could be.
After the breakout: Once the price breaks out of the contraction zone and goes to the expansion phase, and if it coincides with the bands widening significantly, it could reinforce the strength and potential sustainability of the new trend, providing a clearer entry.
3. Price-touching bands during a contraction:
If the price repeatedly touches one of the bands during a contraction phase, it might suggest a buildup of pressure in that direction. For example, if the price is consistently touching the upper band even though the bands are narrow, it might suggest bullish pressure that could occur once the expansion phase begin.
4. Price at the band extreme levels during Expansion:
If the price is at the extreme levels of the bands once the expansion phase occurs, it might indicate unsustainable levels and a low probability of the price continuing beyond those levels. Potentially signaling that a reversal will occur. Some trades could use these extremes to place entries during the expansion phases.
Liquidity Levels:
This script comes with liquidity points, whose functionality goes towards identifying pivotal levels in price action, focusing on swing highs and swing lows in the market. These points represent areas where significant buying (for swing lows) or selling (for swing highs) activity has occurred, implying potential levels or resistance in the price movement.
These liquidity points, often identified as highs and lows, are points where market participants have shown interest in the past. These levels can act as psychological indications where traders might place orders, leading to increased trading activity when these levels are approached or breached. When used with the Forex Master Pattern phases, liquidity levels can enhance trades placed with this indicator. For instance, if the market is expanding and approaches a significant liquidity level, there might be a higher chance of a breakout or reversal, showing a possible entry or exit point.
Liquidity Levels in the Contraction Phase:
Accumulation and Distribution: During the contraction phase, liquidity levels can indicate where huge positions are likely accumulating or distributing quietly. If price is near a known liquidity level and in a contraction phase, it might suggest that a large market player is building a position in anticipation of the next move.
Breakout Points: Liquidity levels can also give clues about where price could go after the breakout from the contraction phase. A break above a liquidity level might indicate a strong move to come as the market overcomes significant selling pressure.
Liquidity Levels in Expansion Phase:
Direct Confirmation: As the expansion phase begins, breaking through liquidity levels can confirm the new trend's direction. If the price moves past these levels with huge volume, it might indicate that the market has enough momentum to continue the trend.
Target Areas: Liquidity levels can act as target areas during the expansion phase. Traders using this indicator could look to take profits if the price approaches these levels, possibly expecting a reaction from the market.
TrendGuard Pullback Trader Signals [Quantigenics]The "TrendGuard Pullback Trader Signals" script, integral to the "TrendGuard Pullback Trader" system, offers a sophisticated suite of trading tools for nearly any market or time frame. Designed to be used alongside the "TrendGuard Pullback Trader Indicators" script, this script is pivotal for identifying Buy/Sell Signals, Profit Target Signals, and Stop Loss Levels.
As with all of our scripts, the "TrendGuard Pullback Trader Signals" script, is designed to work on ANY symbol and time frame. The input parameters can be adjusted to fit your specific trading style.
Methodology and Application:
The script's core methodology lies in identifying primary signals at the onset of a trend and secondary signals during pullbacks or dips. It focuses on pinpointing optimal entry points during market pullbacks, enhancing the "TrendGuard Pullback Trader Indicators" script with well-timed signals for profit targets and stop loss levels.
Technical Composition:
The "TrendGuard Pullback Trader Signals" script combines various technical analysis tools to generate comprehensive trading signals. It calculates stop levels by assessing the highest and lowest bars over a chosen period, defining the market range. Primary signals are derived using a triple exponential moving average (EMA) of logarithmic closing prices, identifying trend changes with stop level plots and directional arrows. For secondary signals, the script uses a sequence of EMAs applied to the average price (HLC3) and an oscillator that measures the extremity of recent price movements, pinpointing potential entry points. The script also incorporates a sideways exit mechanism, comparing short-term and long-term EMAs of the average price to detect significant deviations, suggesting exit opportunities. This layered strategy offers a detailed perspective on market trends, momentum, and possible entry and exit points.
EMA-Based Trend Analysis Algorithm :
Utilizes an advanced algorithm that incorporates exponential moving averages (EMA) with specific length parameters. This algorithm analyzes the slope and direction of EMA lines to identify significant shifts in market trends.
Primary Signal Generation : Logarithmic and Triple EMA Function:
Primary signals are derived from a unique logarithmic function applied to price data, which is then processed through a series of three EMAs with distinct period settings. This combination targets potential trend initiation points by detecting shifts in the logarithmic trend curve.
Dynamic Stop Level Determination :
Employs a methodology involving the calculation of recent high and low price bars, adjusted by a factor that considers market volatility. This factor dynamically alters the sensitivity of the stop levels, aligning them with current market conditions.
Secondary Signal Identification During Pullbacks :
Secondary signals are identified through a complex comparison of the market's relative position to its moving averages. This involves calculating the divergence between price and moving averages, adjusted for the rate of change in the market, to flag strategic entry points during pullbacks.
Composite Market Trend Analysis for Signal Mechanism :
Signal generation integrates a composite of multiple technical indicators, each contributing unique mathematical calculations. This integration enhances the accuracy and reliability of entry and exit signals.
Practical Application in Trading :
> For trade initiation, primary signals are used to identify the start of potential trends, applying a specific mathematical threshold to confirm the trend change. Secondary signals focus on quantifying the pullback depth relative to recent market movements for additional entry opportunities.
> The script's dynamic stop loss adjustment incorporates a calculated moving average of recent highs and lows, providing a responsive and protective mechanism for open positions.
How to Use the Script:
Trade Initiation : Primary signals at trend onset can be used for potential entry points, or to simply establish a trend-bias, to watch for Strategic Entries signals.
Strategic Entries on Pullbacks : Secondary signals provide opportunities for additional entries or scaling into positions during pullbacks within the main trend.
Profit Targets and Exit Strategy : Profit target signals serve as potential exit points. For larger positions, consider partial exits at these targets while adjusting stop loss levels to secure profits, and hold the remaining position for further potential gains.
Dynamic Risk Management : Regularly adjust stop loss levels based on the script's dynamic stop level determination to protect against market reversals and lock in profits.
Integration with TrendGuard Pullback Trader Indicators:
The script is designed and intended to be used in conjunction with the "TrendGuard Pullback Trader Indicators ". This integration ensures a holistic approach to market analysis, combining the strengths of both scripts for a comprehensive understanding of market trends, momentum, and entry points.
Note: The lower indicators are from the 'TrendGuard Pullback Trader Indicators' script, complementing the 'TrendGuard Pullback Trader Signals' script seen here, which generates the 'cloud' and signals on the price chart.
The 'TrendGuard Pullback Traders Indicators” script can be found here :
Input Parameter Settings:
Important Usage Guidance: For seamless integration with its counterpart, the "TrendGuard Pullback Trader Indicators" script, it's crucial to align the input parameter settings across both scripts. When adjusting values from their defaults, ensure that corresponding parameters in both scripts are identically set. This synchronization is key to achieving a cohesive and accurate representation on your charts.
Intra-Bar Order Generation (IntraBar): Determines whether signals are generated within the current bar or only after it closes, enhancing flexibility in signal timing.
Stop Level Strength (StopLvlStr): Sets the strength for calculating stop levels, impacting the sensitivity of the script to market highs and lows for stop placement.
Primary Signal Display (PrimON_OFF): Toggles the visibility of primary signals on the chart, aiding in identifying trend initiation points.
Secondary Signal Display (SecON_OFF): Controls the display of secondary signals for opportunities during pullbacks, allowing traders to capitalize on additional entry points.
Stop Loss Level Display (StopLossLvls): Enables or disables the visualization of stop loss levels, crucial for risk management strategies.
Trend Length (TrendLen): Adjusts the length parameter for the EMA calculations, influencing how the script interprets trend duration and strength.
These parameters allow traders to customize the script’s functionality according to their trading style and preferences, ensuring a tailored approach to signal generation and risk management.
Trade Alerts:
The script includes an advanced alert system designed to notify traders of crucial trading signals. This can Especially be useful when using larger time frames where trade setups can take a longer period of time to develop:
Primary Buy/Sell Alerts: Alerts are triggered at primary signals, indicating potential trend initiation points for entering trades.
Secondary Buy/Sell Alerts: These alerts activate during secondary signals, highlighting opportunities within ongoing trends for strategic entries or exits.
Stop Loss Level Alerts: The script can alert traders when the price reaches or crosses the script-determined stop loss levels, aiding in timely decision-making for risk management.
Sideways Exit Alerts: Alerts for potential exits are generated in sideways market conditions, based on the script’s analysis of average price movements.
To set up these alerts, traders can use TradingView’s alert system to specify the conditions under which they receive notifications, such as when a certain shape (e.g., arrow up for buy, arrow down for sell) appears on the chart. This feature helps traders stay informed and react promptly to the dynamic market conditions.
The "TrendGuard Pullback Trader Signals " script is a meticulously crafted tool, essential for traders aiming to enhance their market analysis and decision-making across diverse trading environments. While the script offers advanced functionalities, it reaches its full potential when used alongside the "TrendGuard Pullback Trader Indicators" script. Traders are advised to familiarize themselves with both scripts for a well-rounded trading strategy.
As always, remember that trading involves risks and past performance is not indicative of future results.
You can see the “Author’s instructions" below to get immediate access to TrendGuard Pullback Trader Signals & the rest of the “Quantigenics Premium Indicator Suite”.
YinYang TrendTrend Analysis has always been an important aspect of Trading. There are so many important types of Trend Analysis and many times it may be difficult to identify what to use; let alone if an Indicator can/should be used in conjunction with another. For these exact reasons, we decided to make YinYang Trend. It is a Trend Analysis Toolkit which features many New and many Well Known Trend Analysis Indicators. However, everything in there is added specifically for the reason that it may work well in conjunction with the other Indicators prevalent within. You may be wondering, why bother including common Trend Analysis, why not make everything unique? Ideally, we would, however, you need to remember Trend Analysis may be one of the most common forms of charting. Therefore, many other traders may be using similar Trend Analysis either through plotting manually or within other Indicators. This all boils down to Psychology; you are trading against other traders, who may be seeing some of the similar information you are, and therefore, you may likewise want to see this information. What affects their trading decisions may affect yours as well.
Now enough about Trend Analysis, what is within this Indicator, and what does it do? Well, first let’s quickly mention all of its components, then we will, through a Tutorial, discuss each individually and finally how each comes together as a cohesive whole. This Indicator features many aspects:
Bull and Bear Signals
Take Profit Signals
Bull and Bear Zones
Information Tables displaying: (Boom Meter, Bull/Bear Strength, Yin/Yang State)
16 Cipher Signals
Extremes
Pivots
Trend Lines
Custom Bollinger Bands
Boom Meter Bar Colors
True Value Zones
Bar Strength Indexes
Volume Profile
There are many things to cover within our Tutorial so let's get started, chronologically from the list above.
Tutorial:
Bull and Bear Signals:
We’ve zoomed out quite a bit for this example to help give you a broader aspect of how these Bull and Bear signals work. When a signal appears, it is displaying that there may be a large amount of Bullish or Bearish Trend Analysis occurring. These signals will remain in their state of Bull or Bear until there is enough momentum change that they change over. There are a couple Options within the Settings that dictate when/where/why these signals appear, and this example is using their default Settings of ‘Medium’. They are, Purchase Speed and Purchase Strength. Purchase Speed refers to how much Price Movement is needed for a signal to occur and Purchase Strength refers to how many verifications are required for a signal to occur. For instance:
'High' uses 15 verifications to ensure signal strength.
'Medium' uses 10 verifications to ensure signal strength.
'Low' uses 5 verifications to ensure signal strength.
'Very Low' uses 3 verifications to ensure signal strength.
By default it is set to Medium (10 verifications). This means each verification is worth 10%. The verifications used are also relevant to the Purchase Speed; meaning they will be verified faster or slower depending on its speed setting. You may find that Faster Speeds and Lower Verifications may work better on Higher Time Frames; and Slower Speeds and Higher Verifications may work better on Lower Time Frames.
We will demonstrate a few examples as to how the Speed and Strength Settings work, and why it may be beneficial to adjust based on the Time Frame you’re on:
In this example above, we’ve kept the same Time Frame (1 Day), and scope; but we’ve changed Purchase Speed from Medium->Fast and Purchase Strength from Medium-Very Low. As you can see, it now generates quite a few more signals. The Speed and Strength settings that you use will likely be based on your trading style / strategy. Are you someone who likes to stay in trades longer or do you like to swing trade daily? Likewise, how do you go about identifying your Entry / Exit locations; do you start on the 1 Day for confirmation, then move to the 15/5 minute for your entry / exit? How you trade may determine which Speed and Strength settings work right for you. Let's jump to a lower Time Frame now so you can see how it works on the 15/5 minute.
Above is what BTC/USDT looks like on the 15 Minute Time Frame with Purchase Speed and Strength set to Medium. You may note that the signals require a certain amount of movement before they get started. This is normal with Medium and the amount of movement is generally dictated by the Time Frame. You may choose to use Medium on a Lower Time Frame as it may work well, but it may also be best to change it to a little slower.
We are still on the 15 Minute Time Frame here, however we simply changed Purchase Speed from Medium->Slow. As you can see, lots of the signals have been removed. Now signals may ‘hold their ground’ for much longer. It is important to adjust your Purchase Speed and Strength Settings to your Time Frame and personalized trading style accordingly.
Above we have now jumped down to the 5 Minute Time Frame. Our Purchase Speed is Slow and our Purchase Strength is Medium. We can see it looks pretty good, although there is some signal clustering going on in the middle there. If we change our Settings, we may be able to get rid of that.
We have changed our Purchase Speed from Slow->Snail (Slowest it can go) and Purchase Strength from Medium->Very Low (Lowest it can go). Changing it from Slow-Snail helped get rid of the signal clustering. You may be wondering why we lowered the Strength from Medium->Very Low, rather than going from Medium->High. This is a use case scenario and one you’ll need to decide for yourself, but we noticed when we changed the Speed from Slow->Snail that the signal clustering was gone, so then we checked both High and Very Low for Strengths to see which produced the best looking signal locations.
Please remember, you don’t have to use it the exact way we’ve displayed in this Tutorial. It is meant to be used to suit your Trading Style and Strategy. This is why we allow you to modify these settings, rather than just automating the change based on Time Frames. You’ll likely need to play around with it, as you’ll notice different settings may work better on certain pairs and Time Frames than others.
Take Profit Signals:
We’ve reset our Purchase Settings, everything is on defaults right now at Medium. We’ve enabled Take Profit signals. As you can see there are both Take Profit signals for the Bulls and the Bears. These signals are not meant to be used within automation. In fact, none of this indicator is. These signals are meant to show there has been a strong change in momentum, to such an extent that the signal may switch from its current (Bull or Bear) and now may be a good time to Take Profit. Your Take Profit Settings likewise has a Speed and Strength, and you can set them differently than your Purchase Settings. This is in case you want to Take Profit in a different manner than your Purchase Signals. For instance:
In the example above we’ve kept Purchase Strength and Speed at Medium but we changed our Take Profit Speed from Medium->Snail and our Take Profit Strength from medium->Very Low. This greatly reduces the amount of Take Profit signals, and in some cases, none are even produced. This form of Take Profit may act more as a Trailing Take Profit that if it’s not hit, nothing appears.
In this example we have changed our Purchase Speed from Medium->Fast, our Purchase Strength from Medium->Very Low. We’ve also changed our Take Profit Speed from Snail->Medium and kept our Take Profit Strength on Very Low. Now we may get our signals quicker and likewise our Take Profit may be more rare. There are many different ways you can set up your Purchase and Take Profit Settings to fit your Trading Style / Strategy.
Bull and Bear Zones:
We have disabled our Take Profit locations so that you can see the Bull and Bear Zones. These zones change color when the Signals switch. They may represent some strong Support and Resistance locations, but more importantly may be useful for visualizing changes in momentum and consolidation. These zones allow you to see various Moving Averages; and when they start to ‘fold’ (cross) each other you may see changes in momentum. Whereas, when they’re fully stretched out and moving all in the same direction, it can provide insight that the current rally may be strong. There is also the case where they look like they’re ‘twisted’ together. This happens when all of the Moving Averages are very close together and may be a sign of Consolidation. We will go over a few examples of each of these scenarios so you can understand what we’re referring to.
In this example above, there are a few different things happening. First we have the yellow circle, where the final and slowest Moving Average (MA) crossed over and now all of the MA’s that form the zone are Bullish. You can see this in the white circle where there are no MA’s that are crossing each other. Lastly, within the blue circle, we can see how some of the faster MA’s are crossing under each other. This is a bullish momentum change. The Faster moving MA’s will always be the first ones to cross before the Slower ones do. There is a color scheme in place here to represent the Speed of the MA within the Zone. Light blue is the fastest moving Bull color -> Light Green and finally -> Dark Green. Yellow is the fastest moving Bear color -> Orange and finally -> Red / Dark Red within the Zone.
Next we will review a couple different examples of what Consolidation looks like and why it is very important to look out for. Consolidation is when Most, if not All of the MA’s are very tightly ‘twisted’ together. There is very little spacing between almost all of the MA’s in the example above; highlighted by the white circle. Consolidation is important as it may indicate a strong price movement in either direction will occur soon. When the price is consolidating it means it has had very little upwards or downwards movement recently. When this happens for long enough, MA’s may all get very similar in value. This may cause high volatility as the price tries to break out of Consolidation. Let's look at another example.
Above we have two more examples of what Consolidation looks like and how high Volatility may occur after the Consolidation is broken. Please note, not all Consolidation will create high Volatility but it is something you may want to look out for.
Information Tables displaying: (Boom Meter, Bull/Bear Strength, Yin/Yang State):
Information tables are a very important way of displaying information. It contains 3 crucial pieces of information:
Boom Meter
Bull/Bear Strength
Yin/Yang State
Boom Meter is a meter that goes from 0-100% and displays whether the current price is Dumping (0 - 29%), Consolidating (30 - 70%) or Pumping (71 - 100%). The Boom Meter is meant to be a Gauge to how the price is currently fairing. It is composed of ~50 different calculations that all vary different weights to calculate its %. Many of the calculations it uses are likewise used in other things, such as the Bull/Bear Strength, Bull/Bear Zone MA cross’, Yin/Yang State, Market Cipher Signals, RSI, Volume and a few others. The Boom Meter, although not meant to be used solely to make purchase decisions, may give you a good idea of current market conditions considering how many different things it evaluates.
Bull/Bear Strength is relevant to your Purchase Speed and Strength. It displays which state it is currently in, and the % it is within that state. When a % hits 0, is when the state changes. When states change, they always start at 100% initially and will go down at the rate of Purchase Strength (how many verifications are needed). For instance, if your Purchase Strength is set to ‘Medium’ it will move 10% per verification +/-, if it is set to High, it will move 6.67% per verification +/-. Bull/Bear Strength is a good indicator of how well that current state is fairing. For instance if you started a Long when the state changed to Bull and now it is currently at Bull with 20% left, that may be a good indication it is time to get out (obviously refer to other data as well, but it may be a good way to know that the state is 20% away from transitioning to Bear).
Yin/Yang State is the strongest MA cross within our Indicator. It is unique in the sense that it is slow to change, but not so much that it moves slowly. It isn’t as simple as say a Golden/Death Cross (50/200), but it crosses more often and may hold similar weight as it. Yin stands for Negative (Bearish) and Yang stands for Positive (Bullish). The price will always be in either a state of Yin or Yang, and just because it is in one, doesn’t mean the price can’t/won’t move in the opposite direction; it simply means the price may be favoring the state it is in.
16 Cipher Signals:
Cipher Signals are key visuals of MA cross’ that may represent price movement and momentum. It would be too confusing and hard to decipher these MA’s as lines on a chart, and therefore we decided to use signals in the form of symbols instead. There are 12 Standard and 4 Predictive/Confirming Cipher signals. The Standard Cipher signals are composed of 6 Bullish and 6 Bearish (they all have opposites that balance each other out). There can never be 2 of the same signal in a row, as the Bull and Bear cancel each other out and it's always in a state of one or the other. When all 6 Bullish or Bearish signals appear in a row, very closely together, without any of the opposing signals it may represent a strong momentum movement is about to occur.
If you refer to the example above, you’ll see that the 6 Bullish Cipher signals appeared exactly as mentioned above. Shortly after the Green Circle appeared, there was a large spike in price movement in favor of the Bulls. Cipher signals don’t need to appear in a cluster exactly like the white circle in this photo for momentum to occur, but when it does, it may represent volatility more than if it is broken up with opposing signals or spaced out over a longer time span.
Above is an example of the opposite, where all 6 Bearish Cipher signals appeared together without being broken by a Bullish Cipher signal or being too far spaced out. As you can see, even though past it there was a few Bullish signals, they were quickly reversed back to Bearish before a large price movement occurred in favor of the Bears.
In the example above we’ve changed Cipher signals to Predictive and Confirming. Support Crosses (Green +) and Blood Diamonds (Red ♦) are the normal Cipher Signals that appear within the Standard Set. They are the first Cipher Signal that appears and are the most common ones as well. However, just because they are the first, that doesn’t mean they aren’t a powerful Cipher signal. For this reason, there are Predictive and Confirming Cipher signals for these. The Predictive do just that, they appear slightly sooner (if not the same bar) as the regular and the Confirming appear later (1+ bars usually). There will be times that the Predictive appears, but it doesn’t resort to the Regular appearing, or the Regular appears and the Confirming doesn’t. This is normal behavior and also the purpose of them. They are meant to be an indication of IF they may appear soon and IF the regular was indeed a valid signal.
Extremes:
Extremes are MA’s that have a very large length. They are useful for seeing Cross’ and Support and Resistance over a long period of time. However, because they are so long and slow moving, they might not always be relevant. It’s usually advised to turn them on, see if any are close to the current price point, and if they aren’t to turn them off. The main reason being is they stretch out the chart too much if they’re too far away and they also may not be relevant at that point.
When they are close to the price however, they may act as strong Support and Resistance locations as circled in the example above.
Pivots:
Pivots are used to help identify key Support and Resistance locations. They adjust on their own in an attempt to keep their locations as relevant as possible and likewise will adjust when the price pushes their current bounds. They may be useful for seeing when the Price is currently testing their level as this may represent Overbought or Oversold. Keep in mind, just because the price is testing their levels doesn’t mean it will correct; sometimes with high volatility or geopolitical news, movement may continue even if it is exhibiting Overbought or Oversold traits. Pivots may also be useful for seeing how far the price may correct to, giving you a benchmark for potential Take Profit and Stop Loss locations.
Trend Lines:
Trend Lines may be useful for identifying Support and Resistance locations on the Vertical. Trend Lines may form many different patterns, such as Pennants, Channels, Flags and Wedges. These formations may help predict and drive the price in specific directions. Many traders draw or use Indicators to help create Trend Lines to visualize where these formations will be and they may be very useful alone even for identifying possible Support and Resistance locations.
If you refer to the previous example, and now to this example, you’ll notice that the Trend Line that supported it in 2023 was actually created in June 2020 (yellow circle). Trend Lines may be crucial for identifying Support and Resistance locations on the Vertical that may withhold over time.
Custom Bollinger Bands:
Bollinger Bands are used to help see Movement vs Consolidation Zones (When it's wide vs narrow). It's also very useful for seeing where the correction areas may be. Price may bounce between top and bottom of the Bollinger Bands, unless in a pump or dump. The Boom Meter will show you whether it is currently: Dumping, Consolidation or Pumping. If combined with Boom Meter Bar Colors it may be a good indication if it will break the Bollinger Band (go outside of it). The Middle Line of the Bollinger Band (White Line) may be a very strong support / resistance location. If the price closes above or below it, it may be a good indication of the trend changing (it may indicate one of the first stages to a pump or dump). The color of the Bollinger Bands change based on if it is within a Bull or Bear Zone.
What makes this Bollinger Band special is not only that it uses a custom multiplier, but it also incorporates volume to help add weight to the calculation.
Boom Meter Bar Colors:
Boom Meter Bar Colors are a way to see potential Overbought and Oversold locations on a per bar basis. There are 6 different colors within the Boom Meter bar colors. You have:
Overbought and Very Bullish = Dark Green
Overbought and Slightly Bullish = Light Green
Overbought and Slight Bearish = Light Red
Oversold and Very Bearish = Dark Red
Oversold and Slightly Bearish = Orange
Oversold and Slightly Bullish = Light Purple
When there is no Boom Meter Bar Color prevalent there won’t be a color change within the bar at all.
Just because there is a Boom Meter Bar Color change doesn’t mean you should act on it purchase or sell wise, but it may be an indication as to how that bar is fairing in an Overbought / Oversold perspective. Boom Meter Bar Colors are mainly based on RSI but do take in other factors like price movement to determine if it is Overbought or Oversold. When it comes to Boom Meter Bar Color, you should take it as it is, in the sense that it may be useful for seeing how Individual bars are fairing, but also note that there may be things such as:
When there is Very Overbought (Dark Green) or Very Oversold (Dark Red), during massive pump or dumps, it will maintain this color. However, once it has lost ‘some’ momentum it will likely lose this color.
When there has been a massive Pump or Dump, and there is likewise a light purple or light red, this may mean there is a correction or consolidation incoming.
True Value Zones:
True Value zones are our custom way of displaying something that is similar to a Bollinger Band that can likewise twist like an MA cross. The main purpose of it is to display where the price may reside within. Much like a Bollinger Band it has its High and Low within its zone to specify this location. Since it has the ability to cross over and under, it has the ability to specify what it thinks may be a Bullish or Bearish zone. This zone uses its upper level to display what may be a Resistance location and its lower level to display what may be a Support location. These Support and Resistance locations are based on Momentum and will move with the price in an attempt to stay relevant.
You may use these True Values zones as a gauge of if the price is Overbought or Oversold. When the price faces high volatility and moves outside of the True Value Zones, it may face consolidation or likewise a correction to bring it back within these zones. These zones may act as a guideline towards where the price is currently valued at and may belong within.
Bar Strength Indexes:
Bar Strength Indexes are our way of ranking each bar in correlation to the last few. It is based on a few things but is highly influenced on Open/Close/High/Low, Volume and how the price has moved recently. They may attempt to ‘rate’ each bar and how Bullish/Bearish each of these bars are. The Green number under the bar is its Bullish % and the Red number above the bar is its Bearish %. These %’s will always equal 100% when combined together. Bar Strength Indexes may be useful for seeing when either Bullish or Bearish momentum is picking up or when there may be a reversal / consolidation.
These Bar Strength Indexes may allow you to decipher different states. If you refer to the example above, you may notice how based on how the numbers are changing, you may see when it has entered / exited Bullish, Bearish and Consolidation. Likewise, if you refer to the current bar (yellow circle), you can see that the Bullish % has dropped from 93 to 49; this may be signifying that the Bullish movement is losing momentum. You may use these changes in Bar Indexes as a guide to when to enter / end trades.
Volume Profile:
Volume Profile has been something that has been within TradingView for quite some time. It is a very useful way of seeing at what Horizontal Price there has been the most volume. This may be very useful for seeing not only Support and Resistance locations based on Volume, but also seeing where the majority of Limit Orders are placed. Limit Orders are where traders decide they want to either Buy / Sell but have the order placed so the trade won’t happen until the price reaches a certain amount. Either through many orders from many traders, or a single order from a ‘Whale’ (trader with a lot of capital); you may see Support and Resistance at specific Price Points that have large Volume.
Many Volume Profile Indicators feature a breakdown of all the different locations of volume, along with a Point Of Control (POC) line to designate where the most Volume has been. To try and reduce clutter within our already very saturated Toolkit Indicator, we’ve decided to strip our Volume Profile to only display this POC line. This may allow you to see where the crucial Volume Support and Resistance is without all of the clutter.
You may be wondering, well how important is this Volume Profile POC line and how do I go about using it? Aside from it being a gauge towards where Support and Resistance may be within Volume, it may also be useful for identifying good Long/Short locations. If you think of the line as a ‘Battle’ between the Bulls and Bears, they’re both fighting over that line. The Bears are wanting to break through it downwards, and the Bulls are wanting to break through it upwards. When one side has temporarily won this battle, this means they may have more Capital to push the price in their direction. For instance, if both the Bulls and the Bears are fighting over this POC price, that means the Bears think that price is a good spot to sell; however, the Bulls also deem that price to be a good point to buy. If the Bulls were to win this battle, that means the Bears either canceled their orders to reevaluate, or all of their orders have been completed from the Bulls buying them all. What may happen after that is, if the Bulls were able to purchase all of these Limit Sell Orders, then they may still have more Capital left to continue to pressure the price upwards. The same may be true for if the Bears were to win this ‘Battle’.
How to use YinYang Trend as a cohesive whole:
Hopefully you’ve read and understand how each aspect of this Indicator works on its own, as knowing how/what they each do is important to understanding how it is used as a cohesive whole. Due to the fact that this Toolkit of an Indicator displays so much data, you may find it easier to use and understand when you’re zoomed in a little, somewhat like we are in this example above.
If we refer to the example above, you may like us, deduce a few things:
1. The current price may be VERY Overbought. This may be seen by a few different things:
The Boom Meter Bar Colors have been exhibiting a Dark Green color for 6 bars in a row.
The price has continuously been moving the High (red) Pivot Upwards.
Our Boom Meter displays ‘Pumping’ at 100%.
The price broke through a Downward Trend Line that was created in February of 2022 at 45,000 like it was nothing.
The Bar Strength Index hit a Bullish value of 93%.
The Price broke out of the Bollinger Bands and continues to test its upper levels.
The Low is much greater than our fastest moving MA that creates the Purchase Zones.
The Price is vastly outside of the True Value Zone.
The Bar Strength Index of our current bar is 50% bullish, which is a massive decrease from the previous bar of 93%. This may indicate that a correction is coming soon.
2. Since we’ve identified the current price may be VERY Overbought, next we need to identify if/when/to where it may correct to:
We’ve created a new example here to display potential correction areas. There are a few places it has the ability to correct to / within:
The downward Trend Line (red) below the current bar sitting currently at 32,750. This downward Trend Line is at the same price point as the Fastest MA of our Purchase Zone which may provide some decent Support there.
Between two crucial Pivot heights, within a zone of 30,000 to 31,815. This zone has the second fastest MA from the Purchase Zone right near the middle of it at 31,200 which may act as a Support within the Zone. Likewise there is the Bollinger Band Basis which is also resting at 30,000 which may provide a strong Support location here.
If 30,000 fails there may be a correction all the way to the bottom of our True Value Zone and the top of one of our Extremes at 27,850.
If 27,850 fails it may correct all the way to the bottom of our Purchase Zone / lowest of our Extremes at 27,350.
If all of the above fails, it may test our Volume Profile POC of 26,430. If this POC fails, the trend may switch to Bearish and continue further down to lower levels of Support.
The price can always correct more than the prices mentioned above, but considering overall this Indicator is favoring the Bulls, we will tailor this analysis in Favor of the Bullish Momentum maintaining even during this correction. For these reasons, we think the price may correct between the 30,000 and 31,815 zone before continuing upwards and maintaining this Bullish Momentum.
Please note, these correction estimates are just that, they’re estimates. Aside from the fact that the price is very overbought right now and our Bar Strength Index may be declining (bar hasn’t closed yet); the Boom Meter Strength remains at 100%, meaning there may not be much Bearish momentum changes happening yet. We just want to show you how an Preemptive analysis may be done before there are even Bearish Cipher Signals appearing.
Using this Indicator, you may be able to decipher Entry and Exits. In the previous example, we went over how you may use it to see where a correction (Exit / Take Profit) may be and how far this correction may go. In this example above we will be discussing how to identify Entry locations. We will be discussing a Bullish Buy entry but the same rules apply for a Bearish Sell Entry just the opposite with the Cipher Signals.
If you refer to where we circled in white, this is where the Purchase Zones faced Consolidation. When the Purchase Zones all get tight and close together like that, this may represent Volatility and Momentum in either direction may occur soon.
This was then followed by all 6 of the Standard Cipher Signals closely in succession to each other. This means the Momentum may be favoring the Bulls. If this was likewise all 6 of the Bearish Cipher Signals closely in succession, than the momentum change would favor the Bears.
If you were looking for an entry, and you saw Consolidation with the Purchase Zones and then shortly after you saw the Green Circle and Blue Flag (they can swap order); this may now be a good Entry location.
We will conclude this Tutorial here. Hopefully this has taught you how this Trend Analysis Toolkit may help you locate multiple different types of important Support and Resistance locations; as well as possible Entry and Exit locations.
Settings:
1. Bull/Bear Zones:
1.1. Purchase Speed (Bull/Bear Signals and Take Profit Signals):
Speed determines how much price movement is needed for a signal to occur.
'Sonic' uses the extremities to try and get you the best entry and exit points, but is so quick, its speed may reduce accuracy.
'Fast' may attempt to capitalize on price movements to help you get SOME or attempt to lose LITTLE quickly.
'Medium' may attempt to get you the most optimal entry and exit locations, but may miss extremities.
'Slow' may stay in trades until it is clear that momentum has changed.
'Snail' may stay in trades even if momentum has changed. Snail may only change when the price has moved significantly (This may result in BIG gains, but potentially also BIG losses).
1.2. Purchase Strength (Bull/Bear Signals and Take Profit Signals):
Strength ensures a certain amount of verifications required for signals to happen. The more verifications the more accurate that signal is, but it may also change entry and exit points, and you may miss out on some of the extremities. It is highly advised to find the best combination between Speed and Strength for the TimeFrame and Pair you are trading in, as all pairs and TimeFrames move differently.
'High' uses 15 verifications to ensure signal strength.
'Medium' uses 10 verifications to ensure signal strength.
'Low' uses 5 verifications to ensure signal strength.
'Very Low' uses 3 verifications to ensure signal strength.
2. Cipher Signals:
Cipher Signals are very strong EMA and SMA crosses, which may drastically help visualize movement and help you to predict where the price will go. All Symbols have counter opposites that cancel each other out (YinYang). Here is a list, in order of general appearance and strength:
White Cross / Diamond (Predictive): The initial indicator showing trend movement.
Green Cross / Diamond (Regular): Confirms the Predictive and may add a fair bit of strength to trend movement.
Blue Cross / Diamond (Confirming): Confirms the Regular, showing the trend might have some decent momentum now.
Green / Red X: Gives momentum to the current trend direction, possibly confirming the Confirming Cross/Diamond.
Blue / Orange Triangle: may confirm the X, Possible pump / dump of decent size may be coming soon.
Green / Red Circle: EITHER confirms the Triangle and may mean big pump / dump is potentially coming, OR it just hit its peak and signifies a potential reversal correction. PAY ATTENTION!
Green / Red Flag: Oddball that helps confirm trend movements on the short term.
Blue / Yellow Flag: Oddball that helps confirm trend movements on the medium term (Yin / Yang is the long term Oddball).
3. Bull/Bear Signals:
Bear and Bull signals are where the momentum has changed enough based on your Purchase Speed and Strength. They generally represent strong price movement in the direction of the signal, and may be more reliable on higher TimeFrames. Please don’t use JUST these signals for analysis, they are only meant to be a fraction of the important data you are using to make your technical analysis.
4. Take Profit Signals:
Take Profit signals are guidelines that momentum has started to change back and now may be a good time to take profit. Your Take Profit signals are based on your Take Profit Speed and Strength and may be adjusted to fit your trading style.
5. Information Tables:
Information tables display very important data and help to declutter the screen as they are much less intrusive compared to labels. Our Information tables display: Boom Meter, Purchase Strength of Bull/Bear Zones and Yin/Yang State.
Boom Meter: Uses over 50 different calculations to determine if the pair is currently 'Dumping' (0-29%), 'Consolidating' (30-70%), or 'Pumping' (71-100%).
Bull / Bear Strength: Shows the strength of the current Bull / Bear signal from 0-100% (Signals start at 100% and change when they hit 0%). The % it moves up or down is based on your 'Purchase Strength'.
Yin / Yang state: Is one of the strongest EMA/SMA crosses (long term Oddball) within this Indicator and may be a great indication of which way the price is moving. Do keep in mind if the price is consolidating when changing state, it may have the highest chance of switching back also. Once momentum kicks in and there is price movement the state may be confirmed. Refer to other Cipher Symbols, Extremes, Trend, BOLL, Boom %, Bull / Bear % and Bar colors when Bull / Bear Zones are consolidating and Yin / Yang State changes as this is a very strong indecision zone.
6. Bull / Bear Zones:
Our Bull / Bear zones are composed of 8 very important EMA lengths that may act as not only Support and Resistance, but they help to potentially display consolidation and momentum change. You can tell when they are getting tight and close together it may represent consolidation and when they start to flip over on each other it may represent a change in momentum.
7. MA Extremes:
Our MA Extremes may be 3 of the most important long term moving averages. They don’t always play a role in trades as sometimes they’re way off from the price (cause they’re extreme lengths), but when they are around price or they cross under or over each other, it may represent large changes in price are about to occur. They may be very useful for seeing strong resistance / support locations based on price averages. Extremes may transition from a Support to a Resistance based on its position above or below them and how many times the price has either bounced up off them (Supporting) or Bounced back down after hitting them (Resistance).
8. Pivots:
Pivots may be a very important indicator of support and resistance for horizontal price movement. Pivots may represent the current strongest Support and Resistance. When the Pivot changes, it means a new strong Support or Resistance has been created. Sometimes you'll notice the price constantly pushes the pivot during a massive Pump or Dump. This is normal, and may indicate high levels of volatility. This generally also happens when the price is outside of the Bollinger Bands and is also Over or Undervalued. The price usually consolidates for a while after something like this happens before more drastic movement may occur.
9. Trend Lines:
Trend lines may be one of the best indicators of support and resistance for diagonal price movement. When a Trend Line fails to hold it may be a strong indication of a dump. Keep a close eye to where Upward and Downward Trend Lines meet. Trend lines can create different trading formations known as Pennants, Flags and Wedges. Please familiarize yourself with these formations So you know what to look for.
10. Bollinger Bands (BOLL):
Bollinger Bands may be very useful, and ours have been customized so they may be even more accurate by using a modified calculation that also incorporates volume.
Bollinger Bands may be used to see Movement vs Consolidation Zones (When it’s wide vs narrow). It also may be very useful for seeing where the correction areas are likely to be. Price may bounce between top and bottom of the BOLL, unless perhaps in a pump or dump. The Boom Meter may show you whether it is currently: Dumping, Consolidation or Pumping, along with Boom Meter Bar Colors, may be a good indication if it will break the BOLL. The Middle Line of the BOLL (White Line) may be a very strong support / resistance line. If the price closes above or below it, it may be a good indication of the trend changing (it may be one of the first stages to a pump or dump).
11. Boom Meter Bar Colors:
Boom Meter bar colors may be very useful for seeing when the bar is Overbought or Underbought. There are 6 different types of boom meter bar colors, they are:
Dark Green: RSI may be very Overbought and price going UP (May be in a big pump. NOTICE, chance of small dump correction if Cherry Red bar appears).
Light Green: RSI may be slightly Overbought and price going UP (chance of small pump).
Light Purple: RSI may be very Underbought and price going UP (May have chance of small correction).
Dark Red: RSI may be very Underbought and price going DOWN (May be in a big dump. NOTICE, chance of small pump correction if Light Purple bar appears).
Light Orange: RSI may be slightly Underbought and price going DOWN (chance of small dump).
Cherry Red: RSI may be very Overbought and price going DOWN (Chance of small correction).
12. True Value Zone:
True Value Zones display zones that represent ranges to show what the price may truly belong within. They may be very useful for knowing if the Price is currently not valued correctly, which generally means a correction may happen soon. True Value Zones can swap from Bullish to Bearish and are represented by Red for Bearish and Green for Bullish. For example, if the price is ABOVE and OUTSIDE of the True Value Zone, this means it may be very overvalued and might correct to go back inside the True Value Zone. This correction may be done by either dumping in price back into the zone, or consolidating horizontally back into it over a longer period of time. Vice Versa is also true if it is BELOW and OUTSIDE of the True Value Zone.
13. Bar Strength Index:
Bar Strength Index may display how Bullish/Bearish the current bar is. The strength is important to help see if a pump may be losing momentum or vice versa if a dump may correct. Keep in mind, the Bar Strength Index does a small 'refresh' to account for new bars. It may help to keep the Index more accurate.
14. Volume Profile:
Volume Profiles may be important to know where the Horizontal Support/Resistance is in Price base on Volume. Our Volume Profile may identify the point where the most volume has occurred within the most relevant timeframe. Volume Profiles are helpful at identifying where Whales have their orders placed. The reason why they are so helpful at identifying whales is when the volume is profiled to a specific area, there may likely be lots of Limit Buy and/or Sells around there. Limit Buys may act as Support and Limit Sells may act as Resistance. It may be very useful to know where these lie within the price, similar to looking at Order Book Data for Whale locations.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Auto Trailing stoploss By InvestYourAsset💥The Auto Trailing Stop-Loss indicator is a technical indicator that uses the ATR (Average True Range) to calculate a trailing stop-loss for both long and short positions.
💥The signals according to the indicator allows traders to exit from the position before its too late! The indicator can be used to determine when to enter and exit trades.
💥To use the indicator, you simply need to set the input parameters to suit your trading style and risk tolerance. The default values for the parameters are:
p: The ATR period (14)
q: The stop period (20)
x: The multiplier used to calculate the initial high and initial low (1.5)
Calculations:
📈Calculates the ATR using the specified period you can modify ATR period according to your trading style.
📈Calculates the initial high and low stop levels based on the highest high and lowest low over the user defined ATR period.
📈Calculates short and long stoploss levels using the initial high and low stops.
💥Once you have set the input parameters according to your trading style whether you are a day trader or a swing trader, the indicator will plot the short stoploss, long stoploss, and stoploss hit signals on your chart.
💥You can use the indicator to enter and exit trades in a various ways.
For example,
🚀 you could enter a long trade when the price crosses above both red and green lines plotted on the chart. (or when price crosses over both short stoploss and long stoploss.) You could also use the indicator to secure your profits by moving your stop-loss up as the price moves in your favor.
Here is an example of how you could use the indicator to enter and exit trades:
🚀Enter a long trade when the price crosses above the red line or short stoploss.
✅keep Moving your stop-loss upward with the long stoploss or green line.
✅Exit the trade when the price crosses below the long stoploss or green line.
💥You can also use the indicator to protect your existing trades. For example, if you are already in a long trade, you could move your stop-loss up to the short stop when the price moves up 10%. This will help you to protect your profits in case the price starts to move against you.
💥💥some additional tips for using the Auto Trailing Stop-Loss indicator:
✅Use the indicator in conjunction with other technical indicators or your own trading strategy to generate entry and exit signals.
✅Backtest your trading strategy before using it live to make sure that it is profitable.
✅Use the indicator to protect your profits by moving your stop-loss up as the price moves in your favor.
✅ Always follow risk management rules and manage your position sizing according to your risk appetite.
✅ Be aware of the overall trend direction. If the trend is up, you should be looking for bullish reversals or continuations. If the trend is down, you should be looking for bearish reversals or continuations.
This script essentially provides a visual representation of a trading strategy that automatically adjusts stop-loss levels based on market volatility (ATR). It also includes signals for entering long or short positions and visually highlights these signals on the chart.
📣📣Follow us for timely updates regarding future indicators and give it a like if you appreciate the work.📣📣
Risk Reward Optimiser [ChartPrime]█ CONCEPTS
In modern day strategy optimization there are few options when it comes to optimizing a risk reward ratio. Users frequently need to experiment and go through countless permutations in order to tweak, adjust and find optimal in their data.
Therefore we have created the Risk Reward Optimizer.
The Risk Reward Optimizer is a technical tool designed to provide traders with comprehensive insights into their trading strategies.
It offers a range of features and functionalities aimed at enhancing traders' decision-making process.
With a focus on comprehensive data, it is there to help traders quickly and efficiently locate Risk Reward optimums for inbuilt of custom strategies.
█ Internal and external Signals:
The script can optimize risk to reward ratio for any type of signals
You can utilize the following :
🔸Internal signals ➞ We have included a number of common indicators into the optimizer such as:
▫️ Aroon
▫️ AO (Awesome Oscillator)
▫️ RSI (Relative Strength Index)
▫️ MACD (Moving Average Convergence Divergence)
▫️ SuperTrend
▫️ Stochastic RSI
▫️ Stochastic
▫️ Moving averages
All these indicators have 3 conditions to generate signals :
Crossover
High Than
Less Than
🔸External signal
▫️ by incorporating your own indicators into the analysis. This flexibility enables you to tailor your strategy to your preferences.
◽️ How to link your signal with the optimizer:
In order to be able to analysis your signal we need to read it and to do so we would need to PLOT your signal with a defined value
plot( YOUR LONG Condition ? 100 : 0 , display = display.data_window)
█ Customizable Risk to Reward Ratios:
This tool allows you to test seven different customizable risk to reward ratios , helping you determine the most suitable risk-reward balance for your trading strategy. This data-driven approach takes the guesswork out of setting stop-loss and take-profit levels.
█ Comprehensive Data Analysis:
The tool provides a table displaying key metrics, including:
Total trades
Wins
Losses
Profit factor
Win rate
Profit and loss (PNL)
This data is essential for refining your trading strategy.
🔸 It includes a tooltip for each risk to reward ratio which gives data for the:
Most Profitable Trade USD value
Most Profitable Trade % value
Most Profitable Trade Bar Index
Most Profitable Trade Time (When it occurred)
Position and size is adjustable
█ Visual insights with histograms:
Visualize your trading performance with histograms displaying each risk to reward ratio trade space, showing total trades, wins, losses, and the ratio of profitable trades.
This visual representation helps you understand the strengths and weaknesses of your strategy.
It offers tooltips for each RR ratio with the average win and loss percentages for further analysis.
█ Dynamic Highlighting:
A drop-down menu allows you to highlight the maximum values of critical metrics such as:
Profit factor
Win rate
PNL
for quick identification of successful setups.
█ Stop Loss Flexibility:
You can adjust stop-loss levels using three different calculation methods:
ATR
Pivot
VWAP
This allows you to align risk-reward ratios with your preferred risk tolerance.
█ Chart Integration:
Visualize your trades directly on your price chart, with each trade displayed in a distinct color for easy tracking.
When your take-profit (TP) level is reached , the tool labels the corresponding risk-reward ratio for that specific TP, simplifying trade management.
█ Detailed Tooltips:
Tooltips provide deeper insights into your trading performance. They include information about the most profitable trade, such as the time it occurred, the bar index, and the percentage gain. Histogram tooltips also offer average win and loss percentages for further analysis.
█ Settings:
█ Code:
In summary, the Risk Reward Optimizer is a data-driven tool that offers traders the ability to optimize their risk-reward ratios, refine their strategies, and gain a deeper understanding of their trading performance. Whether you're a day trader, swing trader, or investor, this tool can help you make informed decisions and improve your trading outcomes.
sᴛᴀɢᴇ ᴀɴᴀʏʟsɪsStage analysis is a technical analysis approach that involves categorizing a stock's price movements into different stages to help traders and investors make more informed decisions. It was popularized by Stan Weinstein in his book, "Secrets for Profiting in Bull and Bear Markets." The stages are used to identify the overall trend and to time entries and exits in the market. Here's an explanation of the typical stages in stage analysis:
1. **Stage 1: Accumulation Phase**
- In this stage, the stock is in a downtrend or has been trading sideways for an extended period.
- Volume is relatively low, indicating that institutions and smart money may be quietly accumulating shares.
- The stock may test and hold support levels, showing signs of stability.
- The goal for traders in this stage is to identify the potential for a trend reversal.
2. **Stage 2: Markup (Bull Market) Phase**
- This is the stage where the stock starts a significant uptrend.
- Volume increases as institutional and retail investors become more interested in the stock.
- Technical indicators like moving averages and trendlines confirm the uptrend.
- Traders and investors look for buying opportunities during pullbacks or consolidations within the uptrend.
3. **Stage 3: Distribution Phase**
- In this stage, the stock's price begins to show signs of weakness.
- Volume might decrease as institutions and smart money start selling their positions.
- The stock may start forming a trading range or exhibit bearish chart patterns.
- Traders should consider taking profits or reducing exposure to the stock as it may enter a downtrend.
4. **Stage 4: Markdown (Bear Market) Phase**
- This is the stage where the stock enters a significant downtrend.
- Volume may remain elevated as selling pressure dominates.
- Technical indicators confirm the downtrend.
- Traders and investors should avoid buying the stock and may consider short-selling or staying on the sidelines.
Stage analysis helps traders and investors make decisions based on the current stage of a stock's price movement. The goal is to enter during the accumulation phase or early in the markup phase and exit during the distribution phase or before the markdown phase to maximize profits and minimize losses.
=============================================================
try to just show the Stage number in a table, but always double check for yourself
MFR RangeHello Traders!
You requested it for many months, we are finally making our proprietary Range available to all.
First of all, how should a trader consider a Range in general:
In trading, a "range" refers to a specific price interval or zone within which an asset's price moves or consolidates for a period of time. Ranges are characterized by relatively horizontal or sideways price movements, where the price oscillates between a defined upper and lower boundary. Traders often use ranges to identify potential trading opportunities, manage risk, and make trading decisions.
Here's how ranges are used in trading:
1. Range Identification:
Traders identify ranges by observing price charts and looking for periods where the price appears to be moving horizontally with clear upper and lower boundaries.
Common range patterns include rectangles, channels, and horizontal consolidations.
2. Range Trading Strategies:
Range trading strategies aim to profit from price movements within the established range. Traders typically use two main approaches within a range:
Buying near the range's lower boundary: Traders buy when the price approaches the lower end of the range, anticipating a bounce or reversal towards the upper boundary. This is often referred to as "buying support."
Selling near the range's upper boundary: Traders sell when the price approaches the upper end of the range, anticipating a pullback or reversal towards the lower boundary. This is known as "selling resistance."
3. Risk Management:
Stop-loss orders are crucial when trading ranges. Traders set stop-loss orders just outside the range's boundaries to limit potential losses if the price breaks out of the range unpredictably.
4. Range Breakouts:
Ranges do not last indefinitely, and eventually, the price may break out of the range, leading to a significant price movement.
Traders often look for breakout patterns and use breakout trading strategies to capitalize on the potential for a strong price movement after the range is broken.
5. Volatility Consideration:
Some traders may assess the volatility within the range. If the price oscillates within the range with high volatility, they may consider trading shorter timeframes for smaller, quicker profits.
Lower volatility may prompt longer-term traders to take positions within the range, expecting a slower, more controlled price movement.
6. Time Frame Analysis:
Traders may analyze the time frame in which the range has developed, in our case MFR range are based solely on the Daily timeframe.
7. Confirmation Indicators:
Traders often use technical indicators like Relative Strength Index (RSI), Moving Averages, or Bollinger Bands to confirm range trading signals and assess overbought or oversold conditions.
8. Range Boundaries as Support and Resistance:
Once a range is identified, its upper and lower boundaries can serve as key support and resistance levels even after the range is broken. Traders pay attention to these levels for future trading decisions.
9. Range Expansion:
Some traders look for signs of range expansion, where the price starts to break out or trend strongly. This can signal the end of a range-bound market and a transition to a trending market.
It's important to note that while range trading can be profitable, it requires careful analysis and risk management. Traders must be prepared for the possibility of a breakout that can result in significant losses if they are on the wrong side of the trade. Additionally, market conditions can change, and ranges can evolve into trends or other patterns, so traders need to adapt their strategies accordingly.
What is specific to MFR range?
This script calculates and plots a trading range on a daily timeframe based on historical price data. Based on Benoit Mandelbrot and Edgar E. Peters publications on Range, we run a set of calculations over a defined period. The script will define those to generate the "Range High" and "Range Low". These values are used to define the upper and lower bounds of the trading range.
In short, how could I use this script?
A trader could use the Range to find overbought or oversold points to enter a position. The Lower Range being the price to buy an asset and the Upper Range being the place to sell an asset. This is recommended to be implemented only when our other indication called Trend matches the strategy: buy when the trend is bullish or short when the trend is bearish.
It's important to note that while Range is a useful tool, it should not be relied upon solely for making trading decisions. It's recommended to use it in conjunction with other technical analysis tools and consider other factors such as market conditions, risk management, and fundamental analysis. Remember that the Range indicator is just one tool among many, and it's important to consider other factors such as volume, momentum, volatility, and overall market conditions when making trading decisions. Additionally, using stop-loss orders and proper risk management techniques is crucial to mitigate potential losses.
We hope that you will find these explanations useful, please contact us by private message for access.
Enjoy!
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorised. This script is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. Myfractalrange is not responsible for any losses you may incur. Please invest wisely.
Ruth Buy/Sell Signal for Day Trade and Swing TradeRuth is based on the most known technical indicators and designed for intraday traders. Ruth's aim is to find the best Buy/Sell points and decide to stop loss point with minimum Loss also Ruth tries to find multiple Profit points as TP1/TP2/TP3/TP4/TP5. Ruth was designed based on the heat map colors to be user-friendly and easy to read. While cold color preferred for Short positions, warm colors preferred for Long positions. The most important feature of Ruth is that after the signal is generated, the candles in which the profitable levels are painted one by one with their own special color codes, so that even the most inexperienced users can understand where they should close their positions.
There are two types of signal Ruth can produce for fast trade.
Short Signal: These signals means market tends to be move to down.
Short Stop Loss Point: This is the maximum risk for the position. Shown with single red line inside of the signal.
Short Entry Point: This is the best entry price for short side position. Shown with single baby blue line inside of the signal.
Short Take Profit (TP1): This level represents the profit level the signal is most likely to reach. Shown with single blue line inside of the signal.
Short Take Profit (TP2): This level represents the profit level with a high probability of the signal occurring. Shown with single light purple line inside of the signal.
Short Take Profit (TP3): This level represents the profit level with an intermediate probability of the signal occurring. Shown with single dark purple line inside of the signal.
Short Take Profit (TP4): This level represents the profit level with a low probability of the signal occurring. Shown with single light lilac line inside of the signal.
Short Take Profit (TP5): This level represents the profit level with a tight probability of the signal occurring. Shown with single dark lilac line inside of the signal.
Long Signal: These signals means market tends to be move to up.
Long Stop Loss Point: This is the maximum risk for the position. Shown with single red line inside of the signal.
Long Entry Point: This is the best entry price for short side position. Shown with single baby blue line inside of the signal.
Long Take Profit (TP1): This level represents the profit level the signal is most likely to reach. Shown with single greenish yellow line inside of the signal.
Long Take Profit (TP2): This level represents the profit level with a high probability of the signal occurring. Shown with yellow purple line inside of the signal.
Long Take Profit (TP3): This level represents the profit level with an intermediate probability of the signal occurring. Shown with single dark yellow line inside of the signal.
Long Take Profit (TP4): This level represents the profit level with a low probability of the signal occurring. Shown with single orange line inside of the signal.
Long Take Profit (TP5): This level represents the profit level with a tight probability of the signal occurring. Shown with single dark orange line inside of the signal.
Timeframe: In general best and fastest results occurred in shorter timeframes like 1 min / 5 mins / 15 mins but feel free to try higher timeframes.
Tips & Tricks:
1) Gray line drawn ot the graph represents Dema, we suggests you to go on Short Singals under gray line and go on Long Signals upper gray line.
2) Mostly, Signals easily reach their TP2 / TP3 levels and then generally there is reaction or take profit desire so commodity price turns the opposite direction. If in short time price won't turn to Signal direction close position.
3) Don't forget, every positions has own risks and profits but trade in main trend is crucial.
Fundamental Metrics v1.2LETS MAKE FUNDAMENTALS GREAT AGAIN!!!
This is a basic Script to show a list of financial metrics or key performance indicators (KPIs) that are commonly used to assess the financial health and performance of a company.
Let's break down what each of these metrics represents:
1. Long-Term Debt (LTD): This represents the total amount of debt that a company owes that is expected to be paid back over a period of more than one year. It includes bonds, loans, and other long-term borrowing.
2. Ex-Capital Lease: This might refer to the company's obligations related to capital leases, which are long-term lease agreements for assets like equipment or property. "Ex" typically stands for "excluding," so this could be the amount of capital lease obligations excluded from the company's financials.
3. Total Revenue: This is the total income generated by a company from its primary operations. It includes sales of goods or services before any deductions for costs or expenses.
4. Total Equity: This is the total value of ownership or shareholders' equity in the company. It represents the residual interest in the assets of the entity after deducting liabilities.
5. Cash & Equivalents: This refers to the total amount of cash and assets that are easily convertible into cash, such as marketable securities or short-term investments.
6. Revenue Estimates: This could refer to the company's projections or estimates of future revenues, typically for the current fiscal year (FY).
7. Free Cash Flow (FCF): FCF represents the cash generated by a company's operations after deducting capital expenditures (CapEx) required to maintain or expand its asset base. It's a measure of a company's ability to generate cash from its core operations.
8. EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization): EBITDA is a measure of a company's operating performance. It looks at earnings before considering the effects of interest, taxes, depreciation, and amortization. It's often used to assess profitability.
9. Market Capitalization (Market Cap): Market cap is the total value of a company's outstanding shares of stock in the stock market. It's calculated by multiplying the current share price by the total number of outstanding shares.
These metrics are essential for investors, analysts, and stakeholders to evaluate a company's financial position, performance, and overall health. They provide insights into various aspects of a company's operations, such as its debt obligations, revenue generation, profitability, and market value. Companies often report these metrics in their financial statements and disclosures to help investors make informed decisions.
[OKX Signal Bot] Indicator Script Set Up TemplateDiscover the power of the Turtle Trade Channels Indicator (TUTCI), an innovative tool that integrates the time-tested principles of the legendary Turtle Trade system. This groundbreaking system shattered the belief that successful traders are born, not made, by transforming ordinary individuals into profitable traders.
The Turtle Trade Experiment, which achieved a remarkable 80% annual return over four years and amassed a staggering $150 million, showcased the immense potential of this trend-following strategy. Unlike the conventional "buy low and sell high" approach, the Turtle Trade system embraces a different philosophy—one of capturing substantial profits by following prevailing trends.
At the heart of the Turtle Trade Channels Indicator lies the concept of Donchian Channels, a powerful technical indicator developed by Richard Donchian. Building upon this foundation, the main rule of TUTCI is to identify 20-day breakouts and capitalize on them, while simultaneously utilizing a profit-taking strategy based on breaching 10-day highs or lows.
For long trades, the indicator signals a buying opportunity when the price breaks above the 20-day high. Conversely, for short trades, a selling opportunity arises when the price falls below the 20-day low. This systematic approach allows traders to align themselves with the prevailing momentum, capturing significant price movements.
To further enhance trading precision, TUTCI incorporates two key lines. The red line represents the trading line, indicating the direction of the trend. Price bars above the trend line suggest an uptrend, while those below indicate a downtrend. The dotted blue line serves as the exit line, guiding traders to close their positions when price action breaches the 10-day high or low. This rule safeguards profits and helps traders avoid potential trend reversals.
The Turtle Trade Channels Indicator (TUTCI) is a versatile tool applicable to various financial markets, including stocks, commodities, and forex. By harnessing the power of breakouts and integrating profit-taking rules, this indicator empowers traders to capitalize on favorable trading opportunities while managing risk effectively.
As with any trading strategy, it is crucial to conduct thorough backtesting and evaluation of the TUTCI system before implementing it in live trading. Traders can customize the indicator's parameters to align with their trading preferences and adapt to changing market conditions. Employing sound risk management techniques, such as position sizing and stop-loss orders, is paramount to protect capital and minimize potential losses.
Experience the transformational potential of the Turtle Trade Channels Indicator (TUTCI) and embark on a journey of trend following, capturing significant profits, and achieving trading success.
These scripts are only functioning as sample script templates to support okx alert standards. It is not intended to provide any investment, tax, or legal advice, nor should it be considered an offer to purchase, sell, hold or offer any services relating to digital assets. Digital assets, including stablecoins, involve a high degree of risk, can fluctuate greatly, and can even become worthless. You should carefully consider whether trading or holding digital assets is suitable for you in light of your financial condition and risk tolerance. OKX does not provide investment or asset recommendations. You are solely responsible for your investment decisions, and OKX is not responsible for any potential losses. Past performance is not indicative of future results. Please consult your legal/tax/investment professional for questions about your specific circumstances.
Agressive ConfirmationThis indicator serves as a guide for aggressive counter-trend trading, offering entries, a trailing stop for trade exits and a performance backtesting system (risk ratio).
AC proves to be an excellent ally in assisting counter-trend entry decisions. The signals come from two different sources, and are positioned almost identically in terms of the timing of entry into a trade on a trend change.
The first is RSI reintegration: simple, effective. The second is price action reintegration (identifies short-term support/resistance, a false break with counter-trend reinjection).
The duality of this entry system means you can be present on most local tops and bottoms without having an excessively high number of trade entries. The failure of the first entry can give a signal on the second (divergence, volatility...): use this complementarity to your advantage! If the first signal ends in a loss, wait for confirmation on the second signal.
The trailing stop system is activated as soon as an entry signal is detected, and if no entry signal is still active. The trade is closed when the candle closes above or below the trailing stop.
Two possible settings:
"passive": (multiply 5, period 8), least reactive trailing stop, willing to hold the trade
"balanced": (multiply 1, period 4): versatile trailing stop, ideal compromise.
These trailing stop parameters are optimized by the automated backtesting strategy of our IRL indicator, which indicates precise reversal levels. To use them in this specific context, you need to be in timeframe m1. For more information on these levels, please see my profile!
The stop loss for each reversal corresponds to the last high/low of the last 4 candles. It's possible to display this value above or below the trade entry signal, which makes it easier to understand the practical application of the signals presented.
An option for displaying more information on trades executed once closed. When an exit signal is detected (stop loss OR trailing stop), the candle leading to the trade's closure is marked with a label, providing information on the trade's profit (expressed in R, risk ratio). A second piece of information, in brackets, is the drawup: this corresponds to the maximum unrealized PNL of the closed trade.
The size of these labels can be modified according to the trade's PNL, all managed by profitability thresholds in R (default: 8R, 4R, 1R).
these latest entry signal performance functions optimize the backtesting process and the identification of relevant reversal strategies, by reversing the methodology: "where are the biggest profits made over such and such a period, what were the signals of my studied strategy, ...". The drawup, for its part, will enable you to appreciate an entry during a volatile period, which can sometimes lead to substantial short-term gains, but which the trailing stop exit failed to capitalize on!
A second signal corresponds to an additional confirmation, generally later in the timing, and informed by candle coloring. Based on RSI convergence/divergence, and to be used as a possible complementary filter to entry signals. Independent and without impact on the entry and exit signals studied.
This indicator has been developed in synergy with our other published technical indicators for identifying reversal zones / reversal timings, and offers a guideline for those less experienced in frontrunning/counter-trending. AC should be the sinequa none for a reversal entry, and will enable you to appreciate the reversal setups studied!
Alpha Fractal BandsWilliams fractals are remarkable support and resistance levels used by many traders. However, it can sometimes be challenging to use them frequently and get confirmation from other oscillators and indicators. With the new "Alpha Fractal Bands", a unique blend of Williams Fractals and Bollinger Bands emerges, offering a fresh perspective. Extremes can be utilized as price reversals or for taking profits. I look forward to hearing your thoughts. Best regards... Happy trading!
An easy solution for long positions is to:
Identify a bullish trend or a potential entry point for a long position.
Set a stop-loss order to limit potential losses if the trade goes against you.
Determine a target price or take-profit level to lock in profits.
Consider using technical indicators or analysis tools to confirm the strength of the bullish trend.
Regularly monitor the trade and make necessary adjustments based on market conditions.
An easy solution for short positions could be to follow these steps:
Identify a bearish trend or a potential entry point for a short position.
Set a stop-loss order to limit potential losses if the trade goes against you.
Determine a target price or take-profit level to lock in profits.
Consider using technical indicators or analysis tools to confirm the strength of the bearish trend.
Regularly monitor the trade and make necessary adjustments based on market conditions.
Remember, it's important to conduct thorough research and analysis before entering any trade and to manage your risk effectively.
To stay updated with the content, don't forget to follow and engage with it on TV, my friends. Remember to leave comments as well :)
Volume-Weighted RSI with Adaptive SmoothingThis indicator is designed to provide traders with insights into the relative strength of a security by incorporating volume-weighted elements, effectively combining the concepts of Relative Strength Index (RSI) and volume-weighted averages to generate meaningful trading signals.
The indicator calculates the traditional RSI, which measures the speed and change of price movements, as well as the volume-weighted RSI, which considers the influence of trading volume on price action. It then applies adaptive smoothing to the volume-weighted RSI, allowing for customization of the smoothing process. The resulting smoothed volume-weighted RSI is plotted alongside the original RSI, providing traders with a comprehensive view of the price strength dynamics.
The line coloration in this indicator is designed to provide visual cues about the relationship between the RSI and the volume-weighted RSI. When the RSI line is above or equal to the volume-weighted RSI line, it suggests a potentially bullish condition with positive market momentum. In such cases, the line is colored lime. Conversely, when the RSI line (fuchsia) is below the volume-weighted RSI line, it indicates a potentially bearish condition with negative market momentum. The line color is set to fuchsia. By observing the line color, traders can quickly assess the relative strength between the RSI and the volume-weighted RSI, aiding their decision-making process.
The bar color and background color further enhance the visual interpretation of the indicator. The bar color reflects the RSI's relationship with the volume-weighted RSI and the predefined thresholds. If the RSI line is above both the volume-weighted RSI line and the overbought threshold (70), the bar color is set to lime, indicating a potentially overbought condition. Conversely, if the RSI line is below both the volume-weighted RSI line and the oversold threshold (30), the bar color is set to fuchsia, suggesting a potentially oversold condition. When the RSI line is between these two thresholds, the bar color is set to yellow, indicating a neutral or intermediate state. The background color, displayed with a semi-transparent shade, provides additional context by reflecting the prevailing market conditions. It turns lime if the volume-weighted RSI is above the overbought threshold, fuchsia if below the oversold threshold, and yellow if it falls between these two thresholds. This coloration scheme aids traders in quickly assessing market conditions and potential trading opportunities.
Calculations:
-- RSI Calculation : The traditional RSI is calculated based on the price movements of the asset. The up and down movements are determined, and exponential moving averages are used to smooth the values. The RSI value ranges from 0 to 100, with levels above 70 indicating overbought conditions and levels below 30 indicating oversold conditions.
-- Volume-Weighted RSI Calculation : The volume-weighted RSI incorporates the trading volume of the asset into the calculations. The closing price is multiplied by the corresponding volume, and the average is taken over a specific length. The up and down movements are smoothed using exponential moving averages to generate the volume-weighted RSI value.
-- Adaptive Smoothing : The indicator offers an adaptive smoothing option, allowing traders to customize the smoothing process of the volume-weighted RSI. By adjusting the smoothing length, traders can fine-tune the responsiveness of the indicator to changes in market conditions. Smoothing helps reduce noise and enhances the clarity of the signals.
Interpretation:
The indicator provides two main components for interpretation:
-- RSI : The traditional RSI reflects the price momentum and potential overbought or oversold conditions. Traders can look for RSI values above 70 as potential overbought signals, suggesting a possible price reversal or correction. Conversely, RSI values below 30 indicate potential oversold signals, indicating a potential price rebound or rally.
-- Volume-Weighted RSI : The volume-weighted RSI incorporates trading volume, which provides insights into the strength of price movements. When the volume-weighted RSI is above the traditional RSI, it suggests that the buying pressure supported by higher volume is stronger, potentially indicating a more reliable trend. Conversely, when the volume-weighted RSI is below the traditional RSI, it suggests that the selling pressure supported by higher volume is stronger, potentially indicating a more significant price reversal.
Potential Strategies:
-- Overbought and Oversold Signals : Traders can utilize the RSI component of the indicator to identify overbought and oversold conditions. A potential strategy is to consider taking short positions when the RSI is above 70 and long positions when the RSI is below 30. These levels can act as dynamic support and resistance areas, indicating possible price reversals.
-- Confirmation with Volume : Traders can use the volume-weighted RSI as a confirmation tool to validate price movements. When the volume-weighted RSI is above the traditional RSI, it may provide additional confirmation for long positions, suggesting stronger buying pressure. Conversely, when the volume-weighted RSI is below the traditional RSI, it may provide confirmation for short positions, indicating stronger selling pressure.
-- Trend Reversal Strategy : Watch for the volume-weighted RSI to reach extreme levels above 70 (overbought) or below 30 (oversold). Look for a reversal signal where the RSI line (green or fuchsia) crosses below or above the volume-weighted RSI line. Enter a trade when the reversal signal occurs, and the RSI line changes color. Exit the trade when the RSI line crosses back in the opposite direction or reaches the opposite extreme level.
-- Divergence Strategy : Compare the direction of the RSI line (green or fuchsia) with the volume-weighted RSI line. A bullish divergence occurs when the RSI line makes higher lows while the volume-weighted RSI line makes lower lows. A bearish divergence occurs when the RSI line makes lower highs while the volume-weighted RSI line makes higher highs. Once a divergence is identified, wait for the RSI line to cross above or below the volume-weighted RSI line as confirmation of a potential trend reversal. Consider using additional indicators or price action analysis to time the entry more accurately. Use stop-loss orders and profit targets to manage risk and secure profits.
-- Trend Continuation Strategy : Assess the overall trend direction by observing the RSI line's position relative to the volume-weighted RSI line. When the RSI line consistently stays above the volume-weighted RSI line, it indicates a bullish trend, while the opposite suggests a bearish trend. Look for temporary pullbacks within the ongoing trend where the RSI line (green or fuchsia) touches or crosses the volume-weighted RSI line. Enter trades in the direction of the dominant trend when the RSI line crosses back in the trend direction. Exit the trade when the RSI line starts to deviate significantly from the volume-weighted RSI line or when the trend shows signs of weakening through other technical or fundamental factors.
Limitations:
-- False Signals : Like any indicator, the "Volume-Weighted RSI with Adaptive Smoothing" may produce false signals, especially during periods of low liquidity or choppy market conditions. Traders should exercise caution and consider using additional confirmation indicators or tools to validate the signals generated by this indicator.
-- Lagging Nature : The indicator relies on historical price data and volume to calculate the RSI and volume-weighted RSI. As a result, the signals provided may have a certain degree of lag compared to real-time price action. Traders should be aware of this inherent lag and consider combining the indicator with other timely indicators to enhance the accuracy of their trading decisions.
-- Parameter Sensitivity : The indicator's effectiveness can be influenced by the choice of parameters, such as the length of the RSI, smoothing length, and adaptive smoothing option. Different market conditions may require adjustments to these parameters to optimize performance. Traders are encouraged to conduct thorough testing and analysis to determine the most suitable parameter values for their specific trading strategies and preferences.
-- Market Conditions : The indicator's performance may vary depending on the prevailing market conditions. It is essential to understand that no indicator can guarantee accurate predictions or consistently profitable trades. Traders should consider the broader market context, fundamental factors, and other technical indicators to complement the insights provided by the "Volume-Weighted RSI with Adaptive Smoothing" indicator.
-- Subjectivity : Interpretation of the indicator's signals involves subjective judgment. Traders may have varying interpretations of overbought and oversold levels, as well as the significance of the volume-weighted RSI in relation to the traditional RSI. It is crucial to combine the indicator with personal analysis and trading experience to make informed trading decisions.
Remember, no single indicator can provide foolproof trading signals. The "Volume-Weighted RSI with Adaptive Smoothing" indicator serves as a valuable tool for analyzing price strength and volume dynamics. It can assist traders in identifying potential entry and exit points, validating trends, and managing risk. However, it should be used as part of a comprehensive trading strategy that considers multiple factors and indicators to increase the likelihood of successful trades.
Goertzel Browser [Loxx]As the financial markets become increasingly complex and data-driven, traders and analysts must leverage powerful tools to gain insights and make informed decisions. One such tool is the Goertzel Browser indicator, a sophisticated technical analysis indicator that helps identify cyclical patterns in financial data. This powerful tool is capable of detecting cyclical patterns in financial data, helping traders to make better predictions and optimize their trading strategies. With its unique combination of mathematical algorithms and advanced charting capabilities, this indicator has the potential to revolutionize the way we approach financial modeling and trading.
█ Brief Overview of the Goertzel Browser
The Goertzel Browser is a sophisticated technical analysis tool that utilizes the Goertzel algorithm to analyze and visualize cyclical components within a financial time series. By identifying these cycles and their characteristics, the indicator aims to provide valuable insights into the market's underlying price movements, which could potentially be used for making informed trading decisions.
The primary purpose of this indicator is to:
1. Detect and analyze the dominant cycles present in the price data.
2. Reconstruct and visualize the composite wave based on the detected cycles.
3. Project the composite wave into the future, providing a potential roadmap for upcoming price movements.
To achieve this, the indicator performs several tasks:
1. Detrending the price data: The indicator preprocesses the price data using various detrending techniques, such as Hodrick-Prescott filters, zero-lag moving averages, and linear regression, to remove the underlying trend and focus on the cyclical components.
2. Applying the Goertzel algorithm: The indicator applies the Goertzel algorithm to the detrended price data, identifying the dominant cycles and their characteristics, such as amplitude, phase, and cycle strength.
3. Constructing the composite wave: The indicator reconstructs the composite wave by combining the detected cycles, either by using a user-defined list of cycles or by selecting the top N cycles based on their amplitude or cycle strength.
4. Visualizing the composite wave: The indicator plots the composite wave, using solid lines for the past and dotted lines for the future projections. The color of the lines indicates whether the wave is increasing or decreasing.
5. Displaying cycle information: The indicator provides a table that displays detailed information about the detected cycles, including their rank, period, Bartel's test results, amplitude, and phase.
This indicator is a powerful tool that employs the Goertzel algorithm to analyze and visualize the cyclical components within a financial time series. By providing insights into the underlying price movements and their potential future trajectory, the indicator aims to assist traders in making more informed decisions.
█ What is the Goertzel Algorithm?
The Goertzel algorithm, named after Gerald Goertzel, is a digital signal processing technique that is used to efficiently compute individual terms of the Discrete Fourier Transform (DFT). It was first introduced in 1958, and since then, it has found various applications in the fields of engineering, mathematics, and physics.
The Goertzel algorithm is primarily used to detect specific frequency components within a digital signal, making it particularly useful in applications where only a few frequency components are of interest. The algorithm is computationally efficient, as it requires fewer calculations than the Fast Fourier Transform (FFT) when detecting a small number of frequency components. This efficiency makes the Goertzel algorithm a popular choice in applications such as:
1. Telecommunications: The Goertzel algorithm is used for decoding Dual-Tone Multi-Frequency (DTMF) signals, which are the tones generated when pressing buttons on a telephone keypad. By identifying specific frequency components, the algorithm can accurately determine which button has been pressed.
2. Audio processing: The algorithm can be used to detect specific pitches or harmonics in an audio signal, making it useful in applications like pitch detection and tuning musical instruments.
3. Vibration analysis: In the field of mechanical engineering, the Goertzel algorithm can be applied to analyze vibrations in rotating machinery, helping to identify faulty components or signs of wear.
4. Power system analysis: The algorithm can be used to measure harmonic content in power systems, allowing engineers to assess power quality and detect potential issues.
The Goertzel algorithm is used in these applications because it offers several advantages over other methods, such as the FFT:
1. Computational efficiency: The Goertzel algorithm requires fewer calculations when detecting a small number of frequency components, making it more computationally efficient than the FFT in these cases.
2. Real-time analysis: The algorithm can be implemented in a streaming fashion, allowing for real-time analysis of signals, which is crucial in applications like telecommunications and audio processing.
3. Memory efficiency: The Goertzel algorithm requires less memory than the FFT, as it only computes the frequency components of interest.
4. Precision: The algorithm is less susceptible to numerical errors compared to the FFT, ensuring more accurate results in applications where precision is essential.
The Goertzel algorithm is an efficient digital signal processing technique that is primarily used to detect specific frequency components within a signal. Its computational efficiency, real-time capabilities, and precision make it an attractive choice for various applications, including telecommunications, audio processing, vibration analysis, and power system analysis. The algorithm has been widely adopted since its introduction in 1958 and continues to be an essential tool in the fields of engineering, mathematics, and physics.
█ Goertzel Algorithm in Quantitative Finance: In-Depth Analysis and Applications
The Goertzel algorithm, initially designed for signal processing in telecommunications, has gained significant traction in the financial industry due to its efficient frequency detection capabilities. In quantitative finance, the Goertzel algorithm has been utilized for uncovering hidden market cycles, developing data-driven trading strategies, and optimizing risk management. This section delves deeper into the applications of the Goertzel algorithm in finance, particularly within the context of quantitative trading and analysis.
Unveiling Hidden Market Cycles:
Market cycles are prevalent in financial markets and arise from various factors, such as economic conditions, investor psychology, and market participant behavior. The Goertzel algorithm's ability to detect and isolate specific frequencies in price data helps trader analysts identify hidden market cycles that may otherwise go unnoticed. By examining the amplitude, phase, and periodicity of each cycle, traders can better understand the underlying market structure and dynamics, enabling them to develop more informed and effective trading strategies.
Developing Quantitative Trading Strategies:
The Goertzel algorithm's versatility allows traders to incorporate its insights into a wide range of trading strategies. By identifying the dominant market cycles in a financial instrument's price data, traders can create data-driven strategies that capitalize on the cyclical nature of markets.
For instance, a trader may develop a mean-reversion strategy that takes advantage of the identified cycles. By establishing positions when the price deviates from the predicted cycle, the trader can profit from the subsequent reversion to the cycle's mean. Similarly, a momentum-based strategy could be designed to exploit the persistence of a dominant cycle by entering positions that align with the cycle's direction.
Enhancing Risk Management:
The Goertzel algorithm plays a vital role in risk management for quantitative strategies. By analyzing the cyclical components of a financial instrument's price data, traders can gain insights into the potential risks associated with their trading strategies.
By monitoring the amplitude and phase of dominant cycles, a trader can detect changes in market dynamics that may pose risks to their positions. For example, a sudden increase in amplitude may indicate heightened volatility, prompting the trader to adjust position sizing or employ hedging techniques to protect their portfolio. Additionally, changes in phase alignment could signal a potential shift in market sentiment, necessitating adjustments to the trading strategy.
Expanding Quantitative Toolkits:
Traders can augment the Goertzel algorithm's insights by combining it with other quantitative techniques, creating a more comprehensive and sophisticated analysis framework. For example, machine learning algorithms, such as neural networks or support vector machines, could be trained on features extracted from the Goertzel algorithm to predict future price movements more accurately.
Furthermore, the Goertzel algorithm can be integrated with other technical analysis tools, such as moving averages or oscillators, to enhance their effectiveness. By applying these tools to the identified cycles, traders can generate more robust and reliable trading signals.
The Goertzel algorithm offers invaluable benefits to quantitative finance practitioners by uncovering hidden market cycles, aiding in the development of data-driven trading strategies, and improving risk management. By leveraging the insights provided by the Goertzel algorithm and integrating it with other quantitative techniques, traders can gain a deeper understanding of market dynamics and devise more effective trading strategies.
█ Indicator Inputs
src: This is the source data for the analysis, typically the closing price of the financial instrument.
detrendornot: This input determines the method used for detrending the source data. Detrending is the process of removing the underlying trend from the data to focus on the cyclical components.
The available options are:
hpsmthdt: Detrend using Hodrick-Prescott filter centered moving average.
zlagsmthdt: Detrend using zero-lag moving average centered moving average.
logZlagRegression: Detrend using logarithmic zero-lag linear regression.
hpsmth: Detrend using Hodrick-Prescott filter.
zlagsmth: Detrend using zero-lag moving average.
DT_HPper1 and DT_HPper2: These inputs define the period range for the Hodrick-Prescott filter centered moving average when detrendornot is set to hpsmthdt.
DT_ZLper1 and DT_ZLper2: These inputs define the period range for the zero-lag moving average centered moving average when detrendornot is set to zlagsmthdt.
DT_RegZLsmoothPer: This input defines the period for the zero-lag moving average used in logarithmic zero-lag linear regression when detrendornot is set to logZlagRegression.
HPsmoothPer: This input defines the period for the Hodrick-Prescott filter when detrendornot is set to hpsmth.
ZLMAsmoothPer: This input defines the period for the zero-lag moving average when detrendornot is set to zlagsmth.
MaxPer: This input sets the maximum period for the Goertzel algorithm to search for cycles.
squaredAmp: This boolean input determines whether the amplitude should be squared in the Goertzel algorithm.
useAddition: This boolean input determines whether the Goertzel algorithm should use addition for combining the cycles.
useCosine: This boolean input determines whether the Goertzel algorithm should use cosine waves instead of sine waves.
UseCycleStrength: This boolean input determines whether the Goertzel algorithm should compute the cycle strength, which is a normalized measure of the cycle's amplitude.
WindowSizePast and WindowSizeFuture: These inputs define the window size for past and future projections of the composite wave.
FilterBartels: This boolean input determines whether Bartel's test should be applied to filter out non-significant cycles.
BartNoCycles: This input sets the number of cycles to be used in Bartel's test.
BartSmoothPer: This input sets the period for the moving average used in Bartel's test.
BartSigLimit: This input sets the significance limit for Bartel's test, below which cycles are considered insignificant.
SortBartels: This boolean input determines whether the cycles should be sorted by their Bartel's test results.
UseCycleList: This boolean input determines whether a user-defined list of cycles should be used for constructing the composite wave. If set to false, the top N cycles will be used.
Cycle1, Cycle2, Cycle3, Cycle4, and Cycle5: These inputs define the user-defined list of cycles when 'UseCycleList' is set to true. If using a user-defined list, each of these inputs represents the period of a specific cycle to include in the composite wave.
StartAtCycle: This input determines the starting index for selecting the top N cycles when UseCycleList is set to false. This allows you to skip a certain number of cycles from the top before selecting the desired number of cycles.
UseTopCycles: This input sets the number of top cycles to use for constructing the composite wave when UseCycleList is set to false. The cycles are ranked based on their amplitudes or cycle strengths, depending on the UseCycleStrength input.
SubtractNoise: This boolean input determines whether to subtract the noise (remaining cycles) from the composite wave. If set to true, the composite wave will only include the top N cycles specified by UseTopCycles.
█ Exploring Auxiliary Functions
The following functions demonstrate advanced techniques for analyzing financial markets, including zero-lag moving averages, Bartels probability, detrending, and Hodrick-Prescott filtering. This section examines each function in detail, explaining their purpose, methodology, and applications in finance. We will examine how each function contributes to the overall performance and effectiveness of the indicator and how they work together to create a powerful analytical tool.
Zero-Lag Moving Average:
The zero-lag moving average function is designed to minimize the lag typically associated with moving averages. This is achieved through a two-step weighted linear regression process that emphasizes more recent data points. The function calculates a linearly weighted moving average (LWMA) on the input data and then applies another LWMA on the result. By doing this, the function creates a moving average that closely follows the price action, reducing the lag and improving the responsiveness of the indicator.
The zero-lag moving average function is used in the indicator to provide a responsive, low-lag smoothing of the input data. This function helps reduce the noise and fluctuations in the data, making it easier to identify and analyze underlying trends and patterns. By minimizing the lag associated with traditional moving averages, this function allows the indicator to react more quickly to changes in market conditions, providing timely signals and improving the overall effectiveness of the indicator.
Bartels Probability:
The Bartels probability function calculates the probability of a given cycle being significant in a time series. It uses a mathematical test called the Bartels test to assess the significance of cycles detected in the data. The function calculates coefficients for each detected cycle and computes an average amplitude and an expected amplitude. By comparing these values, the Bartels probability is derived, indicating the likelihood of a cycle's significance. This information can help in identifying and analyzing dominant cycles in financial markets.
The Bartels probability function is incorporated into the indicator to assess the significance of detected cycles in the input data. By calculating the Bartels probability for each cycle, the indicator can prioritize the most significant cycles and focus on the market dynamics that are most relevant to the current trading environment. This function enhances the indicator's ability to identify dominant market cycles, improving its predictive power and aiding in the development of effective trading strategies.
Detrend Logarithmic Zero-Lag Regression:
The detrend logarithmic zero-lag regression function is used for detrending data while minimizing lag. It combines a zero-lag moving average with a linear regression detrending method. The function first calculates the zero-lag moving average of the logarithm of input data and then applies a linear regression to remove the trend. By detrending the data, the function isolates the cyclical components, making it easier to analyze and interpret the underlying market dynamics.
The detrend logarithmic zero-lag regression function is used in the indicator to isolate the cyclical components of the input data. By detrending the data, the function enables the indicator to focus on the cyclical movements in the market, making it easier to analyze and interpret market dynamics. This function is essential for identifying cyclical patterns and understanding the interactions between different market cycles, which can inform trading decisions and enhance overall market understanding.
Bartels Cycle Significance Test:
The Bartels cycle significance test is a function that combines the Bartels probability function and the detrend logarithmic zero-lag regression function to assess the significance of detected cycles. The function calculates the Bartels probability for each cycle and stores the results in an array. By analyzing the probability values, traders and analysts can identify the most significant cycles in the data, which can be used to develop trading strategies and improve market understanding.
The Bartels cycle significance test function is integrated into the indicator to provide a comprehensive analysis of the significance of detected cycles. By combining the Bartels probability function and the detrend logarithmic zero-lag regression function, this test evaluates the significance of each cycle and stores the results in an array. The indicator can then use this information to prioritize the most significant cycles and focus on the most relevant market dynamics. This function enhances the indicator's ability to identify and analyze dominant market cycles, providing valuable insights for trading and market analysis.
Hodrick-Prescott Filter:
The Hodrick-Prescott filter is a popular technique used to separate the trend and cyclical components of a time series. The function applies a smoothing parameter to the input data and calculates a smoothed series using a two-sided filter. This smoothed series represents the trend component, which can be subtracted from the original data to obtain the cyclical component. The Hodrick-Prescott filter is commonly used in economics and finance to analyze economic data and financial market trends.
The Hodrick-Prescott filter is incorporated into the indicator to separate the trend and cyclical components of the input data. By applying the filter to the data, the indicator can isolate the trend component, which can be used to analyze long-term market trends and inform trading decisions. Additionally, the cyclical component can be used to identify shorter-term market dynamics and provide insights into potential trading opportunities. The inclusion of the Hodrick-Prescott filter adds another layer of analysis to the indicator, making it more versatile and comprehensive.
Detrending Options: Detrend Centered Moving Average:
The detrend centered moving average function provides different detrending methods, including the Hodrick-Prescott filter and the zero-lag moving average, based on the selected detrending method. The function calculates two sets of smoothed values using the chosen method and subtracts one set from the other to obtain a detrended series. By offering multiple detrending options, this function allows traders and analysts to select the most appropriate method for their specific needs and preferences.
The detrend centered moving average function is integrated into the indicator to provide users with multiple detrending options, including the Hodrick-Prescott filter and the zero-lag moving average. By offering multiple detrending methods, the indicator allows users to customize the analysis to their specific needs and preferences, enhancing the indicator's overall utility and adaptability. This function ensures that the indicator can cater to a wide range of trading styles and objectives, making it a valuable tool for a diverse group of market participants.
The auxiliary functions functions discussed in this section demonstrate the power and versatility of mathematical techniques in analyzing financial markets. By understanding and implementing these functions, traders and analysts can gain valuable insights into market dynamics, improve their trading strategies, and make more informed decisions. The combination of zero-lag moving averages, Bartels probability, detrending methods, and the Hodrick-Prescott filter provides a comprehensive toolkit for analyzing and interpreting financial data. The integration of advanced functions in a financial indicator creates a powerful and versatile analytical tool that can provide valuable insights into financial markets. By combining the zero-lag moving average,
█ In-Depth Analysis of the Goertzel Browser Code
The Goertzel Browser code is an implementation of the Goertzel Algorithm, an efficient technique to perform spectral analysis on a signal. The code is designed to detect and analyze dominant cycles within a given financial market data set. This section will provide an extremely detailed explanation of the code, its structure, functions, and intended purpose.
Function signature and input parameters:
The Goertzel Browser function accepts numerous input parameters for customization, including source data (src), the current bar (forBar), sample size (samplesize), period (per), squared amplitude flag (squaredAmp), addition flag (useAddition), cosine flag (useCosine), cycle strength flag (UseCycleStrength), past and future window sizes (WindowSizePast, WindowSizeFuture), Bartels filter flag (FilterBartels), Bartels-related parameters (BartNoCycles, BartSmoothPer, BartSigLimit), sorting flag (SortBartels), and output buffers (goeWorkPast, goeWorkFuture, cyclebuffer, amplitudebuffer, phasebuffer, cycleBartelsBuffer).
Initializing variables and arrays:
The code initializes several float arrays (goeWork1, goeWork2, goeWork3, goeWork4) with the same length as twice the period (2 * per). These arrays store intermediate results during the execution of the algorithm.
Preprocessing input data:
The input data (src) undergoes preprocessing to remove linear trends. This step enhances the algorithm's ability to focus on cyclical components in the data. The linear trend is calculated by finding the slope between the first and last values of the input data within the sample.
Iterative calculation of Goertzel coefficients:
The core of the Goertzel Browser algorithm lies in the iterative calculation of Goertzel coefficients for each frequency bin. These coefficients represent the spectral content of the input data at different frequencies. The code iterates through the range of frequencies, calculating the Goertzel coefficients using a nested loop structure.
Cycle strength computation:
The code calculates the cycle strength based on the Goertzel coefficients. This is an optional step, controlled by the UseCycleStrength flag. The cycle strength provides information on the relative influence of each cycle on the data per bar, considering both amplitude and cycle length. The algorithm computes the cycle strength either by squaring the amplitude (controlled by squaredAmp flag) or using the actual amplitude values.
Phase calculation:
The Goertzel Browser code computes the phase of each cycle, which represents the position of the cycle within the input data. The phase is calculated using the arctangent function (math.atan) based on the ratio of the imaginary and real components of the Goertzel coefficients.
Peak detection and cycle extraction:
The algorithm performs peak detection on the computed amplitudes or cycle strengths to identify dominant cycles. It stores the detected cycles in the cyclebuffer array, along with their corresponding amplitudes and phases in the amplitudebuffer and phasebuffer arrays, respectively.
Sorting cycles by amplitude or cycle strength:
The code sorts the detected cycles based on their amplitude or cycle strength in descending order. This allows the algorithm to prioritize cycles with the most significant impact on the input data.
Bartels cycle significance test:
If the FilterBartels flag is set, the code performs a Bartels cycle significance test on the detected cycles. This test determines the statistical significance of each cycle and filters out the insignificant cycles. The significant cycles are stored in the cycleBartelsBuffer array. If the SortBartels flag is set, the code sorts the significant cycles based on their Bartels significance values.
Waveform calculation:
The Goertzel Browser code calculates the waveform of the significant cycles for both past and future time windows. The past and future windows are defined by the WindowSizePast and WindowSizeFuture parameters, respectively. The algorithm uses either cosine or sine functions (controlled by the useCosine flag) to calculate the waveforms for each cycle. The useAddition flag determines whether the waveforms should be added or subtracted.
Storing waveforms in matrices:
The calculated waveforms for each cycle are stored in two matrices - goeWorkPast and goeWorkFuture. These matrices hold the waveforms for the past and future time windows, respectively. Each row in the matrices represents a time window position, and each column corresponds to a cycle.
Returning the number of cycles:
The Goertzel Browser function returns the total number of detected cycles (number_of_cycles) after processing the input data. This information can be used to further analyze the results or to visualize the detected cycles.
The Goertzel Browser code is a comprehensive implementation of the Goertzel Algorithm, specifically designed for detecting and analyzing dominant cycles within financial market data. The code offers a high level of customization, allowing users to fine-tune the algorithm based on their specific needs. The Goertzel Browser's combination of preprocessing, iterative calculations, cycle extraction, sorting, significance testing, and waveform calculation makes it a powerful tool for understanding cyclical components in financial data.
█ Generating and Visualizing Composite Waveform
The indicator calculates and visualizes the composite waveform for both past and future time windows based on the detected cycles. Here's a detailed explanation of this process:
Updating WindowSizePast and WindowSizeFuture:
The WindowSizePast and WindowSizeFuture are updated to ensure they are at least twice the MaxPer (maximum period).
Initializing matrices and arrays:
Two matrices, goeWorkPast and goeWorkFuture, are initialized to store the Goertzel results for past and future time windows. Multiple arrays are also initialized to store cycle, amplitude, phase, and Bartels information.
Preparing the source data (srcVal) array:
The source data is copied into an array, srcVal, and detrended using one of the selected methods (hpsmthdt, zlagsmthdt, logZlagRegression, hpsmth, or zlagsmth).
Goertzel function call:
The Goertzel function is called to analyze the detrended source data and extract cycle information. The output, number_of_cycles, contains the number of detected cycles.
Initializing arrays for past and future waveforms:
Three arrays, epgoertzel, goertzel, and goertzelFuture, are initialized to store the endpoint Goertzel, non-endpoint Goertzel, and future Goertzel projections, respectively.
Calculating composite waveform for past bars (goertzel array):
The past composite waveform is calculated by summing the selected cycles (either from the user-defined cycle list or the top cycles) and optionally subtracting the noise component.
Calculating composite waveform for future bars (goertzelFuture array):
The future composite waveform is calculated in a similar way as the past composite waveform.
Drawing past composite waveform (pvlines):
The past composite waveform is drawn on the chart using solid lines. The color of the lines is determined by the direction of the waveform (green for upward, red for downward).
Drawing future composite waveform (fvlines):
The future composite waveform is drawn on the chart using dotted lines. The color of the lines is determined by the direction of the waveform (fuchsia for upward, yellow for downward).
Displaying cycle information in a table (table3):
A table is created to display the cycle information, including the rank, period, Bartel value, amplitude (or cycle strength), and phase of each detected cycle.
Filling the table with cycle information:
The indicator iterates through the detected cycles and retrieves the relevant information (period, amplitude, phase, and Bartel value) from the corresponding arrays. It then fills the table with this information, displaying the values up to six decimal places.
To summarize, this indicator generates a composite waveform based on the detected cycles in the financial data. It calculates the composite waveforms for both past and future time windows and visualizes them on the chart using colored lines. Additionally, it displays detailed cycle information in a table, including the rank, period, Bartel value, amplitude (or cycle strength), and phase of each detected cycle.
█ Enhancing the Goertzel Algorithm-Based Script for Financial Modeling and Trading
The Goertzel algorithm-based script for detecting dominant cycles in financial data is a powerful tool for financial modeling and trading. It provides valuable insights into the past behavior of these cycles and potential future impact. However, as with any algorithm, there is always room for improvement. This section discusses potential enhancements to the existing script to make it even more robust and versatile for financial modeling, general trading, advanced trading, and high-frequency finance trading.
Enhancements for Financial Modeling
Data preprocessing: One way to improve the script's performance for financial modeling is to introduce more advanced data preprocessing techniques. This could include removing outliers, handling missing data, and normalizing the data to ensure consistent and accurate results.
Additional detrending and smoothing methods: Incorporating more sophisticated detrending and smoothing techniques, such as wavelet transform or empirical mode decomposition, can help improve the script's ability to accurately identify cycles and trends in the data.
Machine learning integration: Integrating machine learning techniques, such as artificial neural networks or support vector machines, can help enhance the script's predictive capabilities, leading to more accurate financial models.
Enhancements for General and Advanced Trading
Customizable indicator integration: Allowing users to integrate their own technical indicators can help improve the script's effectiveness for both general and advanced trading. By enabling the combination of the dominant cycle information with other technical analysis tools, traders can develop more comprehensive trading strategies.
Risk management and position sizing: Incorporating risk management and position sizing functionality into the script can help traders better manage their trades and control potential losses. This can be achieved by calculating the optimal position size based on the user's risk tolerance and account size.
Multi-timeframe analysis: Enhancing the script to perform multi-timeframe analysis can provide traders with a more holistic view of market trends and cycles. By identifying dominant cycles on different timeframes, traders can gain insights into the potential confluence of cycles and make better-informed trading decisions.
Enhancements for High-Frequency Finance Trading
Algorithm optimization: To ensure the script's suitability for high-frequency finance trading, optimizing the algorithm for faster execution is crucial. This can be achieved by employing efficient data structures and refining the calculation methods to minimize computational complexity.
Real-time data streaming: Integrating real-time data streaming capabilities into the script can help high-frequency traders react to market changes more quickly. By continuously updating the cycle information based on real-time market data, traders can adapt their strategies accordingly and capitalize on short-term market fluctuations.
Order execution and trade management: To fully leverage the script's capabilities for high-frequency trading, implementing functionality for automated order execution and trade management is essential. This can include features such as stop-loss and take-profit orders, trailing stops, and automated trade exit strategies.
While the existing Goertzel algorithm-based script is a valuable tool for detecting dominant cycles in financial data, there are several potential enhancements that can make it even more powerful for financial modeling, general trading, advanced trading, and high-frequency finance trading. By incorporating these improvements, the script can become a more versatile and effective tool for traders and financial analysts alike.
█ Understanding the Limitations of the Goertzel Algorithm
While the Goertzel algorithm-based script for detecting dominant cycles in financial data provides valuable insights, it is important to be aware of its limitations and drawbacks. Some of the key drawbacks of this indicator are:
Lagging nature:
As with many other technical indicators, the Goertzel algorithm-based script can suffer from lagging effects, meaning that it may not immediately react to real-time market changes. This lag can lead to late entries and exits, potentially resulting in reduced profitability or increased losses.
Parameter sensitivity:
The performance of the script can be sensitive to the chosen parameters, such as the detrending methods, smoothing techniques, and cycle detection settings. Improper parameter selection may lead to inaccurate cycle detection or increased false signals, which can negatively impact trading performance.
Complexity:
The Goertzel algorithm itself is relatively complex, making it difficult for novice traders or those unfamiliar with the concept of cycle analysis to fully understand and effectively utilize the script. This complexity can also make it challenging to optimize the script for specific trading styles or market conditions.
Overfitting risk:
As with any data-driven approach, there is a risk of overfitting when using the Goertzel algorithm-based script. Overfitting occurs when a model becomes too specific to the historical data it was trained on, leading to poor performance on new, unseen data. This can result in misleading signals and reduced trading performance.
No guarantee of future performance: While the script can provide insights into past cycles and potential future trends, it is important to remember that past performance does not guarantee future results. Market conditions can change, and relying solely on the script's predictions without considering other factors may lead to poor trading decisions.
Limited applicability: The Goertzel algorithm-based script may not be suitable for all markets, trading styles, or timeframes. Its effectiveness in detecting cycles may be limited in certain market conditions, such as during periods of extreme volatility or low liquidity.
While the Goertzel algorithm-based script offers valuable insights into dominant cycles in financial data, it is essential to consider its drawbacks and limitations when incorporating it into a trading strategy. Traders should always use the script in conjunction with other technical and fundamental analysis tools, as well as proper risk management, to make well-informed trading decisions.
█ Interpreting Results
The Goertzel Browser indicator can be interpreted by analyzing the plotted lines and the table presented alongside them. The indicator plots two lines: past and future composite waves. The past composite wave represents the composite wave of the past price data, and the future composite wave represents the projected composite wave for the next period.
The past composite wave line displays a solid line, with green indicating a bullish trend and red indicating a bearish trend. On the other hand, the future composite wave line is a dotted line with fuchsia indicating a bullish trend and yellow indicating a bearish trend.
The table presented alongside the indicator shows the top cycles with their corresponding rank, period, Bartels, amplitude or cycle strength, and phase. The amplitude is a measure of the strength of the cycle, while the phase is the position of the cycle within the data series.
Interpreting the Goertzel Browser indicator involves identifying the trend of the past and future composite wave lines and matching them with the corresponding bullish or bearish color. Additionally, traders can identify the top cycles with the highest amplitude or cycle strength and utilize them in conjunction with other technical indicators and fundamental analysis for trading decisions.
This indicator is considered a repainting indicator because the value of the indicator is calculated based on the past price data. As new price data becomes available, the indicator's value is recalculated, potentially causing the indicator's past values to change. This can create a false impression of the indicator's performance, as it may appear to have provided a profitable trading signal in the past when, in fact, that signal did not exist at the time.
The Goertzel indicator is also non-endpointed, meaning that it is not calculated up to the current bar or candle. Instead, it uses a fixed amount of historical data to calculate its values, which can make it difficult to use for real-time trading decisions. For example, if the indicator uses 100 bars of historical data to make its calculations, it cannot provide a signal until the current bar has closed and become part of the historical data. This can result in missed trading opportunities or delayed signals.
█ Conclusion
The Goertzel Browser indicator is a powerful tool for identifying and analyzing cyclical patterns in financial markets. Its ability to detect multiple cycles of varying frequencies and strengths make it a valuable addition to any trader's technical analysis toolkit. However, it is important to keep in mind that the Goertzel Browser indicator should be used in conjunction with other technical analysis tools and fundamental analysis to achieve the best results. With continued refinement and development, the Goertzel Browser indicator has the potential to become a highly effective tool for financial modeling, general trading, advanced trading, and high-frequency finance trading. Its accuracy and versatility make it a promising candidate for further research and development.
█ Footnotes
What is the Bartels Test for Cycle Significance?
The Bartels Cycle Significance Test is a statistical method that determines whether the peaks and troughs of a time series are statistically significant. The test is named after its inventor, George Bartels, who developed it in the mid-20th century.
The Bartels test is designed to analyze the cyclical components of a time series, which can help traders and analysts identify trends and cycles in financial markets. The test calculates a Bartels statistic, which measures the degree of non-randomness or autocorrelation in the time series.
The Bartels statistic is calculated by first splitting the time series into two halves and calculating the range of the peaks and troughs in each half. The test then compares these ranges using a t-test, which measures the significance of the difference between the two ranges.
If the Bartels statistic is greater than a critical value, it indicates that the peaks and troughs in the time series are non-random and that there is a significant cyclical component to the data. Conversely, if the Bartels statistic is less than the critical value, it suggests that the peaks and troughs are random and that there is no significant cyclical component.
The Bartels Cycle Significance Test is particularly useful in financial analysis because it can help traders and analysts identify significant cycles in asset prices, which can in turn inform investment decisions. However, it is important to note that the test is not perfect and can produce false signals in certain situations, particularly in noisy or volatile markets. Therefore, it is always recommended to use the test in conjunction with other technical and fundamental indicators to confirm trends and cycles.
Deep-dive into the Hodrick-Prescott Fitler
The Hodrick-Prescott (HP) filter is a statistical tool used in economics and finance to separate a time series into two components: a trend component and a cyclical component. It is a powerful tool for identifying long-term trends in economic and financial data and is widely used by economists, central banks, and financial institutions around the world.
The HP filter was first introduced in the 1990s by economists Robert Hodrick and Edward Prescott. It is a simple, two-parameter filter that separates a time series into a trend component and a cyclical component. The trend component represents the long-term behavior of the data, while the cyclical component captures the shorter-term fluctuations around the trend.
The HP filter works by minimizing the following objective function:
Minimize: (Sum of Squared Deviations) + λ (Sum of Squared Second Differences)
Where:
The first term represents the deviation of the data from the trend.
The second term represents the smoothness of the trend.
λ is a smoothing parameter that determines the degree of smoothness of the trend.
The smoothing parameter λ is typically set to a value between 100 and 1600, depending on the frequency of the data. Higher values of λ lead to a smoother trend, while lower values lead to a more volatile trend.
The HP filter has several advantages over other smoothing techniques. It is a non-parametric method, meaning that it does not make any assumptions about the underlying distribution of the data. It also allows for easy comparison of trends across different time series and can be used with data of any frequency.
However, the HP filter also has some limitations. It assumes that the trend is a smooth function, which may not be the case in some situations. It can also be sensitive to changes in the smoothing parameter λ, which may result in different trends for the same data. Additionally, the filter may produce unrealistic trends for very short time series.
Despite these limitations, the HP filter remains a valuable tool for analyzing economic and financial data. It is widely used by central banks and financial institutions to monitor long-term trends in the economy, and it can be used to identify turning points in the business cycle. The filter can also be used to analyze asset prices, exchange rates, and other financial variables.
The Hodrick-Prescott filter is a powerful tool for analyzing economic and financial data. It separates a time series into a trend component and a cyclical component, allowing for easy identification of long-term trends and turning points in the business cycle. While it has some limitations, it remains a valuable tool for economists, central banks, and financial institutions around the world.
