RSI Volatility Bands [QuantraSystems]RSI Volatility Bands
Introduction
The RSI Volatility Bands indicator introduces a unique approach to market analysis by combining the traditional Relative Strength Index (RSI) with dynamic, volatility adjusted deviation bands. It is designed to provide a highly customizable method of trend analysis, enabling investors to analyze potential entry and exit points in a new and profound way.
The deviation bands are calculated and drawn in a manner which allows investors to view them as areas of dynamic support and resistance.
Legend
Upper and Lower Bands - A dynamic plot of the volatility-adjusted range around the current price.
Signals - Generated when the RSI volatility bands indicate a trend shift.
Case Study
The chart highlights the occurrence of false signals, emphasizing the need for caution when the bands are contracted and market volatility is low.
Juxtaposing this, during volatile market phases as shown, the indicator can effectively adapt to strong trends. This keeps an investor in a position even through a minor drawdown in order to exploit the entire price movement.
Recommended Settings
The RSI Volatility Bands are highly customisable and can be adapted to many assets with diverse behaviors.
The calibrations used in the above screenshots are as follows:
Source = close
RSI Length = 8
RSI Smoothing MA = DEMA
Bandwidth Type = DEMA
Bandwidth Length = 24
Bandwidth Smooth = 25
Methodology
The indicator first calculates the RSI of the price data, and applies a custom moving average.
The deviation bands are then calculated based upon the absolute difference between the RSI and its moving average - providing a unique volatility insight.
The deviation bands are then adjusted with another smoothing function, providing clear visuals of the RSI’s trend within a volatility-adjusted context.
rsiVal = ta.rsi(close, rsiLength)
rsiEma = ma(rsiMA, rsiVal, bandLength)
bandwidth = ma(bandMA, math.abs(rsiVal - rsiEma), bandLength)
upperBand = ma(bandMA, rsiEma + bandwidth, smooth)
lowerBand = ma(bandMA, rsiEma - bandwidth, smooth)
long = upperBand > 50 and not (lowerBand < lowerBand and lowerBand < 50)
short= not (upperBand > 50 and not (lowerBand < lowerBand and lowerBand < 50))
By dynamically adjusting to market conditions, the RSI trend bands offer a unique perspective on market trends, and reversal zones.
波動率
Truncated ATRThis program uses SMA and Truncated Mean to calculate ATR.
A truncated mean or trimmed mean is a statistical measure of central tendency, much like the mean and median. It involves the calculation of the mean after discarding given parts of a probability distribution or sample at the high and low end, and typically discarding an equal amount of both.
TASC 2024.03 Rate of Directional Change█ OVERVIEW
This script implements the Rate of Directional Change (RODC) indicator introduced by Richard Poster in the "Taming The Effects Of Whipsaw" article featured in the March 2024 edition of TASC's Traders' Tips .
█ CONCEPTS
In his article, Richard Poster discusses an approach to potentially reduce false trend-following strategy entry signals due to whipsaws in forex data. The RODC indicator is central to this approach. The idea behind RODC is that one can characterize market whipsaw as alternating up and down ZigZag segments. By counting the number of up and down segments within a lookback window, the RODC indicator aims to identify if the window contains a significant whipsaw pattern:
RODC = 100 * Segments / Window Size (bars)
Larger RODC values suggest elevated whipsaw in the calculation window, while smaller values signify trending price activity.
█ CALCULATIONS
• For each price bar, the script iterates through the lookback window to identify up and down segments.
• If the price change between subsequent bars within the window is in the direction opposite to the current segment and exceeds the specified threshold , the calculation interprets the condition as a reversal point and the start of a new segment.
• The script uses the number of segments within the window to calculate RODC according to the above formula.
• Finally, the script applies a simple moving average to smoothen the RODC data.
Users can change the length of the lookback window , the threshold value, and the smoothing length in the "Inputs" tab of the script's settings.
F.B_Consolidation Range Identifier
The "F.B_Consolidation Range Identifier" (F.B_CRI) is an indicator aimed at identifying consolidation areas in the price chart. Here is an explanation of the logic and usage of this indicator:
Calculation of Standard Deviation
This indicator analyzes the market's volatility by considering the standard deviation of price movements over a defined period. A higher standard deviation indicates larger price movement, while a lower standard deviation suggests potential consolidation, where price movements are limited.
Derivation of Standard Deviation
To track changes in volatility, the derivative of the standard deviation is calculated. Positive derivative values indicate increasing volatility, while negative values suggest a decrease in volatility. This allows for the identification of potential consolidation phases where volatility decreases, and the market may stabilize.
Identification of Consolidation Phase
The indicator signals potential consolidation phases when the standard deviation is low and/or the derivative of the standard deviation is negative. To represent consolidation phases on the chart, the standard deviation line, background, and candles are colored red. However, it's important to note that the display is customizable and can be configured according to individual needs.
🚨 Important 🚨
The indicator only indicates whether consolidation phases exist. If the standard deviation line, background, or candles are gray, it indicates that a trend exists in general, but not whether it is bullish or bearish. It is advisable to use other analytical tools to confirm the direction of the trend.
Supertrend & CCI Strategy ScalpThis strategy is based on 2 Super Trend Indicators along with CCI .
The longer factor length gives you the current trend and the deviation in the short factor length gives us the opportunity to enter in the trade .
CCI indicator is used to determine the overbought and oversold levels.
Setup :
Long : When atrLength1 > close and atrLength2 < close and CCI < -100 we look for long trades as the longer factor length will be bullish .
Short : When atrLength1 < close and atrLength2 > close and CCI > 100 we look for short trades as the longer factor length will be bearish .
Please tune the settings according to your use .
Trade what you see not what you feel .
Please consult with your financial advisor before you deploy any real money for trading .
Pivot Extremes BreakoutI created the "Pivot Extremes Breakout" (PEB) indicator to easily spot breakout zones using pivot points. This tool comes from my need to anticipate market direction and capitalize on breakouts. PEB uses the last two pivot points to predict price paths and highlights potential breakout areas, adjusting for any timeframe. It simplifies seeing where the market might move next with color-coded lines and zones, aiming to improve your trading decisions.
F.B_DI+ DI- Trend TrackerThe F.B_DI+ DI- Trend Tracker is an indicator developed based on Directional Movement and True Range to identify trends in the market and assess their strength. Here is the logic behind the indicator and how to use it for trading:
Direction Determination
Unlike traditional DI+ and DI- based on simple calculations, this indicator utilizes derived versions of these directional indicators. These derived versions offer a more precise measurement of price directional movements by specifically tailoring to market conditions and the chosen time frame.
Trend Strength
The derived directional indicators are generated by dividing smoothed Directional Movements by smoothed True Range and converting them into percentages. These values provide insights into the strength of the trend by considering directional movements relative to market volatility.
Identifying Trend Reversals
To capture changes in trend strength more accurately, the first derivative of DI+ and DI- is computed. A crossover of these derived versions could indicate a potential trend reversal, with a crossover of DI+ over DI- suggesting a possible uptrend and a crossover of DI- over DI+ indicating a potential downtrend.
Making Trading Decisions
Traders can use crossovers between the derived DI+ and DI- to receive signals for potential trend reversals. Additionally, changes in the color of candlesticks or background can be used as confirmation of the trend direction and its strength.
By utilizing these derived directional indicators, the F.B_DI+ DI- Trend Tracker indicator offers more precise trading signals and improved trend analysis, enabling traders to make informed trading decisions.
Volatility Adjusted Profit Target
In my 'Volatility Adjusted Profit Target' indicator, I've crafted a dynamic tool for calculating target profit percentages suitable for both long and short trading strategies. It evaluates the highest and lowest prices over the anticipated duration of your trade, establishing a profit target that shifts with market volatility. As volatility increases, the potential for profit follows, with the target percentage rising accordingly; conversely, it declines with decreasing volatility. As a trader, setting an optimal Take Profit level has always been a challenge. This indicator not only helps in determining that level but also dynamically adjusts it throughout the trade's duration, providing a strategic edge in volatile markets.
Implied Volatility and Historical VolatilityThis indicator provides a visualization of two different volatility measures, aiding in understanding market perceptions and actual price movements. Remember to combine it with other technical analysis tools and risk management strategies for informed trading decisions. The two measures of volatility:
Implied Volatility: Based on the standard deviation of recent price changes, it represents the market's expectation of future volatility.
Historical Volatility: Measured by the daily high-low range as a percentage of the closing price, it reflects the actual volatility experienced recently. It is intended to be used along side the Mean and Standard Deviation Lines indicator.
Inputs:
Period (Days): Defines the number of past bars used to calculate both types of volatility.
Calculations:
Interpretation:
Comparing the lines: Divergence between the lines can indicate potential mispricing:
If the Implied Volatility is higher than the Historical Volatility, the market might be overestimating future volatility.
Conversely, if the Implied Volatility is lower, the market might be underestimating future volatility.
Monitoring trends: Track changes in both lines over time to identify potential shifts in volatility expectations or actual market behavior.
Limitations:
Assumes normality in price distribution, which may not always hold true.
Historical Volatility only reflects past behavior, not future expectations.
Consider other factors like market sentiment and news events for comprehensive volatility analysis.
Trend Continuation Signals [AlgoAlpha]Introducing the Trend Continuation Signals by AlgoAlpha 🌟🚀
Elevate your trading game with this multipurpose indicator, designed to pinpoint trend continuation opportunities as well as highlight volatility and oversold/overbought conditions. Whether you're a trading novice or a seasoned market veteran, this tool offers intuitive visual cues to boost your decision-making and enhance your market analysis. Let's explore the key features, how to use it effectively, and delve into the operational mechanics that make this tool a game-changer in your trading arsenal:
Key Features:
🔥 Advanced Trend Detection : Leverages the Hull Moving Average (HMA) for superior trend tracking as compared to other MAs, offering unique insights into market momentum.
🌈 Volatility Bands : Implements adjustable bands around the trend line, which evolve with market conditions to highlight potential trading opportunities.
⚡ Trend Continuation Signals : Identifies bullish and bearish continuation signals, equipping you with actionable signals to exploit the prevailing market trend.
🎨 Intuitive Color Coding : Employs a vibrant color scheme to distinguish between uptrends, downtrends, and neutral phases, facilitating easy interpretation of the indicator's insights.
🛠 How to Use "Trend Continuation Signals ":
🔍 Setting Up : Incorporate the indicator onto your chart and customize the indicator to suite your preferences.
👀 Reading the Signals : Pay attention to the color-coded trend lines and volatility bands. Green indicates an uptrend, red signifies a downtrend, and gray denotes a neutral market condition.
📈 Identifying Entry Points : Look for bullish (▲) and bearish (▼) continuation icons below or above the price bars as signals for potential entry points for long or short positions, respectively.
🔄 Confirmation : Validate your trades with further analysis or other indicators. The Trend Continuation Signals are most effective when complemented by other technical analysis tools or fundamental insights.
📉 Risk Management : Implement stop-loss orders in line with your risk appetite and adjust them based on the volatility bands provided by the indicator to safeguard your investments.
How It Operates:
The essence of the indicator is captured through the hull moving averages for both the primary and secondary lines, set at periods of 93 and 50, respectively, to reflect market trends and pullbacks that trigger the continuation signals every time price recovers from a detected pullback.
Volatility is quantified through the standard deviation of the midline, magnified by a factor, establishing the upper and lower trend band boundaries.
Further volatility bands are plotted around the main volatility band, providing a granular view of market volatility and potential breakout or breakdown zones.
Market trend direction is determined by comparing the HMA line's current position to its previous value, enhanced by the secondary line to identify continuation patterns.
Embrace the power of the Trend Continuation Signals to enhance your trading strategy! It is important to note that all indicators are best used in confluence with other forms of analysis, happy trading! 📊💥
Candle + Volume as HistogramNow plot Candle and Volume as Histogram Oscillator. It is a very simple but very effective indicator to see what is happening at Volume and Candle levels. It clearly plots whether the market is trending, volatile, what is going to happen in next candles etc. Above Zero is price candle and below Zero is Volume histogram.
SETTINGS:
EMA : 9 period EMA on price is default, which I find the best, but you can change as you likes. Below zero line shows market is in negative phase and above zero market is positive.
PRICE CANDLE : As price and volume have different numeric value, so you have to use multiplier to set the proper price candle, which is plotted above zero
VOLUME : As price and volume have different numeric value, so you have to use multiplier to set the Volume candle, which is plotted below zero.
ZERO LINE : use ‘Gap between Candle and Volume plotting’. Increase the value until you see a thin line between price and volume histogram.
NOTE: (i) When you will plot the indicator for the first time, either price candle may not be appearing properly or volume. It means that non-appearing histogram side needs multiplication, so keep on increasing value on proper side until both side histogram appears properly.
(ii) In other case. Price or volume histogram may appear as full Candle. In this case too, you need to increase multiplier value on opposite side till value becomes equal on both sides.
These settings are important because a share price can be 10 only whereas volume may be in millions. Indicator has been tested on many shares and indexes, so never feels that indicator is improper. Just try to change the setting.
Enjoy.
PresentTrend RMI Synergy - Strategy [presentTrading] █ Introduction and How it is Different
The "PresentTrend RMI Synergy Strategy" is the combined power of the Relative Momentum Index (RMI) and a custom presentTrend indicator. This strategy introduces a multifaceted approach, integrating momentum analysis with trend direction to offer traders a more nuanced and responsive trading mechanism.
BTCUSD 6h L/S Performance
Local
█ Strategy, How It Works: Detailed Explanation
The "PresentTrend RMI Synergy Strategy" intricately combines the Relative Momentum Index (RMI) and a custom SuperTrend indicator to create a powerful tool for traders.
🔶 Relative Momentum Index (RMI)
The RMI is a variation of the Relative Strength Index (RSI), but instead of using price closes against itself, it measures the momentum of up and down movements in price relative to previous prices over a given period. The RMI for a period length `N` is calculated as follows:
RMI = 100 - 100/ (1 + U/D)
where:
- `U` is the average upward price change over `N` periods,
- `D` is the average downward price change over `N` periods.
The RMI oscillates between 0 and 100, with higher values indicating stronger upward momentum and lower values suggesting stronger downward momentum.
RMI = 21
RMI = 42
For more information - RMI Trend Sync - Strategy :
🔶 presentTrend Indicator
The presentTrend indicator combines the Average True Range (ATR) with a moving average to determine trend direction and dynamic support or resistance levels. The presentTrend for a period length `M` and a multiplier `F` is defined as:
- Upper Band: MA + (ATR x F)
- Lower Band: MA - (ATR x F)
where:
- `MA` is the moving average of the close price over `M` periods,
- `ATR` is the Average True Range over the same period,
- `F` is the multiplier to adjust the sensitivity.
The trend direction switches when the price crosses the presentTrend bands, signaling potential entry or exit points.
presentTrend length = 3
presentTrend length = 10
For more information - PresentTrend - Strategy :
🔶 Strategy Logic
Entry Conditions:
- Long Entry: Triggered when the RMI exceeds a threshold, say 60, indicating a strong bullish momentum, and when the price is above the presentTrend, confirming an uptrend.
- Short Entry: Occurs when the RMI drops below a threshold, say 40, showing strong bearish momentum, and the price is below the present trend, indicating a downtrend.
Exit Conditions with Dynamic Trailing Stop:
- Long Exit: Initiated when the price crosses below the lower presentTrend band or when the RMI falls back towards a neutral level, suggesting a weakening of the bullish momentum.
- Short Exit: Executed when the price crosses above the upper presentTrend band or when the RMI rises towards a neutral level, indicating a reduction in bearish momentum.
Equations for Dynamic Trailing Stop:
- For Long Positions: The exit price is set at the lower SuperTrend band once the entry condition is met.
- For Short Positions: The exit price is determined by the upper SuperTrend band post-entry.
These dynamic trailing stops adjust as the market moves, providing a method to lock in profits while allowing room for the position to grow.
This strategy's strength lies in its dual analysis approach, leveraging RMI for momentum insights and presentTrend for trend direction and dynamic stops. This combination offers traders a robust framework to navigate various market conditions, aiming to capture trends early and exit positions strategically to maximize gains and minimize losses.
█ Trade Direction
The strategy provides flexibility in trade direction selection, offering "Long," "Short," or "Both" options to cater to different market conditions and trader preferences. This adaptability ensures that traders can align the strategy with their market outlook, risk tolerance, and trading goals.
█ Usage
To utilize the "PresentTrend RMI Synergy Strategy," traders should input their preferred settings in the Pine Script™ and apply the strategy to their charts. Monitoring RMI for momentum shifts and adjusting positions based on SuperTrend signals can optimize entry and exit points, enhancing potential returns while managing risk.
█ Default Settings
1. RMI Length: 21
The 21-period RMI length strikes a balance between capturing momentum and filtering out market noise, offering a medium-term outlook on market trends.
2. Super Trend Length: 7
A SuperTrend length of 7 periods is chosen for its responsiveness to price movements, providing a dynamic framework for trend identification without excessive sensitivity.
3. Super Trend Multiplier: 4.0
The multiplier of 4.0 for the SuperTrend indicator widens the trend bands, focusing on significant market moves and reducing the impact of minor fluctuations.
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The "PresentTrend RMI Synergy Strategy" represents a significant step forward in trading strategy development, blending momentum and trend analysis in a unique way. By providing a detailed framework for understanding market dynamics, this strategy empowers traders to make more informed decisions.
Gap Removal IndicatorThis gap indicator shows the price of your chosen instrument as if no gaps had occurred overnight. It can be especially useful on highly-volatile exchange-listed instruments that track other 24/7 assets, because the normal candlestick chart of these instruments will create a large amount of noise that may decrease the accuracy of your indicators or make the trend harder to see.
Gaps are determined with the following code:
daychange = ta.change(dayofmonth)
gapup = daychange and open > math.max(open,close)
gapdown = daychange and open < math.min(open,close)
Whereas the gap value is determined by taking the overnight difference in prices:
downgap_change = math.min(open,close) - open
upgap_change = open - math.max(open,close)
The gap changes are cumulatively added and subtracted from the initial closing price to create the gap-adjusted price. The price will depend on how many bars your subscription allows, so pay more attention to the relative differences and/or trend than the cumulative gap-adjusted price itself.
The gap indicator comes pre-built with normal candlestick and Heikin-Ashi candle types, and four indicators (two EMAs, Bollinger bands, and a supertrend). All elements are configurable.
Vo-S-Di-T-I - Volatility Scaled Directional Trend IndicatorThis code represents just the foundation for what's to come. It lays the groundwork for a more sophisticated quant trading model, offering a glimpse into the potential of future developments. I hope my contribution to this community will be valued. I'm here for idea exchanges and coding together, with the key emphasis on ensuring everything we do is grounded on a solid statistical basis.
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The developed code is based on a rigorous quantitative approach for analyzing price trends in the equity sector, utilizing advanced statistical methodology to scale returns based on the volatility observed over predefined periods of 20 and 50 days. This technique for normalizing returns allows us to eliminate distortions due to the intrinsic variability of prices and focus on the underlying structure of price behavior. The primary goal of the code is not to speculatively predict future market movements but rather to identify potential reversal trend signals through price dynamics analysis, within an optimized risk and return context.
Our approach is distinguished by the use of statistical decomposition techniques and time series analysis to interpret price variations as indicators of possible shifts in market behavior. This allows distinguishing between random or short-term price movements and true trend changes, providing a solid foundation for more informed investment decisions.
The current code represents the initial phase of a broader project that envisages the integration of machine learning algorithms to further refine the ability to detect significant changes in price trends. Through the application of predictive models and machine learning techniques, we intend to explore complex patterns in historical price data that may precede trend reversals, always respecting the principles of rigorous statistical analysis and risk management. This development and learning path will allow us to continuously improve investment strategies, leveraging the analytical capabilities of modern data science algorithms applied to the financial sector.
HOW TO READ
Simply put, Z values above 0 indicate an uptrend, while values below indicate a downtrend. IMPORTANT: It is not necessary to consider any crosses between Z-Short and Z-Long, but only potential crosses with 0.
The initial values are set at 20 and 50, but everyone is free to choose the most suitable periods, as long as all choices have valid statistical significance. My advice is to use R or MatLab to explore the best correlation between N and price movements. The reason I have set two values for N (Short and Long) is because it's interesting to assess short-term and medium-to-long-term trends to understand if price movements can lead to reversals only in the short term or also in the medium to long term. This idea came to me because I believe all other trend determination systems have too much lag and unpredictability.
Hamilton - Wick Length PredictionWick Length Prediction is a Pine Script indicator crafted to empower traders by predicting the potential length and direction of the next candle's wick based on historical price action. By analyzing previous candles' wick sizes, this tool provides valuable foresight into future price dynamics, enhancing decision-making for traders.
Key Features:
Wick Percentage Analysis : Calculates the percentages of the upper and lower wicks from the previous candle relative to its total range, offering a predictive insight into the next wick’s potential direction and size.
Directional Bias Indicator : Identifies the longer wick between the previous candle's upper and lower wicks to suggest a directional bias—green indicates an upward prediction, while red suggests downward.
Targeted Plotting : Marks a horizontal line at the anticipated wick position for the forthcoming candle, aiding traders in identifying potential price rejection zones ahead of time.
Strategic Insights for Traders:
Understanding Market Pressure : Recognizes that wicks typically indicate pressure in the opposite direction of their occurrence, presenting potential targets for price movement towards the opposite side. This insight is invaluable for identifying reversal zones or continuation patterns.
Optimal for Scalping : Especially beneficial for scalpers, this tool helps in pinpointing precise entry and exit points by forecasting where the price might face opposition and potentially reverse or absorb the wick.
Timeframe Flexibility : While best suited for higher timeframes, it also delivers on lower timeframes during aggressive market movements, making it a versatile addition to your trading arsenal.
Application Tips :
Leverage in combination with other indicators and support/resistance levels to refine your trading strategy.
Ideal for enhancing price action analysis, providing a clearer understanding of potential market movements.
Use as a strategic complement to your existing approach, mindful of its predictive nature to inform better trading decisions.
Disclaimer: Trading involves significant risk. This tool aims to support a diversified trading strategy, but it's crucial to perform your own analysis and adopt appropriate risk management practices.
Dynamic Price Targets @shrilssDynamic Price Targets is a designed to provide traders with a comprehensive view of dynamic price levels based on Volume Weighted Moving Average (VWMA) and standard deviation. This script allows users to identify potential support and resistance zones, aiding in strategic decision-making during market analysis.
The script calculates the VWMA of a chosen price source over a specified length, establishing a dynamic baseline for market trends. The standard deviation is then used to derive multiple upper and lower targets, each representing a certain deviation from the VWMA. These levels are color-coded for clarity, with upper targets displayed in shades of red and lower targets in shades of green.
SAT - Sentiment Analysis Tool by Csth97This code calculates the correlation between the ATR and the OBV of the price, and plots the difference between the positive and negative OBV correlations as a line. It also plots horizontal lines at the UP and DOWN levels, and signals bullish and bearish crosses when the difference line crosses those levels.
Liquidity LevelsThe "Liquidity Levels" indicator on TradingView is designed to identify and highlight liquidity levels in the market. This indicator is based on pivot highs and lows with an adjustable offset to adjust the importance and length of the identified levels.
The strength of this indicator lies in its ability to highlight changes in liquidity levels, which can be crucial for traders. By marking pivot highs and lows, potential areas of high liquidity are highlighted, which can indicate where significant market movements or reversal points may occur.
The flexibility of whether the calculation is based on the closing price or the high/low prices allows for customisable analysis. The visual representation of liquidity levels by lines makes it easier to identify and monitor these key areas in the chart, which can provide additional value for traders.
Reversal and Breakout Signals [AlgoAlpha]🚀🌟 Introducing the Reversal and Breakout Signals by AlgoAlpha 🌟🚀
This innovative tool is crafted to enhance your chart analysis by identifying potential reversal and breakout opportunities directly on your charts. It's designed with both novice and experienced traders in mind, providing intuitive visual cues for better decision-making. Let's dive into the key features and how it operates:
### Key Features:
🔶 Dynamic Period Settings: Customize the sensitivity of the indicator with user-defined periods for both the indicator and volume strength.
📊 Volume Threshold: Set a threshold to define what constitutes strong volume, enabling the identification of significant market movements.
💡 Trend Coloring: Option to color candles during trends, making it easier to visualize bullish and bearish market conditions.
🌈 Customizable Visuals: Choose your preferred colors for bullish, bearish, and breakout signals, personalizing the chart to your liking.
🚨 Advanced Alert System: Configure alerts for reversal and breakout signals, ensuring you never miss a potential trading opportunity.
### How to Use:
To maximize the effectiveness of the Reversal and Breakout Signals tool, follow these steps:
1. 🔧 Set Up Your Preferences:
- Adjust the Indicator Period and Volume Strength Period to match the timeframe of your trading strategy. This fine-tuning allows the indicator to better align with your specific market analysis needs.
- Define the Strong Volume Threshold to distinguish between ordinary and significant volume movements. This helps in identifying breakout or reversal signals with higher confidence.
2. 🎨 Customize Visuals:
- Choose colors for Bullish , Bearish , and Breakout Signals to visually differentiate between different types of market activities. This customization facilitates quicker decision-making while scanning charts.
3. 🔍 Reversal Signals:
- Bullish Reversal : Look for a triangle below the bar indicating a potential upward movement. It's identified when the price dips below the lower level but closes above it, suggesting a rejection of lower prices.
- Bearish Reversal : A triangle above the bar signals a potential downward movement. This occurs when the price spikes above the upper level but closes below, indicating a rejection of higher prices.
4. 📈 Trend and Breakout Signals:
- Diamonds represent breakout signals. A bullish breakout is marked below the bar when the price closes above the upper level, suggesting strong buying pressure. Conversely, a bearish breakout above the bar indicates strong selling pressure as the price closes below the lower level.
- The tool also features a Trend Tracker that highlights the current market trend using the Hull Moving Average (HMA). This can help you stay aligned with the overall market direction for your trades.
By integrating these steps into your trading strategy, the Reversal and Breakout Signals tool can provide actionable insights to help identify potential entry and exit points, enhancing your trading decisions with visual cues and alerts for market reversals and breakouts.
### How It Works:
The core logic revolves around calculating weighted moving averages of high and low prices over a user-defined period, identifying the highest and lowest points within this period to establish potential breakout or breakdown levels while reducing the amount of noise, hence the use of moving averages.
1. Weighted Moving Averages Calculation:
sh = ta.wma(high, len)
sl = ta.wma(low, len)
h = ta.highest(sh, len)
l = ta.lowest(sl, len)
2. Breakout and Reversal Detection:
The script then employs logic to detect bullish and bearish breakouts and reversals based on the closing price's position relative to these levels, combined with volume analysis to confirm the strength of the move.
if not (h < h or h > h )
hstore := h
if not (l < l or l > l )
lstore := l
bullishbreakout := (breakout or ((breakout or breakout or breakout or breakout ) and candledir == 1)) and strongvol and not (bullishbreakout or bullishbreakout or bullishbreakout )
bearishbreakout := (breakdown or ((breakdown or breakdown or breakdown or breakdown ) and candledir == -1)) and strongvol and not (bearishbreakout or bearishbreakout or bearishbreakout )
3. Visual Indicators and Alerts:
Visual cues such as triangle shapes for reversals and diamonds for breakouts, along with colored bars, make it easy to spot these opportunities. Additionally, alerts can be set up for these events, ensuring traders can react promptly to potential trading setups.
plotshape(bullishrej and not (state ==- 1) ? low * 0.9995 : na, " Bullish Reversal ", shape.triangleup, location.belowbar, color.new(green, 0), size = size.tiny, text = "𝓡", textcolor = color.gray)
plotshape(bearishrej and not (state == 1) ? high * 1.0005 : na, " Bearish Reversal ", shape.triangledown, location.abovebar, color.new(red, 0), size = size.tiny, text = "𝓡", textcolor = color.gray)
plotshape(bullishbreakout ? low * 0.999 : na, " Bullish Breakout ", shape.diamond, location.belowbar, color.new(yellow, 0), size = size.tiny, text = "𝓑", textcolor = color.gray)
plotshape(bearishbreakout ? high * 1.001 : na, " Bearish Breakout ", shape.diamond, location.abovebar, color.new(yellow, 0), size = size.tiny, text = "𝓑", textcolor = color.gray)
This script is a versatile tool designed to aid in the identification of key reversal and breakout points, helping traders to make informed decisions based on technical analysis. Its customization options allow for a tailored analysis experience, fitting the unique needs and strategies of each trader.
Rate of Change MachineRate of Change Machine
Author: RWCS_LTD
Disclaimer: This script is provided for informational purposes only and should not be considered financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always conduct your own research and consult with a qualified financial advisor before making any investment decisions.
Introduction:
The Rate of Change Machine is a script designed to assist traders in analyzing multiple cryptocurrency trading pairs simultaneously. This comprehensive indicator offers a holistic view of the rate of change and related metrics, aiding traders in making informed decisions.
Asset Selection:
The script enables users to select up to nine different cryptocurrency trading pairs for in-depth analysis.
Volume Calculation:
Volume plays a crucial role in the analysis, with customizable parameters for volume weighting and length.
Relative Strength Calculation:
Relative Strength is determined through two Exponential Moving Averages (EMA) with user-defined lengths.
Timeframe Weightings:
Different timeframes (1D, AVG 3D, AVG 5D, AVG 7D, AVG 14D, AVG 30D) are assigned weightings to calculate a comprehensive trend score.
Weighted Average and Individual Rate of Change (RoC) Calculation:
The getWeightedAvgAndIndividualROC function calculates the RoC for each selected trading pair based on the given timeframes and weights.
Table Setup:
A table is created to display the results for each trading pair, including relative strength, volume trend, RoC for different timeframes, and a weighted trend score.
Table Formatting:
The table is formatted with different colors indicating positive or negative values for easier interpretation.
Table Position and Size:
Users can customize the position and size of the table on the chart.
Data Retrieval:
The script retrieves the calculated values for each trading pair using the request.security function.
Output:
The final output is a table on the chart, showing relevant information for the selected trading pairs, aiding traders in making informed decisions based on the rate of change and other factors. This indicator provides a comprehensive view of the rate of change and related metrics for multiple trading pairs, assisting traders in identifying potential trends and making informed trading decisions.
[blackcat] L2 Twisted Pair IndicatorOn the grand stage of the financial market, every trader is looking for a partner who can lead them to dance the tango well. The "Twisted Pair" indicator is that partner who dances gracefully in the market fluctuations. It weaves the rhythm of the market with two lines, helping traders to find the rhythm in the market's dance floor.
Imagine when the market is as calm as water, the "Twisted Pair" is like two ribbons tightly intertwined. They almost overlap on the chart, as if whispering: "Now, let's enjoy these quiet dance steps." This is the market consolidation period, the price fluctuation is not significant, traders can relax and slowly savor every detail of the market.
Now, let's describe the market logic of this code in natural language:
- **HJ_1**: This is the foundation of the market dance steps, by calculating the average price and trading volume, setting the tone for the market rhythm.
- **HJ_2** and **HJ_3**: These two lines are the arms of the dance partner, they help traders identify the long-term trend of the market through smoothing.
- **HJ_4**: This is a magnifying glass for market sentiment, it reveals the tension and excitement of the market by calculating the short-term deviation of the price.
- **A7** and **A9**: These two lines are the guide to the dance steps, they separate when the market volatility increases, guiding the traders in the right direction.
- **WATCH**: This is the signal light of the dance, when the two lines overlap, the market is calm; when they separate, the market is active.
The "Twisted Pair" indicator is like a carefully choreographed dance, it allows traders to find their own rhythm in the market dance floor, whether in a calm slow dance or a passionate tango. Remember, the market is always changing, and the "Twisted Pair" is the perfect dance partner that can lead you to dance out brilliant steps.
The script of this "Twisted Pair" uses three different types of moving averages: EMA (Exponential Moving Average), DEMA (Double EMA), and TEMA (Triple EMA). These types can be selected by the user through exchange input.
Here are the main functions of this code:
1. Defined the DEMA and TEMA functions: These two functions are used to calculate the corresponding moving averages. EMA is the exponential moving average, which is a special type of moving average that gives more weight to recent data. In the first paragraph, ema1 is the EMA of "length", and ema2 is the EMA of ema1. DEMA is 2 times of ema1 minus ema2.
2. Let users choose to use EMA, DEMA or TEMA: This part of the code provides an option for users to choose which type of moving average they want to use.
3. Defined an algorithm called "Twisted Pair algorithm": This part of the code defines a complex algorithm to calculate a value called "HJ". This algorithm involves various complex calculations and applications of EMA, DEMA, TEMA.
4. Plotting charts: The following code is used to plot charts on Tradingview. It uses the plot function to draw lines, the plotcandle function to draw candle (K-line) charts, and yellow and red to represent different conditions.
5. Specify colors: The last two lines of code use yellow and red K-line charts to represent the conditions of HJ_7. If the conditions of HJ_7 are met, the color of the K-line chart will change to the corresponding color.
BetaBeta , also known as the Beta coefficient, is a measure that compares the volatility of an individual underlying or portfolio to the volatility of the entire market, typically represented by a market index like the S&P 500 or an investible product such as the SPY ETF (SPDR S&P 500 ETF Trust). A Beta value provides insight into how an asset's returns are expected to respond to market swings.
Interpretation of Beta Values
Beta = 1: The asset's volatility is in line with the market. If the market rises or falls, the asset is expected to move correspondingly.
Beta > 1: The asset is more volatile than the market. If the market rises or falls, the asset's price is expected to rise or fall more significantly.
Beta < 1 but > 0: The asset is less volatile than the market. It still moves in the same direction as the market but with less magnitude.
Beta = 0: The asset's returns are not correlated with the market's returns.
Beta < 0: The asset moves in the opposite direction to the market.
Example
A beta of 1.20 relative to the S&P 500 Index or SPY implies that if the S&P's return increases by 1%, the portfolio is expected to increase by 12.0%.
A beta of -0.10 relative to the S&P 500 Index or SPY implies that if the S&P's return increases by 1%, the portfolio is expected to decrease by 0.1%. In practical terms, this implies that the portfolio is expected to be predominantly 'market neutral' .
Calculation & Default Values
The Beta of an asset is calculated by dividing the covariance of the asset's returns with the market's returns by the variance of the market's returns over a certain period (standard period: 1 years, 250 trading days). Hint: It's noteworthy to mention that Beta can also be derived through linear regression analysis, although this technique is not employed in this Beta Indicator.
Formula: Beta = Covariance(Asset Returns, Market Returns) / Variance(Market Returns)
Reference Market: Essentially any reference market index or product can be used. The default reference is the SPY (SPDR S&P 500 ETF Trust), primarily due to its investable nature and broad representation of the market. However, it's crucial to note that Beta can also be calculated by comparing specific underlyings, such as two different stocks or commodities, instead of comparing an asset to the broader market. This flexibility allows for a more tailored analysis of volatility and correlation, depending on the user's specific trading or investment focus.
Look-back Period: The standard look-back period is typically 1-5 years (250-1250 trading days), but this can be adjusted based on the user's preference and the specifics of the trading strategy. For robust estimations, use at least 250 trading days.
Option Delta: An optional feature in the Beta Indicator is the ability to select a specific Delta value if options are written on the underlying asset with Deltas less than 1, providing an estimation of the beta-weighted delta of the position. It involves multiplying the beta of the underlying asset by the delta of the option. This addition allows for a more precise assessment of the underlying asset's correspondence with the overall market in case you are an options trader. The default Delta value is set to 1, representing scenarios where no options on the underlying asset are being analyzed. This default setting aligns with analyzing the direct relationship between the asset itself and the market, without the layer of complexity introduced by options.
Calculation: Simple or Log Returns: In the calculation of Beta, users have the option to choose between using simple returns or log returns for both the asset and the market. The default setting is 'Simple Returns'.
Advantages of Using Beta
Risk Management: Beta provides a clear metric for understanding and managing the risk of a portfolio in relation to market movements.
Portfolio Diversification: By knowing the beta of various assets, investors can create a balanced portfolio that aligns with their risk tolerance and investment goals.
Performance Benchmarking: Beta allows investors to compare an asset's risk-adjusted performance against the market or other benchmarks.
Beta-Weighted Deltas for Options Traders
For options traders, understanding the beta-weighted delta is crucial. It involves multiplying the beta of the underlying asset by the delta of the option. This provides a more nuanced view of the option's risk relative to the overall market. However, it's important to note that the delta of an option is dynamic, changing with the asset's price, time to expiration, and other factors.
AI SuperTrend x Pivot Percentile - Strategy [PresentTrading]█ Introduction and How it is Different
The AI SuperTrend x Pivot Percentile strategy is a sophisticated trading approach that integrates AI-driven analysis with traditional technical indicators. Combining the AI SuperTrend with the Pivot Percentile strategy highlights several key advantages:
1. Enhanced Accuracy in Trend Prediction: The AI SuperTrend utilizes K-Nearest Neighbors (KNN) algorithm for trend prediction, improving accuracy by considering historical data patterns. This is complemented by the Pivot Percentile analysis which provides additional context on trend strength.
2. Comprehensive Market Analysis: The integration offers a multi-faceted approach to market analysis, combining AI insights with traditional technical indicators. This dual approach captures a broader range of market dynamics.
BTC 6H L/S Performance
Local
█ Strategy: How it Works - Detailed Explanation
🔶 AI-Enhanced SuperTrend Indicators
1. SuperTrend Calculation:
- The SuperTrend indicator is calculated using a moving average and the Average True Range (ATR). The basic formula is:
- Upper Band = Moving Average + (Multiplier × ATR)
- Lower Band = Moving Average - (Multiplier × ATR)
- The moving average type (SMA, EMA, WMA, RMA, VWMA) and the length of the moving average and ATR are adjustable parameters.
- The direction of the trend is determined based on the position of the closing price in relation to these bands.
2. AI Integration with K-Nearest Neighbors (KNN):
- The KNN algorithm is applied to predict trend direction. It uses historical price data and SuperTrend values to classify the current trend as bullish or bearish.
- The algorithm calculates the 'distance' between the current data point and historical points. The 'k' nearest data points (neighbors) are identified based on this distance.
- A weighted average of these neighbors' trends (bullish or bearish) is calculated to predict the current trend.
For more please check: Multi-TF AI SuperTrend with ADX - Strategy
🔶 Pivot Percentile Analysis
1. Percentile Calculation:
- This involves calculating the percentile ranks for high and low prices over a set of predefined lengths.
- The percentile function is typically defined as:
- Percentile = Value at (P/100) × (N + 1)th position
- Where P is the desired percentile, and N is the number of data points.
2. Trend Strength Evaluation:
- The calculated percentiles for highs and lows are used to determine the strength of bullish and bearish trends.
- For instance, a high percentile rank in the high prices may indicate a strong bullish trend, and vice versa for bearish trends.
For more please check: Pivot Percentile Trend - Strategy
🔶 Strategy Integration
1. Combining SuperTrend and Pivot Percentile:
- The strategy synthesizes the insights from both AI-enhanced SuperTrend and Pivot Percentile analysis.
- It compares the trend direction indicated by the SuperTrend with the strength of the trend as suggested by the Pivot Percentile analysis.
2. Signal Generation:
- A trading signal is generated when both the AI-enhanced SuperTrend and the Pivot Percentile analysis agree on the trend direction.
- For instance, a bullish signal is generated when both the SuperTrend is bullish, and the Pivot Percentile analysis shows strength in bullish trends.
🔶 Risk Management and Filters
- ADX and DMI Filter: The strategy uses the Average Directional Index (ADX) and the Directional Movement Index (DMI) as filters to assess the trend's strength and direction.
- Dynamic Trailing Stop Loss: Based on the SuperTrend indicator, the strategy dynamically adjusts stop-loss levels to manage risk effectively.
This strategy stands out for its ability to combine real-time AI analysis with established technical indicators, offering traders a nuanced and responsive tool for navigating complex market conditions. The equations and algorithms involved are pivotal in accurately identifying market trends and potential trade opportunities.
█ Usage
To effectively use this strategy, traders should:
1. Understand the AI and Pivot Percentile Indicators: A clear grasp of how these indicators work will enable traders to make informed decisions.
2. Interpret the Signals Accurately: The strategy provides bullish, bearish, and neutral signals. Traders should align these signals with their market analysis and trading goals.
3. Monitor Market Conditions: Given that this strategy is sensitive to market dynamics, continuous monitoring is crucial for timely decision-making.
4. Adjust Settings as Needed: Traders should feel free to tweak the input parameters to suit their trading preferences and to respond to changing market conditions.
█Default Settings and Their Impact on Performance
1. Trading Direction (Default: "Both")
Effect: Determines whether the strategy will take long positions, short positions, or both. Adjusting this setting can align the strategy with the trader's market outlook or risk preference.
2. AI Settings (Neighbors: 3, Data Points: 24)
Neighbors: The number of nearest neighbors in the KNN algorithm. A higher number might smooth out noise but could miss subtle, recent changes. A lower number makes the model more sensitive to recent data but may increase noise.
Data Points: Defines the amount of historical data considered. More data points provide a broader context but may dilute recent trends' impact.
3. SuperTrend Settings (Length: 10, Factor: 3.0, MA Source: "WMA")
Length: Affects the sensitivity of the SuperTrend indicator. A longer length results in a smoother, less sensitive indicator, ideal for long-term trends.
Factor: Determines the bandwidth of the SuperTrend. A higher factor creates wider bands, capturing larger price movements but potentially missing short-term signals.
MA Source: The type of moving average used (e.g., WMA - Weighted Moving Average). Different MA types can affect the trend indicator's responsiveness and smoothness.
4. AI Trend Prediction Settings (Price Trend: 10, Prediction Trend: 80)
Price Trend and Prediction Trend Lengths: These settings define the lengths of weighted moving averages for price and SuperTrend, impacting the responsiveness and smoothness of the AI's trend predictions.
5. Pivot Percentile Settings (Length: 10)
Length: Influences the calculation of pivot percentiles. A shorter length makes the percentile more responsive to recent price changes, while a longer length offers a broader view of price trends.
6. ADX and DMI Settings (ADX Length: 14, Time Frame: 'D')
ADX Length: Defines the period for the Average Directional Index calculation. A longer period results in a smoother ADX line.
Time Frame: Sets the time frame for the ADX and DMI calculations, affecting the sensitivity to market changes.
7. Commission, Slippage, and Initial Capital
These settings relate to transaction costs and initial investment, directly impacting net profitability and strategy feasibility.
