FlexiMA x FlexiST - Strategy [presentTrading]█ Introduction and How it is Different
The FlexiMA x FlexiST Strategy blends two analytical methods - FlexiMA and FlexiST, which are opened in my early post.
- FlexiMA calculates deviations between an indicator source and a dynamic moving average, controlled by a starting factor and increment factor.
- FlexiST, on the other hand, leverages the SuperTrend model, adjusting the Average True Range (ATR) length for a comprehensive trend-following oscillator.
This synergy offers traders a more nuanced and multifaceted tool for market analysis.
BTC 6H L/S Performance
Local
█ Strategy, How It Works: Detailed Explanation
The strategy combines two components: FlexiMA and FlexiST, each utilizing unique methodologies to analyze market trends.
🔶FlexiMA Component:
- Calculates deviations between an indicator source and moving averages of variable lengths.
- Moving average lengths are dynamically adjusted using a starting factor and increment factor.
- Deviations are normalized and analyzed to produce median and standard deviation values, forming the FlexiMA oscillator.
Length indicator (50)
🔶FlexiST Component:
- Uses SuperTrend indicators with varying ATR (Average True Range) lengths.
- Trends are identified based on the position of the indicator source relative to the SuperTrend bands.
- Deviations between the indicator source and SuperTrend values are calculated and normalized.
Starting Factor (5)
🔶Combined Strategy Logic:
- Entry Signals:
- Long Entry: Triggered when median values of both FlexiMA and FlexiST are positive.
- Short Entry: Triggered when median values of both FlexiMA and FlexiST are negative.
- Exit Signals:
- Long Exit: Triggered when median values of FlexiMA or FlexiST turn negative.
- Short Exit: Triggered when median values of FlexiMA or FlexiST turn positive.
This strategic blend of FlexiMA and FlexiST allows for a nuanced analysis of market trends, providing traders with signals based on a comprehensive view of market momentum and trend strength.
█ Trade Direction
The strategy is designed to cater to various trading preferences, offering "Long", "Short", and "Both" options. This flexibility allows traders to align the strategy with their specific market outlook, be it bullish, bearish, or a combination of both.
█ Usage
Traders can effectively utilize the FlexiMA x FlexiST Strategy by first selecting their desired trade direction. The strategy then generates entry signals when the conditions for either the FlexiMA or FlexiST are met, indicating potential entry points in the market. Conversely, exit signals are generated when the conditions for these indicators diverge, thus signaling a potential shift in market trends and suggesting a strategic exit point.
█ Default Settings
1. Indicator Source (HLC3): Provides a balanced and stable price source, reducing the impact of extreme market fluctuations.
2. Indicator Lengths (20 for FlexiMA, 10 for FlexiST): Longer FlexiMA length smooths out short-term fluctuations, while shorter FlexiST length allows for quicker response to market changes.
3. Starting Factors (1.0 for FlexiMA, 0.618 for FlexiST): Balanced start for FlexiMA and a harmonized approach for FlexiST, resonating with natural market cycles.
4. Increment Factors (1.0 for FlexiMA, 0.382 for FlexiST): FlexiMA captures a wide range of market behaviors, while FlexiST provides a gradual transition to capture finer trend shifts.
5. Normalization Methods ('None'): Uses raw deviations, suitable for markets where absolute price movements are more significant.
6. Trade Direction ('Both'): Allows strategy to consider both long and short opportunities, ideal for versatile market engagement.
*More details:
1. FlexiMA
2. FlexiST
波動率
Modern Portfolio TheoryModern Portfolio Theory
The indicator is designed to apply the principles of Modern Portfolio Theory, a financial theory developed by Harry Markowitz. MPT aims to maximize portfolio returns for a given level of risk by diversifying investments.
User Inputs:
Users can customize various parameters, including the bar scale, risk-free rate, and the start year for the portfolio. Additionally, users can assign weights to different assets (symbols) in the portfolio.
Asset Selection:
Users can choose up to 10 different symbols (assets) for the portfolio. The script supports a variety of symbols, including cryptocurrencies such as BTCUSD and ETHUSD.
Weights and Allocation:
Users can assign weights to each selected asset, determining its percentage allocation in the portfolio. The script calculates the total portfolio weight to ensure it equals 100%. If total portfolio weight is lower then 100% you will see orange color with additional cash % bellow
If total portfolio weight is bigger then 100% you will see red big % warning.
Warning: (Total Weight must be 100%)
Cash Mode:
Risk and Return Calculation:
The script calculates the daily returns and standard deviation for each selected asset. These metrics are essential for assessing the risk and return of each asset, as well as the overall portfolio.
Scatter Plot Visualization:
The indicator includes a scatter plot that visualizes the risk-return profile of each asset. Each point on the plot represents an asset, and its position is determined by its risk (X-axis) and return (Y-axis).
Portfolio Optimization:
The script calculates the risk and return of the overall portfolio based on the selected assets and their weights. Based on the selected assets and their weights user can create optimal portfolio with preferable risk and return.
It then plots the portfolio point on the scatter plot, indicating its risk-return profile.
Additional Information:
The indicator provides a table displaying information about each selected asset, including its symbol, weight, and total portfolio weight. The table also shows the total portfolio weight and, if applicable, the percentage allocated to cash.
Visualization and Legend:
The script includes visual elements such as a legend, capital allocation line (CAL), and labels for risk-free rate and key information. This enhances the overall understanding of the portfolio's risk and return characteristics.
User Guidance:
The script provides informative labels and comments to guide users through the interpretation of the scatter plot, risk-return axes, and other key elements.
Interactivity:
Users can interact with the indicator on the TradingView platform, exploring different asset combinations and weightings to observe the resulting changes in the portfolio's risk and return.
In summary, this Pine Script serves as a comprehensive tool for traders and investors interested in applying Modern Portfolio Theory principles to optimize their portfolio allocations based on individual asset characteristics, risk preferences, and return
ATR TrendTL;DR - An average true range (ATR) based trend
ATR trend uses a (customizable) ATR calculation and highest high & lowest low prices to calculate the actual trend. Basically it determines the trend direction by using highest high & lowest low and calculates (depending on the determined direction) the ATR trend by using a ATR based calculation and comparison method.
The indicator will draw one trendline by default. It is also possible to draw a second trendline which shows a 'negative trend'. This trendline is calculated the same way the primary trendline is calculated but uses a negative (-1 by default) value for the ATR calculation. This trendline can be used to detect early trend changes and/or micro trends.
How to use:
Due to its ATR nature the ATR trend will show trend changes by changing the trendline direction. This means that when the price crosses the trendline it does not automatically mean a trend change. However using the 'negative trend' option ATR trend can show early trend changes and therefore good entry points.
Some notes:
- A (confirmed) trend change is shown by a changing color and/or moving trendline (up/down)
- Unlike other indicators the 'time period' value is not the primary adjustment setting. This value is only used to calculate highest high & lowest low values and has medium impact on trend calculation. The primary adjustment setting is 'ATR weight'
- Every settings has a tooltip with further explanation
- I added additional color coding which uses a different color when the trend attempts to change but the trend change isn't confirmed (yet)
- Default values work fine (at least in my back testing) but the recommendation is to adjust the settings (especially ATR weight) to your trading style
- You can further finetune this indicator by using custom moving average types for the ATR calculation (like linear regression or Hull moving average)
- Both trendlines can be used to determine future support and resistance zones
- ATR trend can be used as a stop loss finder
- Alerts are using buy/sell signals
- You can use fancy color filling ;)
Happy trading!
Daniel
Momentum Bias Index [AlgoAlpha]Description:
The Momentum Bias Index by AlgoAlpha is designed to provide traders with a powerful tool for assessing market momentum bias. The indicator calculates the positive and negative bias of momentum to gauge which one is greater to determine the trend.
Key Features:
Comprehensive Momentum Analysis: The script aims to detect momentum-trend bias, typically when in an uptrend, the momentum oscillator will oscillate around the zero line but will have stronger positive values than negative values, similarly for a downtrend the momentum will have stronger negative values. This script aims to quantify this phenomenon.
Overlay Mode: Traders can choose to overlay the indicator on the price chart for a clear visual representation of market momentum.
Take-profit Signals: The indicator includes signals to lock in profits, they appear as labels in overlay mode and as crosses when overlay mode is off.
Impulse Boundary: The script includes an impulse boundary, the impulse boundary is a threshold to visualize significant spikes in momentum.
Standard Deviation Multiplier: Users can adjust the standard deviation multiplier to increase the noise tolerance of the impulse boundary.
Bias Length Control: Traders can customize the length for evaluating bias, enabling them to fine-tune the indicator according to their trading preferences. A higher length will give a longer-term bias in trend.
Z-score changeAs a wise man once said that:
1. beginners think in $ change
2. intermediates think in % change
3. pros think in Z change
Here is the "Z-score change" indicator that calculates up/down moves normalized by standard deviation (volatility) displayed as bar chart with 1,2 and 3 stdev levels.
ORB Algo | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ORB Algo indicator! ORB stands for "Opening Range Breakout" which is a common trading strategy. The indicator can analyze the market trend in the current session and give "Buy / Sell", "Take Profit" and "Stop Loss" signals. For more information about the analyzing process of the indicator, you can read "How Does It Work ?" section of the description.
Features of the new ORB Algo indicator :
Buy & Sell Signals
Up To 3 Take Profit Signals
Stop-Loss Signals
Alerts for Buy / Sell, Take-Profit and Stop-Loss
Customizable Algoritm
Session Dashboard
Backtesting Dashboard
📌 HOW DOES IT WORK ?
This indicator works best in 1-minute timeframe. The idea is that the trend of the current session can be forecasted by analyzing the market for a while after the session starts. However, each market has it's own dynamics and the algorithm will need fine-tuning to get the best performance possible. So, we've implemented a "Backtesting Dashboard" that shows the past performance of the algorithm in the current ticker with your current settings. Always keep in mind that past performance does not guarantee future results.
Here are the steps of the algorithm explained briefly :
1. The algorithm follows and analyzes the first 30 minutes (can be adjusted) of the session.
2. Then, algorithm checks for breakouts of the opening range's high or low.
3. If a breakout happens in a bullish or a bearish direction, the algorithm will now check for retests of the breakout. Depending on the sensitivity setting, there must be 0 / 1 / 2 / 3 failed retests for the breakout to be considered as reliable.
4. If the breakout is reliable, the algorithm will give an entry signal.
5. After the position entry, algorithm will now wait for Take-Profit or Stop-Loss zones and signal if any of them occur.
If you wonder how does the indicator find Take-Profit & Stop-Loss zones, you can check the "Settings" section of the description.
🚩UNIQUENESS
While there are indicators that show the opening range of the session, they come short with features like indicating breakouts, entries, and Take-Profit & Stop-Loss zones. We are also aware of that different stock markets have different dynamics, and tuning the algorithm for different markets is really important for better results, so we decided to make the algorithm fully customizable. Besides all that, our indicator contains a detailed backtesting dashboard, so you can see past performance of the algorithm in the current ticker. While past performance does not yield any guarantee for future results, we believe that a backtesting dashboard is necessary for tuning the algorithm. Another strength of this indicator is that there are multiple options for detection of Take-Profit and Stop-Loss zones, which the trader can select one of their liking.
⚙️SETTINGS
Keep in mind that best chart timeframe for this indicator to work is the 1-minute timeframe.
TP = Take-Profit
SL = Stop-Loss
EMA = Exponential Moving Average
OR = Opening Range
ATR = Average True Range
1. Algorithm
ORB Timeframe -> This setting determines the timeframe that the algorithm will analyze the market after a new session begins before giving any signals. It's important to experiment with this setting and find the best option that suits the current ticker for the best performance. More volatile stocks will often require this setting to be larger, while more stabilized stocks may have this setting shorter.
Sensitivity -> This setting determines how much failed retests are needed to take a position entry. Higher senstivity means that less retests are needed to consider the breakout as reliable. If you think that the current ticker makes strong movements in a bullish & bearish direction after a breakout, you should set this setting higher. If you think the opposite, meaning that the ticker does not decide the trend right after a breakout, this setting show be lower.
(High = 0 Retests, Medium = 1 Retest, Low = 2 Retests, Lowest = 3 Retests)
Breakout Condition -> The condition for the algorithm to detect breakouts.
Close = Bar needs to close higher than the OR High Line in a bullish breakout, or lower than the OR Low Line in a bearish breakout. EMA = The EMA of the bar must be higher / lower than OR Lines instead of the close price.
TP Method -> The method for the algorithm to use when determining TP zones.
Dynamic = This TP method essentially tries to find the bar that price starts declining the current trend and going to the other direction, and puts a TP zone there. To achieve this, it uses an EMA line, and when the close price of a bar crosses the EMA line, It's a TP spot.
ATR = In this TP method, instead of a dynamic approach the TP zones are pre-determined using the ATR of the entry bar. This option is generally for traders who just want to know their TP spots beforehand while trading. Selecting this option will also show TP zones at the ORB Dashboard.
"Dynamic" option generally performs better, while the "ATR" method is safer to use.
EMA Length -> This setting determines the length of the EMA line used in "Dynamic TP method" and "EMA Breakout Condition". This is completely up to the trader's choice, though the default option should generally perform well. You might want to experiment with this setting and find the optimal length for the current ticker.
Stop-Loss -> Algorithm will place the Stop-Loss zone using setting.
Safer = The SL zone will be placed closer to the OR High for a bullish entry, and closer to the OR Low for a bearish entry.
Balanced = The SL zone will be placed in the center of OR High & OR Low
Risky = The SL zone will be placed closer to the OR Low for a bullish entry, and closer to the OR High for a bearish entry.
Adaptive SL -> This option only takes effect if the first TP zone is hit.
Enabled = After the 1st TP zone is hit, the SL zone will be moved to the entry price, essentially making the position risk-free.
Disabled = The SL zone will never change.
2. ORB Dashboard
ORB Dashboard shows the information about the current session.
3. ORB Backtesting
ORB Backtesting Dashboard allows you to see past performance of the algorithm in the current ticker with current settings.
Total amount of days that can be backtested depends on your TV subscription.
Backtesting Exit Ratios -> You can select how much of percent your entry will be closed at any TP zone while backtesting. For example, %90, %5, %5 means that %90 of the position will be closed at the first TP zone, %5 of it will be closed at the 2nd TP zone, and %5 of it will be closed at the last TP zone.
Open Interest SThis script shows Open Interest. You can choose measure, view and highlight large OI changes based on Z-Score.
Features
Measure USD or COIN
View OI Candles or OI Change columns with wicks
Z-Score Highlight Z Length is the period for calculations, Z Threshold is the standard
deviation from the average change in OI for the selected period
Color You can change the colors for OI
GARCH Volatility Estimation - The Quant ScienceThe GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model is a statistical model used to forecast the volatility of a financial asset. This model takes into account the fluctuations in volatility over time, recognizing that volatility can vary in a heteroskedastic (i.e., non-constant variance) manner and can be influenced by past events.
The general formula of the GARCH model is:
σ²(t) = ω + α * ε²(t-1) + β * σ²(t-1)
where:
σ²(t) is the conditional variance at time t (i.e., squared volatility)
ω is the constant term (intercept) representing the baseline level of volatility
α is the coefficient representing the impact of the squared lagged error term on the conditional variance
ε²(t-1) is the squared lagged error term at the previous time period
β is the coefficient representing the impact of the lagged conditional variance on the current conditional variance
In the context of financial forecasting, the GARCH model is used to estimate the future volatility of the asset.
HOW TO USE
This quantitative indicator is capable of estimating the probable future movements of volatility. When the GARCH increases in value, it means that the volatility of the asset will likely increase as well, and vice versa. The indicator displays the relationship of the GARCH (bright red) with the trend of historical volatility (dark red).
USER INTERFACE
Alpha: select the starting value of Alpha (default value is 0.10).
Beta: select the starting value of Beta (default value is 0.80).
Lenght: select the period for calculating values within the model such as EMA (Exponential Moving Average) and Historical Volatility (default set to 20).
Forecasting: select the forecasting period, the number of bars you want to visualize data ahead (default set to 30).
Design: customize the indicator with your preferred color and choose from different types of charts, managing the design settings.
Volume Exhaustion [AlgoAlpha]Introducing the Volume Exhaustion by AlgoAlpha, is an innovative tool that aims to identify potential exhaustion or peaks in trading volume , which can be a key indicator for reversals or continuations in market trends 🔶.
Key Features:
Signal Plotting : A special feature is the plotting of 'Release' signals, marked by orange diamonds, indicating points where the exhaustion index crosses under its previous value and is above a certain boundary. This could signify critical market points 🚨.
Calculation Length Customization : Users can adjust the calculation and Signal lengths to suit their trading style, allowing for flexibility in analysis over different time periods. ☝️
len = input(50, "Calculation Length")
len2 = input(8, "Signal Length")
Visual Appeal : The script offers customizable colors (col for the indicator and col1 for the background) enhancing the visual clarity and user experience 💡.
col = input.color(color.white, "Indicator Color")
col1 = input.color(color.gray, "Background Color")
Advanced Volume Processing : At its core, the script utilizes a combination of Hull Moving Average (HMA) and Exponential Moving Average (EMA) applied to the volume data. This sophisticated approach helps in smoothing out the volume data and reducing lag.
sv = ta.hma(volume, len)
ssv = ta.hma(sv, len)
Volume Exhaustion Detection : The script calculates the difference between the volume and its smoothed version, normalizing this value to create an exhaustion index (fff). Positive values of this index suggest potential volume exhaustion.
f = sv-ssv
ff = (f) / (ta.ema(ta.highest(f, len) - ta.lowest(f, len), len)) * 100
fff = ff > 0 ? ff : 0
Boundary and Zero Line : The script includes a boundary line (boundary) and a zero line (zero), with the area between them filled for enhanced visual interpretation. This helps in assessing the relative position of the exhaustion index.
Customizable Background : The script colors the background of the chart for better readability and to distinguish the indicator’s area clearly.
Overall, Volume Exhaustion is designed for traders who focus on volume analysis. It provides a unique perspective on volume trends and potential exhaustion points, which can be crucial for making informed trading decisions. This script is a valuable addition for traders looking to enhance their trading experience with advanced volume analysis tools.
Hedge Coin M - Statistical Support and ResistanceHedge Coin M - Statistical Support and Resistance
Introduction
"Hedge Coin M - Statistical Support and Resistance" is a sophisticated, statistically-driven indicator designed specifically for traders in the COIN-M market on Binance. It offers a nuanced approach to identifying key market levels, focusing on the dynamics of support and resistance through advanced volatility analysis.
Foundation and Credits:
This script is an advanced adaptation of TradingView's standard code for the Bollinger Bands indicator. It extends the foundational concept of Bollinger Bands by integrating additional volatility metrics.
Calculation Method
This indicator employs Volume Weighted Moving Averages (VWMA) to create two distinct sets of Bollinger Bands, named BB-a and BB-b.
BB-a is derived from the VWMA of high prices, targeting potential resistance levels.
BB-b is based on the VWMA of low prices, aimed at identifying critical support levels.
Users can independently adjust the standard deviation (SD) multipliers for the upper and lower bands of both BB-a and BB-b, accommodating different market conditions.
Enhanced Volatility Analysis
The indicator calculates additional standard deviation lines for the upper band of BB-a and the lower band of BB-b. These lines provide deeper insights into market volatility.
Plotted Graphs
The primary plots include the upper and lower bands of BB-a and BB-b, marked in distinct colors for clarity.
Additional SD lines are plotted to indicate potential extended levels of support and resistance, offering traders a broader view of possible market movements.
Purpose and Usage
"Hedge Coin M - Statistical Support and Resistance" is designed to provide traders with a consistent, statistical method for identifying significant price levels.
It aids in scaling entry into positions, helping traders to navigate the COIN-M market with more informed decision-making.
This tool is especially useful for traders who combine long-term holding with swing trading strategies, offering a balanced approach to market engagement.
Integration and Adaptation
Easily integrate this indicator into your TradingView chart for the COIN-M market.
Use the insights provided to complement your overall trading strategy, particularly in identifying and reacting to significant market movements.
Disclaimer
Important Note: This indicator is provided for informational purposes only. It does not constitute financial advice, investment advice, trading advice, or any other sort of advice. Trading decisions should be made based on your own analysis, prudence, and judgment. Please be aware of the risks involved in trading and consult a financial advisor if necessary.
Activity & Chop ScoreRelease Notes:
The Activity and Chop Score was designed to help traders quickly determine if a market is active and/or choppy (not moving with any urgency). Slow and chopping markets should be approached with caution or avoided.
How does it work? The Activity Score incorporates momentum and the linear regression. Momentum (change in price over time) is compared over a long and short time period. Active markets are when those are moving together. This is combined with a linear regression of the price to determine the Correlation Coefficient (r^2) to measure of trend strength. The score is a is the average of the two momentum values, normalized by the standard deviation, and scaled by the trend (r^2 value). Chop is defined as divergence between long and short momentum periods. The divergences (chop) are quantified with a Jaccard Similarity Score, normalized by the standard deviation, and averaged to create a score.
How can you use it? This indicator is best used on lower timeframes. Activity Scores Values below 1 are considered low and values over 2 are high. Avoid markets where the Activity Score is below 1. There is an alert threshold in the options. Pivots are worth paying attention too as well as they indicate the start and stop of a recent move. You can compare markets or assets with the Chop Score. You make chose to avoid those with higher Chop Score. The position of the two lines relative to each other are useful. Ideally, the Activity Score is higher than the Chop Score. As with any indicators, it should be used in combination with others that best suits your trading style.
Zero-lag Volatility-Breakout EMA Trend StrategyThis is a simple volatility-breakout strategy which uses the difference in two different zero-lag* EMAs (explained below on what exactly I mean by this) to track the upwards or downwards strength of an instrument. When the difference breaks above a Bollinger Band of a configurable standard deviation multiple, the strategy enters based off the direction of the base EMA used (i.e. if the difference breaks above and the current EMA is rising, a long entry is produced. If the difference breaks above and the current EMA is falling, a short entry is produced).
The two EMA-type metrics used to calculate the volatility difference are calculated by the following formula:
top_ema = math.max(src, ta.ema(src, length))
bottom_ema = math.min(src, ta.ema(src, length))
ema_difference = (top_ema - bottom_ema) - 1
This produces a difference which responds immediately to large price movements, instead of lagging if it used strictly the EMA itself.
SETTINGS
Source : The source of the strategy - close, hlc3, another indicator plot, etc.
EMA Difference Length : The length of both the EMA difference statistics and the base EMA used to calculate the entry side.
Standard Deviation Multiple : The Bollinger Bands multiple used when the difference is breaking out.
Use Binary Strategy : The strategy has two configurations: Binary and Rapid-Exit. 'Binary' means that it will not close a long position until a short position is generated, and vice-versa. 'Rapid-Exit' will close a long or short position once the difference reaches the middle Bollinger Band MA. This means that turning on 'Binary' will expose you to more market risk, but potentially greater market return. Turning off 'Binary' will exit quickly and reduce drawdown.
The strategy results below use 10% equity and 0.1% fees per trade.
Squeeze & Release [AlgoAlpha]Introduction:
💡The Squeeze & Release by AlgoAlpha is an innovative tool designed to capture price volatility dynamics using a combination of EMA-based calculations and ATR principles. This script aims to provide traders with clear visual cues to spot potential market squeezes and release scenarios. Hence it is important to note that this indicator shows information on volatility, not direction.
Core Logic and Components:
🔶EMA Calculations: The script utilizes the Exponential Moving Average (EMA) in multiple ways to smooth out the data and provide indicator direction. There are specific lengths for the EMAs that users can modify as per their preference.
🔶ATR Dynamics: Average True Range (ATR) is a core component of the script. The differential between the smoothed ATR and its EMA is used to plot the main line. This differential, when represented as a percentage of the high-low range, provides insights into volatility.
🔶Squeeze and Release Detection: The script identifies and highlights squeeze and release scenarios based on the crossover and cross-under events between our main line and its smoothed version. Squeezes are potential setups where the market may be consolidating, and releases indicate a potential breakout or breakdown.
🔶Hyper Squeeze Detection: A unique feature that detects instances when the main line is rising consistently over a user-defined period. Hyper squeeze marks areas of extremely low volatility.
Visual Components:
The main line (ATR-based) changes color depending on its position relative to its EMA.
A middle line plotted at zero level which provides a quick visual cue about the main line's position. If the main line is above the zero level, it indicates that the price is squeezing on a longer time horizon, even if the indicator indicates a shorter-term release.
"𝓢" and "𝓡" characters are plotted to represent 'Squeeze' and 'Release' scenarios respectively.
Standard Deviation Bands are plotted to help users gauge the extremity and significance of the signal from the indicator, if the indicator is closer to either the upper or lower deviation bands, this means that statistically, the current value is considered to be more extreme and as it is further away from the mean where the indicator is oscillating at for the majority of the time. Thus indicating that the price has experienced an unusual amount or squeeze or release depending on the value of the indicator.
Usage Guidelines:
☝️Traders can use the script to:
Identify potential consolidation (squeeze) zones.
Gauge potential breakout or breakdown scenarios (release).
Fine-tune their entries and exits based on volatility.
Adjust the various lengths provided in the input for better customization based on individual trading styles and the asset being traded.
HL range by durgaThe script we've been working on is an indicator designed to display the high-low range of the last candlestick on a TradingView chart. It does so by plotting two lines: one for the high and another for the low of the last completed candlestick.
Additionally, the script includes a label that shows the numerical value of the high-low range. This label is positioned between the plotted lines, showing the difference between the high and low prices of the last candlestick.
The script operates in real-time, updating dynamically as new candlesticks form. Furthermore, it automatically removes the label after the close of the candlestick, maintaining a clean and clutter-free chart.
This indicator can help traders quickly visualize and assess the range of the last completed candlestick, aiding in their analysis of price action.
Open Interest OscillatorIn the middle of a bustling cryptocurrency market, with Bitcoin navigating a critical phase and the community hype over potential ETF approvals, current funding rates, and market leverage, the timing is optimal to harness the capabilities of sophisticated trading tools.
Meet the Open Interest Oscillator – special indicator tailored for the volatile arena of cryptocurrency trading. This powerful instrument is adept at consolidating open interest data from a multitude of exchanges, delivering an in-depth snapshot of market sentiment across all timeframes, be it a 1-minute sprint or a weekly timeframe.
This versatile indicator is compatible with nearly all cryptocurrency pairs, offering an expansive lens through which traders can gauge the market's pulse.
Key Features:
-- Multi-exchange Data Aggregation: This feature taps into the heart of the crypto market by aggregating open interest data from premier exchanges such as BINANCE, BITMEX, BITFINEX, and KRAKEN. It goes a step further by integrating data from various pairs and stablecoins, thus providing traders with a rich, multi-dimensional view of market activities.
-- Open Interest Bars: Witness the flow of market dynamics through bars that depict the volume of positions being opened or closed, offering a clear visual cue of trading behavior. In this mode, If bars are going into negative zone, then traders are closing their positions. If they go into positive territory - leveraged positions are being opened.
-- Bollinger Band Integration: Incorporate a layer of statistical analysis with standard deviation calculations, which frame the open interest changes, giving traders a quantified edge to evaluate the market's volatility and momentum.
-- Oscillator with Customizable Thresholds: Personalize your trading signals by setting thresholds that resonate with your unique trading tactics. This customization brings the power of tailored analytics to your strategic arsenal.
-- Max OI Ceiling Setting: In the fast-paced crypto environment where data can surge to overwhelming levels, the Max OI Ceiling ensures you maintain a clear view by capping the open interest data, thus preserving the readability and interpretability of information, even when market activity reaches feverish heights.
Relative Strength Trend Indicator (RSTI)This indicator is called the "Relative Strength Trend Indicator" (RSTI), designed to assess the relative strength of a trend.
Here is a detailed explanation of how it works and how traders can interpret it:
Indicator Operation:
1. Data Source (src): The indicator considers a data source, typically the closing price (close), but this can be adjusted according to the trader's preferences.
2. Period Length (Length): This determines the period used to calculate the simple moving average (SMA) of the data source. A longer period smoothes the indicator, while a shorter period makes it more responsive.
3. Multiplier (Multiplier): This is a multiplication factor applied to the Average True Range (ATR), adjusting the width of the bands.
4. Signal Length (Signal Length): This period is used to calculate the simple moving average of the relative strength (l_strength). It determines the sensitivity of the signal to changes in relative strength.
Interpretation of the Indicator:
1. Upper Strength Band (Upper Level): This line is drawn at 80 and represents a high strength level. When relative strength exceeds this value, it may indicate a potential overbought market.
2. Lower Strength Band (Lower Level): This line is drawn at 20 and represents a low strength level. When relative strength is below this value, it may indicate a potential oversold market.
3. RSTI Strength: The main line of the indicator, representing the calculated relative strength. When this line exceeds 50, it may indicate an uptrend, while a value below 50 may indicate a downtrend.
4. Filling Zones: These colored zones between levels 80 and 50, and between 50 and 20, can help quickly visualize relative strength. A colored zone above 50 indicates positive strength, while a colored zone below 50 indicates negative strength.
Qualities of the Indicator:
1. Adaptability: The use of ATR and the flexibility of parameters (length, multiplier, signal_length) allow the indicator to adapt to different market conditions.
2. Visual Clarity: Colored filling zones and horizontal lines make it easy to visualize relative strength levels.
3. Strength Signal: The signal line (RSTI Strength) allows traders to quickly spot changes in relative strength, facilitating decision-making.
4. Responsiveness: The combination of smoothed moving averages and relative strength indicators allows responsiveness to trend changes while reducing false signals.
It is essential to note that while this indicator can provide valuable insights, it is always recommended to use it in conjunction with other technical analysis tools for informed decision-making.
ROC & EMAIn summary, this allows you to plot the ROC, its EMA, and dynamically display the value of this EMA on the chart.
You can configure different lengths and colors.
Unpretentious code, just for the pleasure of sharing.
Thank you for sharing your comments with me, which will be welcome.
FX DispersionThis script calculates the dispersion of a basket of 5 FX pairs and then calculates the z-score the z-score is then made into a composite using the 30 and 60 ema of the z-score to smooth any noise. It must be used on one of the FX pairs in the basket and on the 1-minute timeframe as it has been hardcoded for 1 min use below.
Interpretation - Dispersion is a component of volatility - the dispersion of the underlying basket increases above 0.5 and decreases below 0.5.
Although increased dispersion is beneficial to momentum and trend-following strategies on the monthly and weekly timeframes. Observe this on the 1-minute timeframe and how dispersion crossing above/ below 0.5 it can signal reversion or momentum for the next period.
ADX Thrust Reversal & Trend
Created by Love Sharma, CMT, CFTe
the idea is simple. there needs to be thrust in prices before adx goes above any barrier or level say 25/10 or even 10/ The Di plus or Di minus should be above ADX. This indicates the change in direction or change in underlying price and obviously followed by ADX indicator which is dependent on user which level it exceed.
The ADX - Shows Trend Strength
The =/- Di show Thrust or reversal in prices.
it helps in entering the directional change in prices early rather than waiting for ADX
CARNAC Elasticity IndicatorThe CARNAC Elasticity Indicator (EI) is a technical analysis tool designed for traders and investors using TradingView. It calculates the percentage deviation of the current price from an Exponential Moving Average (EMA) and helps traders identify potential overbought and oversold conditions in a financial instrument.
Key Features:
EMA Length: Users can customize the length of the Exponential Moving Average (EMA) used in the calculations by adjusting the "EMA Length" parameter in the indicator settings.
Percentage Deviation: The indicator calculates the percentage deviation of the current price from the EMA. Positive values indicate prices above the EMA, while negative values indicate prices below the EMA.
Maximum Deviations: The indicator tracks the maximum positive (above EMA) and negative (below EMA) percentage deviations over time, allowing traders to monitor extreme price movements.
Bands: Upper and lower bands are displayed on the indicator chart at 100 and -100, respectively. Additionally, dashed middle bands at 50 and -50 provide reference points for moderate deviations.
Dynamic Color Coding: The indicator uses dynamic color coding to highlight the current percentage deviation. It turns red for values above 50 (indicating potential overbought conditions), green for values below -50 (indicating potential oversold conditions), and purple for values in between.
How to Use:
Overbought Conditions: Watch for the percentage deviation to cross above 50, indicating potential overbought conditions. This might be a signal to consider selling or taking profits.
Oversold Conditions: Look for the percentage deviation to cross below -50, signaling potential oversold conditions. This could be an opportunity to consider buying or entering a long position.
Historical Extremes: Keep an eye on the upper and lower bands (100 and -100) to identify historical extremes in percentage deviation.
The CARNAC Elasticity Indicator can be a valuable tool for traders seeking to identify potential trend reversals and assess the strength of price movements. However, it should be used in conjunction with other technical analysis tools and risk management strategies for comprehensive trading decisions.
FlexiSuperTrend - Strategy [presentTrading]█ Introduction and How it is Different
The "FlexiSuperTrend - Strategy" by PresentTrading is a cutting-edge trading strategy that redefines market analysis through the integration of the SuperTrend indicator and advanced variance tracking.
BTC 6H L/S
This strategy stands apart from conventional methods by its dynamic adaptability, capturing market trends and momentum shifts with increased sensitivity. It's designed for traders seeking a more responsive tool to navigate complex market movements.
Local
█ Strategy, How It Works: Detailed Explanation
The "FlexiSuperTrend - Strategy" employs a multifaceted approach, combining the adaptability of the SuperTrend indicator with variance tracking. The strategy's core lies in its unique formulation and application of these components:
🔶 SuperTrend Polyfactor Oscillator:
- Basic Concept: The oscillator is a series of SuperTrend calculations with varying ATR lengths and multipliers. This approach provides a broader and more nuanced perspective of market trends.
- Calculation:
- For each iteration, `i`, the SuperTrend is calculated using:
- `ATR Length = indicatorLength * (startingFactor + i * incrementFactor)`.
- `Multiplier = dynamically adjusted based on market conditions`.
- The SuperTrend output for each iteration is compared with the indicator source (like hlc3), and the deviation is recorded.
SuperTrend Calculation:
- `Upper Band (UB) = hl2 + (ATR Length * Multiplier)`
- `Lower Band (LB) = hl2 - (ATR Length * Multiplier)`
- Where `hl2` is the average of high and low prices.
Deviation Calculation:
- `Deviation = indicatorSource - SuperTrend Value`
- This value is calculated for each SuperTrend setting in the oscillator series.
🔶 Indicator Source (`hlc3`):
- **Usage:** The strategy uses the average of high, low, and close prices, providing a balanced representation of market activity.
🔶 Adaptive ATR Lengths and Factors:
- Dynamic Adjustment: The strategy adjusts the ATR length and multiplier based on the `startingFactor` and `incrementFactor`. This adaptability is key in responding to changing market volatilities.
- Equation: ATR Length at each iteration `i` is given by `len = indicatorLength * (startingFactor + i * incrementFactor)`.
incrementFactor - 1
incrementFactor - 2
🔶 Normalization Methods:
Purpose: To standardize the deviations for comparability.
- Methods:
- 'Max-Min': Scales the deviation based on the range of values.
- 'Absolute Sum': Uses the sum of absolute deviations for normalization.
Normalization 'Absolute Sum'
- For 'Max-Min': `Normalized Deviation = (Deviation - Min(Deviations)) / (Max(Deviations) - Min(Deviations))`
- For 'Absolute Sum': `Normalized Deviation = Deviation / Sum(Absolute(Deviations))`
🔶 Trading Logic:
The strategy integrates the SuperTrend indicator, renowned for its effectiveness in identifying trend direction and reversals. The SuperTrend's incorporation enhances the strategy's ability to filter out false signals and confirm genuine market trends. * The SuperTrend Toolkit is made by @QuantiLuxe
- Long Entry Conditions: A buy signal is generated when the current trend, as indicated by the SuperTrend Polyfactor Oscillator, turns positive.
- Short Entry Conditions: A sell signal is triggered when the current trend turns negative.
- Entry and Exit Strategy: The strategy opens or closes positions based on these signals, aligning with the selected trade direction (long, short, or both).
█ Trade Direction
The strategy is versatile, allowing traders to choose their preferred trading direction: long, short, or both. This flexibility enables traders to tailor their strategies to their market outlook and risk appetite.
█ Usage
The FlexiSuperTrend strategy is suitable for various market conditions and can be adapted to different asset classes and time frames. Traders should set the strategy parameters according to their risk tolerance and trading goals. It's particularly useful for capturing long-term movements, ideal for swing traders, yet adaptable for short-term trading strategies.
█ Default Settings
1. Trading Direction: Choose from "Long", "Short", or "Both" to define the trade type.
2. Indicator Source (HLC3): Utilizes the HLC3 as the primary price reference.
3. Indicator Length (Default: 10): Influences the moving average calculation and trend sensitivity.
4. Starting Factor (0.618): Initiates the ATR length, influenced by Fibonacci ratios.
5. Increment Factor (0.382): Adjusts the ATR length incrementally for dynamic trend tracking.
6. Normalization Method: Options include "None", "Max-Min", and "Absolute Sum" for scaling deviations.
7. SuperTrend Settings: Varied ATR lengths and multipliers tailor the indicator's responsiveness.
8. Additional Settings: Features mesh style plotting and customizable colors for visual distinction.
The default settings provide a balanced approach, but users are encouraged to adjust them based on their individual trading style and market analysis.
Rolling VWAP [QuantraSystems]Rolling VWAP
Introduction
The Rolling VWAP (R͜͡oll-VWAP) indicator modernizes the traditional VWAP by recalculating continuously on a rolling window, making it adept at pinpointing market trends and breakout points.
Its dual functionality includes both the dynamic rolling VWAP and a customizable anchored VWAP, enhanced by color-coded visual cues, thereby offering traders valuable flexibility and insight for their market analysis.
Legend
In the Image you can see the BTCUSD 1D Chart with the R͜͡oll-VWAP overlay.
You can see the individually activatable Standard Deviation (SD) Bands and the main VWAP Line.
It also features a Trend Signal which is deactivated by default and can be enabled if required.
Furthermore you can find the coloring of the VWAP line to represent the Trend.
In this case the trend itself is defined as:
Close being greater than the VWAP line -> Uptrend
Close below the VWAP line -> Downtrend
Notes
The R͜͡oll-VWAP can be used in a variety of ways.
Volatility adjusted expected range
This aims to identify in which range the asset is likely to move - according to the historical values the SD Bands are calculated and thus their according probabilities displayed.
Trend analysis
Trending above or below the VWAP shows up or down trends accordingly.
S/R Levels
Based on the probability distribution the 2. SD often works as a Resistance level and either mid line or 1. SD lines can act as S/R levels
Unsustainable levels
Based on the probability distributions a SD level of beyond 2.5, especially 3 and higher is hit very seldom and highly unsustainable.
This can either mean a mean reversion state or a momentum slowdown is necessary to get back to a sustainable level.
Please note that we always advise to find more confluence by additional indicators.
Traders are encouraged to test and determine the most suitable settings for their specific trading strategies and timeframes.
Methodology
The R͜͡oll-VWAP is based on the inbuilt TV VWAP.
It expands upon the limitations of having an anchored timeframe and thus a limited data set that is being reset constantly.
Instead we have integrated a rolling nature that continuously calculates the VWAP over a customizable lookback.
To also keep the base utility it is possible to use the anchored timeframes as well.
Furthermore the visualization has been improved and we added the coloring of the main VWAP line according to the Trend as stated above.
The applicable Trend signals are also part of that.
The parameter settings and also the visualizations allow for ample customizations by the trader.
For questions or recommendations, please feel free to seek contact in the comments.
Market Phases NJRMarket Phases Indicator
Overview:
The Market Phases Indicator is a versatile tool designed for traders to identify key market phases, including accumulation, distribution, markup, and markdown. By analyzing the relationship between price and volume, this indicator aims to assist traders in recognizing potential shifts in market sentiment and trend direction.
Features:
1. **Moving Average Analysis:**
- Utilizes a customizable moving average length to assess the overall trend direction.
2. **Volume Confirmation:**
- Incorporates volume analysis to confirm the strength of identified market phases.
3. **Visualization:**
- Clearly visualizes accumulation, distribution, markup, and markdown phases on the price chart using intuitive shapes.
Input Parameters:
- **Moving Average Length (default: 20):**
- Adjusts the length of the moving average for trend analysis.
- **Volume Multiplier (default: 1.5):**
- Sets the multiplier to customize the volume threshold for identifying significant market phases.
How to Use:
1. **Accumulation and Distribution:**
- Green triangles indicate potential accumulation phases when the closing price is above the moving average, and volume is higher than the specified threshold. Red triangles indicate potential distribution phases.
2. **Markup and Markdown:**
- Blue triangles suggest potential markup phases when the closing price is above the moving average, and volume is below the specified threshold. Orange triangles indicate potential markdown phases.
Important Notes:
- This indicator is a tool for analysis and should be used in conjunction with other technical analysis methods.
- Parameters can be adjusted based on the specific characteristics of the asset being analyzed.
Disclaimer:
Trading involves risk, and no indicator can guarantee profits. Users should exercise caution, conduct thorough research, and consider risk management principles when making trading decisions.
