Volatility-Adjusted Momentum Oscillator (VAMO)Concept & Rationale: This indicator combines momentum and volatility into one oscillator. The idea is that a price move accompanied by high volatility has greater significance. We use Rate of Change (ROC) for momentum and Average True Range (ATR) for volatility, multiplying them to gauge “volatility-weighted momentum.” This concept is inspired by the Weighted Momentum & Volatility Indicator, which multiplies normalized ROC and ATR values. The result is shown as a histogram oscillating around zero – rising green bars indicate bullish momentum, while falling red bars indicate bearish momentum. When the histogram crosses above or below zero, it provides clear buy/sell signals. Higher magnitude bars suggest a stronger trend move. Crypto markets often see volatility spikes preceding big moves, so VAMO aims to capture those moments when momentum and volatility align for a powerful breakout.
Key Features:
Momentum-Volatility Fusion: Measures momentum (price ROC) adjusted by volatility (ATR). Strong trends register prominently only when price change is significant and volatility is elevated.
Intuitive Histogram: Plotted as a color-coded histogram around a zero line – green bars above zero for bullish trends, red bars below zero for bearish. This makes it easy to visualize trend strength and direction at a glance.
Clear Signals: A cross above 0 signals a buy, and below 0 signals a sell. Traders can also watch for the histogram peaking and then shrinking as an early sign of a trend reversal (e.g. bars switching from growing to shrinking while still positive could mean bullish momentum is waning).
Optimized for Volatility: Because ATR is built-in, the oscillator naturally adapts to crypto volatility. In calm periods, signals will be smaller (reducing noise), whereas during volatile swings the indicator accentuates the move, helping predict big price swings.
Customization: The lookback period is adjustable. Shorter periods (e.g. 5-10) make it more sensitive for scalping, while longer periods (20+) smooth it out for swing trading.
How to Use: When VAMO bars turn green and push above zero, it indicates bullish momentum with strong volatility – a cue that price is likely to rally in the near term. Conversely, red bars below zero signal bearish pressure. For example, if a coin’s price has been flat and then VAMO spikes green above zero, it suggests an explosive upward move is brewing. Traders can enter on the zero-line cross (or on the first green bar) and consider exiting when the histogram peaks and starts shrinking (signaling momentum slowdown). In sideways markets, VAMO will hover near zero – staying out during those low-volatility periods helps avoid false signals. This indicator’s strength is catching the moment when a quiet market turns volatile in one direction, which often precedes the next few candlesticks of sustained movement.
Cerca negli script per "momentum"
BTC Future Gamma-Weighted Momentum Model (BGMM)The BTC Future Gamma-Weighted Momentum Model (BGMM) is a quantitative trading strategy that utilizes the Gamma-weighted average price (GWAP) in conjunction with a momentum-based approach to predict price movements in the Bitcoin futures market. The model combines the concept of weighted price movements with trend identification, where the Gamma factor amplifies the weight assigned to recent prices. It leverages the idea that historical price trends and weighting mechanisms can be utilized to forecast future price behavior.
Theoretical Background:
1. Momentum in Financial Markets:
Momentum is a well-established concept in financial market theory, referring to the tendency of assets to continue moving in the same direction after initiating a trend. Any observed market return over a given time period is likely to continue in the same direction, a phenomenon known as the “momentum effect.” Deviations from a mean or trend provide potential trading opportunities, particularly in highly volatile assets like Bitcoin.
Numerous empirical studies have demonstrated that momentum strategies, based on price movements, especially those correlating long-term and short-term trends, can yield significant returns (Jegadeesh & Titman, 1993). Given Bitcoin’s volatile nature, it is an ideal candidate for momentum-based strategies.
2. Gamma-Weighted Price Strategies:
Gamma weighting is an advanced method of applying weights to price data, where past price movements are weighted by a Gamma factor. This weighting allows for the reinforcement or reduction of the influence of historical prices based on an exponential function. The Gamma factor (ranging from 0.5 to 1.5) controls how much emphasis is placed on recent data: a value closer to 1 applies an even weighting across periods, while a value closer to 0 diminishes the influence of past prices.
Gamma-based models are used in financial analysis and modeling to enhance a model’s adaptability to changing market dynamics. This weighting mechanism is particularly advantageous in volatile markets such as Bitcoin futures, as it facilitates quick adaptation to changing market conditions (Black-Scholes, 1973).
Strategy Mechanism:
The BTC Future Gamma-Weighted Momentum Model (BGMM) utilizes an adaptive weighting strategy, where the Bitcoin futures prices are weighted according to the Gamma factor to calculate the Gamma-Weighted Average Price (GWAP). The GWAP is derived as a weighted average of prices over a specific number of periods, with more weight assigned to recent periods. The calculated GWAP serves as a reference value, and trading decisions are based on whether the current market price is above or below this level.
1. Long Position Conditions:
A long position is initiated when the Bitcoin price is above the GWAP and a positive price movement is observed over the last three periods. This indicates that an upward trend is in place, and the market is likely to continue in the direction of the momentum.
2. Short Position Conditions:
A short position is initiated when the Bitcoin price is below the GWAP and a negative price movement is observed over the last three periods. This suggests that a downtrend is occurring, and a continuation of the negative price movement is expected.
Backtesting and Application to Bitcoin Futures:
The model has been tested exclusively on the Bitcoin futures market due to Bitcoin’s high volatility and strong trend behavior. These characteristics make the market particularly suitable for momentum strategies, as strong upward or downward movements are often followed by persistent trends that can be captured by a momentum-based approach.
Backtests of the BGMM on the Bitcoin futures market indicate that the model achieves above-average returns during periods of strong momentum, especially when the Gamma factor is optimized to suit the specific dynamics of the Bitcoin market. The high volatility of Bitcoin, combined with adaptive weighting, allows the model to respond quickly to price changes and maximize trading opportunities.
Scientific Citations and Sources:
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637–654.
• Fama, E. F., & French, K. R. (1992). The Cross-Section of Expected Stock Returns. The Journal of Finance, 47(2), 427–465.
Volatility Momentum Breakout StrategyDescription:
Overview:
The Volatility Momentum Breakout Strategy is designed to capture significant price moves by combining a volatility breakout approach with trend and momentum filters. This strategy dynamically calculates breakout levels based on market volatility and uses these levels along with trend and momentum conditions to identify trade opportunities.
How It Works:
1. Volatility Breakout:
• Methodology:
The strategy computes the highest high and lowest low over a defined lookback period (excluding the current bar to avoid look-ahead bias). A multiple of the Average True Range (ATR) is then added to (or subtracted from) these levels to form dynamic breakout thresholds.
• Purpose:
This method helps capture significant price movements (breakouts) while ensuring that only past data is used, thereby maintaining realistic signal generation.
2. Trend Filtering:
• Methodology:
A short-term Exponential Moving Average (EMA) is applied to determine the prevailing trend.
• Purpose:
Long trades are considered only when the current price is above the EMA, indicating an uptrend, while short trades are taken only when the price is below the EMA, indicating a downtrend.
3. Momentum Confirmation:
• Methodology:
The Relative Strength Index (RSI) is used to gauge market momentum.
• Purpose:
For long entries, the RSI must be above a mid-level (e.g., above 50) to confirm upward momentum, and for short entries, it must be below a similar threshold. This helps filter out signals during overextended conditions.
Entry Conditions:
• Long Entry:
A long position is triggered when the current closing price exceeds the calculated long breakout level, the price is above the short-term EMA, and the RSI confirms momentum (e.g., above 50).
• Short Entry:
A short position is triggered when the closing price falls below the calculated short breakout level, the price is below the EMA, and the RSI confirms momentum (e.g., below 50).
Risk Management:
• Position Sizing:
Trades are sized to risk a fixed percentage of account equity (set here to 5% per trade in the code, with each trade’s stop loss defined so that risk is limited to approximately 2% of the entry price).
• Stop Loss & Take Profit:
A stop loss is placed a fixed ATR multiple away from the entry price, and a take profit target is set to achieve a 1:2 risk-reward ratio.
• Realistic Backtesting:
The strategy is backtested using an initial capital of $10,000, with a commission of 0.1% per trade and slippage of 1 tick per bar—parameters chosen to reflect conditions faced by the average trader.
Important Disclaimers:
• No Look-Ahead Bias:
All breakout levels are calculated using only past data (excluding the current bar) to ensure that the strategy does not “peek” into future data.
• Educational Purpose:
This strategy is experimental and provided solely for educational purposes. Past performance is not indicative of future results.
• User Responsibility:
Traders should thoroughly backtest and paper trade the strategy under various market conditions and adjust parameters to fit their own risk tolerance and trading style before live deployment.
Conclusion:
By integrating volatility-based breakout signals with trend and momentum filters, the Volatility Momentum Breakout Strategy offers a unique method to capture significant price moves in a disciplined manner. This publication provides a transparent explanation of the strategy’s components and realistic backtesting parameters, making it a useful tool for educational purposes and further customization by the TradingView community.
Trend Analysis with Volatility and MomentumVolatility and Momentum Trend Analyzer
The Volatility and Momentum Trend Analyzer is a multi-faceted TradingView indicator designed to provide a comprehensive analysis of market trends, volatility, and momentum. It incorporates key features to identify trend direction (uptrend, downtrend, or sideways), visualize weekly support and resistance levels, and offer a detailed assessment of market strength and activity. Below is a breakdown of its functionality:
1. Input Parameters
The indicator provides customizable settings for precision and adaptability:
Volatility Lookback Period: Configurable period (default: 14) for calculating Average True Range (ATR), which measures market volatility.
Momentum Lookback Period: Configurable period (default: 14) for calculating the Rate of Change (ROC), which measures the speed and strength of price movements.
Support/Resistance Lookback Period: Configurable period (default: 7 weeks) to determine critical support and resistance levels based on weekly high and low prices.
2. Volatility Analysis (ATR)
The Average True Range (ATR) is calculated to quantify the market's volatility:
What It Does: ATR measures the average range of price movement over the specified lookback period.
Visualization: Plotted as a purple line in a separate panel below the price chart, with values amplified (multiplied by 10) for better visibility.
3. Momentum Analysis (ROC)
The Rate of Change (ROC) evaluates the momentum of price movements:
What It Does: ROC calculates the percentage change in closing prices over the specified lookback period, indicating the strength and direction of market moves.
Visualization: Plotted as a yellow line in a separate panel below the price chart, with values amplified (multiplied by 10) for better visibility.
4. Trend Detection
The indicator identifies the current market trend based on momentum and the position of the price relative to its moving average:
Uptrend: Occurs when momentum is positive, and the closing price is above the simple moving average (SMA) of the specified lookback period.
Downtrend: Occurs when momentum is negative, and the closing price is below the SMA.
Sideways Trend: Occurs when neither of the above conditions is met.
Visualization: The background of the price chart changes color to reflect the detected trend:
Green: Uptrend.
Red: Downtrend.
Gray: Sideways trend.
5. Weekly Support and Resistance
Critical levels are calculated based on weekly high and low prices:
Support: The lowest price observed over the last specified number of weeks.
Resistance: The highest price observed over the last specified number of weeks.
Visualization:
Blue Line: Indicates the support level.
Orange Line: Indicates the resistance level.
Both lines are displayed on the main price chart, dynamically updating as new data becomes available.
6. Alerts
The indicator provides configurable alerts for trend changes, helping traders stay informed without constant monitoring:
Uptrend Alert: Notifies when the market enters an uptrend.
Downtrend Alert: Notifies when the market enters a downtrend.
Sideways Alert: Notifies when the market moves sideways.
7. Key Use Cases
Trend Following: Identify and follow the dominant trend to capitalize on sustained price movements.
Volatility Assessment: Measure market activity to determine potential breakouts or quiet consolidation phases.
Support and Resistance: Highlight key levels where price is likely to react, assisting in decision-making for entries, exits, or stop-loss placement.
Momentum Tracking: Gauge the strength and speed of price moves to validate trends or anticipate reversals.
8. Visualization Summary
Main Chart:
Background color-coded for trend direction (green, red, gray).
Blue and orange lines for weekly support and resistance.
Lower Panels:
Purple line for volatility (ATR).
Yellow line for momentum (ROC).
Adaptive Momentum Cycle Oscillator (AMCO)1. Concept and Foundation
The Adaptive Momentum Cycle Oscillator (AMCO) is an advanced indicator designed to dynamically adjust to varying market conditions while identifying price cycles and trends. It combines momentum and volatility into a single, oscillating signal that helps traders detect turning points in price movements. By incorporating adaptive periods and trend filtering, AMCO ensures relevance across different asset classes and timeframes. This innovation bridges the gap between traditional oscillators and trending indicators, providing a comprehensive tool for both cycle identification and trend confirmation.
2. Dynamic Adaptation to Market Conditions
A standout feature of AMCO is its ability to adapt its sensitivity based on market volatility. Using the ATR (Average True Range) as a measure of current volatility, AMCO adjusts its calculation periods dynamically. During periods of high volatility, it extends its lookback periods to smooth out noise and avoid false signals. Conversely, in low-volatility environments, it shortens its periods to remain responsive to smaller price fluctuations. This adaptability ensures that AMCO remains effective and reliable in both trending and ranging markets.
3. Trend Awareness and Directional Weighting
AMCO integrates a trend filter based on a long-term moving average, such as SMA(200), to align its signals with the broader market direction. This filter ensures that buy signals are prioritized during uptrends and sell signals during downtrends, reducing counter-trend trades. Additionally, a directional weighting mechanism amplifies momentum signals that align with the prevailing trend. This dual-layer approach significantly enhances the accuracy of signals, making AMCO especially useful in markets with clear directional bias.
4. Normalized Visualization for Clarity
The AMCO includes a normalized histogram that provides a clear visual representation of momentum strength relative to recent volatility. By dividing the raw AMCO value by the ATR, the histogram ensures consistency across assets with varying price ranges and volatility levels. Positive bars indicate bullish momentum, while negative bars signify bearish momentum. This intuitive visualization makes it easier for traders to interpret market dynamics and act on actionable signals, regardless of asset type or timeframe.
5. Practical and Actionable Signals
AMCO generates practical signals based on zero-line crossovers, allowing traders to easily identify shifts between bullish and bearish cycles. Positive values above the zero line suggest upward momentum, signaling potential buying opportunities, while negative values below the zero line indicate downward momentum, signaling potential sell opportunities. By combining adaptive behavior, trend filtering, and momentum-strength normalization, AMCO offers traders a robust framework for navigating complex markets with confidence. Its versatility makes it suitable for scalping, swing trading, and even longer-term investing.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Crypto Market Cap Momentum Analyzer (AiBitcoinTrend)The Crypto Market Cap Momentum Analyzer (AiBitcoinTrend) is a robust tool designed to uncover trading opportunities by blending market cap analysis and momentum dynamics. Inspired by research-backed quantitative strategies, this indicator helps traders identify trend-following and mean-reversion setups in the cryptocurrency market by evaluating recent performance and market cap size.
This indicator classifies cryptocurrencies into market cap quintiles and ranks them based on their 2-week momentum. It then suggests potential trades—whether to go long, anticipate reversals, or simply hold—based on the crypto's market cap group and momentum trends.
👽 How the Indicator Works
👾 Market Cap Classification
The indicator categorizes cryptocurrencies into one of five market cap groups based on user-defined inputs:
Large Cap: Highest market cap tier
Upper Mid Cap: Second highest group
Mid Cap: Middle-tier market caps
Lower Mid Cap: Slightly below the mid-tier
Small Cap: Lowest market cap tier
This classification dynamically adjusts based on the provided market cap data, ensuring that you’re always working with a representative market structure.
👾 Momentum Calculation
By default, the indicator uses a 2-week momentum measure (e.g., a 14-day lookback when set to daily). It compares a cryptocurrency’s current price to its price 14 bars ago, thereby quantifying its short-term performance. Users can adjust the momentum period and rebalance period to capture shorter or longer-term trends depending on their trading style.
👾 Dynamic Ranking and Trade Suggestions
After assigning cryptos to size quintiles, the indicator sorts them by their momentum within each quintile. This two-step process results in:
Long Trade: For smaller market cap groups (Small, Lower Mid, Mid Cap) that have low (bottom-quintile) momentum, anticipating a trend continuation or breakout.
Reversal Trade: For the largest market cap group (Large Cap) that shows low momentum, expecting a mean-reversion back to equilibrium.
Hold: In scenarios where the coin’s momentum doesn’t present a strong contrarian or trend-following signal.
👽 Applications
👾 Trend-Following in Smaller Caps: Identify small or mid-cap cryptos with low momentum that might be poised for a breakout or sustained trend.
👾 Mean-Reversion in Large Caps: Pinpoint large-cap cryptocurrencies experiencing a temporary lull in performance, potentially ripe for a rebound.
👽 Why It Works in Crypto
The cryptocurrency market is heavily driven by retail investor sentiment and volatility. Research shows that:
Small-Cap Cryptos: Tend to experience higher volatility and speculative trends, making them ideal for momentum trades.
Large-Cap Cryptos: Exhibit more predictable behavior, making them suitable for mean-reversion strategies when momentum is low.
This indicator captures these dynamics to give traders a strategic edge in identifying both momentum and reversal opportunities.
👽 Indicator Settings
👾 Rebalance Period: The frequency at which momentum and trade suggestions are recalculated (Daily, Weekly, Monthly).
Shorter Periods (Daily): Fast updates, suitable for short-term trades, but more noise.
Longer Periods (Weekly/Monthly): Smoother signals, ideal for swing trading and more stable trends.
👾 Momentum Period: The lookback period for momentum calculation (default is 14 bars).
Shorter Periods: More responsive but prone to noise.
Longer Periods : Reflects broader trends, reducing sensitivity to short-term fluctuations.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
LRI Momentum Cycles [AlgoAlpha]Discover the LRI Momentum Cycles indicator by AlgoAlpha, a cutting-edge tool designed to identify market momentum shifts using trend normalization and linear regression analysis. This advanced indicator helps traders detect bullish and bearish cycles with enhanced accuracy, making it ideal for swing traders and intraday enthusiasts alike.
Key Features :
🎨 Customizable Appearance : Set personalized colors for bullish and bearish trends to match your charting style.
🔧 Dynamic Trend Analysis : Tracks market momentum using a unique trend normalization algorithm.
📊 Linear Regression Insight : Calculates real-time trend direction using linear regression for better precision.
🔔 Alert Notifications : Receive alerts when the market switches from bearish to bullish or vice versa.
How to Use :
🛠 Add the Indicator : Favorite and apply the indicator to your TradingView chart. Adjust the lookback period, linear regression source, and regression length to fit your strategy.
📊 Market Analysis : Watch for color changes on the trend line. Green signals bullish momentum, while red indicates bearish cycles. Use these shifts to time entries and exits.
🔔 Set Alerts : Enable notifications for momentum shifts, ensuring you never miss critical market moves.
How It Works :
The LRI Momentum Cycles indicator calculates trend direction by applying linear regression on a user-defined price source over a specified period. It compares historical trend values, detecting bullish or bearish momentum through a dynamic scoring system. This score is normalized to ensure consistent readings, regardless of market conditions. The indicator visually represents trends using gradient-colored plots and fills to highlight changes in momentum. Alerts trigger when the momentum state changes, providing actionable trading signals.
GMO (Gyroscopic Momentum Oscillator) GMO
Overview
This indicator fuses multiple advanced concepts to give traders a comprehensive view of market momentum, volatility, and potential turning points. It leverages the Gyroscopic Momentum Oscillator (GMO) foundation and layers on IQR-based bands, dynamic ATR-adjusted OB/OS levels, torque filtering, and divergence detection. The outcome is a versatile tool that can assist in identifying both short-term squeezes and long-term reversal zones while detecting subtle shifts in momentum acceleration.
Key Components:
Gyroscopic Momentum Oscillator (GMO) – A physics-inspired metric capturing trend stability and momentum by treating price dynamics as “angle,” “angular velocity,” and “inertia.”
IQR Bands – Highlight statistically typical oscillation ranges, providing insight into short-term squeezes and potential near-term trend shifts.
ATR-Adjusted OB/OS Levels – Dynamic thresholds for overbought/oversold conditions, adapting to volatility, aiding in identifying long-term potential reversal zones.
Torque Filtering & Scaling – Smooths and thresholds torque (the rate of change of momentum) and visually scales it for clarity, indicating sudden force changes that may precede volatility adjustments.
Divergence Detection – Highlights potential reversal cues by comparing oscillator swings against price swings, revealing regular and hidden bullish/bearish divergences.
Conceptual Insights
IQR Bands (Short-Term Squeeze & Trend Direction):
Short-Term Momentum and Squeeze: The IQR (Interquartile Range) bands show where the oscillator tends to “live” statistically. When the GMO line hovers within compressed IQR bands, it can signal a momentum squeeze phase. Exiting these tight ranges often correlates with short-term breakout opportunities.
Trend Reversals: If the oscillator pushes beyond these IQR ranges, it may indicate an emerging short-term trend change. Traders can watch for GMO escaping the IQR “comfort zone” to anticipate a new directional move.
Dynamic OB/OS Levels (Long-Term Reversal Zones):
ATR-Based Adaptive Thresholds: Instead of static overbought/oversold lines, this tool uses ATR to adjust OB/OS boundaries. In calm markets, these lines remain closer to ±90. As volatility rises, they approach ±100, reflecting greater permissible swings.
Long-Term Trend Reversal Potential: If GMO hits these dynamically adjusted OB/OS extremes, it suggests conditions ripe for possible long-term trend reversals. Traders seeking major inflection points may find these adaptive levels more reliable than fixed thresholds.
Torque (Sudden Force & Directional Shifts):
Momentum Acceleration Insight: Torque represents the second derivative of momentum, highlighting how quickly momentum is changing. High positive torque suggests a rapidly strengthening bullish force, while high negative torque warns of sudden bearish pressure.
Early Warning & Stability/Volatility Adjustments: By monitoring torque spikes, traders can anticipate momentum shifts before price fully confirms them. This can signal imminent changes in stability or increased volatility phases.
Indicator Parameters and Usage
GMO-Related Inputs:
lenPivot (Default 100): Length for calculating the pivot line (slow market axis).
lenSmoothAngle (Default 200): Smooths the angle measure, reducing noise.
lenATR (Default 14): ATR period for scaling factor, linking price changes to volatility.
useVolatility (Default true): If true, volatility (ATR) influences inertia, adjusting momentum calculations.
useVolume (Default false): If true, volume affects inertia, adding a liquidity dimension to momentum.
lenVolSmoothing (Default 50): Smooths volume calculations if useVolume is enabled.
lenMomentumSmooth (Default 20): EMA smoothing of GMO for a cleaner oscillator line.
normalizeRange (Default true): Normalizes GMO to a fixed range for consistent interpretation.
lenNorm (Default 100): Length for normalization window, ensuring GMO’s scale adapts to recent extremes.
IQR Bands Settings:
iqrLength (Default 14): Period to compute the oscillator’s statistical IQR.
iqrMult (Default 1.5): Multiplier to define the upper and lower IQR-based bands.
ATR-Adjusted OB/OS Settings:
baseOBLevel (Fixed at 90) and baseOSLevel (Fixed at 90): Base lines for OB/OS.
atrPeriodForOBOS (Default 50): ATR length for adjusting OB/OS thresholds dynamically.
atrScaling (Default 0.2): Controls how strongly volatility affects OB/OS lines.
Torque Filtering & Visualization:
torqueSmoothLength (Default 10): EMA length to smooth raw torque values.
atrPeriodForTorque (Default 14): ATR period to determine torque threshold.
atrTorqueScaling (Default 0.5): Scales ATR for determining torque’s “significant” threshold.
torqueScaleFactor (Default 10.0): Multiplies the torque values for better visual prominence on the chart.
Divergence Inputs:
showDivergences (Default true): Toggles divergence signals.
lbR, lbL (Defaults 5): Pivot lookback periods to identify swing highs and lows.
rangeUpper, rangeLower: Bar constraints to validate potential divergences.
plotBull, plotHiddenBull, plotBear, plotHiddenBear: Toggles for each divergence type.
Visual Elements on the Chart
GMO Line (Blue) & Zero Line (Gray):
GMO line oscillates around zero. Positive territory hints bullish momentum, negative suggests bearish.
IQR Bands (Teal Lines & Yellow Fill):
Upper/lower bands form a statistical “normal range” for GMO. The median line (purple) provides a central reference. Contraction near these bands indicates a short-term squeeze, expansions beyond them can signal emerging short-term trend changes.
Dynamic OB/OS (Red & Green Lines):
Red line near +90 to +100: Overbought zone (dynamic).
Green line near -90 to -100: Oversold zone (dynamic).
Movement into these zones may mark significant, longer-term reversal potential.
Torque Histogram (Colored Bars):
Plotted below GMO. Green bars = torque above positive threshold (bullish acceleration).
Red bars = torque below negative threshold (bearish acceleration).
Gray bars = neutral range.
This provides early warnings of momentum shifts before price responds fully.
Precession (Orange Line):
Scaled for visibility, adds context to long-term angular shifts in the oscillator.
Divergence Signals (Shapes):
Circles and offset lines highlight regular or hidden bullish/bearish divergences, offering potential reversal signals.
Practical Interpretation & Strategy
Short-Term Opportunities (IQR Focus):
If GMO compresses within IQR bands, the market might be “winding up.” A break above/below these bands can signal a short-term trade opportunity.
Long-Term Reversal Zones (Dynamic OB/OS):
When GMO approaches these dynamically adjusted extremes, conditions may be ripe for a major trend shift. This is particularly useful for swing or position traders looking for significant turnarounds.
Monitoring Torque for Acceleration Cues:
Torque spikes can precede price action, serving as an early catalyst signal. If torque turns strongly positive, anticipate bullish acceleration; strongly negative torque may warn of upcoming bearish pressure.
Confirm with Divergences:
Divergences between price and GMO reinforce potential reversal or continuation signals identified by IQR, OB/OS, or torque. Use them to increase confidence in setups.
Tips and Best Practices
Combine with Price & Volume Action:
While the indicator is powerful, always confirm signals with actual price structure, volume patterns, or other trend-following tools.
Adjust Lengths & Periods as Needed:
Shorter lengths = more responsiveness but more noise. Longer lengths = smoother signals but greater lag. Tune parameters to match your trading style and timeframe.
Use ATR and Volume Settings Wisely:
If markets are highly volatile, consider useVolatility to refine momentum readings. If liquidity is key, enable useVolume.
Scaling Torque:
If torque bars are hard to read, increase torqueScaleFactor further. The scaling doesn’t affect logic—only visibility.
Conclusion
The “GMO + IQR Bands + ATR-Adjusted OB/OS + Torque Filtering (Scaled)” indicator presents a holistic framework for understanding market momentum across multiple timescales and conditions. By interpreting short-term squeezes via IQR bands, long-term reversal zones via adaptive OB/OS, and subtle acceleration changes through torque, traders can gain advanced insights into when to anticipate breakouts, manage risk around potential reversals, and fine-tune timing for entries and exits.
This integrated approach helps navigate complex market dynamics, making it a valuable addition to any technical analysis toolkit.
Accumulation Momentum IndicatorEveryone wants to be in a trend, I think this indicator does a great job at showing that key momentum that traders try and capitalize on everyday. I used a Stochastic Momentum Indicator (SMI) indicator. It's a lot like a slower MACD which allows me to capitalize on changing momentum. My goal was to make an indicator that was able to use a weighted mean of many accumulation/momentum indicators. This would give me a well rounded look to really see what direction the momentum and volume is heading.
I did some research on some of the best Accumulation and Momentum Indicators. I landed on 4.
The Accumulation Distribution line which measures the cumulative flow of money in or out of a security. It helps show how quickly money is going in and out of a commodity. The line moving up quickly indicates fast Accumulation while the A/C line is moving down quickly is shows falling Distribution. This can show the momentum and accumulation of a commodity in short and long term based off of Volume.
The On Balance Volume, OBV is a combination of Price Movement and Volume. If price closes higher then the previous bar volume is added while if the price closes lower volume is subtracted. This gives us an overall tally of whether volume is increasing with price or slowing down the momentum in the direction of the current trend. This gives us the ability to see if volume is supporting the price increasing (beginning/middle of a trend) or price is slowing down even though it is still heading in the direction of the current trend (signaling the end of the current trend).
The Force Index, this indicator measures the overall strength of the price movements. It does this by a calculation of price and volume. The close of the current bar subtracted by the previous multiplied by the volume. The result gives us either strong upward or downward motion. This adds magnitude to the overall movement/momentum of the indicator.
Lastly but most certainly not least is the Momentum indicator, (Price Momentum) a simple indicator that shows you the difference between the current close price and the close price from a specified period ago (Most commonly 14 periods/bars ago). Having this indicator is a must because it shows the speed at which price is accelerating or decelerating.
These 4 indicators together help round out the current volume, price movements, accumulation, and momentum of the current market. Since these indicators all have different scales and calculations I had to Normalize the Values to a 0-100 scale. This gives us 1 line and a much more readable easy to understand indicator. After they were normalized I gave them a weighted average that you can control. So lets say you cared more about the Force Index and the OBV rather then the Momentum and the Accumulation Distribution indicators, you would be able to give them more weight in the overall calculation as well as 0 out those you don't even want involved.
I hope the flexibility and the combination of 4 strong Accumulation Momentum indicators helps you better gauge the direction a commodity might head. The way it's used is when the Accumulation Momentum line is Above 50 buying pressure is stronger then selling pressure. An Accumulation Momentum line Below 50 suggests that distribution is more dominant in the current market. This indicator combines four different methods of analyzing price and volume to give you a single composite momentum score, making it easier to visualize when a commodity is being accumulated or distributed and how quickly this process is happening. It helps you track market sentiment based on both price movement and volume, with a clear, visual representation of buying and selling pressure.
Please let me know what you think and how you think I might be able to improve the script. Enjoy!
Adaptive Squeeze Momentum StrategyThe Adaptive Squeeze Momentum Strategy is a versatile trading algorithm designed to capitalize on periods of low volatility that often precede significant price movements. By integrating multiple technical indicators and customizable settings, this strategy aims to identify optimal entry and exit points for both long and short positions.
Key Features:
Long/Short Trade Control:
Toggle Options: Easily enable or disable long and short trades according to your trading preferences or market conditions.
Flexible Application: Adapt the strategy for bullish, bearish, or neutral market outlooks.
Squeeze Detection Mechanism:
Bollinger Bands and Keltner Channels: Utilizes the convergence of Bollinger Bands inside Keltner Channels to detect "squeeze" conditions, indicating a potential breakout.
Dynamic Squeeze Length: Calculates the average squeeze duration to adapt to changing market volatility.
Momentum Analysis:
Linear Regression: Applies linear regression to price changes over a specified momentum length to gauge the strength and direction of momentum.
Dynamic Thresholds: Sets momentum thresholds based on standard deviations, allowing for adaptive sensitivity to market movements.
Momentum Multiplier: Adjustable setting to fine-tune the aggressiveness of momentum detection.
Trend Filtering:
Exponential Moving Average (EMA): Implements a trend filter using an EMA to align trades with the prevailing market direction.
Customizable Length: Adjust the EMA length to suit different trading timeframes and assets.
Relative Strength Index (RSI) Filtering:
Overbought/Oversold Signals: Incorporates RSI to avoid entering trades during overextended market conditions.
Adjustable Levels: Set your own RSI oversold and overbought thresholds for personalized signal generation.
Advanced Risk Management:
ATR-Based Stop Loss and Take Profit:
Adaptive Levels: Uses the Average True Range (ATR) to set stop loss and take profit points that adjust to market volatility.
Custom Multipliers: Modify ATR multipliers for both stop loss and take profit to control risk and reward ratios.
Minimum Volatility Filter: Ensures trades are only taken when market volatility exceeds a user-defined minimum, avoiding periods of low activity.
Time-Based Exit:
Holding Period Multiplier: Defines a maximum holding period based on the momentum length to reduce exposure to adverse movements.
Automatic Position Closure: Closes positions after the specified holding period is reached.
Session Filtering:
Trading Session Control: Limits trading to predefined market hours, helping to avoid illiquid periods.
Custom Session Times: Set your preferred trading session to match market openings, closings, or specific timeframes.
Visualization Tools:
Indicator Plots: Displays Bollinger Bands, Keltner Channels, and trend EMA on the chart for visual analysis.
Squeeze Signals: Marks squeeze conditions on the chart, providing clear visual cues for potential trade setups.
Customization Options:
Indicator Parameters: Fine-tune lengths and multipliers for Bollinger Bands, Keltner Channels, momentum calculation, and ATR.
Entry Filters: Choose to use trend and RSI filters to refine trade entries based on your strategy.
Risk Management Settings: Adjust stop loss, take profit, and holding periods to match your risk tolerance.
Trade Direction Control: Enable or disable long and short trades independently to align with your market strategy or compliance requirements.
Time Settings: Modify the trading session times and enable or disable the time filter as needed.
Use Cases:
Trend Traders: Benefit from aligning entries with the broader market trend while capturing breakout movements.
Swing Traders: Exploit periods of low volatility leading to significant price swings.
Risk-Averse Traders: Utilize advanced risk management features to protect capital and manage exposure.
Disclaimer:
This strategy is a tool to assist in trading decisions and should be used in conjunction with other analyses and risk management practices. Past performance is not indicative of future results. Always test the strategy thoroughly and adjust settings to suit your specific trading style and market conditions.
Trend Momentum Indicator with MACD ConfirmationTrend Momentum Indicator with MACD Confirmation
Overview: The Trend Momentum Indicator with MACD Confirmation is a versatile trading tool designed to help traders identify potential buy and sell signals in the market based on the interaction between price action, a Simple Moving Average (SMA), and the Moving Average Convergence Divergence (MACD) indicator. This strategy aims to enhance trading decisions by waiting for MACD confirmation before executing trades, thereby reducing false signals.
Components:
Simple Moving Average (SMA):
The SMA is calculated over a user-defined period (default: 20 bars) and serves as a trend indicator. It provides a smoothed representation of price action and helps traders identify the overall market direction.
MACD:
The MACD is calculated using standard parameters (12 for fast length, 26 for slow length, and 9 for signal length) but can be adjusted to suit individual trading preferences. The MACD consists of two lines:
MACD Line: The difference between the fast and slow EMAs.
Signal Line: An EMA of the MACD Line, which helps indicate buy and sell conditions.
Buy and Sell Signals:
Buy Signal: A buy signal is triggered when the price crosses above the SMA, coupled with the MACD line crossing above the signal line, indicating a bullish momentum.
Sell Signal: A sell signal occurs when the price crosses below the SMA, alongside the MACD line crossing below the signal line, indicating a bearish momentum.
Visual Features:
The SMA is plotted on the main price chart, allowing traders to easily visualize trend direction.
Buy signals are indicated by green triangle shapes below the price bars, while sell signals are shown by red triangle shapes above the price bars.
Optionally, a MACD histogram can be plotted to visualize the difference between the MACD line and the signal line, helping to confirm trade signals visually.
Usage:
This indicator is suitable for various trading styles, including day trading, swing trading, and trend-following strategies. It can be applied to any financial instrument, including stocks, forex, and cryptocurrencies.
Traders should consider combining this indicator with additional tools and analysis to enhance decision-making and manage risk effectively.
Volume Surge Momentum Detector [CHE]Volume Surge Momentum Detector – Discover explosive price movements fueled by sudden volume spikes.
Volume Surge Momentum Detector – Capture Key Inflection Points Using Volume Dynamics
Description:
This indicator helps traders identify highprobability entries by focusing on volume dynamics. Significant price movements often occur when interest in a stock rises, and this is reflected in volume spikes. The Volume Analysis Indicator is designed to detect key inflection points such as breakouts and capitulations by analyzing the relationship between volume and price. It enables traders to avoid false breakouts, identify trend exhaustion, and make informed trading decisions.
Key Features:
VolumeBased Inflection Points: The indicator tracks the volume levels to detect when there is significant interest in a stock. High volume signals increased market participation, often preceding large price moves.
Breakout Detection: It identifies breakouts by detecting price moves beyond a key level (the highest price over a certain period) along with a volume spike, indicating strong momentum.
Capitulation Detection: Capitulation is detected when a strong trend weakens and reverses with increased volume, signaling potential trend exhaustion.
Volume Thresholds: By using statistical measures, the indicator identifies unusually high or low volume based on the average volume and standard deviations, helping traders to spot major turning points in the market.
This tool simplifies volume bar analysis by automatically highlighting significant volume events, which often indicate large upcoming price movements.
Detailed Breakdown:
1. Volume as a Catalyst for Price Movements:
Volume is essential for price action. Without sufficient volume, price moves may not be sustained. This indicator highlights moments of increased market interest by tracking significant volume increases, helping traders stay ahead of major price movements.
2. Breakouts and Capitulation Detection:
Breakout: Detected when the volume exceeds an upper threshold (based on two standard deviations above the average volume) and the price breaks above the highest close of the previous period. These moments are marked with green labels on the chart.
Capitulation: Detected when volume increases significantly but the trend cannot sustain itself, and the price reverses below the lowest close of the previous period. These moments are marked with red labels on the chart, indicating potential trend exhaustion.
3. Sentiment and Market Dynamics:
Market sentiment can lead to price inflections when one side of the market becomes overbought or exhausted. Volume spikes in either direction provide clues as to whether a trend will continue or reverse. This indicator helps identify these critical points by monitoring volume patterns.
4. Visual Representation:
Green Bars: High volume indicating strong market interest or momentum.
Red Bars: Low volume, signaling potential lack of interest or exhaustion.
Gray Bars: Normal volume, helping to distinguish significant market events from regular activity.
Breakout and Capitulation Labels: Green labels for breakouts and red labels for capitulation points are shown directly on the chart for easy reference.
5. Alerts for Key Signals:
Breakout Alert: Notifies traders when a breakout occurs with strong volume, indicating a potential for significant price movement.
Capitulation Alert: Alerts traders when a capitulation occurs, suggesting a trend reversal.
High and Low Volume Alerts: Receive notifications when the volume exceeds the upper or lower thresholds, highlighting key moments of market interest or disinterest.
Why This Indicator Matters:
Traders often miss significant price moves or enter too late. This indicator helps traders by identifying highprobability entry points before the stock makes major moves. By focusing on volume spikes, the indicator provides insight into market sentiment and allows traders to act quickly.
How It Works:
1. Calculate Volume Significance: The indicator calculates the average volume over a userdefined period (`length`) and identifies significant deviations using standard deviations.
2. Mark Key Levels: Breakouts are detected when price moves above recent highs with significant volume, while capitulation is flagged when trends show exhaustion with a volume spike and price reversal.
3. Receive Alerts: Traders can set up alerts for key events like breakouts, capitulations, and significant volume changes to stay informed in realtime.
Perfect For:
Active traders looking to spot early market movements driven by volume changes.
Traders who want to avoid false breakouts by confirming price moves with volume spikes.
Swing traders identifying capitulation points to reduce exposure or enter positions on trend reversals.
How to Use:
Customize the "Average Period" to determine how many bars are used to calculate the average volume.
Adjust the "Multiplier for Standard Deviation" to finetune the sensitivity of high and low volume detection.
Enable alerts to receive realtime notifications for breakouts, capitulations, or volume spikes.
Conclusion:
Volume analysis is essential to understanding stock movements. This indicator simplifies the process of identifying breakouts and capitulation points by using volume dynamics. Whether you are a beginner looking for powerful tools or an experienced trader refining your strategy, this indicator offers valuable insights into market behavior driven by volume.
Additional Insights:
1. Statistical Significance: The use of standard deviations to identify high and low volume gives the indicator a statistical basis, helping to reduce noise and false signals.
2. Flexible Alerts: Traders can set up custom alerts based on their trading preferences, whether they focus on volume changes or price breakouts and reversals.
This detailed description now includes all the important aspects of the script without referencing any external sources, focusing solely on the functionality and trading strategy the script provides.
Best regards
Chervolino
RSI Momentum [CrossTrade]The RSI Momentum indicator generates buy and sell signals based on the Relative Strength Index (RSI) crossing specific thresholds. The Key difference is that we're using RSI overbought and oversold readings as the foundation for finding continuation signals in the same direction of that momentum. This solves the issue of trying to buy the bottom or sell the top and offsets any oscillators main weakness, divergence and false signals in a strong trend.
Key Parameters:
RSI Length: Determines the calculation period for the RSI.
Overbought Threshold: The RSI level above which the asset is considered overbought.
Momentum Loss Threshold for Buy: The RSI level below which a loss in upward momentum is indicated, triggering a potential buy signal.
Oversold Threshold: The RSI level below which the asset is considered oversold.
Momentum Loss Threshold for Sell: The RSI level above which a loss in downward momentum is indicated, triggering a potential sell signal.
Allow Additional Retracement Signals: A toggle to allow more than one signal within a certain number of bars after the first signal.
Max Additional Signals: The maximum number of additional signals allowed after the first signal.
Buy Signal Logic:
Initial Signal: Generated when the RSI first exceeds the overbought threshold and then falls below the momentum loss buy threshold. Defaults are 70 for the overbought threshold and 60 for the retracement level.
Additional Signals for Deeper Retracements: If enabled, the script shows additional buy signals within the maximum limit set by Max Additional Signals. These additional signals are shown only if each new signal's bar has a lower low than the previous signal's bar.
Sell Signal Logic:
Initial Signal: Similar to the buy signal, a sell signal is generated when the RSI first drops below the oversold threshold and then rises above the momentum loss sell threshold. Defaults are 30 for the oversold threshold and 40 for the retracement level.
Additional Signals for Deeper Retracements: If enabled, additional sell signals are shown, limited by Max Additional Signals, and only if each new signal's bar has a higher high than the previous signal's bar.
Continuation Signals in Strong Trends:
The script allows for a new series of signals (starting with the first signal again) when the RSI pattern repeats. For buy signals, this means going above the overbought and then below the momentum loss buy threshold. For sell signals, it's dropping below oversold and then above the momentum loss sell threshold.
Alerts:
The script includes alert conditions for both buy and sell signals, which can be configured in the TradingView alerts.
Approximate Spectral Entropy-Based Market Momentum (SEMM)Overview
The Approximate Spectral Entropy-Based Market Momentum (SEMM) indicator combines the concepts of spectral entropy and traditional momentum to provide traders with insights into both the strength and the complexity of market movements. By measuring the randomness or predictability of price changes, SEMM helps traders understand whether the market is in a trending or consolidating state and how strong that trend or consolidation might be.
Key Features
Entropy Measurement: Calculates the approximate spectral entropy of price movements to quantify market randomness.
Momentum Analysis: Integrates entropy with rate-of-change (ROC) to highlight periods of strong or weak momentum.
Dynamic Market Insight: Provides a dual perspective on market behavior—both the trend strength and the underlying complexity.
Customizable Parameters: Adjustable window length for entropy calculation, allowing for fine-tuning to suit different market conditions.
Concepts Underlying the Calculations
The indicator utilizes Shannon entropy, a concept from information theory, to approximate the spectral entropy of price returns. Spectral entropy traditionally involves a Fourier Transform to analyze the frequency components of a signal, but due to Pine Script limitations, this indicator uses a simplified approach. It calculates log returns over a rolling window, normalizes them, and then computes the Shannon entropy. This entropy value represents the level of disorder or complexity in the market, which is then multiplied by traditional momentum measures like the rate of change (ROC).
How It Works
Price Returns Calculation: The indicator first computes the log returns of price data over a specified window length.
Entropy Calculation: These log returns are normalized and used to calculate the Shannon entropy, representing market complexity.
Momentum Integration: The calculated entropy is then multiplied by the rate of change (ROC) of prices to generate the SEMM value.
Signal Generation: High SEMM values indicate strong momentum with higher randomness, while low SEMM values indicate lower momentum with more predictable trends.
How Traders Can Use It
Trend Identification: Use SEMM to identify strong trends or potential trend reversals. Low entropy values can indicate a trending market, whereas high entropy suggests choppy or consolidating conditions.
Market State Analysis: Combine SEMM with other indicators or chart patterns to confirm the market's state—whether it's trending, ranging, or transitioning between states.
Risk Management: Consider high SEMM values as a signal to be cautious, as they suggest increased market unpredictability.
Example Usage Instructions
Add the Indicator: Apply the "Approximate Spectral Entropy-Based Market Momentum (SEMM)" indicator to your chart.
Adjust Parameters: Modify the length parameter to suit your trading timeframe. Shorter lengths are more responsive, while longer lengths smooth out the signal.
Analyze the Output: Observe the blue line for entropy and the red line for SEMM. Look for divergences or confirmations with price action to guide your trades.
Combine with Other Tools: Use SEMM alongside moving averages, support/resistance levels, or other indicators to build a comprehensive trading strategy.
Volume, Volatility, and Momentum Metrics IndicatorVolume, Volatility, and Momentum Metrics Indicator
Welcome to our comprehensive TradingView indicator designed to provide traders with essential volume, volatility, and momentum metrics. This powerful tool is ideal for traders looking to enhance their market analysis by visualizing key indicators in a concise and easy-to-read format.
Key Features
1. Volume Metrics:
• Daily Dollar Volume: Understand the monetary value of the traded volume each day.
• Relative Volume (RVOL) Day: Compare the current volume to the previous day’s volume to gauge trading activity.
• Relative Volume (RVOL) 30D: Assess the average trading volume over the past 30 days.
• Relative Volume (RVOL) 90D: Evaluate the average trading volume over the past 90 days.
2. Volatility and Momentum Metrics:
• Average Daily Range (ADR) %: Measure the average daily price range as a percentage of the current price.
• Average True Range (ATR): Track the volatility by calculating the average true range over a specified period.
• Relative Strength Index (RSI): Determine the momentum by analyzing the speed and change of price movements.
3. Customizable Table Positions:
• Place the volume metrics table and the volatility/momentum metrics table in the bottom-left or bottom-right corners of your chart for optimal visibility and convenience.
Why Use This Indicator?
• Enhanced Market Analysis: Quickly assess volume trends, volatility, and momentum to make informed trading decisions.
• User-Friendly Interface: The clear and concise tables provide at-a-glance information without cluttering your chart.
• Customization Options: Choose where to display the tables to suit your trading style and preferences.
How It Works
This indicator uses advanced calculations to provide real-time data on trading volume, price range, and momentum. By displaying this information in separate, neatly organized tables, traders can easily monitor these critical metrics without diverting their focus from the main chart.
Who Can Benefit?
• Day Traders: Quickly gauge intraday trading activity and volatility.
• Swing Traders: Analyze longer-term volume trends and momentum to identify potential trade setups.
• Technical Analysts: Utilize comprehensive metrics to enhance technical analysis and trading strategies.
Get Started
To add this powerful indicator to your TradingView chart, simply search for “Volume, Volatility, and Momentum Metrics” in the TradingView public library, or use the provided link to add it directly to your chart. Enhance your trading analysis and make more informed decisions with our comprehensive TradingView indicator.
Dynamic Momentum Oscillator (DMO) [Angel Algo]Dynamic Momentum Oscillator (DMO)
OVERVIEW: The Dynamic Momentum Oscillator (DMO) is a technical indicator designed to measure the momentum of price movements in financial markets. It combines momentum calculation with dynamic range assessment to provide insights into potential trend reversals and overbought/oversold conditions.
DMO is different from classic momentum oscillators like the RSI or Stochastic Oscillator because it looks at the momentum in relation to how much the price is moving. This helps it give signals that better match what's happening in the market, especially when the market's volatility is changing.
HOW TO USE:
Interpretation:
Thresholds: Horizontal lines mark user-defined threshold levels for overbought (OB) and oversold (OS) conditions, aiding in identifying potential trend pullbacks and reversals.
DMO Line: The primary line on the indicator plot. It reflects momentum in relation to the dynamic price range. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
Filled Area: The area between the DMO line and the zero line is filled with color to enhance visualization of momentum shifts.
Trading Signals:
Thresholds: Monitor for potential trend reversals when the DMO crosses above the overbought threshold or below the oversold threshold.
Crossovers: Look for buy signals when the DMO line crosses above the zero and sell signals when it crosses below.
Filled Area: The green color indicates bullish momentum, red indicates bearish momentum and gray color indicates neutral conditions.
Signals: Circles appear on the chart when the DMO crosses the overbought or oversold thresholds, indicating conditions for potential trend pullbacks or reversals.
SETTINGS:
Length: Adjust the length parameter to vary the number of periods considered in the momentum calculation.
Smoothing: Enable or disable smoothing of the DMO line using the provided option.
Thresholds: Customize the overbought and oversold threshold levels to suit specific market conditions and trading preferences.
Disclaimer: The DMO indicator serves as part of a comprehensive trading strategy and should not be solely relied upon for trading decisions. Past performance is not indicative of future results, and trading involves inherent risks.
MADALGO`s Enhanced OBV DivergencesDescription:
MADALGO's Enhanced OBV Divergences indicator is a unique tool designed for traders to visualize the divergences between price action and On Balance Volume (OBV), a fundamental aspect often indicative of underlying strength or weakness in the market. By keenly identifying these divergences, traders are better positioned to anticipate potential trend reversals or trend continuations, making this script an invaluable addition to their technical analysis toolkit.
This script meticulously scans for both regular and hidden bullish/bearish divergences, providing a comprehensive view of market sentiment. The core of this indicator is built around the OBV, which cumulatively adds or subtracts volume based on the price movement per period, thus providing a running total of volume and portraying the force behind the price movements.
The regular divergences are classic indicators of a potential reversal in the current trend, while hidden divergences are often indicative of trend continuation. These divergences are pinpointed based on the relative positions of the OBV and price highs/lows, over customizable lookback periods and within specified lookback ranges.
Features:
Regular and Hidden Divergences: Clearly marked bullish and bearish divergences provide insights into potential market turning points.
On Balance Volume (OBV) Line: Visualize the continuous flow of buying and selling pressure, enabling the identification of accumulation or distribution phases essential for understanding the market's strength or weakness.
Moving Average of OBV: An optional feature to smooth the OBV line, aiding in the identification of the overarching trend.
Dynamic Statistics Label: A floating label provides real-time updates on essential statistics like the Rate of Percentage Change (RPC) of OBV, the last divergences, and bars since the last divergences.
Inputs:
Pivot Lookback Right and Pivot Lookback Left: Define the lookback periods for identifying pivot points in the OBV line.
Max of Lookback Range and Min of Lookback Range: Define the range for considering divergences.
RPC Period: Defines the period for calculating the Rate of Percentage Change of the OBV.
MA Period: Defines the period for the optional moving average of the OBV.
Plot Bullish, Plot Hidden Bullish, Plot Bearish, Plot Hidden Bearish: Toggle visibility of respective divergences.
Plot Moving Average: Toggle visibility of the OBV moving average.
Usage:
Add the script to your TradingView chart.
Tailor the input parameters in the settings panel to align with your analysis requirements.
The divergences, OBV line, and optional moving average will be plotted on your chart, with a dynamic label displaying real-time statistics.
Set up alerts to be notified of identified divergences, enabling timely decision-making.
Alerts:
Regular bullish/bearish divergence in OBV found: Triggered when a regular bullish or bearish divergence is identified.
Hidden bullish/bearish divergence in OBV found: Triggered when a hidden bullish or bearish divergence is identified.
Underlying Concepts:
The OBV Divergences indicator is rooted in the principle that volume precedes price movement. When prices are rising with increased volume, it suggests that buying pressure is prevailing and may lead to continued upward momentum. Conversely, rising prices with decreasing volume might indicate a lack of buying conviction and could signal a potential price reversal. The identification of divergences between price and OBV can therefore serve as a powerful signal for traders. These examples can be seen below in the image
The Moving Average of the OBV further aids in understanding the prevailing trend by smoothing out the OBV line, providing a clearer picture of the market's longer-term momentum. The Rate of Percentage Change (RPC) provides insight into the momentum of volume, offering an additional layer of analysis. Together, these additional features enhance the core OBV analysis, enabling a more nuanced understanding of volume dynamics fundamental for making more informed trading decisions.
License:
This Source Code Form is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this file, you can obtain one at Mozilla Public License 2.0.
Thange Momentum KicksTitle: Thange Momentum Kicks Indicator - Identify Strong Bullish and Bearish Candles
Description:
The Thange Momentum Kicks indicator is a small tool designed to identify strong bullish and bearish candles in a candlestick price chart. By analyzing the momentum and size of each candle, this indicator highlights potential significant price movements.
The indicator marks strong bullish candles with a "Bull Kick" label to signal their strength on price action. Similarly, strong bearish candles are identified with the "Bear Kick" label. These kicks are characterized by their size and momentum, indicating a high probability of significant price movement.
The indicator allows traders and investors to easily spot these kicks on their charts, helping them make quick decisions. It calculates the percentage momentum of each candle and compares it to the specified thresholds for bullish and bearish kicks.
Key Features:
- Identifies strong bullish and bearish candles ("Kicks") based on momentum and size.
- Customizable input parameters for setting the percentage thresholds for kicks.
- Labels and tooltips provide essential information such as momentum, percentage change, open, and close prices.
- Differentiates between bullish kicks with blue color and bearish kicks with a unique pink color.
- Plots the candles with the specified colors for easy visualization.
Instructions:
1. Look for the "Kicks" labeled candles on your chart.
2. Bullish kicks indicate strong upward momentum, while bearish kicks represent strong downward momentum.
3. Consider the size and momentum of the kicks when making trading decisions.
4. Combine the Thange Momentum Kicks indicator with other technical analysis tools for a comprehensive market analysis.
Note: The Thange Momentum Kicks indicator is most effective when used in conjunction with other indicators, chart patterns, and risk management strategies to confirm signals and optimize trade entries and exits.
Disclaimer: This indicator should be used as a tool for technical analysis and does not guarantee specific trading outcomes. Users should exercise their own discretion and risk management when making trading decisions based on this indicator.
I hope my Thange Momentum Kicks indicator enhances your trading experience and helps you identify strong bullish and bearish candles with ease. Happy trading!
Advanced Volatility-Adjusted Momentum IndexAdvanced Volatility-Adjusted Momentum Index (AVAMI)
The AVAMI is a powerful and versatile trading index which enhances the traditional momentum readings by introducing a volatility adjustment. This results in a more nuanced interpretation of market momentum, considering not only the rate of price changes but also the inherent volatility of the asset.
Settings and Parameters:
Momentum Length: This parameter sets the number of periods used to calculate the momentum, which is essentially the rate of change of the asset's price. A shorter length value means the momentum calculation will be more sensitive to recent price changes. Conversely, a longer length will yield a smoother and more stabilized momentum value, thereby reducing the impact of short-term price fluctuations.
Volatility Length: This parameter is responsible for determining the number of periods to be considered in the calculation of standard deviation of returns, which acts as the volatility measure. A shorter length will result in a more reactive volatility measure, while a longer length will produce a more stable, but less sensitive measure of volatility.
Smoothing Length: This parameter sets the number of periods used to apply a moving average smoothing to the AVAMI and its signal line. The purpose of this is to minimize the impact of volatile periods and to make the indicator's lines smoother and easier to interpret.
Lookback Period for Scaling: This is the number of periods used when rescaling the AVAMI values. The rescaling process is necessary to ensure that the AVAMI values remain within a consistent and interpretable range over time.
Overbought and Oversold Levels: These levels are thresholds at which the asset is considered overbought (potentially overvalued) or oversold (potentially undervalued), respectively. For instance, if the AVAMI exceeds the overbought level, traders may consider it as a possible selling opportunity, anticipating a price correction. Conversely, if the AVAMI falls below the oversold level, it could be seen as a buying opportunity, with the expectation of a price bounce.
Mid Level: This level represents the middle ground between the overbought and oversold levels. Crossing the mid-level line from below can be perceived as an increasing bullish momentum, and vice versa.
Show Divergences and Hidden Divergences: These checkboxes give traders the option to display regular and hidden divergences between the AVAMI and the asset's price. Divergences are crucial market structures that often signal potential price reversals.
Index Logic:
The AVAMI index begins with the calculation of a simple rate of change momentum indicator. This raw momentum is then adjusted by the standard deviation of log returns, which acts as a measure of market volatility. This adjustment process ensures that the resulting momentum index encapsulates not only the speed of price changes but also the market's volatility context.
The raw AVAMI is then smoothed using a moving average, and a signal line is generated as an exponential moving average (EMA) of this smoothed AVAMI. This signal line serves as a trigger for potential trading signals when crossed by the AVAMI.
The script also includes an algorithm to identify 'fractals', which are distinct price patterns that often act as potential market reversal points. These fractals are utilized to spot both regular and hidden divergences between the asset's price and the AVAMI.
Application and Strategy Concepts:
The AVAMI is a versatile tool that can be integrated into various trading strategies. Traders can utilize the overbought and oversold levels to identify potential reversal points. The AVAMI crossing the mid-level line can signify a change in market momentum. Additionally, the identification of regular and hidden divergences can serve as potential trading signals:
Regular Divergence: This happens when the asset's price records a new high/low, but the AVAMI fails to follow suit, suggesting a possible trend reversal. For instance, if the asset's price forms a higher high but the AVAMI forms a lower high, it's a regular bearish divergence, indicating potential price downturn.
Hidden Divergence: This is observed when the price forms a lower high/higher low, but the AVAMI forms a higher high/lower low, suggesting the continuation of the prevailing trend. For example, if the price forms a lower low during a downtrend, but the AVAMI forms a higher low, it's a hidden bullish divergence, signaling the potential continuation of the downtrend.
As with any trading tool, the AVAMI should not be used in isolation but in conjunction with other technical analysis tools and within the context of a well-defined trading plan.
RSI MTF [Market Yogi]The Multi-Time Frame RSI with Money Flow Index and Average is a powerful trading indicator designed to help traders identify overbought and oversold conditions across multiple time frames. It combines the Relative Strength Index (RSI) with the Money Flow Index (MFI) and provides an average value for better accuracy.
The Relative Strength Index (RSI) is a popular momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100 and is used to identify overbought and oversold conditions in an asset. By incorporating the RSI across multiple time frames, this indicator offers a broader perspective on market sentiment.
In addition to the RSI, this indicator also includes the Money Flow Index (MFI). The MFI is a volume-based oscillator that measures the inflow and outflow of money into an asset. It takes into account both price and volume, providing insights into the strength and direction of buying and selling pressure.
By combining the RSI and MFI across multiple time frames, traders gain a comprehensive understanding of market dynamics. The indicator allows for comparing the RSI and MFI values across different time frames, enabling traders to identify divergences and potential trend reversals.
Furthermore, this indicator provides an average value of the multi-time frame RSI, offering a consolidated signal that helps filter out noise and enhance the accuracy of trading decisions.
Key Features:
1. Multi-Time Frame RSI: Combines the RSI across different time frames to provide a comprehensive view of market sentiment.
2. Money Flow Index (MFI): Incorporates the MFI to gauge buying and selling pressure based on both price and volume.
3. Average Calculation: Computes the average value of the multi-time frame RSI to generate a consolidated trading signal.
4. Divergence Detection: Enables traders to spot divergences between the RSI and MFI values, indicating potential trend reversals.
5. Overbought and Oversold Levels: Highlights overbought and oversold levels on the RSI, aiding in timing entry and exit points.
The Multi-Time Frame RSI with Money Flow Index and Average is a versatile tool that can be applied to various trading strategies, including trend following, swing trading, and mean reversion. Traders can adjust the time frame settings to suit their preferences and trading style.
Note: It's important to use this indicator in conjunction with other technical analysis tools and indicators to validate signals and make informed trading decisions.
Volume Accumulation Oscillator (VAO)The Volume Accumulation Oscillator (VAO) is a powerful momentum-based indicator designed to assess the strength of volume accumulation in a given asset. It helps traders identify periods of intense buying or selling pressure and potential trend reversals.
The VAO calculates the Net Volume Accumulation (NVA) by considering the volume, open, close, high, and low prices. It then applies exponential moving averages (EMAs) to smooth the NVA and calculates the VAO by comparing the smoothed NVA with its EMA over a specified signal period.
The VAO is plotted as a line chart, providing a clear visual representation of its values. Positive VAO values indicate strong bullish volume accumulation, suggesting potential upward price movement. Conversely, negative VAO values indicate significant selling pressure and the possibility of a downtrend.
To enhance the analysis, the indicator includes reference levels such as the zero line and +/-1 levels. These levels serve as important reference points for interpreting the VAO values and identifying key turning points in the market.
Additionally, the VAO histogram is included, which further illustrates the strength and direction of volume accumulation. The histogram bars are color-coded, with green bars representing positive VAO values and red bars representing negative VAO values.
The Volume Accumulation Oscillator is a versatile tool that can be used in various trading strategies. Traders can look for divergences between the VAO and the price chart to identify potential trend reversals. Combining the VAO with other technical analysis techniques can provide valuable insights into market dynamics and help traders make informed trading decisions.
Note: It is recommended to customize the indicator's parameters and conduct thorough backtesting to align it with your specific trading strategy and preferences before using it for live trading.
Disclaimer: This indicator is provided for educational and informational purposes only. Trading involves risks, and it is important to exercise caution and conduct your own analysis before making any investment decisions.
Composite MomentumComposite Momentum Indicator - Enhancing Trading Insights with RSI & Williams %R
The Composite Momentum Indicator is a powerful technical tool that combines the Relative Strength Index (RSI) and Williams %R indicators from TradingView. This unique composite indicator offers enhanced insights into market momentum and provides traders with a comprehensive perspective on price movements. By leveraging the strengths of both RSI and Williams %R, the Composite Momentum Indicator offers distinct advantages over a simple RSI calculation.
1. Comprehensive Momentum Analysis:
The Composite Momentum Indicator integrates the RSI and Williams %R indicators to provide a comprehensive analysis of market momentum. It takes into account both the strength of recent price gains and losses (RSI) and the relationship between the current closing price and the highest-high and lowest-low price range (Williams %R). By combining these two momentum indicators, traders gain a more holistic view of market conditions.
2. Increased Accuracy:
While the RSI is widely used for measuring overbought and oversold conditions, it can sometimes generate false signals in certain market environments. The Composite Momentum Indicator addresses this limitation by incorporating the Williams %R, which focuses on the price range and can offer more accurate signals in volatile market conditions. This combination enhances the accuracy of momentum analysis, allowing traders to make more informed trading decisions.
3. Improved Timing of Reversals:
One of the key advantages of the Composite Momentum Indicator is its ability to provide improved timing for trend reversals. By incorporating both RSI and Williams %R, traders can identify potential turning points more effectively. The Composite Momentum Indicator offers an early warning system for identifying overbought and oversold conditions and potential trend shifts, helping traders seize opportunities with better timing.
4. Enhanced Divergence Analysis:
Divergence analysis is a popular technique among traders, and the Composite Momentum Indicator strengthens this analysis further. By comparing the RSI and Williams %R within the composite calculation, traders can identify divergences between the two indicators more easily. Divergence between the RSI and Williams %R can signal potential trend reversals or the weakening of an existing trend, providing valuable insights for traders.
5. Customizable Moving Average:
The Composite Momentum Indicator also features a customizable moving average (MA), allowing traders to further fine-tune their analysis. By incorporating the MA, traders can smooth out the composite momentum line and identify longer-term trends. This additional layer of customization enhances the versatility of the indicator, catering to various trading styles and timeframes.
The Composite Momentum Indicator, developed using the popular TradingView indicators RSI and Williams %R, offers a powerful tool for comprehensive momentum analysis. By combining the strengths of both indicators, traders can gain deeper insights into market conditions, improve accuracy, enhance timing for reversals, and leverage divergence analysis. With the added customization of the moving average, the Composite Momentum Indicator provides traders with a versatile and effective tool to make more informed trading decisions.
