Advanced Momentum Scanner [QuantAlgo]The Advanced Momentum Scanner is a sophisticated technical indicator designed to identify market momentum and trend direction using multiple exponential moving averages (EMAs), momentum metrics, and adaptive visualization techniques. It is particularly valuable for those looking to identify trading and investing opportunities based on trend changes and momentum shifts across any market and timeframe.
🟢 Technical Foundation
The Advanced Momentum Scanner utilizes a multi-layered approach with four different EMA periods to identify market momentum and trend direction:
Ultra-Fast EMA for quick trend changes detection (default: 5)
Fast EMA for short-term trend analysis (default: 10)
Mid EMA for intermediate confirmation (default: 30)
Slow EMA for long-term trend identification (default: 100)
For momentum detection, the indicator implements a Rate of Change (RoC) calculation to measure price momentum over a specified period. It further enhances analysis by incorporating RSI readings for overbought/oversold conditions, volatility measurements through ATR, and optional volume confirmation. When these elements align, the indicator generates trading signals based on the selected sensitivity mode (Conservative, Balanced, or Aggressive).
🟢 Key Features & Signals
1. Multi-Period Trend Identification
The indicator combines multiple EMAs of different lengths to provide comprehensive trend analysis within the same timeframe, displaying the information through color-coded visual elements on the chart.
When an uptrend is detected, chart elements are colored with the bullish theme color (default: green/teal).
Similarly, when a downtrend is detected, chart elements are colored with the bearish theme color (default: red).
During neutral or indecisive periods, chart elements are colored with a neutral gray color, providing clear visual distinction between trending and non-trending market conditions.
This visualization provides immediate insights into underlying trend direction without requiring separate indicators, helping traders and investors quickly identify the market's current state.
2. Trend Strength Information Panel
The trend panel operates in three different sensitivity modes (Conservative, Aggressive, and Balanced), each affecting how the indicator processes and displays market information.
The Conservative mode prioritizes trend sustainability over frequency, showing only strong trend movements with high probability.
The Aggressive mode detects early trend changes, providing more frequent signals but potentially more false positives.
The Balanced mode offers a middle ground with moderate signal frequency and reliability.
Regardless of the selected mode, the panel displays:
Current trend direction (UPTREND, DOWNTREND, or NEUTRAL)
Trend strength percentage (0-100%)
Early detection signals when applicable
The active sensitivity mode
This comprehensive approach helps traders and investors:
→ Assess the strength of current market trends
→ Identify early potential trend changes before full confirmation
→ Make more informed trading and investing decisions based on trend context
3. Customizable Visualization Settings
This indicator offers extensive visual customization options to suit different trading styles and preferences:
Display options:
→ Fully customizable uptrend, downtrend, and neutral colors
→ Color-coded price bars showing trend direction
→ Dynamic gradient bands visualizing potential trend channels
→ Optional background coloring based on trend intensity
→ Adjustable transparency levels for all visual elements
These visualization settings can be fine-tuned through the indicator's interface, allowing traders and investors to create a personalized chart environment that emphasizes the most relevant information for their strategy.
The indicator also features a comprehensive alert system with notifications for:
New trend formations (uptrend, downtrend, neutral)
Early trend change signals
Momentum threshold crossovers
Other significant market conditions
Alerts can be customized and delivered through TradingView's notification system, making it easy to stay informed of important market developments even when you are away from the charts.
🟢 Practical Usage Tips
→ Trend Analysis and Interpretation: The indicator visualizes trend direction and strength directly on the chart through color-coding and the information panel, allowing traders and investors to immediately identify the current market context. This information helps in assessing the potential for continuation or reversal.
→ Signal Generation Strategies: The indicator generates potential trading signals based on trend direction, momentum confirmation, and selected sensitivity mode. Users can choose between Conservative (fewer but more reliable signals), Balanced (moderate approach), or Aggressive (more frequent but potentially less reliable signals).
→ Multi-Period Trend Assessment: Through its layered EMA approach, the indicator enables users to understand trend conditions across different lookback periods within the same timeframe. This helps in identifying the dominant trend and potential turning points.
🟢 Pro Tips
Adjust EMA periods based on your timeframe:
→ Lower values for shorter timeframes and more frequent signals
→ Higher values for higher timeframes and more reliable signals
Fine-tune sensitivity mode based on your trading style:
→ "Conservative" for position trading/long-term investing and fewer false signals
→ "Balanced" for swing trading/medium-term investing with moderate signal frequency
→ "Aggressive" for scalping/day trading and catching early trend changes
Look for confluence between components:
→ Strong trend strength percentage and direction in the information panel
→ Overall market context aligning with the expected direction
Use for multiple trading approaches:
→ Trend following during strong momentum periods
→ Counter-trend trading at band extremes during overextension
→ Early trend change detection with sensitivity adjustments
→ Stop loss placement using dynamic bands
Combine with:
→ Volume indicators for additional confirmation
→ Support/resistance analysis for strategic entry/exit points
→ Multiple timeframe analysis for broader market context
Cerca negli script per "momentum"
Institutional MACD (Z-Score Edition) [VolumeVigilante]📈 Institutional MACD (Z-Score Edition) — Professional-Grade Momentum Signal
This is not your average MACD .
The Institutional MACD (Z-Score Edition) is a statistically enhanced momentum tool, purpose-built for serious traders and breakout hunters . By applying Z-Score normalization to the classic MACD structure, this indicator uncovers statistically significant momentum shifts , enabling cleaner reads on price extremes, trend continuation, and potential reversals.
💡 Why It Matters
The classic MACD is powerful — but raw momentum values can be noisy and relative , especially on volatile assets like BTC/USD . By transforming the MACD line, signal line, and histogram into Z-scores , we anchor these signals in statistical context . This makes the Institutional MACD:
✔️ Timeframe-agnostic and asset-normalized
✔️ Ideal for spotting true breakouts , not false flags
✔️ A reliable tool for detecting momentum divergence and exhaustion
🧪 Key Features
✅ Full Z-Score normalization (MACD, Signal, Histogram)
✅ Highlighted ±Z threshold bands for overbought/oversold zones
✅ Customizable histogram coloring for visual momentum shifts
✅ Built-in alerts for zero-crosses and Z-threshold breaks
✅ Clean overlay with optional display toggles
🔁 Strategy Tip: Mean Reversion Signals with Statistical Confidence
This indicator isn't just for spotting breakouts — it also shines as a mean reversion tool , thanks to its Z-Score normalization .
When the Z-Score histogram crosses beyond ±2, it marks a statistically significant deviation from the mean — often signaling that momentum is overstretched and the asset may be due for a pullback or reversal .
📌 How to use it:
Z > +2 → Price action is in overbought territory. Watch for exhaustion or short setups.
Z < -2 → Momentum is deeply oversold. Look for reversal confirmation or long opportunities.
These zones often precede snap-back moves , especially in range-bound or corrective markets .
🎯 Combine Z-Score extremes with:
Candlestick confirmation
Support/resistance zones
Volume or price divergence
Other mean reversion tools (e.g., RSI, Bollinger Bands)
Unlike the raw MACD, this version delivers statistical thresholds , not guesswork — helping traders make decisions rooted in probability, not emotion.
📢 Trade Smart. Trade Vigilantly.
Published by VolumeVigilante
RSI + MFI Momentum Mapper - CoffeeKillerRSI + MFI Momentum Mapper - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the RSI + MFI Momentum Mapper indicator, an innovative market analysis tool developed by CoffeeKiller that combines two powerful oscillators to create a comprehensive momentum visualization system.
🔔 **Warning: This Is Not a Standard RSI or MFI Indicator** 🔔 This indicator combines and normalizes RSI and MFI data to create a unified momentum representation with boundary detection and peak signaling features.
Core Concept: Combined Momentum Analysis
The foundation of this indicator lies in merging the strengths of two complementary oscillators - Relative Strength Index (RSI) and Money Flow Index (MFI) - to provide a more robust momentum signal that accounts for both price action and volume.
Directional Columns: Momentum Strength
- Positive Green Columns: Bullish momentum
- Negative Red Columns: Bearish momentum
- Color intensity varies based on momentum strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during a bullish phase
- Low Marker Line (Cyan): Tracks the lowest point reached during a bearish phase
- Creates visual boundaries showing momentum extremes
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important momentum peaks
- Helps identify potential reversal points and momentum exhaustion
Reference Lines:
- Zero Line (Gray): Divides bullish from bearish momentum
- High Line (+1): Upper threshold for extremely bullish conditions
- Low Line (-1): Lower threshold for extremely bearish conditions
Core Components
1. Oscillator Normalization
- RSI and MFI values centered around zero
- Values scaled to create consistent visualization
- Normalized range typically between -1 and +1
- Combination of indicators for signal reliability
2. Boundary Tracking System
- Automatic detection of highest values in bullish phases
- Automatic detection of lowest values in bearish phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Signal Smoothing
- Signal line calculation via SMA
- Helps filter noise and identify trends
- Provides confirmation of momentum direction
Main Features
Oscillator Settings
- Customizable RSI length for sensitivity control
- Customizable MFI length for sensitivity control
- Normalized display for consistent visualization
- Signal smoothing for clearer readings
Visual Elements
- Color-coded columns showing momentum direction and strength
- Dynamic marker lines for momentum boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
- Reference lines for momentum threshold levels
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for momentum strength
- Peak formation for potential reversals
- Color changes for momentum direction and acceleration
Customization Options
- RSI and MFI length parameters
- Marker line visibility and colors
- Peak marker color selection
- Peak background display options
Trading Applications
1. Trend Identification
- Directional line crossing above zero: bullish trend beginning
- Directional line crossing below zero: bearish trend beginning
- Column color: indicates momentum direction
- Column height: indicates momentum strength
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Directional line approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing momentum
3. Momentum Analysis
- Breaking above previous high boundary: accelerating bullish momentum
- Breaking below previous low boundary: accelerating bearish momentum
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Approaching +1/-1 lines: extreme momentum conditions
4. Market Structure Assessment
- Consecutive higher peaks: strengthening bullish structure
- Consecutive lower troughs: strengthening bearish structure
- Peak comparisons: relative strength of momentum phases
- Boundary line steps: market structure levels
Optimization Guide
1. Oscillator Settings
- RSI Length: Default 14 provides balanced signals
- Lower values (7-10): More responsive, potentially noisier
- Higher values (20-30): Smoother, fewer false signals
- MFI Length: Default 14 provides balanced signals
- Lower values: More responsive to volume changes
- Higher values: Less sensitive to short-term volume spikes
2. Visual Customization
- Marker Line Colors: Adjust for visibility on your chart
- Peak Marker Color: Default yellow provides good contrast
- Enable/disable background highlights based on preference
- Consider chart background when selecting colors
3. Signal Interpretation
- Stronger signals: When directional line approaches +1/-1
- Confirmation: When peaks form after extended momentum
- Early warnings: When color intensity changes before direction
- Trend strength: Distance between zero line and current reading
4. Reference Line Usage
- Zero line: Primary trend divider
- +1/-1 lines: Extreme momentum thresholds
- Marker lines: Dynamic support/resistance levels
- Distance from reference: Momentum strength measure
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm trend changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong momentum
- Use with price action for entry/exit precision
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Multiple timeframes: confirm signals across time horizons
- Match to your trading style and holding period
3. Market Context
- Strong bullish phase: positive columns breaking above marker line
- Strong bearish phase: negative columns breaking below marker line
- Columns approaching zero: potential trend change
- Columns approaching +1/-1: extreme conditions, potential reversal
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with other oscillators for divergence detection
- Combine with volume analysis for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when directional line breaks above previous high marker line
- Enter short when directional line breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in bullish phases for shorting opportunities
- Look for consecutive higher troughs in bearish phases for buying opportunities
- Use zero-line crosses as confirmation
3. Extreme Reading Strategy
- Look for directional line approaching +1/-1 lines
- Watch for color changes and peak formations
- Enter counter-trend positions after confirmed peaks
- Use tight stops due to extreme momentum conditions
4. Column Color Strategy
- Enter long when columns turn bright green (increasing momentum)
- Enter short when columns turn bright red (increasing momentum)
- Exit when color intensity fades (decreasing momentum)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Directional line crosses above zero line
- Green columns grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant momentum peaks
Bearish Market Scenario
- Directional line crosses below zero line
- Red columns grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant momentum troughs
Consolidation Scenario
- Directional line oscillates around zero line
- Column colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Directional values remain small
Understanding Market Dynamics Through RSI + MFI Momentum Mapper
At its core, this indicator provides a unique lens to visualize market momentum by combining two complementary oscillators:
1. Combined Strength: By averaging RSI (price-based) and MFI (volume-based), the indicator provides a more comprehensive view of market momentum that considers both price action and buying/selling pressure.
2. Normalized Scale: The indicator normalizes values around zero, making it easier to identify bullish vs bearish conditions and the relative strength of momentum in either direction.
3. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of momentum in both directions, helping to identify when markets are making new momentum extremes.
4. Exhaustion Signals: The peak detection system highlights moments where momentum has reached a local maximum or minimum, often precursors to reversals or consolidations.
Remember:
- Combine signals from directional line, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences
- Consider market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
Waldo Momentum Cloud Bollinger Bands (WMCBB)
Title: Waldo Momentum Cloud Bollinger Bands (WMCBB)
Description:
Introducing the "Waldo Momentum Cloud Bollinger Bands (WMCBB)," an innovative trading tool crafted for those who aim to deepen their market analysis by merging two dynamic technical indicators: Dynamic RSI Bollinger Bands and the Waldo Cloud.
What is this Indicator?
WMCBB integrates the volatility-based traditional Bollinger Bands with a momentum-sensitive approach through the Relative Strength Index (RSI). Here’s how it works:
Dynamic RSI Bollinger Bands: These bands dynamically adjust according to the RSI, which tracks the momentum of price movements. By scaling the RSI to align with price levels, we generate bands that not only reflect market volatility but also the underlying momentum, offering a refined view of overbought and oversold conditions.
Waldo Cloud: This feature adds a layer of traditional Bollinger Bands, visualized as a 'cloud' on your chart. It employs standard Bollinger Band methodology but enhances it with additional moving average layers to better define market trends.
The cloud's color changes dynamically based on various market conditions, providing visual signals for trend direction and potential trend reversals.
Why Combine These Indicators?
Combining Dynamic RSI Bollinger Bands with the Waldo Cloud in WMCBB aims to:
Enhance Trend Identification: The Waldo Cloud's color-coded system aids in recognizing the overarching market trend, while the Dynamic RSI Bands give insights into momentum changes within that trend, offering a comprehensive view.
Improve Volatility and Momentum Analysis: While traditional Bollinger Bands measure market volatility, integrating RSI adds a layer of momentum analysis, potentially leading to more accurate trading signals.
Visual Clarity: The unified color scheme for both sets of bands, which changes according to RSI levels, moving average crossovers, and price positioning, simplifies the process of gauging market sentiment at a glance.
Customization: Users have the option to toggle the visibility of moving averages (MA) through the settings, allowing for tailored analysis based on individual trading strategies.
Usage:
Utilize WMCBB to identify potential trend shifts by observing price interactions with the dynamic bands or changes in the Waldo Cloud's color.
Watch for divergences between price movements and RSI to forecast potential market reversals or continuations.
This combination shines in sideways markets where traditional indicators might fall short, as it provides additional context through RSI momentum analysis.
Settings:
Customize parameters for both the Dynamic RSI and Waldo Cloud Bollinger Bands, including the calculation source, standard deviation factors, and moving average lengths.
WMCBB is perfect for traders seeking to enhance their market analysis through the synergy of momentum and volatility, all while maintaining visual simplicity. Trade with greater insight using the Waldo Momentum Cloud Bollinger Bands!
75th-25th Percentile Momentum | QuantumResearchIntroducing QuantumResearch’s 75th-25th Percentile Momentum Indicator
The 75th-25th Percentile Momentum indicator is a cutting-edge tool that combines percentile rank analysis with ATR-based deviation to detect significant bullish and bearish momentum in the market. By analyzing price movements relative to the 75th and 25th percentiles of recent data, the indicator provides traders with clear and dynamic signals for long and short opportunities.
How It Works
Percentile Analysis:
The 75th and 25th percentiles are calculated over a user-defined lookback period, representing the upper and lower thresholds for price action.
ATR-Based Adjustment:
ATR (Average True Range) is used to account for market volatility, dynamically adjusting the thresholds with user-defined multipliers.
Signal Generation:
Long Signal: Triggered when the price exceeds the 75th percentile plus the ATR-based adjustment (default multiplier: 1.3).
Short Signal: Triggered when the price falls below the 25th percentile minus the ATR-based adjustment (default multiplier: 1.3).
Visual Representation
The indicator offers a clear and customizable visual interface:
Green Bars: Indicate a bullish trend, signaling a potential long opportunity when the price surpasses the adjusted 75th percentile.
Red Bars: Indicate a bearish trend, signaling a potential short opportunity when the price drops below the adjusted 25th percentile.
Additional visuals include:
A dynamically colored 54-period EMA line, representing trend direction:
Green Line: Indicates a bullish trend.
Red Line: Indicates a bearish trend.
A filled area between the EMA line and the midpoint (HL2), offering enhanced trend visibility.
Customization & Parameters
The 75th-25th Percentile Momentum indicator includes several adjustable parameters to suit different trading styles:
Source: Defines the input price (default: close).
Percentile Length: Default set to 25, determines the lookback period for percentile calculations.
ATR Length: Default set to 14, adjusts the sensitivity of volatility measurement.
Multiplier for 75th Percentile: Default set to 1.3, adjusts the threshold for long signals.
Multiplier for 25th Percentile: Default set to 1.3, adjusts the threshold for short signals.
Color Modes: Choose from eight visual themes to personalize the appearance of trend signals.
Trading Applications
This indicator is versatile and can be applied across various markets and strategies:
Momentum Trading: Highlights when price action demonstrates strong upward or downward momentum relative to recent percentiles.
Volatility-Adaptive Strategies: By incorporating ATR-based thresholds, the indicator adjusts dynamically to market conditions.
Reversal Detection: Identifies potential turning points when the price moves significantly beyond the 75th or 25th percentiles.
Final Note
QuantumResearch’s 75th-25th Percentile Momentum indicator is a powerful tool for traders looking to capture momentum and trend opportunities in the market.
Its combination of percentile analysis, volatility adjustment, and visual clarity offers a robust framework for making informed trading decisions. As with all indicators, it is recommended to backtest thoroughly and integrate this tool into a comprehensive trading strategy.
Squeeze Momentum Indicator [CHE] Squeeze Momentum Indicator
The Squeeze Momentum Indicator is an improved and simplified version of the classic Squeeze Momentum Indicator by LazyBear. It focuses on precise detection of squeeze phases without relying on Keltner Channels (KC) or complex momentum calculations. Instead, it emphasizes the dynamic analysis of Bollinger Band widths and their distance changes to provide clear and intuitive signals.
What is the Squeeze Momentum Indicator ?
This indicator helps you identify periods of low volatility (squeeze phases) when the market is often poised for significant moves. With its clear visualization and innovative methods, it enables traders to spot breakout opportunities early and trade strategically.
Differences from the Original LazyBear Indicator
1. Use of Bollinger Bands (BB):
- LazyBear Indicator combines Bollinger Bands with Keltner Channels. A squeeze is detected when the Bollinger Bands fall inside the Keltner Channels.
- CHE Indicator relies solely on Bollinger Bands and an additional analysis of their width (distance between the upper and lower bands). This makes the calculation more straightforward and reduces dependency on multiple indicator families.
2. Squeeze Detection:
- LazyBear: A squeeze is defined based on the relationship between Bollinger Bands and Keltner Channels. It has three states: “Squeeze On,” “Squeeze Off,” and “No Squeeze.”
- CHE: A squeeze is detected when the width of the Bollinger Bands falls below the lower "Distance Bollinger Bands." It only has two states: Squeeze Active and No Squeeze.
3. Momentum Calculation:
- LazyBear: Uses linear regression (LinReg) to calculate momentum and displays it as color-coded histograms.
- CHE: Does not include momentum calculations. The focus is entirely on volatility visualization and squeeze detection.
4. Visualization:
- LazyBear: Displays momentum histograms and horizontal lines to signal different states.
- CHE: Visualizes the width of the Bollinger Bands and their Distance Bollinger Bands as lines on the chart. The chart background turns green when a squeeze is detected, simplifying interpretation.
What Is Plotted?
1. Bollinger Band Width:
- A line representing the distance between the upper and lower Bollinger Bands, measuring market volatility.
2. Distance Bollinger Bands:
- Two additional lines (upper and lower Distance Bollinger Bands) based on the Bollinger Band width, defining thresholds for squeeze conditions.
3. Session-Specific Box:
- A dynamic box is drawn on the chart during a squeeze phase. The box marks the high and low of the market for the squeeze duration. It visually frames the range, helping traders monitor breakouts beyond these levels.
4. Max/Min Markers:
- The indicator dynamically updates and marks the maximum and minimum price levels during a squeeze. These levels can serve as breakout thresholds or critical reference points for price action.
5. Background Color:
- The chart background turns green when a squeeze is active (Bollinger Band width falls below the lower Distance Bollinger Bands). This highlights potential breakout conditions.
How to Use the CHE Indicator
1. Add the Indicator:
- Add the indicator to your chart and customize settings such as Bollinger Band length (`sqz_length`) and multiplier (`sqz_multiplier`) to fit your strategy.
2. Identify Squeeze Conditions:
- Watch for the green background, which signals a squeeze—indicating a period of low volatility where significant market moves often follow.
3. Monitor the Box and Max/Min Levels:
- During a squeeze, the box outlines the trading range, and the maximum and minimum levels are updated in real time. Use these as breakout triggers or support/resistance zones.
4. Session-Specific Analysis:
- The indicator can highlight squeezes during specific trading sessions (e.g., market open), allowing you to focus on key time frames.
5. Additional Confirmation:
- Combine the CHE Indicator with price action analysis or momentum tools to determine the direction of potential breakouts.
Why Use the Squeeze Momentum Indicator ?
- Simplicity: Clear visualization and reduced complexity by eliminating Keltner Channels and momentum calculations.
- Flexibility: Suitable for all markets—stocks, forex, crypto, and more.
- Enhanced Visualization: The box and max/min markers provide real-time visual cues for range-bound trading and breakout strategies.
- Efficiency: Focuses on what matters most—identifying volatility and squeeze phases.
With the Squeeze Momentum Indicator , you can take your trading strategy to the next level. Thanks to its clear design, dynamic range visualization, and innovative methods, you’ll recognize breakout opportunities earlier and trade with greater precision. Try it out and experience its user-friendliness and effectiveness for yourself!
Custom RSI & MACD Momentum Entry SignalsIndicator Explanation: Custom RSI & MACD Momentum Entry Signals
Introduction
The "Custom RSI & MACD Momentum Entry Signals" indicator combines the Relative Strength Index (RSI) and the Moving Average Convergence Divergence (MACD) to generate precise long and short entry signals. This indicator offers a powerful combination of overbought/oversold zones, momentum analysis, and RSI-EMA crossovers to assist traders in making better decisions.
How the Indicator Works
1. RSI Calculation and EMA
The RSI is calculated based on the closing price with an adjustable period (default: 14).
An Exponential Moving Average (EMA) of the RSI (default: 9) is plotted to identify RSI trend changes.
When the RSI crosses its EMA upwards, it signals a bullish impulse. Conversely, a downward cross indicates a bearish impulse.
2. MACD Calculation and Momentum Shifts
The MACD line is derived from the difference between a fast EMA (default: 12) and a slow EMA (default: 26).
The Signal line is the EMA of the MACD line (default: 9).
The MACD histogram represents the difference between the MACD line and the Signal line.
Momentum shifts are detected as follows:
Weakening Bearish: Histogram is negative but increasing (less bearish pressure).
Strengthening Bullish: Histogram is positive and rising.
Weakening Bullish: Histogram is positive but decreasing.
Strengthening Bearish: Histogram is negative and falling.
Signal Generation
Long Signals
A Long signal is triggered when all of the following conditions are met:
The RSI was previously below 30 (oversold condition).
MACD momentum shifts from "strengthening bearish" to "weakening bearish" or turns bullish.
The RSI crosses its EMA upwards.
A green upward arrow is displayed below the bar, and the background is lightly shaded green for additional visualization.
Short Signals
A Short signal is triggered when all of the following conditions are met:
The RSI was previously above 70 (overbought condition).
MACD momentum shifts from "strengthening bullish" to "weakening bullish" or turns bearish.
The RSI crosses its EMA downwards.
A red downward arrow is displayed above the bar, and the background is lightly shaded red for additional visualization.
Visual Elements
RSI and EMA:
The RSI is shown in purple.
The RSI EMA is shown in blue.
Horizontal lines at 30 (oversold) and 70 (overbought) provide additional context.
MACD:
The MACD line is displayed in blue.
The Signal line is displayed in orange.
The zero line is added for easier interpretation.
Signals:
Green arrows: Long signals.
Red arrows: Short signals.
Background color: Light green for long conditions, light red for short conditions.
Use Cases
This indicator is ideal for:
Trend Followers: Combining RSI and MACD allows traders to identify entry points during impulsive trend shifts.
Swing Traders: Long and short signals can be used at reversal points to capture short-term price movements.
Momentum Traders: By considering MACD momentum, the indicator provides additional confidence in signal generation.
Customizable Settings
The indicator provides flexible input options:
RSI Period (default: 14)
RSI EMA Period (default: 9)
MACD Parameters: Fast, slow, and signal EMAs can be adjusted.
Conclusion
The Custom RSI & MACD Momentum Entry Signals indicator is a powerful tool for traders looking to combine RSI and MACD to identify high-probability entry signals. With clear visualization and precise signal generation, traders can make decisions more efficiently and capitalize on market movements.
Relative Momentum StrengthThe Relative Momentum Strength (RMS) indicator is designed to help traders and investors identify tokens with the strongest momentum over two customizable timeframes. It calculates and plots the percentage price change over 30-day and 90-day periods (or user-defined periods) to evaluate a token's relative performance.
30-Day Momentum (Green Line): Short-term price momentum, highlighting recent trends and movements.
90-Day Momentum (Blue Line): Medium-term price momentum, providing insights into broader trends.
This tool is ideal for comparing multiple tokens or assets to identify those showing consistent strength or weakness. Use it to spot outperformers and potential reversals in a competitive universe of assets.
How to Use:
Apply this indicator to your TradingView chart for any token or asset.
Look for tokens with consistently high positive momentum for potential strength.
Use the plotted values to compare relative performance across your watchlist.
Customization:
Adjust the momentum periods to suit your trading strategy.
Overlay it with other indicators like RSI or volume for deeper analysis.
Dual Momentum StrategyThis Pine Script™ strategy implements the "Dual Momentum" approach developed by Gary Antonacci, as presented in his book Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk (McGraw Hill Professional, 2014). Dual momentum investing combines relative momentum and absolute momentum to maximize returns while minimizing risk. Relative momentum involves selecting the asset with the highest recent performance between two options (a risky asset and a safe asset), while absolute momentum considers whether the chosen asset has a positive return over a specified lookback period.
In this strategy:
Risky Asset (SPY): Represents a stock index fund, typically more volatile but with higher potential returns.
Safe Asset (TLT): Represents a bond index fund, which generally has lower volatility and acts as a hedge during market downturns.
Monthly Momentum Calculation: The momentum for each asset is calculated based on its price change over the last 12 months. Only assets with a positive momentum (absolute momentum) are considered for investment.
Decision Rules:
Invest in the risky asset if its momentum is positive and greater than that of the safe asset.
If the risky asset’s momentum is negative or lower than the safe asset's, the strategy shifts the allocation to the safe asset.
Scientific Reference
Antonacci's work on dual momentum investing has shown the strategy's ability to outperform traditional buy-and-hold methods while reducing downside risk. This approach has been reviewed and discussed in both academic and investment publications, highlighting its strong risk-adjusted returns (Antonacci, 2014).
Reference: Antonacci, G. (2014). Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk. McGraw Hill Professional.
Chande Momentum Oscillator StrategyThe Chande Momentum Oscillator (CMO) Trading Strategy is based on the momentum oscillator developed by Tushar Chande in 1994. The CMO measures the momentum of a security by calculating the difference between the sum of recent gains and losses over a defined period. The indicator offers a means to identify overbought and oversold conditions, making it suitable for developing mean-reversion trading strategies (Chande, 1997).
Strategy Overview:
Calculation of the Chande Momentum Oscillator (CMO):
The CMO formula considers both positive and negative price changes over a defined period (commonly set to 9 days) and computes the net momentum as a percentage.
The formula is as follows:
CMO=100×(Sum of Gains−Sum of Losses)(Sum of Gains+Sum of Losses)
CMO=100×(Sum of Gains+Sum of Losses)(Sum of Gains−Sum of Losses)
This approach distinguishes the CMO from other oscillators like the RSI by using both price gains and losses in the numerator, providing a more symmetrical measurement of momentum (Chande, 1997).
Entry Condition:
The strategy opens a long position when the CMO value falls below -50, signaling an oversold condition where the price may revert to the mean. Research in mean-reversion, such as by Poterba and Summers (1988), supports this approach, highlighting that prices often revert after sharp movements due to overreaction in the markets.
Exit Conditions:
The strategy closes the long position when:
The CMO rises above 50, indicating that the price may have become overbought and may not provide further upside potential.
Alternatively, the position is closed 5 days after the buy signal is triggered, regardless of the CMO value, to ensure a timely exit even if the momentum signal does not reach the predefined level.
This exit strategy aligns with the concept of time-based exits, reducing the risk of prolonged exposure to adverse price movements (Fama, 1970).
Scientific Basis and Rationale:
Momentum and Mean-Reversion:
The strategy leverages the well-known phenomenon of mean-reversion in financial markets. According to research by Jegadeesh and Titman (1993), prices tend to revert to their mean over short periods following strong movements, creating opportunities for traders to profit from temporary deviations.
The CMO captures this mean-reversion behavior by monitoring extreme price conditions. When the CMO reaches oversold levels (below -50), it signals potential buying opportunities, whereas crossing overbought levels (above 50) indicates conditions for selling.
Market Efficiency and Overreaction:
The strategy takes advantage of behavioral inefficiencies and overreactions, which are often the drivers behind sharp price movements (Shiller, 2003). By identifying these extreme conditions with the CMO, the strategy aims to capitalize on the market’s tendency to correct itself when price deviations become too large.
Optimization and Parameter Selection:
The 9-day period used for the CMO calculation is a widely accepted timeframe that balances responsiveness and noise reduction, making it suitable for capturing short-term price fluctuations. Studies in technical analysis suggest that oscillators optimized over such periods are effective in detecting reversals (Murphy, 1999).
Performance and Backtesting:
The strategy's effectiveness is confirmed through backtesting, which shows that using the CMO as a mean-reversion tool yields profitable opportunities. The use of time-based exits alongside momentum-based signals enhances the reliability of the strategy by ensuring that trades are closed even when the momentum signal alone does not materialize.
Conclusion:
The Chande Momentum Oscillator Trading Strategy combines the principles of momentum measurement and mean-reversion to identify and capitalize on short-term price fluctuations. By using a widely tested oscillator like the CMO and integrating a systematic exit approach, the strategy effectively addresses both entry and exit conditions, providing a robust method for trading in diverse market environments.
References:
Chande, T. S. (1997). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. John Wiley & Sons.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
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.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. New York Institute of Finance.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Shiller, R. J. (2003). From Efficient Markets Theory to Behavioral Finance. Journal of Economic Perspectives, 17(1), 83-104.
Multi-Asset Cross Timeframe Divergence Ind. (MACDI) // AlgoFyreThe Multi-Asset Cross Timeframe Divergence Indicator (MACDI) identifies divergences in momentum like RSI across multiple assets and timeframes. It visually highlights lagging correlated asset momentum divergences, helping traders spot inefficiencies and potential trade opportunities in the following asset.
🔶 KEY FEATURES
🔸Average Momentum Trendline for Each Timeframe
The Average Momentum Trendline feature calculates the average momentum of multiple assets over specified timeframes. It uses smoothed values to determine the momentum trend for each timeframe on the average aggregated momentum of both assets. This trendline helps traders identify the overall direction of the market momentum, providing a clearer picture of potential price movements.
🔸Real-time Divergence Indication and Alert Table
The Real-time Divergence Indications and Alert Table feature visualizes detected divergences between the momentum values of the two assets across different timeframes. It identifies both bullish and bearish divergences, signaling lagging reversals in the the following asset and potential trading opportunities. When a divergence is detected, the system generates real-time visual indications on the chart and in an overview table for traders to act promptly. The alert table provides a comprehensive overview of all detected divergences, making it easier for traders to monitor and respond to market changes.
🔸Color and Size Based Labels on Price Chart based on Divergence Type
The Color and Size Based Labels feature visually represents divergences directly on the price chart. Bullish and bearish divergences are marked with distinct colors and sizes, making them easily identifiable at a glance. Larger labels indicate higher timeframes and thus generally more significance.
🔶 INSTRUCTION GUIDELINES
🔸Identify Divergence Clusters
The more divergences align, the higher the probability of a potential trend reversal in the asset. When multiple multi-timeframe divergences occur in both lower and higher timeframes within a local cluster, the probability of a reversal increases. This is valid for both for bullish and bearish divergences.
🔸Spot Low Probability Divergences
To further increase the probability, analyze the current state of the average momentum trendline. For a bullish reversal, a relatively low level of the average momentum trendline is preferred, whereas for a bearish reversal, a relatively high level is preferred.
🔶 INDIVIDUAL CONFIGURATION
🔸Leading Asset
This input allows the user to select the leading asset for the divergence analysis.
🔸Following Asset
This input allows the user to select the following asset for the divergence analysis.
🔸Higher Timeframe
This input sets the higher timeframe for the analysis.
🔸Lower Timeframe
This input sets the lower timeframe for the analysis.
🔸Show RSI Divergence
This input enables or disables the display of RSI divergence signals.
🔸RSI Length
This input sets the length of the RSI calculation.
🔸RSI Source
This input sets the source data for the RSI calculation (e.g., close price).
🔸RSI Smoothing Length
This input sets the length of the smoothing applied to the RSI values.
🔸Smoothing Method
This input sets the method used for smoothing the RSI values.
🔶 CONCLUSION
The Multi-Asset Cross Timeframe Divergence Indicator (MACDI) is a powerful tool for identifying momentum divergences across multiple assets and timeframes. Its visual cues and customizable table make it easy to use and interpret, providing valuable insights for trading decisions.
Dynamic Bollinger Bands with Momentum and Volume (DBBMV)Overview
The Dynamic Bollinger Bands with Momentum and Volume (DBBMV) indicator enhances the traditional Bollinger Bands by dynamically adjusting their width and position based on momentum and volume. This provides a more responsive and context-aware indication of price volatility and potential reversals.
Key Features
Momentum Adjusted Bands: Adjusts the bands' width based on the momentum indicator, reflecting the rate of change in price.
Volume Weighted Bands: Further adjusts the bands based on trading volume to reflect market activity and price volatility.
Signal Alerts: Provides buy and sell signals based on price action relative to the dynamic bands, helping traders identify entry and exit points.
Customizable Parameters: Allows users to adjust the lookback period, momentum sensitivity, and volume weighting for personalized analysis.
How It Works
The DBBMV indicator starts with the traditional Bollinger Bands, which are calculated using a moving average and standard deviation of the selected price source. The width of these bands is then adjusted based on the momentum of the price, making them more sensitive to price changes. Further adjustments are made based on trading volume, which ensures that the bands accurately reflect current market conditions. This results in a set of dynamic Bollinger Bands that provide more nuanced insights into price volatility and potential reversals.
Usage Instructions
Identify Volatile Periods: Use the dynamically adjusted bands to identify periods of high and low volatility in the market.
Spot Reversals: Look for buy signals when the price crosses above the lower band and sell signals when the price crosses below the upper band.
Adjust Sensitivity: Customize the lookback period, momentum sensitivity, and volume weighting to fine-tune the indicator to your specific trading strategy and market conditions.
Enhance Analysis: Combine the DBBMV indicator with other technical analysis tools for a more comprehensive market analysis.
Volume Confirmation: Use the volume-weighted adjustments to confirm the strength of price movements and potential breakouts.
The Dynamic Bollinger Bands with Momentum and Volume (DBBMV) indicator provides traders with a powerful tool to understand market dynamics better and make informed trading decisions based on adjusted volatility and market activity.
Squeeze Momentum Oscillator [AlgoAlpha]🎉📈 Introducing the Squeeze Momentum Oscillator by AlgoAlpha 📉🎊
Unlock the secrets of market dynamics with our innovative Squeeze Momentum Oscillator! Crafted for those who seek to stay ahead in the fast-paced trading environment, this tool amalgamates critical market momentum and volatility indicators to offer a multifaceted view of potential market movements. Here's why it's an indispensable part of your trading toolkit:
Key Features:
🌈 Customizable Color Schemes: Easily distinguish between bullish (green) and bearish (red) momentum phases for intuitive analysis.
🔧 Extensive Input Settings: Tailor the oscillator lengths for both Underlying and Swing Momentum to match your unique trading approach.
📊 Dedicated Squeeze Settings: Leverage precise volatility insights to identify market squeeze scenarios, signaling potential breakouts or consolidations.
🔍 Advanced Divergence Detection: Utilize sophisticated algorithms to detect and visualize both bullish and bearish divergences, pointing towards possible market reversals.
📈 Hyper Squeeze Detection: Stay alert to high-momentum market movements with our hyper squeeze feature, designed to extremely suppressed market volatility.
🔔 Comprehensive Alert System: Never miss a trading opportunity with alerts for momentum changes, squeeze conditions, and more.
Quick Guide to Using the Squeeze Momentum Oscillator:
🛠 Add the Indicator: Add the indicator to your favourites. Adjust the oscillator and squeeze settings to suit your trading preferences.
📊 Market Analysis: Keep an eye on the squeeze value and momentum z-score for insights into volatility and market direction. Hyper Squeeze signals are your cue for high momentum trading opportunities.
🔔 Alerts: Configure alerts for shifts in underlying and swing momentum, as well as entry and exit points for squeeze conditions, to capture market moves efficiently.
How It Works:
The Squeeze Momentum Oscillator by AlgoAlpha synergistically combines the principles of momentum tracking and market squeeze detection. By integrating the core logic of the Squeeze & Release indicator, it calculates the Squeeze Value (SV) through a comparison of the Exponential Moving Average (EMA) of the Average True Range (ATR) against the high-low price EMA. This SV is further analyzed alongside its EMA to pinpoint squeeze conditions, indicative of potential market breakouts or consolidations. In addition to this, the oscillator employs Hyper Squeeze Detection for identifying extremely low volatility. The momentum aspect of the oscillator evaluates the price movement relative to EMAs of significant highs and lows, refining these observations with a z-score normalization for short-term momentum insights. Moreover, the incorporation of divergence detection aids in identifying potential reversals, making this oscillator a comprehensive tool for traders looking to harness the power of volatility and momentum in their market analysis. The combination of the Squeeze & Release and the Momentum Oscillator allows traders to time their trades with more precision by entering when the market is in a squeeze and front running the volatility of a major move.
Elevate your trading strategy with the Squeeze Momentum Oscillator by AlgoAlpha and gain a competitive edge in deciphering market dynamics! 🌟💼 Happy trading!
Weighted Momentum Forecast
The Weighted Momentum Forecast (EWMF) is a predictive indicator designed to forecast the potential direction and magnitude of the next candle's close. It combines the principles of momentum, trend confirmation, and volatility adjustment to make its predictions.
**Components:**
1. **Rate of Change (ROC)**: Measures the momentum of the market.
2. **Average True Range (ATR)**: Represents the market's recent volatility.
3. **Moving Average Convergence Divergence (MACD)**: Used to confirm the momentum's direction.
4. **Trend Moving Average**: A longer-term moving average to confirm the general trend.
5. **Bollinger Bands**: Adjusts the forecast to account for extreme predictions.
**Logic:**
1. **Momentum Bias**: The crossover and crossunder of the MACD line and its signal line are used to determine the momentum's bias. A crossover indicates a bullish bias, while a crossunder indicates a bearish bias.
2. **Trend Confirmation**: If the current close is above the trend moving average, the indicator has a bullish bias, and vice versa.
3. **Forecast Calculation**: The forecast for the next candle's close is calculated based on the current close, the rate of change, the momentum's bias, and the trend's bias. This value is then adjusted for volatility using the ATR.
4. **Volatility Adjustment**: If the forecasted value is beyond the Bollinger Bands, it's adjusted to be within the bands to account for extreme predictions.
**Usage:**
The EWMF plots a purple line representing the forecasted value of the next candle's close. This forecasted value provides traders with a visual representation of where the price might head in the next period, based on recent momentum, trend, and volatility.
**Note**: This is a heuristic approach and is not guaranteed to be accurate. It's essential to use this indicator in conjunction with other tools, backtest on historical data, and use proper risk management techniques. Always be aware of the inherent risks involved in trading and never risk more than you're willing to lose.
The Swinging Momentum IndicatorThe Swinging Momentum indicator is a custom trading indicator that looks at price momentum to identify potential buy and sell signals. It uses the rate of change in closing price over the last few bars to determine if momentum is increasing or decreasing. It also looks at the relationship of the close price to recent highs and lows, volume, and short term moving averages to confirm the strength of the momentum signal.
The indicator has two main components - identifying initial buy and sell signals, and then rating the strength of those signals. For buys, it looks for an increase in closing price momentum along with a close above recent highs and highest volume. For sells, it looks for a decrease in momentum and close below recent lows and highest volume. This identifies the initial signal without too many false signals.
It then looks at multiple factors to grade the strength of the signal, on a scale of 0 to 3. For buys it looks at how the close compares to the open, high and low of the last 4 bars, if the current low is above the recent low, and if there are more gaining days than losing days recently. For sells it looks at the close versus the open/high/low, if the current high is below the recent high, and if there are more losing than gaining days.
Each condition met adds 1 point to the strength rating. A rating above 2 is considered a strong momentum signal. This filters out weaker signals and reduces whipsaws.
The end result is plotted on the chart. Buy signals are triangles pointing up below the bars, sells are triangles pointing down above the bars. The colors help visualize the strength - strong signals are green for buys and red for sells, while weaker signals are yellow.
Trading with the Swinging Momentum indicator is straightforward. Strong buy signals identify upside momentum, so traders would look to enter long positions on a retest of the buy signal bar high. Strong sell signals identify downside momentum, so short positions can be entered on a retest of the bar low. Stops are placed beyond recent swing points in the opposite direction of the trade.
Since momentum can quickly change, risk management is key. Traders should look for other confirming indicators to strengthen the probability of a momentum trade working out. Good additional indicators to use with momentum include volume, trends, support/resistance and volatility measures.
The advantage of the Swinging Momentum indicator is that isolating the strongest momentum moves helps traders focus on higher probability trade setups. Monitoring both the initial signal and the strength rating gives an added level of confidence compared to standard momentum indicators. This custom indicator combines multiple momentum strategies into one, allowing traders to quickly identify and evaluate momentum opportunities on the chart.
Used appropriately with sound risk management, the Swinging Momentum indicator can be a valuable addition to a trading system. It visualizes both the direction and strength of momentum, key factors when trading trends and breakouts. While no indicator is perfect, understanding and utilizing momentum is a key concept for traders to master. This indicator provides a graphical representation to improve the way momentum is incorporated into trading decisions.
RSI Momentum TrendThe "RSI Momentum Trend" indicator is a valuable tool for traders seeking to identify momentum trends.
By utilizing the Relative Strength Index (RSI) and customizable momentum thresholds, this indicator helps traders spot potential bullish and bearish signals.
you can adjust input parameters such as the RSI period, positive and negative momentum thresholds, and visual settings to align with their trading strategies.
The indicator calculates the RSI and evaluates two momentum conditions: positive and negative.
The positive condition considers the previous RSI value, current RSI value, and positive change in the 5-period exponential moving average (EMA) of the closing price.
The negative condition looks at the current RSI value and negative change in the 5-period EMA.
Once a momentum condition is met, the indicator visually represents the signal on the chart.
The "RSI Momentum Trend" indicator provides you with a quick and effective way to identify momentum trends using RSI calculations.
By incorporating visual cues and customizable parameters, it assists traders in making informed decisions about potential market movements.
Trailing Stop with RSI - Momentum-Based StrategyTrailing Stop with RSI - Momentum-Based Strategy
Description:
The Trailing Stop with RSI strategy combines momentum analysis and trailing stop functionality to help traders identify potential entry and exit points in their trading decisions. This strategy is suitable for various markets and timeframes.
Key Features:
Momentum Analysis: The strategy incorporates momentum indicators to identify potential buying and selling opportunities based on momentum shifts in the price.
Trailing Stop Functionality: The strategy utilizes a trailing stop to protect profits and dynamically adjust the stop loss level as the trade moves in the desired direction.
RSI Confirmation: The Relative Strength Index (RSI) is included to provide additional confirmation for trade entries by considering overbought and oversold conditions.
How to Use:
Entry Conditions: Long positions are triggered when positive momentum is detected, and the RSI confirms an oversold condition. Short positions are triggered when negative momentum is detected, and the RSI confirms an overbought condition.
Trailing Stop Activation: Once a position is opened, the trailing stop is activated when the specified profit level (as a percentage) is reached.
Trailing Stop Level: The trailing stop maintains a stop loss level at a specified distance (as a percentage) from the highest profit achieved since opening the position.
Exit Conditions: The trailing stop will trigger an exit and close all positions when the trailing stop level is breached.
Markets and Conditions:
This strategy can be applied to various markets, including stocks, forex, cryptocurrencies, and commodities. It can be used in trending and ranging market conditions, making it versatile for different market environments.
Important Considerations:
Adjust Parameters: Traders can modify the length of the momentum and RSI indicators to suit their preferred timeframe and trading style.
Risk Management: It is recommended to consider appropriate position sizing, risk-to-reward ratios, and overall risk management practices when using this strategy.
Backtesting and Optimization: Traders are encouraged to backtest the strategy on historical data and optimize the parameters to find the best settings for their chosen market and timeframe.
By incorporating momentum analysis, trailing stop functionality, and RSI confirmation, this strategy aims to provide traders with a systematic approach to capturing profitable trades while managing risk effectively.
Strategy Myth-Busting #11 - TrendMagic+SqzMom+CDV - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our 11th one is an automated version of the "Magic Trading Strategy : Most Profitable Indicator : 1 Minute Scalping Strategy Crypto" strategy from "Fx MENTOR US" who doesn't make any official claims but given the indicators he was using, it looked like on the surface that this might actually work. The strategy author uses this on the 1 minute and 3 minute timeframes on mostly FOREX and Heiken Ashi candles but as the title of his strategy indicates is designed for Crypto. So who knows..
To backtest this accurately and get a better picture we resolved the Heiken Ashi bars to standard candlesticks . Even so, I was unable to sustain any consistency in my results on either the 1 or 3 min time frames and both FOREX and Crypto. 10000% Busted.
This strategy uses a combination of 3 open-source public indicators:
Trend Magic by KivancOzbilgic
Squeeze Momentum by LazyBear
Cumulative Delta Volume by LonesomeTheBlue
Trend Magic consists of two main indicators to validate momentum and volatility. It uses an ATR like a trailing Stop to determine the overarching momentum and CCI as a means to validate volatility. Together these are used as the primary indicator in this strategy. When the CCI is above 0 this is confirmation of a volatility event is occurring with affirmation based upon current momentum (ATR).
The CCI volatility indicator gets confirmation by the the Cumulative Delta Volume indicator which calculates the difference between buying and selling pressure. Volume Delta is calculated by taking the difference of the volume that traded at the offer price and the volume that traded at the bid price. The more volume that is traded at the bid price, the more likely there is momentum in the market.
And lastly the Squeeze Momentum indicator which uses a combination of Bollinger Bands, Keltner Channels and Momentum are used to again confirm momentum and volatility. During periods of low volatility, Bollinger bands narrow and trade inside Keltner channels. They can only contract so much before it can’t contain the energy it’s been building. When the Bollinger bands come back out, it explodes higher. When we see the histogram bar exploding into green above 0 that is a clear confirmation of increased momentum and volatile. The opposite (red) below 0 is true when there are low periods. This indicator is used as a means to really determine when there is premium selling plays going on leading to big directional movements again confirming the positive or negative momentum and volatility direction.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Trading Rules
1 - 3 min candles
FOREX or Crypto
Stop loss at swing high/low | 1.5 risk/ratio
Long Condition
Trend Magic line is Blue ( CCI is above 0) and above the current close on the bar
Squeeze Momentum's histogram bar is green/lime
Cumulative Delta Volume line is green
Short Condition
Trend Magic line is Red ( CCI is below 0) and below the current close on the bar
Squeeze Momentum's histogram bar is red/maroon
Cumulative Delta Volume line is peach
Reverse Stochastic Momentum Index On ChartIntroducing the Reverse Stochastic Momentum Index "On Chart" version
According to Investopedia :
“The Stochastic Momentum Index (SMI) is a more refined version of the stochastic oscillator, employing a wider range of values and having a higher sensitivity to closing prices.”
The SMI is considered a refinement of the stochastic oscillator developed by William Blau and introduced in 1993 in an attempt to provide a more reliable indicator, less subject to false swings.
It calculates the distance of the current closing price as it relates to the median of the high/low range of price.
The SMI has a normal range of values between +100 and -100.
When the present closing price is higher than the median, or midpoint value of the high/low range, the resulting value is positive.
When the current closing price is lower than that of the midpoint of the high/low range, the SMI has a negative value.
Here I have reverse engineered the SMI formula to derive 2 functions.
One function calculates the chart price at which the SMI will reach a particular SMI scale value.
The second function calculates the chart price at which the SMI will crossover its signal line.
I have employed those functions here to give the "crossover" price levels for :
Upper alert level ( default 40, color : aqua blue )
Mid-Line ( default value 0, color : white )
Lower alert level ( default -40, color : purple )
Signal line ( default 13, colors : bright red & lime green )
And also to give the SMI eq price ( colors : red & green )
The midline, upper and lower alert levels return the closing price which would make SMI equal to their respective values
The user can infer from this that.....
Closing above these prices will cause the Stochastic Momentum Index to cross above the associated levels
Closing below these prices will cause the Stochastic Momentum Index to cross below the associated levels
Signal line returns the closing price where Stochastic Momentum Index is equal to its signal line
The user can infer from this that.....
Closing above this price will cause the Stochastic Momentum Index to cross above the signal line
Closing below this price will cause the Stochastic Momentum Index to cross below the signal line
SMI eq price returns the closing price which would make the SMI equal to its previous value
The user can infer from this that.....
Closing above this price will cause the Stochastic Momentum Index to increase
Closing below this price will cause the Stochastic Momentum Index to decrease
Note : all returned prices have a returned value filter to replace any values below zero with zero to help prevent auto focus issues.
These levels are displayed as plotted lines on the chart and also as an optional infobox with choice of displayed info.
This allows the user to see directly on the chart the interplay between the various crossover levels and price action and to precisely plan entries, exits and stops for their SMI based trades.
Traditionally traders and analysts will consider:
Positives values above 40 indicate a bullish trend
Negative values below -40 indicate a bearish trend .
Common traditional ways to derive signals from the SMI :
When the SMI crosses below -40 and then moves back above it, a buy signal is generated.
When the SMI crosses above +40 and then moves back below it, a sell signal is generated.
When the SMI line crosses above the signal line. A signal to buy is generated
When the SMI line crosses below the signal line signal to sell is generated.
When the SMI crosses above the zeroline, signal line and the SMI eq level many interpret that as a full bullish bias signal and take trades only in that direction, vice versa for bearish bias.
Traders also look for divergences between the SMI and price action.
The SMI is often used in conjunction with the Chande Momentum Oscillator or R squared indicator to determine overall market trendiness where the SMI is used to determine the direction of the trend, and also with volume indicators to show if the momentum carries significant selling or buying pressure.
CT Reverse Chande Momentum OscillatorIntroducing the Caretakers Reverse Chande Momentum Oscillator.
The Chande momentum oscillator is a technical momentum indicator which calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
It is used to gauge “pure momentum”.
It bears similarities to other momentum indicators such as the Stochastic, Rate of Change and the Relative Strength Index, but other unique features render it a handy tool in the traders handset.
The CMO was developed by Tushar Chande.
The author introduced the indicator in his 1994 book “The New Technical Trader “.
The CMO has a normal range of values between +100 and -100.
I have reverse engineered the CMO formula to derive a dual purpose function.
The function can calculate the chart price at which the CMO will reach a particular CMO scale value.
The function can also calculate the chart price at which the CMO will equal its previous value.
I have employed this function here to give the price level where the CMO will equal :
Upper alert level ( default 50 )
Zero-Line
Lower alert level ( default -50 )
Previous CMO value
These crossover levels are displayed via an optional infobox with choice of user selected info.
The advantage of knowing the exact prices that this will happen should give the user an additional edge and precision in risk management.
Traditionally traders and analysts will consider:
Positives values above 50 indicate an “overbought” condition
Negative values below -50 indicate an “oversold” condition
Common traditional ways to derive signals from the CMO :
When the CMO crosses above the zeroline, a buy signal is generated.
When the CMO crosses below the zeroline, a sell signal is generated.
When the SMI crosses below -50 and then moves back above it, a buy signal is generated.
When the SMI crosses above +50 and then moves back below it, a sell signal is generated.
Traditionally, traders also look for divergences between the CMO and price action.
Chande Momentum oscillating in a narrower band around the zero line, with no penetration of the Overbought and Oversold levels indicates a ranging market.
This should not be confused with Chande Momentum oscillating between either the Overbought and the zero line, or the Oversold level and the zero line, which indicates a strong up, or down-trend.
It is traditionally considered that the strongest trend signals are from failed swing patterns.
It measures momentum on both up and down days and does not smooth results, triggering more frequent oversold and overbought penetrations.
The CMO is often used to determine overall market trendiness in conjunction with the SMI where the SMI is used to determine the direction of the trend, and also with volume indicators to show if the momentum carries significant selling or buying pressure.
Price Action and 3 EMAs Momentum plus Sessions FilterThis indicator plots on the chart the parameters and signals of the Price Action and 3 EMAs Momentum plus Sessions Filter Algorithmic Strategy. The strategy trades based on time-series (absolute) and relative momentum of price close, highs, lows and 3 EMAs.
I am still learning PS and therefore I have only been able to write the indicator up to the Signal generation. I plan to expand the indicator to Entry Signals as well as the full Strategy.
The strategy works best on EURUSD in the 15 minutes TF during London and New York sessions with 1 to 1 TP and SL of 30 pips with lots resulting in 3% risk of the account per trade. I have already written the full strategy in another language and platform and back tested it for ten years and it was profitable for 7 of the 10 years with average profit of 15% p.a which can be easily increased by increasing risk per trade. I have been trading it live in that platform for over two years and it is profitable.
Contributions from experienced PS coders in completing the Indicator as well as writing the Strategy and back testing it on Trading View will be appreciated.
STRATEGY AND INDICATOR PARAMETERS
Three periods of 12, 48 and 96 in the 15 min TF which are equivalent to 3, 12 and 24 hours i.e (15 min * period / 60 min) are the foundational inputs for all the parameters of the PA & 3 EMAs Momentum + SF Algo Strategy and its Indicator.
3 EMAs momentum parameters and conditions
• FastEMA = ema of 12 periods
• MedEMA = ema of 48 periods
• SlowEMA = ema of 96 periods
• All the EMAs analyse price close for up to 96 (15 min periods) equivalent to 24 hours
• There’s Upward EMA momentum if price close > FastEMA and FastEMA > MedEMA and MedEMA > SlowEMA
• There’s Downward EMA momentum if price close < FastEMA and FastEMA < MedEMA and MedEMA < SlowEMA
PA momentum parameters and conditions
• HH = Highest High of 48 periods from 1st closed bar before current bar
• LL = Lowest Low of 48 periods from 1st closed bar from current bar
• Previous HH = Highest High of 84 periods from 12th closed bar before current bar
• Previous LL = Lowest Low of 84 periods from 12th closed bar before current bar
• All the HH & LL and prevHH & prevLL are within the 96 periods from the 1st closed bar before current bar and therefore indicative of momentum during the past 24 hours
• There’s Upward PA momentum if price close > HH and HH > prevHH and LL > prevLL
• There’s Downward PA momentum if price close < LL and LL < prevLL and HH < prevHH
Signal conditions and Status (BuySignal, SellSignal or Neutral)
• The strategy generates Buy or Sell Signals if both 3 EMAs and PA momentum conditions are met for each direction and these occur during the London and New York sessions
• BuySignal if price close > FastEMA and FastEMA > MedEMA and MedEMA > SlowEMA and price close > HH and HH > prevHH and LL > prevLL and timeinrange (LDN&NY) else Neutral
• SellSignal if price close < FastEMA and FastEMA < MedEMA and MedEMA < SlowEMA and price close < LL and LL < prevLL and HH < prevHH and timeinrange (LDN&NY) else Neutral
Entry conditions and Status (EnterBuy, EnterSell or Neutral)(NOT CODED YET)
• ENTRY IS NOT AT THE SIGNAL BAR but at the current bar tick price retracement to FastEMA after the signal
• EnterBuy if current bar tick price <= FastEMA and current bar tick price > prevHH at the time of the Buy Signal
• EnterSell if current bar tick price >= FastEMA and current bar tick price > prevLL at the time of the Sell Signal
Linear Momentum and Performance IndicatorsThis a porting to Trading View of the 12 new indicators introduced in IFTA Journal (January Edition) by Akram El Sherbini, MFTA, CFTe, CETA.
Indicators are available in "Linear Momentum and Performance Indicators" at page four.
IFTA Journal is available below:
ifta.org
Indicators implemented herein:
Linear Force Index: The linear force index LFI measures the force of buyers and sellers during rallies and declines, respectively. It combines two important pieces of market information—the price acceleration
and volumes.
Pressure Index: The pressure index PRI measures the buying and selling pressure over a certain range within a time interval by moving around its zero line. The index indicates a rise in buying pressure when it crosses above the zero line and a rise in selling pressure
when it crosses below the zero line level. The buying and selling force moves the last price during the session to form a range with low and high boundaries.
Strength Index Index: The strength index SI is a leading indicator to the pressure index. It measures the ability of buyers to resist sellers and vice versa. SI of today is the ratio of the latest pressure index value to the strain of today.
Power Index: It measures the buying and selling power within a time interval by moving around its zero line.
Intensity Index: The intensity index II measures the buying and selling intensity within a time interval by moving around its zero line.
Dynamic Strength Index: The sole purpose of the dynamic strength index DSI and the integral dynamic strength index IDSI is to lead their intensity indicator peers.
Integral Force Index
Integral Pressure Index
Integral Strength Index
Integral Power Index
Integral Intensity Index
Integral Dynamic Strength Index
The following example shows a trade following the signal while several indicators are crossing the zero line:
Integral performance indicators have a fewer number of trades than the performance indicators. This result is normal, as the integral indicators are less sensitive than their peers. Moreover, the power, intensity, and dynamic strength are less sensitive than the force, pressure, and strength indicators. The same applies for their integrals. Therefore, the integrals of power, intensity, and dynamic strength indicators are more inclined to be medium-term indicators.
As the paper is suggesting "the linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Technical indicators are using biased mathematical implementations. For example Momentum Index is in reality a velocity indicator, Force index a Momentum indicator and so on. From a Physical perspective correct momentum, force, velocity etc. needs to be corrected and re-categorized.
The author also gives important insights in how these indicators can be used "simultaneously to identify price turning points and filter irrelevant divergences."
"This paper will attempt to adjust the price momentum and force concepts introduced by Welles Wilder and Alexander Elder, respectively. By introducing the concept of linear momentum, new indicators will emerge to dissect the market performance into six main elements: market’s force, pressure, strength, power, intensity, and dynamic strength. This will lead to a deeper insight about market action. The leading performance indicators can be used simultaneously to identify price turning points and filter irrelevant divergences. The linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Suggestions and feedbacks are welcome
Hope you enjoy this,
CryptoStatistical
Linear Momentum and Performance Indicators (IFTA Jan 2019)This a porting to Trading View of the 12 new indicators introduced in IFTA Journal (January Edition) by Akram El Sherbini, MFTA, CFTe, CETA.
Indicators are available in "Linear Momentum and Performance Indicators" at page four.
IFTA Journal is available below:
ifta.org
Indicators implemented herein:
Linear Force Index: The linear force index LFI measures the force of buyers and sellers during rallies and declines, respectively. It combines two important pieces of market information—the price acceleration
and volumes.
Pressure Index: The pressure index PRI measures the buying and selling pressure over a certain range within a time interval by moving around its zero line. The index indicates a rise in buying pressure when it crosses above the zero line and a rise in selling pressure
when it crosses below the zero line level. The buying and selling force moves the last price during the session to form a range with low and high boundaries.
Strength Index Index : The strength index SI is a leading indicator to the pressure index. It measures the ability of buyers to resist sellers and vice versa. SI of today is the ratio of the latest pressure index value to the strain of today.
Power Index : It measures the buying and selling power within a time interval by moving around its zero line.
Intensity Index : The intensity index II measures the buying and selling intensity within a time interval by moving around its zero line.
Dynamic Strength Index : The sole purpose of the dynamic strength index DSI and the integral dynamic strength index IDSI is to lead their intensity indicator peers.
Integral Force Index
Integral Pressure Index
Integral Strength Index
Integral Power Index
Integral Intensity Index
Integral Dynamic Strength Index
The following example shows a trade following the signal while several indicators are crossing the zero line:
Integral performance indicators have a fewer number of trades than the performance indicators. This result is normal, as the integral indicators are less sensitive than their peers. Moreover, the power, intensity, and dynamic strength are less sensitive than the force, pressure, and strength indicators. The same applies for their integrals. Therefore, the integrals of power, intensity, and dynamic strength indicators are more inclined to be medium-term indicators.
As the paper is suggesting "the linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Technical indicators are using biased mathematical implementations. For example Momentum Index is in reality a velocity indicator, Force index a Momentum indicator and so on. From a Physical perspective correct momentum, force, velocity etc. needs to be corrected and re-categorized.
The author also gives important insights in how these indicators can be used "simultaneously to identify price turning points and filter irrelevant divergences."
"This paper will attempt to adjust the price momentum and force concepts introduced by Welles Wilder and Alexander Elder, respectively. By introducing the concept of linear momentum, new indicators will emerge to dissect the market performance into six main elements: market’s force, pressure, strength, power, intensity, and dynamic strength. This will lead to a deeper insight about market action. The leading performance indicators can be used simultaneously to identify price turning points and filter irrelevant divergences. The linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Suggestions and feedback are welcome
Hope you enjoy this,
CryptoStatistical
