Relative Performance SuiteOverview
The Relative Performance Suite (RPS) is a versatile and comprehensive indicator designed to evaluate an asset's performance relative to a benchmark. By offering multiple methods to measure performance, including Relative Performance, Alpha, and Price Ratio, this tool helps traders and investors assess asset strength, resilience, and overall behavior in different market conditions.
Key Features:
✅ Multiple Performance Measures:
Choose from various relative performance calculations, including:
Relative Performance:
Measures how much an asset has outperformed or underperformed its benchmark over a given period.
Relative Performance (Proportional):
A proportional version of relative performance,
factoring in scaling effects.
Relative Performance (MA Based):
Uses moving averages to smooth performance fluctuations.
Alpha:
A measure of an asset’s performance relative to what would be expected based on its beta and the benchmark’s return. It represents the excess return above the risk-free rate after adjusting for market risk.
Price Ratio:
Compares asset prices directly to determine relative value over time.
✅ Customizable Moving Averages:
Apply different moving average types (SMA, EMA, SMMA, WMA, VWMA) to smooth price inputs and refine calculations.
✅ Beta Calculation:
Includes a Beta measure used in Alpha calculation, which users can toggle the visibility of helping users understand an asset's sensitivity to market movements.
✅ Risk-Free Rate Adjustment:
Incorporate risk-free rates (e.g., US Treasury yields, Fed Funds Rate) for a more accurate calculation of Alpha.
✅ Logarithmic Returns Option:
Users can switch between standard returns and log returns for more refined performance analysis.
✅ Dynamic Color Coding:
Identify outperformance or underperformance with intuitive color coding.
Option to color bars based on relative strength, making chart analysis easier.
✅ Customizable Tables for Data Display:
Overview table summarizing key metrics.
Explanation table offering insights into how values are derived.
How to Use:
Select a Benchmark: Choose a comparison symbol (e.g., TOTAL or SPX ).
Pick a Performance Metric: Use different modes to analyze relative performance.
Customize Calculation Methods: Adjust moving averages, timeframes, and log returns based on preference.
Interpret the Colors & Tables: Utilize the dynamic coloring and tables to quickly assess market conditions.
Ideal For:
Traders looking to compare individual asset performance against an index or benchmark.
Investors analyzing Alpha & Beta to understand risk-adjusted returns.
Market analysts who want a visually intuitive and data-rich performance tracking tool.
This indicator provides a powerful and flexible way to track relative asset strength, helping users make more informed trading decisions.
Pengayun
Delta Volume Histogram with Filters and AlertsОписание (Russian):
Индикатор "Delta Volume Histogram" определяет дельту объёма и отображает её в виде гистограммы. Он показывает разницу между объёмами покупок и продаж, с возможностью фильтрации значений и вызова алертов.
Функции:
Фильтр для отображения только значений выше заданного порога.
Режим отображения всех значений выше нуля.
Алерт при появлении дельты, превышающей установленный фильтр.
Description (English):
The "Delta Volume Histogram" indicator calculates volume delta and displays it as a histogram. It highlights the difference between buy and sell volumes, with options for filtering values and triggering alerts.
Features:
Filter to display only values above a specified threshold.
**Features (continued):**
- Mode to display both positive and negative delta values above the zero line for better visualization.
- Alert functionality that notifies you when the delta volume exceeds the specified filter value.
This indicator is ideal for traders who want to track buying and selling pressure in the market, helping to identify strong movements and potential reversals based on volume delta analysis.
Support and Resistance with Buy/Sell SignalsSwing Highs and Lows:
The script identifies swing highs and lows using the ta.highest and ta.lowest functions over a user-defined swing_length period.
Swing highs are treated as resistance levels.
Swing lows are treated as support levels.
Buy Signal:
A buy signal is generated when the price closes above the resistance level (ta.crossover(close, swing_high)).
Sell Signal:
A sell signal is generated when the price closes below the support level (ta.crossunder(close, swing_low)).
Plotting:
Support and resistance levels are plotted on the chart.
Buy and sell signals are displayed as labels on the chart.
Background Highlighting:
The background is highlighted in green for buy signals and red for sell signals (optional).
Tri-Fold BB(Trend-Strength)*indicator isn't preset to look as displayed, do so accordingly*
"Tri-Fold BB" is an indicator that utilizes three Bollinger Bands, each of different length as a way to represent trend strength. This allows one to see the trend strength relative to multiple timeframes: short, mid, and long term trend strength. This is helpful because it provides the user with a holistic view of the asset.
How it Works
The indicator is preset to utilizing three different Bollinger Bands with length: 20, 50, and 100. This indicator simply plots the price of an asset relative to its specified Bollinger Band. For an example, if the price of the asset were to surpass its 20BB standard deviations, it would display so accordingly, though from the perspective of lets say... the 100, it may have looked like it barely moved up a standard deviation relative to 100BB because the standard deviations of a 100BB are more spread out.
Its important to view the trend strength from multiple lengths because it allows one to gauge whether the short term trend strength is likely to hold or not. A better way to speculate on asset behavior.
Another way to view this indicator is similar to that of the BB% indicator, except this indicator allows us to view price relative to standard deviations, across multiple timeframes. More holistic, more utility provided.
Basic Understanding:
Each line = Standard Deviation (3 upper, 3 lower)
Mid-Line = Basis relative to BB(20sma, 50sma, 100sma)
If price goes under Basis, that means it crossed below their specified sma(significant bull or bear signal)
I've also added HMA's relative to each BB incase one were to decide in creating some sort of trading strategy with it. I personally don't use them but I understand that it could be helpful to some so I left it in there. If you don't like them then simply deselect them and then save your desired setup as default.
In regard to regular indications of bullish or bearishness, i'd like to add that I use this indicator for the sole purpose of providing an idea of trend strength. I personally am unsure to state that cross overs directly indicate that there is a bull or bear move because I've seen instances where the price of an asset went in a direction contrary to what it 'should' have if we were to use that cross over strategy. Though of course, feel free to use this indicator as desired.
Iron Bot Statistical Trend Filter📌 Iron Bot Statistical Trend Filter
📌 Overview
Iron Bot Statistical Trend Filter is an advanced trend filtering strategy that combines statistical methods with technical analysis.
By leveraging Z-score and Fibonacci levels, this strategy quantitatively analyzes market trends to provide high-precision entry signals.
Additionally, it includes an optional EMA filter to enhance trend reliability.
Risk management is reinforced with Stop Loss (SL) and four Take Profit (TP) levels, ensuring a balanced approach to risk and reward.
📌 Key Features
🔹 1. Statistical Trend Filtering with Z-Score
This strategy calculates the Z-score to measure how much the price deviates from its historical mean.
Positive Z-score: Indicates a statistically high price, suggesting a strong uptrend.
Negative Z-score: Indicates a statistically low price, signaling a potential downtrend.
Z-score near zero: Suggests a ranging market with no strong trend.
By using the Z-score as a filter, market noise is reduced, leading to more reliable entry signals.
🔹 2. Fibonacci Levels for Trend Reversal Detection
The strategy integrates Fibonacci retracement levels to identify potential reversal points in the market.
High Trend Level (Fibo 23.6%): When the price surpasses this level, an uptrend is likely.
Low Trend Level (Fibo 78.6%): When the price falls below this level, a downtrend is expected.
Trend Line (Fibo 50%): Acts as a midpoint, helping to assess market balance.
This allows traders to visually confirm trend strength and turning points, improving entry accuracy.
🔹 3. EMA Filter for Trend Confirmation (Optional)
The strategy includes an optional 200 EMA (Exponential Moving Average) filter for trend validation.
Price above 200 EMA: Indicates a bullish trend (long entries preferred).
Price below 200 EMA: Indicates a bearish trend (short entries preferred).
Enabling this filter reduces false signals and improves trend-following accuracy.
🔹 4. Multi-Level Take Profit (TP) and Stop Loss (SL) Management
To ensure effective risk management, the strategy includes four Take Profit levels and a Stop Loss:
Stop Loss (SL): Automatically closes trades when the price moves against the position by a certain percentage.
TP1 (+0.75%): First profit-taking level.
TP2 (+1.1%): A higher probability profit target.
TP3 (+1.5%): Aiming for a stronger trend move.
TP4 (+2.0%): Maximum profit target.
This system secures profits at different stages and optimizes risk-reward balance.
🔹 5. Automated Long & Short Trading Logic
The strategy is built using Pine Script®’s strategy.entry() and strategy.exit(), allowing fully automated trading.
Long Entry:
Price is above the trend line & high trend level.
Z-score is positive (indicating an uptrend).
(Optional) Price is also above the EMA for stronger confirmation.
Short Entry:
Price is below the trend line & low trend level.
Z-score is negative (indicating a downtrend).
(Optional) Price is also below the EMA for stronger confirmation.
This logic helps filter out unnecessary trades and focus only on high-probability entries.
📌 Trading Parameters
This strategy is designed for flexible capital management and risk control.
💰 Account Size: $5000
📉 Commissions and Slippage: Assumes 94 pips commission per trade and 1 pip slippage.
⚖️ Risk per Trade: Adjustable, with a default setting of 1% of equity.
These parameters help preserve capital while optimizing the risk-reward balance.
📌 Visual Aids for Clarity
To enhance usability, the strategy includes clear visual elements for easy market analysis.
✅ Trend Line (Blue): Indicates market midpoint and helps with entry decisions.
✅ Fibonacci Levels (Yellow): Highlights high and low trend levels.
✅ EMA Line (Green, Optional): Confirms long-term trend direction.
✅ Entry Signals (Green for Long, Red for Short): Clearly marked buy and sell signals.
These features allow traders to quickly interpret market conditions, even without advanced technical analysis skills.
📌 Originality & Enhancements
This strategy is developed based on the IronXtreme and BigBeluga indicators,
combining a unique Z-score statistical method with Fibonacci trend analysis.
Compared to conventional trend-following strategies, it leverages statistical techniques
to provide higher-precision entry signals, reducing false trades and improving overall reliability.
📌 Summary
Iron Bot Statistical Trend Filter is a statistically-driven trend strategy that utilizes Z-score and Fibonacci levels.
High-precision trend analysis
Enhanced accuracy with an optional EMA filter
Optimized risk management with multiple TP & SL levels
Visually intuitive chart design
Fully customizable parameters & leverage support
This strategy reduces false signals and helps traders ride the trend with confidence.
Try it out and take your trading to the next level! 🚀
Advanced Supertrend Enhanced ADXEnhanced Supertrend ADX Indicator - Technical Documentation
Overview
The Enhanced Supertrend ADX indicator combines ADX directional strength with Supertrend trend-following capabilities, creating a comprehensive trend detection system. It's enhanced with normalization techniques and multiple filters to provide reliable trading signals.
Key Features and Components
The indicator incorporates three main components:
Core ADX and Supertrend Fusion
Uses a shorter ADX period for increased sensitivity
Integrates Supertrend signals for trend confirmation
Applies a long-term moving average for trend context
Advanced Filtering System
Volatility filter: Identifies periods of significant market movement
Momentum filter: Confirms the strength and sustainability of trends
Lateral market detection: Identifies ranging market conditions
Data Normalization
Standardizes indicator readings across different instruments
Makes signals comparable across various market conditions
Reduces extreme values and false signals
Model Assumptions
The indicator operates under several key assumptions:
Market Behavior
Markets alternate between trending and lateral phases
Strong trends correlate with increased volatility
Price momentum confirms trend strength
Market transitions follow identifiable patterns
Signal Reliability
Low ADX values indicate lateral markets
Valid signals require both volatility and momentum confirmation
Multi-filter confirmation increases signal reliability
Price normalization enhances signal quality
Trading Applications
The indicator supports different trading approaches:
Trend Trading
Strong signals when all filters align
Clear distinction between bullish and bearish trends
Momentum confirmation for trend continuation
Range Trading
Clear identification of lateral markets
Band-based trading boundaries
Reduced false breakout signals
Transition Trading
Early identification of trend-to-range transitions
Clear signals for range-to-trend transitions
Momentum-based confirmation of breakouts
Risk Considerations
Important factors to consider:
Signal Limitations
Potential delay in fast-moving markets
False signals during extreme volatility
Time frame dependency
Best Practices
Use in conjunction with other indicators
Apply proper position sizing
Focus on liquid instruments
Consider market context
Performance Characteristics
The indicator shows optimal performance under specific conditions:
Ideal Conditions
Daily timeframe analysis
Clear trending market phases
Liquid market environments
Normal volatility conditions
Challenging Conditions
Choppy market conditions
Extremely low volatility
Highly volatile markets
Illiquid instruments
Implementation Recommendations
For optimal use, consider:
Market Selection
Best suited for major markets
Requires adequate liquidity
Works well with trending instruments
Timeframe Selection
Primary: Daily charts
Secondary: 4-hour charts
Caution on lower timeframes
Risk Management
Use appropriate position sizing
Set clear stop-loss levels
Consider market volatility
Monitor overall exposure
This indicator serves as a comprehensive tool for market analysis, combining traditional technical analysis with modern filtering techniques. Its effectiveness depends on proper implementation and understanding of market conditions.
SNR Quarter Pointsfor btmm swingers
this is qp /quater point find in trading view
Here's a description for your TradingView Pine Script indicator:
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**Support & Resistance (SNR) Lines Indicator**
This TradingView indicator automatically draws Support and Resistance (SNR) lines on the chart at every 250-pip level, starting from 0.0000. The indicator aims to help traders identify key price levels where the market is likely to experience reversal or consolidation. By plotting lines at regular intervals, the script provides a clear visual representation of potential support and resistance zones, aiding traders in making more informed trading decisions. The levels are dynamically adjusted based on market price movement, ensuring they stay relevant for active trading.
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Let me know if you’d like to tweak it further!
ZenAlgo - WavesZenAlgo - Waves is an advanced technical analysis indicator designed to refine trading decisions through a unique combination of multiple methodologies. By integrating Wave-like oscilator, RSI+MFI, and a dynamic Extra Moving Average (MA), it provides a structured approach to trend analysis and momentum detection. Unlike standalone indicators, this tool synchronizes multiple perspectives to provide holistic view and reduce noise.
Purpose and Justification for Integration
ZenAlgo - Waves strategically integrates multiple methodologies to provide trend validation. This indicator goes beyond standalone calculations by layering:
Original Wave Oscillator: Used to detect market momentum shifts and overbought/oversold conditions, further filtered by additional trend confirmation layers.
RSI + MFI Fusion: Introduces price-volume relationship validation, reducing misleading momentum reading.
Dynamic Extra Moving Average (MA): Acts as an adaptive trend filter, ensuring signals align with prevailing market direction rather than reacting to noise.
Divergence Detection: Contextualized divergence detection for both Wave and RSI+MFI.
Multi-Timeframe Trend Table: Facilitates confirmation across different timeframes, helping traders validate trade setups.
Attribution & Originality
ZenAlgo - Waves is an independently developed indicator that builds upon well-known technical analysis techniques while introducing significant enhancements. Unlike traditional WaveTrend indicator, it replaces the fixed constants of the original WaveTrend approach with a dynamic formula based on standard deviation , allowing for more adaptive and responsive calculations.
Additionally, this script integrates Ehlers' Super Smoother Filter , a highly regarded smoothing technique pioneered by John F. Ehlers and freely available for public use. Beyond these foundations, ZenAlgo - Waves incorporates proprietary logic and unique enhancements, setting it apart from conventional alternatives.
If you're seeking an exact replication of WaveTrend, please note that this indicator follows a distinct methodology, producing different calculations and outputs.
How to Use
Identify Key Zones: Observe Wave oscillator values to detect potential overbought and oversold conditions, which may vary based on settings.
Check RSI+MFI Histogram: Confirm momentum strength—bullish (increasing green bars) or bearish (increasing red bars).
Assess Trend via Extra MA: Use the Extra Moving Average to determine overall trend direction.
Look for Divergences: Identify divergences between price action and Wave/RSI+MFI for potential reversals.
Monitor Multi-Timeframe Trend Table: Check for alignment across timeframes for additional confirmation.
Set Alerts for Key Conditions: Configure alerts for Wave crossovers, divergences, and Extra MA state changes.
Analyze Conditions Before Making Decisions: The indicator does not execute trades. Traders should use it as a confirmation tool alongside a broader strategy.
Detailed Explanation of Calculation Logic
ZenAlgo - Waves builds on established wave-based oscillator principles, fine-tuning them for greater adaptability:
Baseline & Difference: Computes a smoothed average of the price source (e.g., HLC3) and measures the difference (or "deviation") between the current price and this baseline.
Volatility Scaling: Uses standard deviation to capture market volatility instead of relying on a static multiplier.
Normalization & Smoothing: Processes the resulting ratio into an oscillator, helping identify overbought and oversold zones. Optionally applies a secondary smoothing pass (including Ehlers' Super Smoother - SMMA) to reduce noise while preserving trend structure.
RSI + MFI Integration: Fuses RSI and MFI into a single composite metric, weighting RSI momentum with volume-adjusted MFI values for a clearer representation of momentum strength.
Extra Moving Average Filtering: A variety of moving average types (EMA, Hull, ZEMA, etc.) smooth the underlying trend, with sensitivity to trend changes customizable.
Divergence Detection: Identifies both regular and hidden divergences by comparing oscillator movements against price action, adjusting dynamically based on historical volatility.
Multi-Timeframe Trend Confirmation: Aggregates data across multiple timeframes (e.g., 1m, 5m, 15m, 1h) to provide a broader market context.
Alerts and Key Conditions: Alerts can be configured for specific conditions such as Wave crossovers, RSI+MFI confirmation, or Extra MA transitions. These alerts serve as notifications, not as automatic trading signals.
Why It’s Worth Paying For
ZenAlgo - Waves differentiates itself from free indicators by providing:
Contextual Signal Filtering: Integrates price-volume analysis and trend alignment checks.
Adaptive Trend Classification: Dynamically adjusts to market conditions.
Multi-Layer Confirmation: Requires momentum, volume, and trend agreement before providing insights.
Advanced Divergence Detection: Filters out noise-based divergences, highlighting only significant price-action-driven reversals.
Multi-Timeframe Validation: Helps ensure that observed trends are consistent across different timeframes.
Considerations for Use:
During periods of low trading volume, as price action lacks conviction.
In highly volatile market conditions, rapid price swings can introduce uncertainty.
Fundamental news events can override technical patterns.
If trends contradict across multiple timeframes, additional confirmation is recommended before making decisions.
Important Notes
This indicator is a tool for technical analysis and does not guarantee trading success.
Best Practices: Use ZenAlgo - Waves in conjunction with other indicators and fundamental analysis for a well-rounded approach.
Opening Range, Initial Balance, Opening Price, Pre-market Levels### Description of the Indicator: **Opening Range, Initial Balance, Opening Price, Pre-market Levels**
This custom TradingView indicator provides a comprehensive view of key price levels for intraday trading, specifically designed to track important levels from the Opening Range (OR), Initial Balance (IB), Opening Price (OP), and Pre-market session (PM). These levels are essential for traders to gauge potential market movements and identify critical areas of support and resistance.
#### **Features:**
1. **Opening Range (OR):**
- This is the high and low of the first 30 minutes of the regular market session (09:30 - 10:00 EST).
- The OR high and low act as significant levels that may influence price movement for the rest of the day.
- The mid-level of the Opening Range (OR Mid) is also plotted to give a more detailed view of potential price action.
2. **Initial Balance (IB):**
- The Initial Balance is the range created during the first hour of market activity (09:30 - 10:30 EST).
- This range often sets the tone for the market's direction. The IB high and low, along with the IB midline, are plotted for quick reference.
3. **Opening Price (OP):**
- The opening price of the market is marked as a circle and labeled "OP."
- This level provides context for market sentiment when compared to the high and low levels.
4. **Pre-market Levels (PM):**
- The pre-market session (04:00 - 09:30 EST) has its own important levels that are calculated for the high, low, and mid range (PM High, PM Low, and PM Mid).
- These levels are plotted and are useful for traders to understand where the market stood before the regular session opened.
#### **Customization Options:**
- **Exchange Timezone:** You can choose whether to display the times in the exchange's local timezone or in your own preferred timezone.
- **Mid Levels Display:** You can toggle whether the mid levels for each range (OR, IB, PM) should be shown on the chart.
- **Level Color Change:** The colors of the plotted levels (high, low, mid) change based on whether the price is above or below the respective level, making it easy to visualize potential support and resistance.
- **Label Positions:** The position of the labels (OR, IB, OP, PM) on the chart can be customized to avoid overlap with other data points.
#### **Key Use Cases:**
- **Intraday Trend Analysis:** Use the OR and IB to identify key levels for the day, providing insights into the possible trend or range for the day.
- **Pre-market Insights:** The PM levels are crucial for understanding where the market stood during the pre-market hours and can be used as reference points during the regular session.
- **Potential Support and Resistance:** The high and low levels of the OR, IB, and PM sessions can act as potential support or resistance, which are useful for setting stop-loss and take-profit levels.
#### **How to Use:**
- Pay attention to the levels provided for OR, IB, and PM as potential entry and exit points.
- Watch for breakouts or reversals around these levels, especially when combined with other technical indicators or price action patterns.
- The mid levels offer an additional reference to assess price direction or identify possible areas of consolidation.
This indicator is perfect for day traders who rely on key intraday levels and pre-market activity to make informed trading decisions. It helps to streamline the process of identifying potential breakouts, reversals, and ranges in the market.
Kalman weighted price For Loop | QuantumResearchQuantumResearch Kalman Weighted Price For Loop Indicator
The QuantumResearch Kalman Weighted Price For Loop Indicator is an advanced tool designed for traders looking for precise trend detection and adaptive market analysis. This indicator integrates a Kalman filter, a weighted price calculation, and a for-loop scoring mechanism to dynamically assess price movements and provide clear trading signals.
Overview
Reduce Market Noise: The Kalman filter smooths price fluctuations for a clearer trend assessment.
Detect Trends: A weighted price calculation enhances trend analysis by adjusting dynamically to market conditions.
Adaptive Thresholds: ATR-based dynamic thresholds help traders assess breakout levels effectively.
Generate Trading Signals: A for-loop scoring mechanism evaluates historical price movements to identify long and short opportunities.
How It Works
A. Kalman Filter Smoothing
Purpose: The Kalman filter refines the selected price source (e.g., close price) by reducing short-term fluctuations, offering a clearer view of the underlying price movement.
Customization: Users can adjust key parameters such as:
Process Noise: Controls the filter’s sensitivity to recent changes.
Measurement Noise: Determines how responsive the filter is to incoming price data.
Filter Order: Sets the number of data points considered in the smoothing process.
B. Weighted Price & For-Loop Scoring
Weighted Price Calculation: A smoothing factor (alpha) is applied to blend the Kalman-filtered price with previous data, allowing for a more stable trend evaluation.
For-Loop Mechanism:
A dynamic scoring system iterates through a predefined price range, measuring if the weighted price is higher or lower than past values.
This score determines the overall trend strength and signals potential buy/sell conditions.
C. Threshold-Based Signal Generation
User-defined thresholds classify market conditions into bullish or bearish zones.
Default settings:
Long Signal: Triggered when the for-loop score exceeds the long_threshold.
Short Signal: Triggered when the score falls below the short_threshold.
Threshold bands dynamically adjust based on price behavior.
Visual Representation
The indicator’s design focuses on easy interpretation and usability:
Color-Coded Bar Signals:
Green Bars: Indicate bullish conditions when a long signal is active.
Red Bars: Indicate bearish conditions when a short signal is active.
Trend Confirmation Bands: The indicator plots upper, middle, and lower bands to visually represent market conditions.
Background Fill: The space between bands is shaded to highlight price deviations from equilibrium.
Customization & Parameters
This indicator is highly configurable, allowing traders to customize settings based on their strategy:
Kalman Filter Settings:
Process Noise: Default is 1.0, adjusts how much recent price data affects the filter.
Measurement Noise: Default is 0.05, determines responsiveness to price changes.
Filter Order: Default is 1, defines how many data points are analyzed at once.
For-Loop Parameters:
Lookback Range: Default is 1 to 50, determines how many past bars are used for scoring.
Scoring Thresholds:
Long Signal: Default threshold set at 40.
Short Signal: Default threshold set at -10.
Color Modes: Eight customizable color themes for individual preferences.
Trading Applications
This indicator is adaptable for various trading strategies:
Trend Following: Helps traders stay aligned with the dominant market direction by filtering noise and detecting sustained movements.
Momentum Analysis: Evaluates price strength and potential breakout conditions using adaptive scoring.
Reversal Detection: Identifies when momentum weakens, signaling possible trend shifts.
Risk Management: Uses for-loop scoring to minimize false signals and improve entry/exit precision.
Final Thoughts
The QuantumResearch Kalman Weighted Price For Loop Indicator combines Kalman filtering, adaptive price weighting, and for-loop scoring to deliver a structured approach to market trend analysis.
This unique methodology provides traders with enhanced noise reduction, improved signal clarity, and a flexible framework adaptable to different market conditions.
By adjusting the Kalman filter parameters, traders can fine-tune responsiveness and optimize settings for their specific trading style.
Important Disclaimer: This indicator is a tool for analysis and does not guarantee profitable outcomes. Traders should use proper risk management strategies and perform extensive backtesting before live trading.
Enhanced Momentum Divergence Radar+ [Alpha Extract]Enhanced Momentum Divergence Radar+
The AE's Enhanced Momentum Divergence Radar+ is designed to detect momentum shifts and divergence patterns, helping traders identify potential trend reversals and continuation points. By normalizing momentum readings and applying divergence detection, it enhances market timing for entries and exits.
🔶 CALCULATION
The indicator calculates normalized momentum using a combination of Detrended Price Oscillator (DPO) and volatility-adjusted smoothing techniques. It highlights overbought and oversold conditions while identifying bullish and bearish divergences.
Core Calculation:
ATR-based volatility adjustment ensures dynamic sensitivity.
DPO is derived from the price minus a simple moving average (SMA) to isolate cyclical movements.
Momentum score is normalized using historical max values for consistent scaling.
Thresholds are dynamically adjusted based on average absolute momentum.
dpo = close - ma
sd = (dpo / volatility) * 100
normalizedSD = sd / maxAbsSD
The momentum score is plotted as a histogram, where:
Green bars indicate strong upward momentum.
Red bars indicate strong downward momentum.
Neutral values fade into gray.
🔶 DETAILS
📊 Visual Features:
Histogram bars dynamically color-coded based on momentum strength.
Threshold bands provide reference points for overbought and oversold levels.
Divergence markers (Bullish/Bearish & Hidden Bullish/Bearish) highlight key reversal signals.
🛠 How Divergences Work:
Bullish Divergence (𝓞𝓢): Price makes a lower low while momentum makes a higher low.
Bearish Divergence (𝓞𝓑): Price makes a higher high while momentum makes a lower high.
Hidden Divergences confirm trend continuations rather than reversals.
📌 Example of Divergence Logic:
bullishDiv = (low == priceLow) and (sd > momentumLow)
bearishDiv = (high == priceHigh) and (sd < momentumHigh)
🔶 EXAMPLES
📍 The chart below illustrates price reacting to momentum divergences, identifying potential tops and bottoms before major price moves.
📌 Example snapshots:
A bullish divergence leading to a reversal in price.
A bearish divergence marking the beginning of a downtrend.
🔶 SETTINGS
🔹 Customization Options:
Lookback Period: Adjusts sensitivity to market cycles.
Smoothing Period: Controls signal clarity.
Color Options: Enables bar coloring based on momentum strength.
Divergence Sensitivity: Choose to display hidden divergences.
Trend Strength & Direction📌 Assumptions of the "Trend Strength & Direction" Model
This model is designed to measure both trend strength and trend direction, using a modified version of the ADX (Average Directional Index) while also identifying ranging markets. Below is a detailed breakdown of all key assumptions.
1️⃣ Using ADX as the Basis for Trend Strength
Why ADX?
The ADX (Average Directional Index) is one of the most commonly used indicators for measuring trend strength, regardless of direction.
How is it calculated?
ATR (Average True Range) is used to normalize volatility.
Directional movement (+DM and -DM) is smoothed with an Exponential Moving Average (EMA) to obtain the +DI (Positive Directional Indicator) and -DI (Negative Directional Indicator).
Trend strength is derived by normalizing the absolute difference between +DI and -DI, divided by the sum of both.
🔹 Assumption: A high ADX means the trend is strong (whether bullish or bearish).
2️⃣ 50-Period Moving Average for Trend Strength
Why add a moving average?
ADX can be very volatile in the short term.
A 50-period SMA (Simple Moving Average) is used to smooth out trend strength and identify sustained trends.
🔹 Assumption: The SMA reduces false signals caused by short-term ADX spikes.
3️⃣ Identifying a Ranging Market (ADX Below 35)
How is a ranging market defined?
If the trend strength (ADX) is below 35, the market is considered "ranging".
The 35-level threshold is chosen empirically since ADX values below this level often indicate a lack of strong price direction.
When the market is ranging, the background color turns yellow.
🔹 Assumption: ADX < 35 indicates a sideways market, so the indicator colors the background yellow.
4️⃣ Determining Trend Direction Using +DI and -DI
How is direction determined?
If +DI > -DI, the trend is bullish (green).
If -DI > +DI, the trend is bearish (red).
If ADX is below 35, the market is ranging and turns yellow.
🔹 Assumption: Trend direction is determined by the relationship between +DI and -DI, not ADX values.
5️⃣ Background Color to Highlight Market Conditions
Yellow background if ADX < 35 → Ranging market.
Green background if ADX ≥ 35 and bullish.
Red background if ADX ≥ 35 and bearish.
🔹 Assumption: The background color visually differentiates trending vs. ranging phases.
6️⃣ Reference Levels for ADX
Lateral Threshold (35) → Below this, the trend is weak or ranging.
Neutral Threshold (50) → Intermediate level indicating moderate trend strength.
Strong Trend Threshold (75) → Above this, the trend is very strong and possibly overextended.
🔹 Assumption: ADX above 75 indicates a very strong trend, potentially near exhaustion.
🔹 Summary of Key Assumptions
1️⃣ ADX is the core strength metric → Strong trends when ADX > 35, weak below 35.
2️⃣ The 50-period SMA smooths out volatility → Prevents false signals.
3️⃣ Ranging markets are defined as ADX < 35 → Yellow background color.
4️⃣ Trend direction is based on +DI vs. -DI → Green = bullish, Red = bearish.
5️⃣ Background colors enhance readability → Helps distinguish different market phases.
6️⃣ ADX reference levels (35, 50, 75) indicate increasing trend strength.
Conclusion
This model combines ADX with a moving average and color-based logic to highlight trend strength, trend direction, and sideways markets. It helps traders quickly identify the best conditions for entering or exiting trades. 🚀
Absolute Volume Levels MA [AlgoRich]This script allows you to:
Choose between dynamic or static thresholds to classify the volume of the bars.
Select the type of moving average (SMA, EMA, RMA, or KAMA) and the period for calculating the volume's moving average, making it easier to adapt to different asset behaviors and volatilities.
Configure multiplier factors that determine the intermediate and strong thresholds based on the volume's moving average.
Assign differentiated colors for bullish and bearish bars, depending on whether the volume is weak, intermediate, or strong.
Visualize the classified volume in a histogram, which helps quickly identify the bars with the highest activity.
This flexibility and customization allow the indicator to adapt to various assets and timeframes, providing a robust visual tool for analyzing volume behavior.
Smart Money Index + True Strength IndexThe Smart Money Index + True Strength Index indicator is a combination of two popular technical analysis indicators: the Smart Money Index (SMI) and the True Strength Index (TSI). This combined indicator helps traders identify potential entry points for long and short positions based on signals from both indexes.
Main Components:
Smart Money Index (SMI):
The SMI measures the difference between the closing and opening price of a candle multiplied by the trading volume over a certain period of time. This allows you to assess the activity of large players ("smart money") in the market. If the SMI value is above a certain threshold (smiThreshold), it may indicate a bullish trend, and if lower, it may indicate a bearish trend.
True Strength Index (TSI):
The TSI is an oscillator that measures the strength of a trend by comparing the price change of the current bar with the previous bar. It uses two exponential moving averages (EMAS) to smooth the data. TSI values can fluctuate around zero, with values above the overbought level indicating a possible downward correction, and values below the oversold level signaling a possible upward correction.
Parameters:
SMI Length: Defines the number of candles used to calculate the average SMI value. The default value is 14.
SMI Threshold: A threshold value that is used to determine a buy or sell signal. The default value is 0.
Length of the first TSI smoothing (tsiLength1): The length of the first EMA for calculating TSI. The default value is 25.
Second TSI smoothing length (tsiLength2): The length of the second EMA for additional smoothing of TSI values. The default value is 13.
TSI Overbought level: The level at which the market is considered to be overbought. The default value is 25.
Oversold level TSI: The level at which it is considered that the market is in an oversold state. The default value is -25.
Logic of operation:
SMI calculation:
First, the difference between the closing and opening price of each candle (close - open) is calculated.
This difference is then multiplied by the trading volume.
The resulting product is averaged using a simple moving average (SMA) over a specified period (smiLength).
Calculation of TSI:
The price change relative to the previous bar is calculated (close - close ).
The first EMA with the length tsiLength1 is applied.
Next, a second EMA with a length of tsiLength2 is applied to obtain the final TSI value.
The absolute value of price changes is calculated in the same way, and two emas are also applied.
The final TSI index is calculated as the ratio of these two values multiplied by 100.
Graphical representation:
The SMI and TSI lines are plotted on the graph along with their respective thresholds.
For SMI, the line is drawn in orange, and the threshold level is dotted in gray.
For the TSI, the line is plotted in blue, the overbought and oversold levels are indicated by red and green dotted lines, respectively.
Conditions for buy/sell signals:
A buy (long) signal is generated when:
SMI is greater than the threshold (smi > smiThreshold)
TSI crosses the oversold level from bottom to top (ta.crossover(tsi, oversold)).
A sell (short) signal is generated when:
SMI is less than the threshold (smi < smiThreshold)
TSI crosses the overbought level from top to bottom (ta.crossunder(tsi, overbought)).
Signal display:
When the conditions for a long or short are met, labels labeled "LONG" or "SHORT" appear on the chart.
The label for the long is located under the candle and is colored green, and for the short it is above the candle and is colored red.
Notification generation:
The indicator also supports notifications via the TradingView platform. Notifications are sent when conditions arise for a long or short position.
This combined indicator provides the trader with the opportunity to use both SMI and TSI signals simultaneously, which can improve the accuracy of trading decisions.
Bollinger Bands with Narrow ConsolidationThe indicator is based on the standard Bollinger Bands indicator in TradingView. Its main difference is the ability to display narrow consolidation zones (with an adjustable percentage) and generate signals in these zones.
Narrow consolidation zones can be considered as a signal before the start of a strong trend, whether upward or downward.
Индикатор построен на стандартном индикаторе полос боллинджера в трейдинг вью. Его отличие заключается в том, что здесь есть возможность отображения зон узкой консолидации (процент настраивается) и генерации сигналов на этих зонах.
Зоны узкой консолидации можно рассматривать как сигнал перед началом сильного треда как восходящего, так и нисходящего.
Fractal Trend Anticipator (FTA)How to Use FTA
Purpose:
FTA is designed to detect when a consolidating (or choppy) market—with a high choppiness index—is poised to break into a trend as indicated by an RSI crossover.
Signals:
Bullish Breakout: When the Choppiness Index is above your set threshold and the RSI crosses upward over 50, a bullish arrow (triangle up) appears below the bar.
Bearish Breakout: Conversely, when the RSI crosses downward from above 50 under high choppiness, a bearish arrow (triangle down) appears above the bar.
Trading Insight:
In crypto markets, when price is range-bound, a sudden release of momentum can be captured early by FTA. Use these signals as early alerts to join moves as they begin—whether you plan to ride a short-term spike or a medium-term trend.
Feel free to adjust the and parameters to suit your trading style and asset volatility. Enjoy trading with your updated Fractal Trend Anticipator!
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.
Zerg range filter credit to Kivanc turkish pinecoder for base indicator i reworked with chatgpt and some common sense
this indicator similar to the ADX but i think its better visually to keep you out of market conditions that are unfavorable.
i made original indicator to work in a 0-100 enviroment (before it was a zero middle line oscillator) and added background coloring that has a lower and higher threshold setting. i also added a smoothing moving average. this will trigger threshold levels (not the core oscillator)
above higher level would indicate trending market conditions and its purple. these are the areas where you might want to buy low period moving average bounces like 10 or 21 ema
lower band will paint indicator background blue and its cold, meaning range bound trade ideas are likely play out better. selling resistance and buying horizontal supports for example.
you are encourage to play with lookback period and change thresholds until you find something that works for your trading.
on the picture above it illustrates how i intended its usage.
it also shows divergences which was not intended but also a function.
you can also observe as the oscillator likes to coil up into a tight range (horizontal or a wedge formation) and when these break their trendlines explosive moves are incoming usually.
if you have a trading system and can generate a lot of signals but want to filter out some loser trades this could be the indicator you were looking for.
i hope this will be inline with community guidelines. my other publishing got removed unfortunately
MA Smoothed RSI For Loop | QuantPabloMA Smoothed Source For RSI Loop | Crypto_Mercenary_
Conceptual Foundation and Innovation
The "MA Smoothed Source For RSI Loop" indicator developed by Crypto_Mercenary_ innovates by smoothing the source data used for RSI calculation with various moving averages before feeding it into a for-loop scoring system. Rather than smoothing the RSI itself, this approach focuses on pre-processing the price data to reduce noise, thereby providing a cleaner input for RSI computation. The for-loop then evaluates this smoothed RSI to generate momentum signals, offering traders a refined method for detecting market trends and potential reversals.
Technical Composition and Calculation
The indicator's functionality is divided into two main parts:
Source Smoothing: Before calculating RSI, the source data (typically close price) is smoothed using one of several moving averages (EMA, SMA, WMA, VWMA, HMA, RMA, DEMA, or none) as selected by the user. This smoothing aims to filter out short-term volatility, providing a more consistent base for RSI calculation.
RSI Calculation and For-Loop Scoring:
RSI: Calculated using the smoothed source data over a user-defined length.
For-Loop Mechanism: A loop runs from a to b, comparing the current RSI value with past values of this smoothed RSI. A score (counter) is generated, which increases or decreases based on whether the current RSI exceeds or falls below past values. If the weighted option is activated, this comparison gives more weight to recent data points, adjusting the score accordingly.
The final score is then potentially normalized for better interpretation, compared against thresholds to determine market momentum signals.
Features and User Inputs
This indicator is highly customizable, allowing traders to tailor its behavior:
Weighted Calculation: Option to adjust scoring to favor recent price action.
RSI Length: Sets the period for RSI calculation.
Source: The price data to be smoothed before RSI calculation, default is close.
MA Type: Choice from various moving averages to smooth the source data.
Smooth Length: Length of the moving average used for smoothing.
For Loop Range: Defines the historical range (a to b) for the scoring loop.
Thresholds: Custom thresholds to define when signals for uptrends or downtrends are generated.
Practical Applications
This indicator is particularly beneficial for:
Identifying Momentum Shifts: The scoring system helps in detecting potential changes in market momentum.
Noise Reduction: By smoothing the source data, it aims to provide more reliable RSI signals in volatile markets.
Trend Analysis: Assists in confirming or challenging the current market trend based on the smoothed RSI's performance.
Advantages and Strategic Value
The "MA Smoothed Source For RSI Loop" offers an advantage by focusing on cleaning the input data for RSI, which can lead to more accurate momentum readings. Its flexibility in configuration allows traders to adapt the indicator to different market conditions or asset volatilities, enhancing its strategic value in trading decisions.
Alerts and Visual Cues
Visual Signals: The indicator plots the loop score, with colors indicating uptrends (gold) or downtrends (blue). Horizontal lines at thresholds and shaded areas between them provide visual aids for trend analysis.
**No explicit alerts in the script, but users can set up custom alerts based on the signals.
Summary and Usage Tips
The "MA Smoothed Source For RSI Loop | Crypto_Mercenary_" provides a nuanced approach to RSI by smoothing the price data before its calculation, resulting in potentially more reliable signals. Traders can use this indicator to gain a clearer picture of market momentum, adjusting parameters to fit different market behaviors or trading strategies. Remember, the effectiveness of this tool largely depends on its customization to the specific market context.
Note: Backtests are based on past results and do not guarantee future performance.
Volatility Arbitrage Spread Oscillator Model (VASOM)The Volatility Arbitrage Spread Oscillator Model (VASOM) is a systematic approach to capitalizing on price inefficiencies in the VIX futures term structure. By analyzing the differential between front-month and second-month VIX futures contracts, we employ a momentum-based oscillator (Relative Strength Index, RSI) to signal potential market reversion opportunities. Our research builds upon existing financial literature on volatility risk premia and contango/backwardation dynamics in the volatility markets (Zhang & Zhu, 2006; Alexander & Korovilas, 2012).
Volatility derivatives have become essential tools for managing risk and engaging in speculative trades (Whaley, 2009). The Chicago Board Options Exchange (CBOE) Volatility Index (VIX) measures the market’s expectation of 30-day forward-looking volatility derived from S&P 500 option prices (CBOE, 2018). Term structures in VIX futures often exhibit contango or backwardation, depending on macroeconomic and market conditions (Alexander & Korovilas, 2012).
This strategy seeks to exploit the spread between the front-month and second-month VIX futures as a proxy for term structure dynamics. The spread’s momentum, quantified by the RSI, serves as a signal for entry and exit points, aligning with empirical findings on mean reversion in volatility markets (Zhang & Zhu, 2006).
• Entry Signal: When RSI_t falls below the user-defined threshold (e.g., 30), indicating a potential undervaluation in the spread.
• Exit Signal: When RSI_t exceeds a threshold (e.g., 70), suggesting mean reversion has occurred.
Empirical Justification
The strategy aligns with findings that suggest predictable patterns in volatility futures spreads (Alexander & Korovilas, 2012). Furthermore, the use of RSI leverages insights from momentum-based trading models, which have demonstrated efficacy in various asset classes, including commodities and derivatives (Jegadeesh & Titman, 1993).
References
• Alexander, C., & Korovilas, D. (2012). The Hazards of Volatility Investing. Journal of Alternative Investments, 15(2), 92-104.
• CBOE. (2018). The VIX White Paper. Chicago Board Options Exchange.
• 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.
• Zhang, C., & Zhu, Y. (2006). Exploiting Predictability in Volatility Futures Spreads. Financial Analysts Journal, 62(6), 62-72.
• Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105.
Ichimoku Score Indicator [tanayroy]The Ichimoku Cloud is a comprehensive indicator that provides a clear view of market states through five key components. By analyzing the interaction between these components and the asset's price, traders can gain insights into trend direction, momentum, and potential reversals.
Introducing the Ichimoku Score System
I have developed a scoring system that quantifies these interactions, offering an objective method to evaluate market conditions. The score is calculated based on the relative positioning of Ichimoku components, with adjustable weightings via user input.
Scoring Criteria
Each component contributes to the overall score as follows:
Price vs. Cloud (Kumo) & Other Components
Price vs. Kumo → 2 Points
Price vs. Kumo Shadow → 0.5 Points
Tenkan vs. Kijun
Tenkan vs. Kijun → 2 Points
Tenkan vs. Kumo → 0.5 Points
Kijun vs. Kumo → 0.5 Points
Tenkan Slope → 0.5 Points
Kijun Slope → 0.5 Points
Chikou Span Interactions
Price vs. Chikou → 2 Points
Chikou vs. Kumo → 0.5 Points
Chikou Consolidation → 0.5 Points
Senkou Span Analysis
Senkou A vs. Senkou B → 2 Points
Senkou Slope → 0.5 Points
Price vs. Key Levels
Price vs. Tenkan → 2 Points
Price vs. Kijun → 2 Points
Interpreting the Score
The aggregate score functions as an oscillator, fluctuating between a range of ±16.0.
A higher score indicates strong bullish momentum.
A lower score suggests bearish market conditions.
To enhance readability and smooth fluctuations, a 9-period SMA is applied to the score.
Application in Algorithmic Trading
This scoring system helps integrate Ichimoku Cloud principles into algorithmic trading strategies by providing a structured and quantifiable method for assessing market conditions.
Would love to hear your feedback! 🚀 Let me know how this system works for you.
Opening Score with DivergenceOverview
The Opening Score Indicator is a versatile tool designed to help traders assess market sentiment, trend direction, and potential reversals. By combining Opening Range Breakout (ORB), VWAP, Trend, Volatility, and Divergence Detection, this indicator provides a composite score that adapts to different market conditions.
This version includes divergence detection between the Opening Score and price, which highlights potential trend reversals or continuations before they happen. When a regular divergence occurs, the histogram bar turns orange, signaling an increased probability of a trend change.
Best for Both Intraday & Longer-Term Charts
📊 Optimized for intraday trading → Works well on 1m to 30m timeframes for short-term strategies.
📈 Also effective on longer-term charts → Can be used on 1-hour, 4-hour, daily, or weekly charts to identify macro trends and momentum shifts.
🕰️ Adapts to different market conditions → Whether you’re a day trader, swing trader, or position trader, the Opening Score helps you track trend health and reversals.
How It Works
📊 Composite Opening Score Calculation
• ORB Signal → Detects bullish/bearish breakouts based on the opening range.
• VWAP Signal → Measures price positioning relative to VWAP for trend confirmation.
• Trend Signal → Uses a moving average to determine market direction.
• Volatility Signal → Tracks ATR changes to assess market strength.
• Divergence Detection → Identifies regular and hidden divergences for potential reversals or trend continuation.
🔹 Reversal Alerts with Color-Coded Histogram
• Green Bars → Normal bullish Opening Score.
• Red Bars → Normal bearish Opening Score.
• Orange Bars → Warning! Regular Divergence detected → Possible trend reversal.
🔹 Hidden & Regular Divergence Detection
• Regular Divergence (Reversal Signals)
• 📉 Bearish Regular Divergence → Price makes a Higher High, but Opening Score makes a Lower High → 🔻 Possible Downtrend Reversal.
• 📈 Bullish Regular Divergence → Price makes a Lower Low, but Opening Score makes a Higher Low → 🔼 Possible Uptrend Reversal.
• Hidden Divergence (Trend Continuation Signals)
• 📉 Bearish Hidden Divergence → Price makes a Lower High, but Opening Score makes a Higher High → 🔻 Trend Likely to Continue Down.
• 📈 Bullish Hidden Divergence → Price makes a Higher Low, but Opening Score makes a Lower Low → 🔼 Trend Likely to Continue Up.
How to Use It
✅ Watch for Reversal Alerts (Orange Bars) → These highlight potential market turning points.
✅ Use the Zero Line as a Trend Filter → A score above 0 suggests bullish conditions, while below 0 signals bearish conditions.
✅ Combine with Market Structure & Volume Profile → Works well when paired with support/resistance levels, liquidity zones, and order flow data.
✅ Adjust settings based on timeframe → Increase moving average length & lookback periods for longer-term analysis.
Why Use This Indicator?
🚀 Works for both short-term and long-term traders → Adapts to intraday and higher timeframes.
📊 Multi-Factor Analysis → Combines multiple key market indicators for better accuracy.
🎯 Customizable Weighting → Adjust the influence of each signal to suit your trading style.
✅ No Clutter – Only the Opening Score is plotted → Keeps your chart clean & efficient.
🔔 Recommended for Intraday Trading (1m – 30m) AND Longer-Term Analysis (1H – Weekly) → Use this indicator to enhance your trend detection & reversal strategy! 🚀
Normalized ROC²Normalized Rate of Change of Rate of Change (ROC²) Histogram
Overview
The Normalized ROC² Histogram is a momentum-based indicator designed to detect potential trend reversals by measuring the rate of change of the rate of change of price (the second derivative of price movement). This provides insight into when momentum is slowing down, signaling that a price reversal may be approaching.
The indicator also dynamically changes color to highlight shifts in momentum strength, allowing traders to visualize when price acceleration is increasing or decreasing.
How It Works
🔹 Zero Line Crossovers → Potential Direction Change
• When the histogram approaches zero and crosses over, it suggests that price momentum is shifting and a reversal may be imminent.
• Positive to Negative Crossover: Bearish momentum shift.
• Negative to Positive Crossover: Bullish momentum shift.
🔹 Momentum Strength Visualization → Color Shift
• Dark Blue (⬆️ Increasing Positive Momentum) → Price is accelerating upward.
• Light Blue (🔽 Decreasing Positive Momentum) → Uptrend is weakening.
• Dark Red (⬇️ Increasing Negative Momentum) → Price is accelerating downward.
• Light Red (🔼 Decreasing Negative Momentum) → Downtrend is weakening.
🔹 Normalization for Cleaner Visualization
• Prevents extreme volatility spikes from distorting the histogram.
• Normalizes values on a 0 to 100 scale, ensuring consistent bar height.
How to Use It
✅ Watch for Crossovers Near Zero → These can indicate a trend reversal is forming.
✅ Observe Color Changes → A shift from dark to light signals a deceleration, which often precedes price turning points.
✅ Combine with Other Indicators → Works well with Volume Profile, Moving Averages, and Market Structure analysis.
Why This Indicator is Unique
🚀 Second-derivative momentum detection → Provides early insight into potential price shifts.
📊 Normalized bars prevent distortion → No more extreme spikes ruining the scale.
🎯 Color-coded visual cues → Instantly see when momentum is gaining or fading.
📌 Add the Normalized ROC² Histogram to your charts today to detect potential reversals and momentum shifts in real-time! 🚀
