Moving Average Convergence DivergenceThis script is written in Pine Script (version 6) for TradingView and implements the **Moving Average Convergence Divergence (MACD)** indicator. The MACD is a popular momentum oscillator used to identify trend direction, strength, and potential reversals. This version includes customizable inputs, visual enhancements (like crossover markers), and alerts for key events. Below is a detailed explanation of the script:
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### **1. Purpose**
- The script calculates and displays the MACD line, signal line, and histogram.
- It highlights key events such as MACD/signal line crossovers and zero-line crosses with shapes and colors.
- It provides alerts for changes in the histogram's direction (rising to falling or vice versa).
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### **2. User Inputs**
- **Fast Length**: Period for the fast moving average (default: 12).
- **Slow Length**: Period for the slow moving average (default: 26).
- **Source**: Data input for calculation (default: closing price, `close`).
- **Signal Smoothing**: Period for the signal line (default: 9, range: 1–50).
- **Oscillator MA Type**: Type of moving average for MACD calculation (options: SMA or EMA, default: EMA).
- **Signal Line MA Type**: Type of moving average for the signal line (options: SMA or EMA, default: EMA).
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### **3. MACD Calculation**
The MACD is calculated in three parts:
1. **MACD Line**: Difference between the fast and slow moving averages.
- Fast MA: Either SMA or EMA of the source over `fast_length`.
- Slow MA: Either SMA or EMA of the source over `slow_length`.
- Formula: `macd = fast_ma - slow_ma`.
2. **Signal Line**: A moving average (SMA or EMA) of the MACD line over `signal_length`.
- Formula: `signal = sma_signal == "SMA" ? ta.sma(macd, signal_length) : ta.ema(macd, signal_length)`.
3. **Histogram**: Difference between the MACD line and the signal line.
- Formula: `hist = macd - signal`.
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### **4. Key Events Detection**
#### **MACD/Signal Line Crossovers**
- **Bullish Cross**: MACD crosses above the signal line (`ta.crossover(macd, signal)`).
- **Bearish Cross**: MACD crosses below the signal line (`ta.crossunder(macd, signal)`).
#### **Zero Line Crosses**
- **Cross Above Zero**: MACD crosses above 0 (`ta.crossover(macd, 0)`).
- **Cross Below Zero**: MACD crosses below 0 (`ta.crossunder(macd, 0)`).
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### **5. Colors**
- **MACD Line**: Green (#089981) if MACD > signal (bullish), red (#f23645) if MACD < signal (bearish).
- **Signal Line**: White (`color.white`).
- **Histogram**:
- Positive (MACD > signal): Light green (#B2DFDB) if decreasing, darker green (#26A69A) if increasing.
- Negative (MACD < signal): Light red (#FFCDD2) if increasing in magnitude, darker red (#FF5252) if decreasing in magnitude.
- **Zero Line**: Gray with 50% transparency (`color.new(#787B86, 50)`).
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### **6. Visual Outputs**
#### **Plotted Lines**
- **MACD Line**: Plotted with dynamic coloring based on its position relative to the signal line.
- **Signal Line**: Plotted in white.
- **Histogram**: Displayed as columns, with colors indicating direction and momentum.
- **Zero Line**: Horizontal line at 0 for reference.
#### **Shapes for Key Events**
- **Bullish Cross Below Zero**: Green circle on the MACD line when MACD crosses above the signal line while still below zero.
- **Bearish Cross Above Zero**: Red circle on the MACD line when MACD crosses below the signal line while still above zero.
- **Cross Above Zero**: Green upward label at the zero line when MACD crosses above 0.
- **Cross Below Zero**: Red downward label at the zero line when MACD crosses below 0.
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### **7. Alerts**
- **Rising to Falling**: Triggers when the histogram switches from positive (or zero) to negative.
- Condition: `hist >= 0 and hist < 0`.
- Message: "MACD histogram switched from rising to falling".
- **Falling to Rising**: Triggers when the histogram switches from negative (or zero) to positive.
- Condition: `hist <= 0 and hist > 0`.
- Message: "MACD histogram switched from falling to rising".
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### **8. How It Works**
1. **Trend Direction**:
- MACD above signal line (green) suggests bullish momentum.
- MACD below signal line (red) suggests bearish momentum.
2. **Momentum Strength**:
- Histogram height shows the strength of the momentum (larger bars = stronger momentum).
- Histogram color changes indicate whether momentum is increasing or decreasing.
3. **Reversal Signals**:
- Crossovers between MACD and signal lines often signal potential trend changes.
- Zero-line crosses indicate shifts between bullish (above 0) and bearish (below 0) territory.
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### **9. How to Use**
1. Add the script to TradingView.
2. Adjust inputs (e.g., fast/slow lengths, MA types) to suit your trading style.
3. Monitor the chart:
- Green MACD and upward histogram bars suggest bullish conditions.
- Red MACD and downward histogram bars suggest bearish conditions.
- Watch for circles (crossovers) and labels (zero-line crosses) for trade signals.
4. Set up alerts to notify you of histogram direction changes.
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### **10. Key Features**
- **Customization**: Flexible MA types and periods.
- **Visual Clarity**: Dynamic colors and shapes highlight key events.
- **Alerts**: Notifies users of momentum shifts via histogram changes.
- **Intuitive**: Combines all MACD components (line, signal, histogram) in one indicator.
This script is ideal for traders who rely on MACD for momentum analysis and want clear visual cues and alerts for decision-making.
센터드 오실레이터
Momentum Strategy with Selectable PositionsThis strategy is written based on momentum 5 and 10. If both momentums are positive, it takes a long position and when both momentums are negative, it takes a short position.
ALTIN.S1 to XAU/TRY RatioThis script calculates the ratio between the Turkish Mint Gold Certificate (ALTIN.S1) and the gold price in TRY (XAU/TRY). It helps traders track the premium or discount of ALTIN.S1 compared to the actual gold price. The script also includes upper (1.15) and lower (1.00) boundary lines for reference.
Money Printer V3 – BTC 15M EMA Crossover Strategy🚀 Overview
Money Printer V3 is a trend-following strategy built for crypto markets. It uses fast EMA crossovers with RSI filtering, optional MACD and volume confirmation, and ATR-based trailing stops to capture high-probability momentum trades. This version is optimized for 15-minute timeframes with responsive parameters to increase trade frequency and signal clarity.
📈 How It Works
Buy Conditions:
Fast EMA crosses above Slow EMA
RSI > 40 (customizable)
Optional: MACD histogram > 0
Optional: Volume above 1.5x 20-period average
Sell Conditions:
Opposite of the buy conditions
Risk Management:
Stop-loss and trailing stop are dynamically set using ATR
Position size based on account equity and ATR distance (2% risk per trade)
⚙️ Default Settings
Fast EMA: 5
Slow EMA: 20
RSI Threshold: 40
MACD Filter: OFF
Volume Filter: ON
ATR SL Multiplier: 2.5
ATR Trailing Multiplier: 3.5
Risk: 2% of equity per trade
Initial Capital: $5,000
Commission: 0.1%
Slippage: 0.5%
📊 Backtest Notes
Tested on BTC/USD 15-minute timeframe from 2018 to 2024
Produces 100+ trades for statistically relevant sample size
Strategy is not predictive — it reacts to confirmed trends with filters to reduce false signals
Past performance does not guarantee future results
📌 How to Use
Add this strategy to your BTC/USD 15M chart
Customize the input parameters to match your trading style
Enable alerts for buy/sell conditions
Always forward test before using with real funds
⚠️ Disclaimer
This script is for educational and research purposes only. Use at your own risk. Markets are unpredictable, and no strategy can guarantee profits. Always use proper risk management.
[NLR] - MACD OverlayOverview
This script is an enhanced version of the classic MACD indicator, designed to be plotted directly on the price chart as an overlay. It provides a visual representation of trend direction by coloring moving averages, a zero reference line, and an optional histogram. The script allows for a higher timeframe MACD calculation through a configurable multiplier.
Features
MACD Calculation: Uses Exponential Moving Averages (EMA) to calculate the MACD line, Signal line, and Histogram.
Higher Timeframe Support: Multiplier option to adjust MACD parameters for a broader trend perspective.
Color-Coded Trend Visualization: Dynamic color changes based on MACD crossovers for easy trend identification.
Optional Histogram: Toggle histogram visibility to see momentum shifts.
Zero Line Reference: Helps traders interpret trend direction and strength.
How to Use
Customize Inputs: Adjust Fast, Slow, and Signal lengths as needed. Modify the multiplier to view a higher timeframe MACD.
Enable Histogram: Use the "Show Histogram" toggle to display additional visual cues for momentum shifts.
Interpret the Signals:
Uptrend (Lime): Fast EMA is above Slow EMA.
Downtrend (Fuchsia): Fast EMA is below Slow EMA.
Histogram Changes: Increasing histogram bars indicate growing momentum, while decreasing bars suggest weakening momentum.
[blackcat] L3 Volatility Ehlers Stochastic CGOOVERVIEW
This advanced indicator integrates the Center of Gravity Oscillator (CGO) with an Ehlers-Stochastic framework and an Adaptive Local Minimum-Maximum Average (ALMA) smoothing algorithm. Designed for non-overlaid charts, it identifies market momentum shifts by analyzing price action through multi-layer volatility analysis.
FEATURES
• Dual-line system:
✓ Stochastic CGO: Core oscillating line derived from weighted OHLC price calculations
✓ ALMA Lagging Line: Smoothing component using customizable offset/sigma parameters
• Dynamic color scheme:
✓ Green/red trend differentiation via crossover comparison
✓ Optional fill areas between lines (toggleable)
• Clear trade signals:
✓ Buy/Sell labels triggered by mathematically defined crossovers
✓ Zero-reference baseline marker (#0ebb23)
• Customizable parameters:
Fast Length (9 default) controls CGO sensitivity
Slow Length (5 default) governs ALMA responsiveness
ALMA Offset/Sigma allow adaptive curve optimization
HOW TO USE
Configure core parameters:
• Adjust Fast Length (CGO timeframe window)
• Set Slow Length, ALMA Offset, and Sigma for smoother/laggier response
Interpret visuals:
• Bullish trend = green shaded zone (when primary line above lagging line)
• Bearish trend = red shaded zone (primary line below lagging line)
Analyze signals:
• Buy triggers occur when rising CGO crosses above ALMA while below zero
• Sell triggers activate when falling CGO breaks below ALMA after exceeding zero base
Optimize display:
✓ Enable/disable fill area via Fill Between Lines
LIMITATIONS
• Relies heavily on lookback periods - rapid market changes may reduce predictive accuracy
• Signal frequency increases during high-volatility environments
• Requires additional confirmation methods due to occasional premature crossovers
• Default parameter settings may lack universality across asset classes
NOTES
• Best paired with volume-based confirmations for stronger signals
• Reducing ALMA Sigma sharpens line responsiveness at cost of noise susceptibility
• Increasing Fast Length extends calculation horizon while reducing peak sensitivity
• Weighted OHLC source formula prioritizes closing prices for swing direction assessment
Weight Convergence DivergenceWeight Convergence Divergence ⚖️
1. Introduction
The Weight Convergence Divergence (WCD) indicator applies principles of rotational equilibrium from classical physics to financial market analysis. By quantifying market momentum as a physical balance system, this indicator helps traders identify potential price reversals and continuation patterns through the visualization of market forces .
2. Theoretical Grounds 📚
The WCD draws inspiration from the physical concept of rotational equilibrium, where opposing forces create a balance or imbalance in a system (Giancoli, 2016, pp.247–249). In market analysis, this can be translated to the comparative measurement of bullish and bearish momentum (Bouchaud and Potters, 2003) . Lo and MacKinlay (1988) and Corbet and Katsiampa (2018) demonstrate that markets exhibit both mean-reverting and momentum characteristics, supporting the concept of opposing market forces that the WCD seeks to visualize. Bouchaud and Potters (2003) further highlight that principles from statistical physics can be applied to financial markets, providing a theoretical foundation for approaches like we are doing with the WCD.
3. Methodology 🧪
The WCD indicator quantifies market mass through the following approach:
Calculates mass by multiplying the candle's body (close-open) with volume mass = body * volume
Compares recent market mass (right side) with historical mass (left side)
Visualizes the equilibrium point with a dynamic balance line balance_ln
Generates signals when the balance shifts buy_signal = ta.crossover(right_mass, 0) and left_mass <= 0 and ly > middle_level
sell_signal = ta.crossunder(right_mass, 0) and left_mass >= 0 and ly < middle_level
4. Visual Elements 🎨
Balance Line: A tilting dashed line representing equilibrium between past and present market forces
🟩 Green Boxes: Positive market mass (bullishness)
🟥 Red Boxes: Negative market mass (bearishness)
▲ Buy Signals: When right mass turns positive while left mass is negative
▼ Sell Signals: When right mass turns negative while left mass is positive
5. Integrated Risk Management 🛡️
Automatic stop loss calculation based on Average True Range (ATR)
Dynamic profit targets calibrated to user-defined risk-reward ratios
Visual position management table to track entries, targets, and stops throughout trade duration
6. Parametrization ⚙️
Distance: Number of bars for mass calculation
ATR Length: Period for volatility calculation
ATR Factor: Multiplier applied to ATR for stop loss determination
Risk-Reward Ratio: Factor used for target calculation
7. Implementation Strategies 📈
7.1. Trend Reversal Strategy (More Risky) 🔄
Identify overextended market conditions
Wait for a counter-trend signal
Consider the calculated stop loss and take profit
7.2. Momentum Continuation Strategy (Less Risky) ➡️
Identify the prevailing trend
Look for multiple signals in the trend direction ( the balance line is not the trend! )
Wait for a second or third signal confirmation
Consider the calculated stop loss and take profit
8. Timeframe Flexibility: ⏱️
Lower timeframes (5-15m): Quick signals for scalping
Medium timeframes (30m-4h): Balanced for day trading
Higher timeframes (Daily+): Reliable signals for swing trading
9. References 📗
Bouchaud, J.-P. and Potters, M. (2003). Theory of Financial Risk and Derivative Pricing. doi: doi.org .
Corbet, S. and Katsiampa, P. (2018). Asymmetric mean reversion of Bitcoin price returns. International Review of Financial Analysis. doi: doi.org .
Giancoli, D.C. (2016). Physics : Principles with Applications. 7th ed. Harlow: Pearson Education, pp.247–249.
Lo, A.W. and MacKinlay, A.C. (1988). Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test. Review of Financial Studies, 1(1), pp.41–66. doi: doi.org .
Disclaimer ⚠️
The Weight Convergence Divergence indicator is designed for informational and educational purposes only. Past performance is not necessarily indicative of future results. Traders should conduct thorough analysis and employ proper risk management techniques. This tool does not constitute financial advice and should be used at the user's own discretion.
CyclePulse MomentumCyclePulse Momentum
Overview
CyclePulse Momentum is a powerful, adaptable indicator designed to identify momentum shifts and cyclic reversals across any asset—stocks, forex, cryptocurrencies, and more. By integrating a Cyclic Smoothed RSI (cRSI) with an innovative auto-detected dominant cycle, this tool delivers precise, market-tuned signals for traders seeking to capitalize on price and volume dynamics.
How It Works
Momentum Signals (Green/Red Triangles)
Green Triangles (Below Bars): Signal bullish momentum when volume exceeds a dynamic threshold (default 1.5x the 10-period average) and price rises significantly (default ≥1.5%) or volume momentum spikes (>20% over 5 bars).
Red Triangles (Above Bars): Signal bearish momentum under the same conditions with a price drop.
These highlight high-impact moves driven by volume and price surges.
cRSI Band Crossovers (Diamonds)
Light Turquoise Diamonds (Below Bars): cRSI crosses up through the low band, indicating a potential bullish reversal from oversold territory.
Light Purple Diamonds (Above Bars): cRSI crosses down through the high band, suggesting a bearish reversal from overbought levels.
Bands adapt dynamically to market conditions, enhancing reversal precision.
cRSI 25% Level Signals (Yellow X and Circle)
Yellow X (Above Bars): cRSI crosses below the 25% level under the high band, marking an early bearish pullback.
Yellow Circle (Below Bars): cRSI crosses above the 25% level over the low band, signaling an early bullish recovery.
These provide early warnings of momentum shifts within the cycle.
Auto Dominant Cycle Advantage
The standout feature is the auto-detected dominant cycle length, which adjusts between 10 and 40 bars based on real-time peak and trough analysis (50-bar lookback). Unlike fixed-cycle indicators, this adapts to each asset’s unique rhythm, making triggers—triangles, diamonds, and X’s/circles—significantly more accurate by aligning with the market’s natural tempo. A white number (e.g., "18") appears above bars when the cycle changes, keeping you informed without clutter.
Usage Tips
Momentum Trading: Use green/red triangles to catch strong trends or reversals.
Cycle Timing: Leverage turquoise/purple diamonds for high-probability reversal points, enhanced by the auto-cycle’s precision.
Early Entries: Yellow X’s and circles offer advance signals for momentum shifts.
Customization: Adjust thresholds for your asset—lower (e.g., 1.0) for stocks, higher (e.g., 2.0) for volatile crypto. Pair with support/resistance for confirmation.
Settings
Use Auto Dominant Cycle Length: Enable (default) for adaptive, accurate triggers; disable for a fixed cycle (default 20).
Base Volume Threshold: Default 1.5—tweak for signal frequency.
Base Price Change % Threshold: Default 1.5%—adjust to asset volatility.
Volume Momentum Lookback: Default 5—shorten for faster signals, lengthen for smoother ones.
Show cRSI Band Crossovers: Enable (default) for cRSI signals; disable for simplicity.
Why It Stands Out
The auto dominant cycle sets CyclePulse Momentum apart by dynamically syncing with market waves, ensuring triggers hit when they matter most. Whether you’re scalping on 15M or swinging on 1D, this indicator adapts to deliver sharper, more reliable insights.
Spot - Fut spread v2"Spot - Fut Spread v2"
indicator is designed to track the difference between spot and futures prices on various exchanges. It automatically identifies the corresponding instrument (spot or futures) based on the current symbol and calculates the spread between the prices. This tool is useful for analyzing the delta between spot and futures markets, helping traders assess arbitrage opportunities and market sentiment.
Key Features:
- Automatic detection of spot and futures assets based on the current chart symbol.
- Flexible asset selection: the ability to manually choose the second asset if automatic selection is disabled.
- Spread calculation between futures and spot prices.
- Moving average of the spread for smoothing data and trend analysis.
Flexible visualization:
- Color indication of positive and negative spread.
- Adjustable background transparency.
- Text label displaying the current spread and moving average values.
- Error alerts in case of invalid data.
How the Indicator Works:
- Determines whether the current symbol is a futures contract.
- Based on this, selects the corresponding spot or futures symbol.
- Retrieves price data and calculates the spread between them.
- Displays the spread value and its moving average.
- The chart background color changes based on the spread value (positive or negative).
- In case of an error, the indicator provides an alert with an explanation.
Customization Parameters:
-Exchange selection: the ability to specify a particular exchange from the list.
- Automatic pair selection: enable or disable automatic selection of the second asset.
- Moving average period: user-defined.
- Colors for positive and negative spread values.
- Moving average color.
- Background transparency.
- Background coloring source (based on spread or its moving average).
Application:
The indicator is suitable for traders who analyze the difference between spot and futures prices, look for arbitrage opportunities, and assess the premium or discount of futures relative to the spot market.
Nasan Ultimate Health Index (NUHI)The Nasan Ultimate Health Index (NUHI) is a technical indicator designed to measure the relative health of a stock compared to a benchmark index or sector. By incorporating price action, volume dynamics, and volatility, NUHI provides traders with a clearer picture of a stock’s performance relative to the broader market.
The NUHI is based on the idea that a stock’s relative strength and momentum can be assessed more effectively when adjusted for volume behavior and benchmark comparison. Instead of looking at price movement alone, this indicator factors in:
The stock’s price trend (via EMA)
Volume participation (green vs. red volume) and volume ratio - SMA(volume, 21)/ SMA(volume, 252)
Volatility-adjusted performance (ATR-based scaling)
Comparison with a selected benchmark (e.g., SPX, NDX, sector ETFs)
This results in a normalized and comparative score that helps traders identify outperforming, neutral, and underperforming stocks within a specific market environment.
The NUHI is constructed using the following elements:
1️⃣ Stock Raw Score (Unadjusted Momentum)
The exponential moving average (EMA) of the hlc3 (average of high, low, close) is used to define the price trend.
The difference between the current EMA and the EMA from n bars ago shows whether the stock is gaining or losing momentum.
This difference is divided by the ATR (Average True Range) to adjust for volatility.
2️⃣ Volume Behavior Adjustment
Volume is split into green volume (up candles) and red volume (down candles).
The ratio of green to red volume determines whether buyers or sellers dominate over the selected period (n bars).
If the stock is in an uptrend, green volume is weighted higher; if in a downtrend, red volume is weighted higher.
The stock’s Volume Ratio (short-term SMA divided by long-term SMA) is adjusted based on this weight.
3️⃣ Benchmark Comparison
A similar Raw Score calculation is performed on the selected benchmark (SPX, NDX, or sector ETF).
Benchmark price movements, volume behavior, and ATR adjustments mirror the stock’s calculations.
This provides a reference point for evaluating the stock’s relative strength.
4️⃣ Normalization Process
Both the stock and benchmark raw scores are min-max normalized over the past 252 bars (1-year lookback).
This scales values between 0 and 1, ensuring fair comparisons regardless of absolute price differences.
5️⃣ NUHI Calculation
The final NUHI value is computed using a logarithmic ratio between the normalized stock score and the normalized benchmark score:
This transformation ensures a more symmetrical representation of overperformance and underperformance.
Performance Zones
Strong Outperforming (NUHI between >0.41 and 0.69)
Leading (NUHI between >0.10 and 0.41)
Transitioning Outperformance (NUHI between 0.10 and 0)
Equilibrium (NUHI 0)
Transitioning Underperformance (NUHI between -0.10 and 0)
Lagging (NUHI between < -0.1 and -0.41)
Strong Underperforming (NUHI between< -0.41 and -0.69 )
How to Use NUHI
✅ Identifying Strong Stocks
If NUHI > 0, the stock is outperforming its benchmark.
If NUHI < 0, the stock is underperforming the benchmark.
✅ Trend Confirmation
A steadily rising NUHI and raw score (colored green) suggests sustained strength bullish conditions.
A falling NUHI and raw score (colored orange) indicates weakness and possible rotation into other assets.
✅ Finding Reversals
Bullish Divergence: If NUHI is improving while the stock’s raw score is negative, it may signal a bottoming opportunity.
Bearish Signs: If NUHI is dropping despite price strength, it could hint at underlying weakness.
Why a Stock in a Downtrend Can Have NUHI > 0 (and Vice Versa )
NUHI measures performance relative to both its own history and the benchmark.
A stock’s recent movement is compared to how it usually behaves and how the benchmark is performing.
Example Scenarios:
Stock in a Downtrend but NUHI > 0
The stock may still be in a downtrend (negative raw score), but it’s performing better relative to its past downtrend behavior and better than the benchmark over the same period.
This could mean it’s showing relative strength compared to the broader market or sector.
Stock in an Uptrend but NUHI < 0
Even in a uptrend (positive raw score), the stock might be underperforming relative to its past uptrend behavior and underperforming the benchmark.
What This Means:
NUHI > 0 in a downtrend → The stock is falling less aggressively than usual and/or holding up better than the benchmark.
NUHI < 0 in an uptrend → The stock is gaining less than expected based on its history and/or lagging behind the benchmark.
NUHI helps identify relative strength or weakness .
alphaJohnny Dynamic RSI IndicatorAlphaJohnny Dynamic RSI Indicator (Dyn RSI)
The Dynamic RSI Indicator (Dyn RSI) is a custom Pine Script tool designed for TradingView that aggregates Relative Strength Index (RSI) signals from multiple timeframes to provide a comprehensive view of market momentum. It combines RSI data from Weekly, Daily, 4-hour, 1-hour, and 30-minute intervals, offering traders a flexible and customizable way to analyze trends across different periods.
Key Features:
Multi-Timeframe RSI Aggregation: Combines RSI signals from user-selected timeframes for a holistic momentum assessment.
Dynamic or Equal Weighting: Choose between correlation-based dynamic weights (adjusting based on each timeframe’s correlation with price changes) or equal weights for simplicity.
Smoothed Momentum Line: A visually intuitive line that reflects the strength of the aggregate signal, smoothed for clarity.
Color-Coded Signal Strength:
Dark Green: Strong buy signal
Light Green: Weak buy signal
Yellow: Neutral
Light Red: Weak sell signal
Dark Red: Strong sell signal
Visual Markers: Large green triangles at the bottom for strong buy signals and red triangles at the top for strong sell signals.
How to Use:
Apply to Chart: Add the indicator to your TradingView chart (it will appear in a separate pane).
Customize Settings: Adjust inputs like RSI period, signal thresholds, included timeframes, weighting method, and smoothing period to fit your trading style.
Interpret Signals:
Momentum Line: Watch for color changes to gauge market conditions.
Triangles: Green at the bottom for strong buy opportunities, red at the top for strong sell opportunities.
Notes:
The indicator is designed for a separate pane (overlay=false), with triangles positioned relative to the pane’s range.
Fine-tune thresholds and weights based on your strategy and the asset being analyzed.
The source code is open for modification to suit your needs.
This indicator is ideal for traders seeking a multi-timeframe perspective on RSI to identify potential trend reversals and momentum shifts.
Aggregated Spot vs Perp Volume (% Change)Aggregated Spot vs Perp Volume (% Change)
Description
The "Aggregated Spot vs Perp Volume (% Change)" indicator helps crypto traders compare the momentum of spot and perpetual futures (perp) trading volumes across 12 major exchanges. It calculates the percentage change in volume from one bar to the next, highlighting divergences and showing which market—spot or perp—is leading a move. By focusing on relative changes, it eliminates the issue of absolute volume differences, making trends clear.
The indicator aggregates data from Binance, Bybit, OKX, Coinbase, Bitget, MEXC, Phemex, BingX, WhiteBIT, BitMEX, Kraken, and HTX. Users can toggle exchanges and choose to measure volume in coin units (e.g., BTC) or USD.
How It Works
Volume Aggregation:
Fetches spot and perp volume data for the selected crypto (e.g., BTC) from up to 12 exchanges.
Spot volume is included only if perp volume is available for the same pair, ensuring consistency.
Volume can be measured in coin units or USD (volume × spot price).
Percentage Change:
Calculates the percentage change in spot and perp volumes from the previous bar:
Percentage Change = ((Current Volume − Previous Volume) / Previous Volume) ×100
This focuses on relative momentum, making spot and perp volumes directly comparable.
Visualization:
Spot volume % change is plotted as a blue line, and perp volume % change as a red line, both with a linewidth of 1.
Who Should Use It
Crypto Traders: To understand spot vs. perp market dynamics across exchanges.
Momentum Traders: To spot which market is driving price moves via volume divergences.
Scalpers/Day Traders: For identifying short-term shifts in market activity.
Analysts: To study liquidity and sentiment in crypto markets.
How to Use It
Blue line: Spot volume % change.
Red line: Perp volume % change.
Look for divergences (e.g., a sharp rise in the red line but not the blue line suggests perp markets are leading).
Combine with Price:
Use alongside price charts to confirm trends or spot potential reversals.
Context
Spot markets reflect actual asset trading, while perp markets, with leverage, attract speculative activity and often show higher volumes. This indicator uses percentage change to compare their momentum, helping traders identify market leadership and divergences. For example, a 50% increase in both spot and perp volumes plots at the same level, making it easy to see relative shifts across exchanges.
Stochastic Fusion Elite [trade_lexx]📈 Stochastic Fusion Elite is your reliable trading assistant!
📊 What is Stochastic Fusion Elite ?
Stochastic Fusion Elite is a trading indicator based on a stochastic oscillator. It analyzes the rate of price change and generates buy or sell signals based on various technical analysis methods.
💡 The main components of the indicator
📊 Stochastic oscillator (K and D)
Stochastic shows the position of the current price relative to the price range for a certain period. Values above 80 indicate overbought (an early sale is possible), and values below 20 indicate oversold (an early purchase is possible).
📈 Moving Averages (MA)
The indicator uses 10 different types of moving averages to smooth stochastic lines.:
- SMA: Simple moving average
- EMA: Exponential moving average
- WMA: Weighted moving average
- HMA: Moving Average Scale
- KAMA: Kaufman Adaptive Moving Average
- VWMA: Volume-weighted moving average
- ALMA: Arnaud Legoux Moving Average
- TEMA: Triple exponential moving average
- ZLEMA: zero delay exponential moving average
- DEMA: Double exponential moving average
The choice of the type of moving average affects the speed of the indicator's response to market changes.
🎯 Bollinger Bands (BB)
Bands around the moving average that widen and narrow depending on volatility. They help determine when the stochastic is out of the normal range.
🔄 Divergences
Divergences show discrepancies between price and stochastic:
- Bullish divergence: price is falling and stochastic is rising — an upward reversal is possible
- Bearish divergence: the price is rising, and stochastic is falling — a downward reversal is possible
🔍 Indicator signals
1️⃣ KD signals (K and D stochastic lines)
- Buy signal:
- What happens: the %K line crosses the %D line from bottom to top
- What does it look like: a green triangle with the label "KD" under the chart and the label "Buy" below the bar
- What does this mean: the price is gaining an upward momentum, growth is possible
- Sell signal:
- What happens: the %K line crosses the %D line from top to bottom
- What it looks like: a red triangle with the label "KD" above the chart and the label "Sell" above the bar
- What does this mean: the price is losing its upward momentum, possibly falling
2️⃣ Moving Average Signals (MA)
- Buy Signal:
- What happens: stochastic crosses the moving average from bottom to top
- What it looks like: a green triangle with the label "MA" under the chart and the label "Buy" below the bar
- What does this mean: stochastic is starting to accelerate upward, price growth is possible
- Sell signal:
- What happens: stochastic crosses the moving average from top to bottom
- What it looks like: a red triangle with the label "MA" above the chart and the label "Sell" above the bar
- What does this mean: stochastic is starting to accelerate downwards, a price drop is possible
3️⃣ Bollinger Band Signals (BB)
- Buy signal:
- What happens: stochastic crosses the lower Bollinger band from bottom to top
- What it looks like: a green triangle with the label "BB" under the chart and the label "Buy" below the bar
- What does this mean: stochastic was too low and is now starting to recover
- Sell signal:
- What happens: Stochastic crosses the upper Bollinger band from top to bottom
- What it looks like: a red triangle with a "BB" label above the chart and a "Sell" label above the bar
- What does this mean: stochastic was too high and is now starting to decline
4️⃣ Divergence Signals (Div)
- Buy Signal (Bullish Divergence):
- What's happening: the price is falling, and stochastic is forming higher lows
- What it looks like: a green triangle with a "Div" label under the chart and a "Buy" label below the bar
- What does this mean: despite the falling price, the momentum is already changing in an upward direction
- Sell signal (bearish divergence):
- What's going on: the price is rising, and stochastic is forming lower highs
- What it looks like: a red triangle with a "Div" label above the chart and a "Sell" label above the bar
- What does this mean: despite the price increase, the momentum is already weakening
🛠️ Filters to filter out false signals
1️⃣ Minimum distance between the signals
- What it does: sets the minimum number of candles between signals
- Why it is needed: prevents signals from being too frequent during strong market fluctuations
- How to set it up: Set the number from 0 and above (default: 5)
2️⃣ "Waiting for the opposite signal" mode
- What it does: waits for a signal in the opposite direction before generating a new signal
- Why you need it: it helps you not to miss important trend reversals
- How to set up: just turn the function on or off
3️⃣ Filter by stochastic levels
- What it does: generates signals only when the stochastic is in the specified ranges
- Why it is needed: it helps to catch the moments when the market is oversold or overbought
- How to set up:
- For buy signals: set a range for oversold (for example, 1-20)
- For sell signals: set a range for overbought (for example, 80-100)
4️⃣ MFI filter
- What it does: additionally checks the values of the cash flow index (MFI)
- Why it is needed: confirms stochastic signals with cash flow data
- How to set it up:
- For buy signals: set the range for oversold MFI (for example, 1-25)
- For sell signals: set the range for overbought MFI (for example, 75-100)
5️⃣ The RSI filter
- What it does: additionally checks the RSI values to confirm the signals
- Why it is needed: adds additional confirmation from another popular indicator
- How to set up:
- For buy signals: set the range for oversold MFI (for example, 1-30)
- For sell signals: set the range for overbought MFI (for example, 70-100)
🔄 Signal combination modes
1️⃣ Normal mode
- How it works: all signals (KD, MA, BB, Div) work independently of each other
- When to use it: for general market analysis or when learning how to work with the indicator
2️⃣ "AND" Mode ("AND Mode")
- How it works: the alarm appears only when several conditions are triggered simultaneously
- Combination options:
- KD+MA: signals from the KD and moving average lines
- KD+BB: signals from KD lines and Bollinger bands
- KD+Div: signals from the KD and divergence lines
- KD+MA+BB: three signals simultaneously
- KD+MA+Div: three signals at the same time
- KD+BB+Div: three signals at the same time
- KD+MA+BB+Div: all four signals at the same time
- When to use: for more reliable but rare signals
🔌 Connecting to trading strategies
The indicator can be connected to your trading strategies using 6 different channels.:
1. Connector KD signals: connects only the signals from the intersection of lines K and D
2. Connector MA signals: connects only signals from moving averages
3. Connector BB signal: connects only the signals from the Bollinger bands
4. Connector divergence signals: connects only divergence signals
5. Combined Connector: connects any signals
6. Connector for "And" mode: connects only combined signals
🔔 Setting up alerts
The indicator can send alerts when alarms appear.:
- Alerts for KD: when the %K line crosses the %D line
- Alerts for MA: when stochastic crosses the moving average
- Alerts for BB: when stochastic crosses the Bollinger bands
- Divergence alerts: when a divergence is detected
- Combined alerts: for all types of alarms
- Alerts for "And" mode: for combined signals
🎭 What does the indicator look like on the chart ?
- Main lines K and D: blue and orange lines
- Overbought/oversold levels: horizontal lines at levels 20 and 80
- Middle line: dotted line at level 50
- Stochastic Moving Average: yellow line
- Bollinger bands: green lines around the moving average
- Signals: green and red triangles with corresponding labels
📚 How to start using Stochastic Fusion Elite
1️⃣ Initial setup
- Add an indicator to your chart
- Select the types of signals you want to use (KD, MA, BB, Div)
- Adjust the period and smoothing for the K and D lines
2️⃣ Filter settings
- Set the distance between the signals to get rid of unnecessary noise
- Adjust stochastic, MFI and RSI levels depending on the volatility of your asset
- If you need more reliable signals, turn on the "Waiting for the opposite signal" mode.
3️⃣ Operation mode selection
- First, use the standard mode to see all possible signals.
- When you get comfortable, try the "And" mode for rarer signals.
4️⃣ Setting up Alerts
- Select the types of signals you want to be notified about
- Set up alerts for these types of signals
5️⃣ Verification and adaptation
- Check the operation of the indicator on historical data
- Adjust the parameters for a specific asset
- Adapt the settings to your trading style
🌟 Usage examples
For trend trading
- Use the KD and MA signals in the direction of the main trend
- Set the distance between the signals
- Set stricter levels for filters
For trading in a sideways range
- Use BB signals to detect bounces from the range boundaries
- Use a stochastic level filter to confirm overbought/oversold conditions
- Adjust the Bollinger bands according to the width of the range
To determine the pivot points
- Pay attention to the divergence signals
- Set the distance between the signals
- Check the MFI and RSI filters for additional confirmation
Highest High Line with Multi-Timeframe Supertrend and RSIOverview:
This powerful indicator combines three essential elements for traders:
Highest High Line – Tracks the highest price over a customizable lookback period across different timeframes.
Multi-Timeframe Supertrend – Displays Supertrend values and trend directions for multiple timeframes simultaneously.
Relative Strength Index (RSI) – Shows RSI values across different timeframes for momentum analysis.
Features:
✅ Customizable Highest High Line:
Selectable timeframes: Daily, Weekly, Monthly, Quarterly, Yearly
Adjustable lookback period
✅ Multi-Timeframe Supertrend:
Supports 1min, 5min, 10min, 15min, 30min, 1H, Daily, Weekly, Monthly, Quarterly, Yearly
ATR-based calculation with configurable ATR period and multiplier
Identifies bullish (green) & bearish (red) trends
✅ Multi-Timeframe RSI:
Calculates RSI for the same timeframes as Supertrend
Overbought (≥70) and Oversold (≤30) signals with color coding
✅ Comprehensive Table Display:
A clean, structured table in the bottom-right corner
Displays Supertrend direction, value, and RSI for all timeframes
Helps traders quickly assess trend and momentum alignment
How to Use:
Use the Highest High Line to identify key resistance zones.
Confirm trend direction with Multi-Timeframe Supertrend.
Check RSI values to avoid overbought/oversold conditions before entering trades.
Align multiple timeframes for stronger confirmation of trend shifts.
Ideal For:
✅ Scalpers (lower timeframes: 1m–30m)
✅ Swing Traders (higher timeframes: 1H–D)
✅ Position Traders (Weekly, Monthly, Quarterly)
💡 Tip: Look for Supertrend & RSI confluence across multiple timeframes for higher probability setups.
CCI with Zero Signal by Edwin KCCI with Zero Signal by Edwin K is a custom Commodity Channel Index (CCI) indicator designed for traders to analyze market trends and momentum more effectively. It combines the CCI calculation with a visually distinct histogram and color-coded candlestick bars for enhanced clarity and decision-making.
Key Features:
CCI Line:
Plots the CCI line based on the specified length (default: 21).
Helps identify overbought or oversold conditions, momentum shifts, and trend reversals.
Zero Signal Line:
A horizontal line at 0 serves as a reference point to distinguish between bullish and bearish momentum.
Histogram:
Displays a histogram that reflects the CCI's values.
Histogram bars change colors dynamically based on their relation to the zero line and the trend's direction.
Green/Lime: Positive momentum (above zero).
Red/Maroon: Negative momentum (below zero).
Candlestick Coloring:
Automatically paints candlesticks based on the histogram's color.
Provides an intuitive visual cue for momentum shifts directly on the price chart.
Use Cases:
Trend Confirmation: Use the histogram and candlestick colors to confirm the strength and direction of trends.
Momentum Shifts: Identify transitions between bullish and bearish momentum when the CCI crosses the zero line.
Entry and Exit Points: Combine this indicator with other tools to pinpoint optimal trade entries and exits.
This indicator offers a user-friendly yet powerful visualization of the CCI, making it an excellent tool for traders aiming to enhance their technical analysis.
Multi-Indicator Trading DashboardMulti-Indicator Trading Dashboard: Comprehensive Analysis and Actionable Signals
This Pine Script indicator, "Multi-Indicator Trading Dashboard," provides a comprehensive overview of key market indicators and generates actionable trading signals, all presented in a clear, easy-to-read table format on your TradingView chart.
Key Features:
Real-time Indicator Analysis: The dashboard displays real-time values and signals for:
RSI (Relative Strength Index): Tracks overbought and oversold conditions.
MACD (Moving Average Convergence Divergence): Identifies trend changes and momentum.
ADX (Average Directional Index): Measures trend strength.
Volatility (ATR-based): Estimates volatility as a percentage, acting as a VIX proxy for single-symbol charts.
Trend Determination: Analyzes 20, 50, and 200-period EMAs to provide a clear trend assessment (Strong Bullish, Cautious Bullish, Cautious Bearish, Strong Bearish).
Combined Trading Signals: Integrates signals from RSI, MACD, ADX, and trend analysis to generate a combined "Buy," "Sell," or "Neutral" action signal.
User-Friendly Table Display: Presents all information in a neatly organized table, positioned at the top-right of your chart.
Visual Chart Overlays: Plots 20, 50, and 200-period EMAs directly on the chart for visual trend confirmation.
Background Color Alerts: Colors the chart's background based on the "Buy" or "Sell" action signal for quick visual cues.
Customizable Inputs: Allows you to adjust key parameters like RSI lengths, MACD settings, ADX thresholds, and EMA periods.
How It Works:
Indicator Calculations: The script calculates RSI, MACD, ADX, and a volatility proxy (ATR) using standard Pine Script functions.
Trend Analysis: It compares 20, 50, and 200-period EMAs to determine the overall trend direction.
Individual Signal Generation: It generates individual "Buy," "Sell," or "Neutral" signals based on RSI, MACD, and ADX values.
Combined Signal Logic: It combines the individual signals and trend analysis, assigning a "Buy" or "Sell" action only when at least two indicators align.
Table Display: It creates a table and populates it with the calculated values, signals, and trend information.
Chart Overlays: It plots the EMAs on the chart and colors the background based on the combined action signal.
Use Cases:
Quick Market Overview: Get a snapshot of key market indicators and trend direction at a glance.
Confirmation Tool: Use the combined signals to confirm your existing trading strategies.
Educational Purpose: Learn how different indicators interact and influence trading decisions.
Automated Alerting: Set up alerts based on the "Buy" or "Sell" action signals.
Customization:
Adjust the input parameters to fine-tune the indicator's sensitivity to your trading style and the specific market you're analyzing.
Disclaimer:
This indicator is for informational and educational purposes only and should not be considered financial advice. Always conduct thorough research and consult with 1 a qualified professional before making any 2 trading decisions.
Multi-Oscillator Adaptive Kernel | AlphaAlgosMulti-Oscillator Adaptive Kernel | AlphaAlgos
Overview
The Multi-Oscillator Adaptive Kernel (MOAK) is an advanced technical analysis tool that combines multiple oscillators through sophisticated kernel-based smoothing algorithms. This indicator is designed to provide clearer trend signals while filtering out market noise, offering traders a comprehensive view of market momentum across multiple timeframes.
Key Features
• Fusion of multiple technical oscillators (RSI, Stochastic, MFI, CCI)
• Advanced kernel smoothing technology with three distinct mathematical models
• Customizable sensitivity and lookback periods
• Clear visual signals for trend shifts and reversals
• Overbought/oversold zones for precise entry and exit timing
• Adaptive signal that responds to varying market conditions
Technical Components
The MOAK indicator utilizes a multi-layer approach to signal generation:
1. Oscillator Fusion
The core of the indicator combines normalized readings from up to four popular oscillators:
• RSI (Relative Strength Index) - Measures the speed and change of price movements
• Stochastic - Compares the closing price to the price range over a specific period
• MFI (Money Flow Index) - Volume-weighted RSI that includes trading volume
• CCI (Commodity Channel Index) - Measures current price level relative to an average price
2. Kernel Smoothing
The combined oscillator data is processed through one of three kernel functions:
• Exponential Kernel - Provides stronger weighting to recent data with exponential decay
• Linear Kernel - Applies a linear weighting from most recent to oldest data points
• Gaussian Kernel - Uses a bell curve distribution that helps filter out extreme values
3. Dual Signal Lines
• Fast Signal Line - Responds quickly to price changes
• Slow Signal Line - Provides confirmation and shows the underlying trend direction
Configuration Options
Oscillator Selection:
• Enable/disable each oscillator (RSI, Stochastic, MFI, CCI)
• Customize individual lookback periods for each oscillator
Kernel Settings:
• Kernel Type - Choose between Exponential, Linear, or Gaussian mathematical models
• Kernel Length - Adjust the smoothing period (higher values = smoother line)
• Sensitivity - Fine-tune the indicator's responsiveness (higher values = more responsive)
Display Options:
• Color Bars - Toggle price bar coloring based on indicator direction
How to Interpret the Indicator
Signal Line Direction:
• Upward movement (teal) indicates bullish momentum
• Downward movement (magenta) indicates bearish momentum
Trend Shifts:
• Small circles mark the beginning of new uptrends
• X-marks indicate the start of new downtrends
Overbought/Oversold Conditions:
• Values above +50 suggest overbought conditions (potential reversal or pullback)
• Values below -50 suggest oversold conditions (potential reversal or bounce)
Trading Strategies
Trend Following:
• Enter long positions when the signal line turns teal and shows an uptrend
• Enter short positions when the signal line turns magenta and shows a downtrend
• Use the slow signal line (area fill) as confirmation of the underlying trend
Counter-Trend Trading:
• Look for divergences between price and the indicator
• Consider profit-taking when the indicator reaches overbought/oversold areas
• Wait for trend shift signals before entering counter-trend positions
Multiple Timeframe Analysis:
• Use the indicator across different timeframes for confirmation
• Higher timeframe signals carry more weight than lower timeframe signals
Best Practices
• Experiment with different kernel types for various market conditions
• Gaussian kernels often work well in ranging markets
• Exponential kernels can provide earlier signals in trending markets
• Combine with volume analysis for higher probability trades
• Use appropriate stop-loss levels as the indicator does not guarantee price movements
This indicator is provided as-is with no guarantees of profit. Always use proper risk management when trading with any technical indicator. Nothing is financial advise.
Smart Liquidity Wave [The_lurker]"Smart Liquidity Wave" هو مؤشر تحليلي متطور يهدف لتحديد نقاط الدخول والخروج المثلى بناءً على تحليل السيولة، قوة الاتجاه، وإشارات السوق المفلترة. يتميز المؤشر بقدرته على تصنيف الأدوات المالية إلى أربع فئات سيولة (ضعيفة، متوسطة، عالية، عالية جدًا)، مع تطبيق شروط مخصصة لكل فئة تعتمد على تحليل الموجات السعرية، الفلاتر المتعددة، ومؤشر ADX.
فكرة المؤشر
الفكرة الأساسية هي الجمع بين قياس السيولة اليومية الثابتة وتحليل ديناميكي للسعر باستخدام فلاتر متقدمة لتوليد إشارات دقيقة. المؤشر يركز على تصفية الضوضاء في السوق من خلال طبقات متعددة من التحليل، مما يجعله أداة ذكية تتكيف مع الأدوات المالية المختلفة بناءً على مستوى سيولتها.
طريقة عمل المؤشر
1- قياس السيولة:
يتم حساب السيولة باستخدام متوسط حجم التداول على مدى 14 يومًا مضروبًا في سعر الإغلاق، ويتم ذلك دائمًا على الإطار الزمني اليومي لضمان ثبات القيمة بغض النظر عن الإطار الزمني المستخدم في الرسم البياني.
يتم تصنيف السيولة إلى:
ضعيفة: أقل من 5 ملايين (قابل للتعديل).
متوسطة: من 5 إلى 20 مليون.
عالية: من 20 إلى 50 مليون.
عالية جدًا: أكثر من 50 مليون.
هذا الثبات في القياس يضمن أن تصنيف السيولة لا يتغير مع تغير الإطار الزمني، مما يوفر أساسًا موثوقًا للإشارات.
2- تحليل الموجات السعرية:
يعتمد المؤشر على تحليل الموجات باستخدام متوسطات متحركة متعددة الأنواع (مثل SMA، EMA، WMA، HMA، وغيرها) يمكن للمستخدم اختيارها وتخصيص فتراتها ، يتم دمج هذا التحليل مع مؤشرات إضافية مثل RSI (مؤشر القوة النسبية) وMFI (مؤشر تدفق الأموال) بوزن محدد (40% للموجات، 30% لكل من RSI وMFI) للحصول على تقييم شامل للاتجاه.
3- الفلاتر وطريقة عملها:
المؤشر يستخدم نظام فلاتر متعدد الطبقات لتصفية الإشارات وتقليل الضوضاء، وهي من أبرز الجوانب المخفية التي تعزز دقته:
الفلتر الرئيسي (Main Filter):
يعمل على تنعيم التغيرات السعرية السريعة باستخدام معادلة رياضية تعتمد على تحليل الإشارات (Signal Processing).
يتم تطبيقه على السعر لاستخراج الاتجاهات الأساسية بعيدًا عن التقلبات العشوائية، مع فترة زمنية قابلة للتعديل (افتراضي: 30).
يستخدم تقنية مشابهة للفلاتر عالية التردد (High-Pass Filter) للتركيز على الحركات الكبيرة.
الفلتر الفرعي (Sub Filter):
يعمل كطبقة ثانية للتصفية، مع فترة أقصر (افتراضي: 12)، لضبط الإشارات بدقة أكبر.
يستخدم معادلات تعتمد على الترددات المنخفضة للتأكد من أن الإشارات الناتجة تعكس تغيرات حقيقية وليست مجرد ضوضاء.
إشارة الزناد (Signal Trigger):
يتم تطبيق متوسط متحرك على نتائج الفلتر الرئيسي لتوليد خط إشارة (Signal Line) يُقارن مع عتبات محددة للدخول والخروج.
يمكن تعديل فترة الزناد (افتراضي: 3 للدخول، 5 للخروج) لتسريع أو تبطيء الإشارات.
الفلتر المربع (Square Filter):
خاصية مخفية تُفعّل افتراضيًا تعزز دقة الفلاتر عن طريق تضييق نطاق التذبذبات المسموح بها، مما يقلل من الإشارات العشوائية في الأسواق المتقلبة.
4- تصفية الإشارات باستخدام ADX:
يتم استخدام مؤشر ADX كفلتر نهائي للتأكد من قوة الاتجاه قبل إصدار الإشارة:
ضعيفة ومتوسطة: دخول عندما يكون ADX فوق 40، خروج فوق 50.
عالية: دخول فوق 40، خروج فوق 55.
عالية جدًا: دخول فوق 35، خروج فوق 38.
هذه العتبات قابلة للتعديل، مما يسمح بتكييف المؤشر مع استراتيجيات مختلفة.
5- توليد الإشارات:
الدخول: يتم إصدار إشارة شراء عندما تنخفض خطوط الإشارة إلى ما دون عتبة محددة (مثل -9) مع تحقق شروط الفلاتر، السيولة، وADX.
الخروج: يتم إصدار إشارة بيع عندما ترتفع الخطوط فوق عتبة (مثل 109 أو 106 حسب الفئة) مع تحقق الشروط الأخرى.
تُعرض الإشارات بألوان مميزة (أزرق للدخول، برتقالي للضعيفة والمتوسطة، أحمر للعالية والعالية جدًا) وبثلاثة أحجام (صغير، متوسط، كبير).
6- عرض النتائج:
يظهر مستوى السيولة الحالي في جدول في أعلى يمين الرسم البياني، مما يتيح للمستخدم معرفة فئة الأصل بسهولة.
7- دعم التنبيهات:
تنبيهات فورية لكل فئة سيولة، مما يسهل التداول الآلي أو اليدوي.
%%%%% الجوانب المخفية في الكود %%%%%
معادلات الفلاتر المتقدمة: يستخدم المؤشر معادلات رياضية معقدة مستوحاة من معالجة الإشارات لتنعيم البيانات واستخراج الاتجاهات، مما يجعله أكثر دقة من المؤشرات التقليدية.
التكيف التلقائي: النظام يضبط نفسه داخليًا بناءً على التغيرات في السعر والحجم، مع عوامل تصحيح مخفية (مثل معامل التنعيم في الفلاتر) للحفاظ على الاستقرار.
التوزيع الموزون: الدمج بين الموجات، RSI، وMFI يتم بأوزان محددة (40%، 30%، 30%) لضمان توازن التحليل، وهي تفاصيل غير ظاهرة مباشرة للمستخدم لكنها تؤثر على النتائج.
الفلتر المربع: خيار مخفي يتم تفعيله افتراضيًا لتضييق نطاق الإشارات، مما يقلل من التشتت في الأسواق ذات التقلبات العالية.
مميزات المؤشر
1- فلاتر متعددة الطبقات: تضمن تصفية الضوضاء وإنتاج إشارات موثوقة فقط.
2- ثبات السيولة: قياس السيولة اليومي يجعل التصنيف متسقًا عبر الإطارات الزمنية.
3- تخصيص شامل: يمكن تعديل حدود السيولة، عتبات ADX، فترات الفلاتر، وأنواع المتوسطات المتحركة.
4- إشارات مرئية واضحة: تصميم بصري يسهل التفسير مع تنبيهات فورية.
5- تقليل الإشارات الخاطئة: الجمع بين الفلاتر وADX يعزز الدقة ويقلل من التشتت.
إخلاء المسؤولية
لا يُقصد بالمعلومات والمنشورات أن تكون، أو تشكل، أي نصيحة مالية أو استثمارية أو تجارية أو أنواع أخرى من النصائح أو التوصيات المقدمة أو المعتمدة من TradingView.
#### **What is the Smart Liquidity Wave Indicator?**
"Smart Liquidity Wave" is an advanced analytical indicator designed to identify optimal entry and exit points based on liquidity analysis, trend strength, and filtered market signals. It stands out with its ability to categorize financial instruments into four liquidity levels (Weak, Medium, High, Very High), applying customized conditions for each category based on price wave analysis, multi-layered filters, and the ADX (Average Directional Index).
#### **Concept of the Indicator**
The core idea is to combine a stable daily liquidity measurement with dynamic price analysis using sophisticated filters to generate precise signals. The indicator focuses on eliminating market noise through multiple analytical layers, making it an intelligent tool that adapts to various financial instruments based on their liquidity levels.
#### **How the Indicator Works**
1. **Liquidity Measurement:**
- Liquidity is calculated using the 14-day average trading volume multiplied by the closing price, always based on the daily timeframe to ensure value consistency regardless of the chart’s timeframe.
- Liquidity is classified as:
- **Weak:** Less than 5 million (adjustable).
- **Medium:** 5 to 20 million.
- **High:** 20 to 50 million.
- **Very High:** Over 50 million.
- This consistency in measurement ensures that liquidity classification remains unchanged across different timeframes, providing a reliable foundation for signals.
2. **Price Wave Analysis:**
- The indicator relies on wave analysis using various types of moving averages (e.g., SMA, EMA, WMA, HMA, etc.), which users can select and customize in terms of periods.
- This analysis is integrated with additional indicators like RSI (Relative Strength Index) and MFI (Money Flow Index), weighted specifically (40% waves, 30% RSI, 30% MFI) to provide a comprehensive trend assessment.
3. **Filters and Their Functionality:**
- The indicator employs a multi-layered filtering system to refine signals and reduce noise, a key hidden feature that enhances its accuracy:
- **Main Filter:**
- Smooths rapid price fluctuations using a mathematical equation rooted in signal processing techniques.
- Applied to price data to extract core trends away from random volatility, with an adjustable period (default: 30).
- Utilizes a technique similar to high-pass filters to focus on significant movements.
- **Sub Filter:**
- Acts as a secondary filtering layer with a shorter period (default: 12) for finer signal tuning.
- Employs low-frequency-based equations to ensure resulting signals reflect genuine changes rather than mere noise.
- **Signal Trigger:**
- Applies a moving average to the main filter’s output to generate a signal line, compared against predefined entry and exit thresholds.
- Trigger period is adjustable (default: 3 for entry, 5 for exit) to speed up or slow down signals.
- **Square Filter:**
- A hidden feature activated by default, enhancing filter precision by narrowing the range of permissible oscillations, reducing random signals in volatile markets.
4. **Signal Filtering with ADX:**
- ADX is used as a final filter to confirm trend strength before issuing signals:
- **Weak and Medium:** Entry when ADX exceeds 40, exit above 50.
- **High:** Entry above 40, exit above 55.
- **Very High:** Entry above 35, exit above 38.
- These thresholds are adjustable, allowing the indicator to adapt to different trading strategies.
5. **Signal Generation:**
- **Entry:** A buy signal is triggered when signal lines drop below a specific threshold (e.g., -9) and conditions for filters, liquidity, and ADX are met.
- **Exit:** A sell signal is issued when signal lines rise above a threshold (e.g., 109 or 106, depending on the category) with all conditions satisfied.
- Signals are displayed in distinct colors (blue for entry, orange for Weak/Medium, red for High/Very High) and three sizes (small, medium, large).
6. **Result Display:**
- The current liquidity level is shown in a table at the top-right of the chart, enabling users to easily identify the asset’s category.
7. **Alert Support:**
- Instant alerts are provided for each liquidity category, facilitating both automated and manual trading.
#### **Hidden Aspects in the Code**
- **Advanced Filter Equations:** The indicator uses complex mathematical formulas inspired by signal processing to smooth data and extract trends, making it more precise than traditional indicators.
- **Automatic Adaptation:** The system internally adjusts based on price and volume changes, with hidden correction factors (e.g., smoothing coefficients in filters) to maintain stability.
- **Weighted Distribution:** The integration of waves, RSI, and MFI uses fixed weights (40%, 30%, 30%) for balanced analysis, a detail not directly visible but impactful on results.
- **Square Filter:** A hidden option, enabled by default, narrows signal range to minimize dispersion in high-volatility markets.
#### **Indicator Features**
1. **Multi-Layered Filters:** Ensures noise reduction and delivers only reliable signals.
2. **Liquidity Stability:** Daily liquidity measurement keeps classification consistent across timeframes.
3. **Comprehensive Customization:** Allows adjustments to liquidity thresholds, ADX levels, filter periods, and moving average types.
4. **Clear Visual Signals:** User-friendly design with easy-to-read visuals and instant alerts.
5. **Reduced False Signals:** Combining filters and ADX enhances accuracy and minimizes clutter.
#### **Disclaimer**
The information and publications are not intended to be, nor do they constitute, financial, investment, trading, or other types of advice or recommendations provided or endorsed by TradingView.
Session Profile AnalyzerWhat’s This Thing Do?
Hey there, trader! Meet the Session Profile Analyzer (SPA) your new go-to pal for breaking down market action within your favorite trading sessions. It’s an overlay indicator that mixes Rotation Factor (RF), Average Subperiod Range (ASPR), Volume Value Area Range (VOLVAR), and TPO Value Area Range (TPOVAR) into one tidy little toolkit. Think of it as your market vibe checker momentum, volatility, and key levels, all served up with a grin.
The Cool Stuff It Does:
Rotation Factor (RF) : Keeps tabs on whether the market’s feeling bullish, bearish, or just chilling. It’s like a mood ring for price action shows “UP ↑,” “DOWN ↓,” or “NONE ↔.”
ASPR : Averages out the range of your chosen blocks. Big swings? Tiny wiggles? This tells you the session’s energy level.
VOLVAR : Dives into volume to find where the action’s at, with a smart twist it adjusts price levels based on the session’s size and tiny timeframe moves (capped at 128 so your chart doesn’t cry).
TPOVAR : Grabs lower timeframe data to spot where price hung out the most, TPO-style. Value zones, anyone?
Dynamic Precision : No ugly decimal overload SPA matches your asset’s style (2 decimals for BTC, 5 for TRX, you get it).
How to Play With It:
Session Start/End : Pick your trading window (say, 0930-2200) and a timezone (America/New_York, or wherever you’re at).
Block Size : Set the chunk size for RF and ASPR like 30M if you’re into half-hour vibes.
Value Area Timeframe : Go micro with something like 1S for VOLVAR and TPOVAR precision.
Label : Size it (small to huge), color it (white, neon pink, whatever), and slap it where you want (start, mid, end).
How It All Works (No PhD Required):
RF : Imagine breaking your session into blocks (via Block Size). For each block, SPA checks if the high beats the last high (+1) or not (0), and if the low dips below the last low (-1) or not (0). Add those up, and boom positive RF means upward vibes, negative means downward, near zero is “meh.” Use it to catch trends or spot when the market’s napping.
ASPR : Takes those same blocks, measures high-to-low range each time, and averages them. It’s your volatility pulse big ASPR = wild ride, small ASPR = snooze fest. Great for sizing up session action.
VOLVAR : Here’s the fun part. It takes the session’s full range (high minus low), divides it by the average range of your tiny Value Area Timeframe bars (e.g., 1S), and picks a sensible number of price levels capped at 128 so it doesn’t overthink. Then it bins volume into those levels, finds the busiest price (POC), and grows a 70% value area around it. Perfect for spotting where the big players parked their cash.
TPOVAR : Grabs midpoints from those tiny timeframe bars, sorts them, and snips off the top and bottom 15% to find the 70% “value zone” where price chilled the most. Think of it as the market’s comfort zone great for support/resistance hunting.
Why You’ll Like It:
Whether you’re scalping crypto, swinging forex, or dissecting stocks, SPA’s got your back. Use RF to catch momentum shifts like jumping on an “UP ↑” trend or fading a “DOWN ↓” exhaustion. ASPR’s your secret weapon for sizing up trades: a big ASPR (say, 100 on BTC) means you can aim for juicy targets (like 1-2x ASPR) or set invalidations tight when it’s tiny (e.g., 0.001 on TRX) to dodge chop. VOLVAR and TPOVAR are your level-finders nail those key zones where price loves to bounce or break, perfect for entries, stops, or profit grabs. It’s like having a trading co-pilot who’s chill but knows their stuff.
Heads-Up:
Load enough history for those micro timeframes to shine (1S needs some bars to work with).
Keeps things light won’t bog down your chart even with decent-sized sessions.
Let’s Roll:
Slap SPA on your chart, tweak it to your style, and watch it spill the beans on your session. Happy trading, fam may your pips be plenty and your losses few!
Schaff Trend Cycle (STC)The STC (Schaff Trend Cycle) indicator is a momentum oscillator that combines elements of MACD and stochastic indicators to identify market cycles and potential trend reversals.
Key features of the STC indicator:
Oscillates between 0 and 100, similar to a stochastic oscillator
Values above 75 generally indicate overbought conditions
Values below 25 generally indicate oversold conditions
Signal line crossovers (above 75 or below 25) can suggest potential entry/exit points
Faster and more responsive than traditional MACD
Designed to filter out market noise and identify cyclical trends
Traders typically use the STC indicator to:
Identify potential trend reversals
Confirm existing trends
Generate buy/sell signals when combined with other technical indicators
Filter out false signals in choppy market conditions
This STC implementation includes multiple smoothing options that act as filters:
None: Raw STC values without additional smoothing, which provides the most responsive but potentially noisier signals.
EMA Smoothing: Applies a 3-period Exponential Moving Average to reduce noise while maintaining reasonable responsiveness (default).
Sigmoid Smoothing: Transforms the STC values using a sigmoid (S-curve) function, creating more gradual transitions between signals and potentially reducing whipsaw trades.
Digital (Schmitt Trigger) Smoothing: Creates a binary output (0 or 100) with built-in hysteresis to prevent rapid switching.
The STC indicator uses dynamic color coding to visually represent momentum:
Green: When the STC value is above its 5-period EMA, indicating positive momentum
Red: When the STC value is below its 5-period EMA, indicating negative momentum
The neutral zone (25-75) is highlighted with a light gray fill to clearly distinguish between normal and extreme readings.
Alerts:
Bullish Signal Alert:
The STC has been falling
It bottoms below the 25 level
It begins to rise again
This pattern helps confirm potential uptrend starts with higher reliability.
Bearish Signal Alert:
The STC has been rising
It peaks above the 75 level
It begins to decline
This pattern helps identify potential downtrend starts.
Multi-Timeframe Stochastic RSI ArrowsMulti-Timeframe Stochastic RSI Arrows Indicator by The Venetian
Dear Moderators before you torch me alive theres nothing groundbreaking just very handy indicator for some users.
This indicator provides traders with a jet fighter-style heads-up display for market momentum across multiple timeframes. By displaying Stochastic RSI directional arrows for 12 different timeframes simultaneously, it offers a comprehensive view of market conditions without requiring multiple chart windows.
How It Works
The indicator calculates the Stochastic RSI for each of 12 common timeframes (1m to 3M) and represents directional movements with intuitive arrows:
- ▲ Green up arrow = Rising momentum
- ▼ Red down arrow = Falling momentum
- ◄► Yellow horizontal arrows = Flat/sideways momentum
- ► Gray right arrow = Just peaked (crossed above overbought)
- ◄ Gray left arrow = Just bottomed (crossed below oversold)
Each timeframe's status appears with its label (e.g., "1m ▲") in a clean, vertically-stacked display using ATR-based spacing to maintain consistent visual appearance regardless of price scale.
Key Features
- ATR-Based Spacing : Uses Average True Range to maintain consistent distances between labels even as chart scale changes
- Multi-Timeframe Analysis: Easily spot divergences and confluences across timeframes (1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 1D, 1W, 1M, 3M)
- Sensitivity Control: Adjust flat detection sensitivity to filter out noise
- Customisable Appearance: Modify arrow size, vertical spacing, and show/hide timeframe labels
- Overbought/Oversold Detection: Highlights when momentum has peaked or bottomed at extreme levels
- Trading Applications
- Trend Alignment: Quickly identify when multiple timeframes align in the same direction
- Divergence Detection: Spot when shorter timeframes begin to shift against longer ones
- Entry/Exit Timing: Use crossovers of significant timeframes as potential signals
- Market Context: Maintain awareness of the bigger picture while trading shorter timeframes
This indicator doesn't break new ground technically but excels in presenting complex multi-timeframe information in a clean, actionable format — much like a pilot's heads-up display provides critical information at a glance. The ATR-based positioning ensures consistent visibility across different instruments and market conditions.
Great effort has been made for this script to adhere to TradingView's Pine Script house rules and focuses on trader usability rather than introducing novel technical concepts.
Jigga-SectorTrendViewThe Jigga-SectorView script is indicator designed to analyze and visualize sector trends based on given input. Based on input of multiple sector indices, calculates key technical values, and presents a structured summary in a table.
Calculating Sector Strength & Momentum:
For each selected symbol
Step 1 - 52-week lowest low is fetched.
Step 2 - Daily closing price is retrieved.
Step 3 - A crossover between 50-day EMA and 200-day EMA determines trend shifts.
Step 4 - Percentage difference from the identified level is calculated.
Output:
A bottom-right table is created with sector-wise trend insights which shows Symbol name and how much its away from SL in percentage terms.
Elastic Volume-Weighted Student-T TensionOverview
The Elastic Volume-Weighted Student-T Tension Bands indicator dynamically adapts to market conditions using an advanced statistical model based on the Student-T distribution. Unlike traditional Bollinger Bands or Keltner Channels, this indicator leverages elastic volume-weighted averaging to compute real-time dispersion and location parameters, making it highly responsive to volatility changes while maintaining robustness against price fluctuations.
This methodology is inspired by incremental calculation techniques for weighted mean and variance, as outlined in the paper by Tony Finch:
📄 "Incremental Calculation of Weighted Mean and Variance" .
Key Features
✅ Adaptive Volatility Estimation – Uses an exponentially weighted Student-T model to dynamically adjust band width.
✅ Volume-Weighted Mean & Dispersion – Incorporates real-time volume weighting, ensuring a more accurate representation of market sentiment.
✅ High-Timeframe Volume Normalization – Provides an option to smooth volume impact by referencing a higher timeframe’s cumulative volume, reducing noise from high-variability bars.
✅ Customizable Tension Parameters – Configurable standard deviation multipliers (σ) allow for fine-tuned volatility sensitivity.
✅ %B-Like Oscillator for Relative Price Positioning – The main indicator is in form of a dedicated oscillator pane that normalizes price position within the sigma ranges, helping identify overbought/oversold conditions and potential momentum shifts.
✅ Robust Statistical Foundation – Utilizes kurtosis-based degree-of-freedom estimation, enhancing responsiveness across different market conditions.
How It Works
Volume-Weighted Elastic Mean (eμ) – Computes a dynamic mean price using an elastic weighted moving average approach, influenced by trade volume, if not volume detected in series, study takes true range as replacement.
Dispersion (eσ) via Student-T Distribution – Instead of assuming a fixed normal distribution, the bands adapt to heavy-tailed distributions using kurtosis-driven degrees of freedom.
Incremental Calculation of Variance – The indicator applies Tony Finch’s incremental method for computing weighted variance instead of arithmetic sum's of fixed bar window or arrays, improving efficiency and numerical stability.
Tension Calculation – There are 2 dispersion custom "zones" that are computed based on the weighted mean and dynamically adjusted standard student-t deviation.
%B-Like Oscillator Calculation – The oscillator normalizes the price within the band structure, with values between 0 and 1:
* 0.00 → Price is at the lower band (-2σ).
* 0.50 → Price is at the volume-weighted mean (eμ).
* 1.00 → Price is at the upper band (+2σ).
* Readings above 1.00 or below 0.00 suggest extreme movements or possible breakouts.
Recommended Usage
For scalping in lower timeframes, it is recommended to use the fixed α Decay Factor, it is in raw format for better control, but you can easily make a like of transformation to N-bar size window like in EMA-1 bar dividing 2 / decayFactor or like an RMA dividing 1 / decayFactor.
The HTF selector catch quite well Higher Time Frame analysis, for example using a Daily chart and using as HTF the 200-day timeframe, weekly or monthly.
Suitable for trend confirmation, breakout detection, and mean reversion plays.
The %B-like oscillator helps gauge momentum strength and detect divergences in price action if user prefer a clean chart without bands, this thanks to pineScript v6 force overlay feature.
Ideal for markets with volume-driven momentum shifts (e.g., futures, forex, crypto).
Customization Parameters
Fixed α Decay Factor – Controls the rate of volume weighting influence for an approximation EWMA approach instead of using sum of series or arrays, making the code lightweight & computing fast O(1).
HTF Volume Smoothing – Instead of a fixed denominator for computing α , a volume sum of the last 2 higher timeframe closed candles are used as denominator for our α weight factor. This is useful to review mayor trends like in daily, weekly, monthly.
Tension Multipliers (±σ) – Adjusts sensitivity to dispersion sigma parameter (volatility).
Oscillator Zone Fills – Visual cues for price positioning within the cloud range.
Posible Interpretations
As market within indicators relay on each individual edge, this are just some key ideas to glimpse how the indicator could be interpreted by the user:
📌 Price inside bands – Market is considered somehow "stable"; price is like resting from tension or "charging batteries" for volume spike moves.
📌 Price breaking outer bands – Potential breakout or extreme movement; watch for reversals or continuation from strong moves. Market is already in tension or generating it.
📌 Narrowing Bands – Decreasing volatility; expect contraction before expansion.
📌 Widening Bands – Increased volatility; prepare for high probability pull-back moves, specially to the center location of the bands (the mean) or the other side of them.
📌 Oscillator is just the interpretation of the price normalized across the Student-T distribution fitting "curve" using the location parameter, our Elastic Volume weighted mean (eμ) fixed at 0.5 value.
Final Thoughts
The Elastic Volume-Weighted Student-T Tension indicator provides a powerful, volume-sensitive alternative to traditional volatility bands. By integrating real-time volume analysis with an adaptive statistical model, incremental variance computation, in a relative price oscillator that can be overlayed in the chart as bands, it offers traders an edge in identifying momentum shifts, trend strength, and breakout potential. Think of the distribution as a relative "tension" rubber band in which price never leave so far alone.
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is, following TradingView's regulations. Use of indicator and their code are published for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s).
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED FOR TESTING. The models included in the indicator have been taken from open sources on the web and some of them has been modified by the author, problems could occur at diverse data sceneries, compiler version, or any other externality.
Hurst-Based Trend Persistence w/Poisson Prediction
---
# **Hurst-Based Trend Persistence w/ Poisson Prediction**
## **Introduction**
The **Hurst-Based Trend Persistence with Poisson Prediction** is a **statistically-driven trend-following oscillator** that provides traders with **a structured approach to identifying trend strength, persistence, and potential reversals**.
This indicator combines:
- **Hurst Exponent Analysis** (to measure how persistent or mean-reverting price action is).
- **Color-Coded Trend Detection** (to highlight bullish and bearish conditions).
- **Poisson-Based Trend Reversal Probability Projection** (to anticipate when a trend is likely to end based on statistical models).
By integrating **fractal market theory (Hurst exponent)** with **Poisson probability distributions**, this indicator gives traders a **probability-weighted view of trend duration** while dynamically adapting to market volatility.
---
## **Simplified Explanation (How to Read the Indicator at a Glance)**
1. **If the oscillator line is going up → The trend is strong.**
2. **If the oscillator line is going down → The trend is weakening.**
3. **If the color shifts from red to green (or vice versa), a trend shift has occurred.**
- **Strong trends can change color without weakening** (meaning a bullish or bearish move can remain powerful even as the trend shifts).
4. **A weakening trend does NOT necessarily mean a reversal is coming.**
- The trend may slow down but continue in the same direction.
5. **A strong trend does NOT guarantee it will last.**
- Even a powerful move can **suddenly reverse**, which is why the **Poisson-based background shading** helps anticipate probabilities of change.
---
## **How to Use the Indicator**
### **1. Understanding the Rolling Hurst-Based Trend Oscillator (Main Line)**
The **oscillator line** is based on the **Hurst exponent (H)**, which quantifies whether price movements are:
- **Trending** (values above 0 → momentum-driven, persistent trends).
- **Mean-reverting** (values below 0 → price action is choppy, likely to revert to the mean).
- **Neutral (Random Walk)** (values around 0 → price behaves like a purely stochastic process).
#### **Interpreting the Oscillator:**
- **H > 0.5 → Persistent Trends:**
- Price moves tend to sustain in one direction for longer periods.
- Example: Strong uptrends in bull markets.
- **H < 0.5 → Mean-Reverting Behavior:**
- Price has a tendency to revert back to its mean.
- Example: Sideways markets or fading momentum.
- **H ≈ 0.5 → Random Walk:**
- No clear trend; price is unpredictable.
A **gray dashed horizontal line at 0** serves as a **baseline**, helping traders quickly assess whether the market is **favoring trends or mean reversion**.
---
### **2. Color-Coded Trend Signal (Visual Confirmation of Trend Shifts)**
The oscillator **changes color** based on **price slope** over the lookback period:
- **🟢 Green → Uptrend (Price Increasing)**
- Price is rising relative to the selected lookback period.
- Suggests sustained bullish pressure.
- **🔴 Red → Downtrend (Price Decreasing)**
- Price is falling relative to the selected lookback period.
- Suggests sustained bearish pressure.
#### **How to Use This in Trading**
✔ **Stay in trends until a color change occurs.**
✔ **Use color changes as confirmation for trend reversals.**
✔ **Avoid counter-trend trades when the oscillator remains strongly colored.**
---
### **3. Poisson-Based Trend Reversal Projection (Anticipating Future Shifts)**
The **shaded orange background** represents a **Poisson-based probability estimation** of when the trend is likely to reverse.
- **Darker Orange = Higher Probability of Trend Reversal**
- **Lighter Orange / No Shade = Low Probability of Immediate Reversal**
💡 **The idea behind this model:**
✔ Trends **don’t last forever**, and their duration follows **statistical patterns**.
✔ By calculating the **average historical trend duration**, the indicator predicts **how likely a trend shift is at any given time**.
✔ The **Poisson probability function** is applied to determine the **expected likelihood of a reversal as time progresses**.
---
## **Mathematical Foundations of the Indicator**
This indicator is based on **two primary statistical models**:
### **1. Hurst Exponent & Trend Persistence (Fractal Market Theory)**
- The **Hurst exponent (H)** measures **autocorrelation** in price movements.
- If past trends **persist**, H will be **above 0.5** (meaning trend-following strategies are favorable).
- If past trends tend to **mean-revert**, H will be **below 0.5** (meaning reversal strategies are more effective).
- The **Rolling Hurst Oscillator** calculates this exponent over a moving window to track real-time trend conditions.
#### **Formula Breakdown (Simplified for Traders)**
The Hurst exponent (H) is derived using the **Rescaled Range (R/S) Analysis**:
\
Where:
- **R** = **Range** (difference between max cumulative deviation and min cumulative deviation).
- **S** = **Standard deviation** of price fluctuations.
- **Lookback** = The number of periods analyzed.
---
### **2. Poisson-Based Trend Reversal Probability (Stochastic Process Modeling)**
The **Poisson process** is a **probabilistic model used for estimating time-based events**, applied here to **predict trend reversals based on past trend durations**.
#### **How It Works**
- The indicator **tracks trend durations** (the time between color changes).
- A **Poisson rate parameter (λ)** is computed as:
\
- The **probability of a reversal at any given time (t)** is estimated using:
\
- **As t increases (trend continues), the probability of reversal rises**.
- The indicator **shades the background based on this probability**, visually displaying the likelihood of a **trend shift**.
---
## **Dynamic Adaptation to Market Conditions**
✔ **Volatility-Adjusted Trend Shifts:**
- A **custom volatility calculation** dynamically adjusts the **minimum trend duration** required before a trend shift is recognized.
- **Higher volatility → Requires longer confirmation before switching trend color.**
- **Lower volatility → Allows faster trend shifts.**
✔ **Adaptive Poisson Weighting:**
- **Recent trends are weighted more heavily** using an exponential decay function:
- **Decay Factor (0.618 by default)** prioritizes **recent intervals** while still considering historical trends.
- This ensures the model adapts to changing market conditions.
---
## **Key Takeaways for Traders**
✅ **Identify Persistent Trends vs. Mean Reversion:**
- Use the oscillator line to determine whether the market favors **trend-following or counter-trend strategies**.
✅ **Visual Trend Confirmation via Color Coding:**
- **Green = Uptrend**, **Red = Downtrend**.
- Trend changes help confirm **entry and exit points**.
✅ **Anticipate Trend Reversals Using Probability Models:**
- The **Poisson projection** provides a **statistical edge** in **timing exits before trends reverse**.
✅ **Adapt to Market Volatility Automatically:**
- Dynamic **volatility scaling** ensures the indicator remains effective in **both high and low volatility environments**.
Happy trading and enjoy!
