Tsallis Entropy Market RiskTsallis Entropy Market Risk Indicator
What Is It?
The Tsallis Entropy Market Risk Indicator is a market analysis tool that measures the degree of randomness or disorder in price movements. Unlike traditional technical indicators that focus on price patterns or momentum, this indicator takes a statistical physics approach to market analysis.
Scientific Foundation
The indicator is based on Tsallis entropy, a generalization of traditional Shannon entropy developed by physicist Constantino Tsallis. The Tsallis entropy is particularly effective at analyzing complex systems with long-range correlations and memory effects—precisely the characteristics found in crypto and stock markets.
The indicator also borrows from Log-Periodic Power Law (LPPL).
Core Concepts
1. Entropy Deficit
The primary measurement is the "entropy deficit," which represents how far the market is from a state of maximum randomness:
Low Entropy Deficit (0-0.3): The market exhibits random, uncorrelated price movements typical of efficient markets
Medium Entropy Deficit (0.3-0.5): Some patterns emerging, moderate deviation from randomness
High Entropy Deficit (0.5-0.7): Strong correlation patterns, potentially indicating herding behavior
Extreme Entropy Deficit (0.7-1.0): Highly ordered price movements, often seen before significant market events
2. Multi-Scale Analysis
The indicator calculates entropy across different timeframes:
Short-term Entropy (blue line): Captures recent market behavior (20-day window)
Long-term Entropy (green line): Captures structural market behavior (120-day window)
Main Entropy (purple line): Primary measurement (60-day window)
3. Scale Ratio
This measures the relationship between long-term and short-term entropy. A healthy market typically has a scale ratio above 0.85. When this ratio drops below 0.85, it suggests abnormal relationships between timeframes that often precede market dislocations.
How It Works
Data Collection: The indicator samples price returns over specific lookback periods
Probability Distribution Estimation: It creates a histogram of these returns to estimate their probability distribution
Entropy Calculation: Using the Tsallis q-parameter (typically 1.5), it calculates how far this distribution is from maximum entropy
Normalization: Results are normalized against theoretical maximum entropy to create the entropy deficit measure
Risk Assessment: Multiple factors are combined to generate a composite risk score and classification
Market Interpretation
Low Risk Environments (Risk Score < 25)
Market is functioning efficiently with reasonable randomness
Price discovery is likely effective
Normal trading and investment approaches appropriate
Medium Risk Environments (Risk Score 25-50)
Increasing correlation in price movements
Beginning of trend formation or momentum
Time to monitor positions more closely
High Risk Environments (Risk Score 50-75)
Strong herding behavior present
Market potentially becoming one-sided
Consider reducing position sizes or implementing hedges
Extreme Risk Environments (Risk Score > 75)
Highly ordered market behavior
Significant imbalance between buyers and sellers
Heightened probability of sharp reversals or corrections
Practical Application Examples
Market Tops: Often characterized by gradually increasing entropy deficit as momentum builds, followed by extreme readings near the actual top
Market Bottoms: Can show high entropy deficit during capitulation, followed by normalization
Range-Bound Markets: Typically display low and stable entropy deficit measurements
Trending Markets: Often show moderate entropy deficit that remains relatively consistent
Advantages Over Traditional Indicators
Forward-Looking: Identifies changing market structure before price action confirms it
Statistical Foundation: Based on robust mathematical principles rather than empirical patterns
Adaptability: Functions across different market regimes and asset classes
Noise Filtering: Focuses on meaningful structural changes rather than price fluctuations
Limitations
Not a Timing Tool: Signals market risk conditions, not precise entry/exit points
Parameter Sensitivity: Results can vary based on the chosen parameters
Historical Context: Requires some historical perspective to interpret effectively
Complementary Tool: Works best alongside other analysis methods
Enjoy :)
Indicadores e estratégias
ZYTX GKDDThe ZYTX High-Sell Low-Buy Indicator Strategy is a trend-following indicator that integrates multiple indicator resonances. It demonstrates the perfect performance of an automated trading robot, truly achieving the high-sell low-buy strategy in trading.
Price Change Rate with Pivot Labels (%)Bull/Bear labels to show the exact price change percentage at the pivot.
1. Calculates Price Change %
Measures the percentage change in closing price over a user-defined number of bars.
2. Identifies Pivot Points
Finds local highs (pivot highs) and lows (pivot lows) using configurable left/right bar settings.
3. Labels Bullish/Bearish Trends
Bull label: Appears at pivot lows if price is rising and forming higher lows.
Bear label: Appears at pivot highs if price is falling and forming lower highs.
4. Displays % on Labels
Each label includes the current price change percentage, e.g.,
"Bull +2.34%"
"Bear -1.78%"
5. Optional Visuals
Pivot shapes (triangles) are plotted for clarity.
RSI-Adaptive T3 + Squeeze Momentum Strategy✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy
📌 Overview
The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection .
It adapts in real-time to market volatility to enhance entry precision and optimize risk.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals.
Designed to be intuitive and accessible for traders from beginner to advanced levels.
✨ Key Features
RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection
Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases
Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release
📊 Trading Rules
Long Entry:
When T3 crosses upward, momentum is positive, and the squeeze has just been released.
Short Entry:
When T3 crosses downward, momentum is negative, and the squeeze has just been released.
Exit (Reversal):
When the opposite condition to the entry is triggered, the position is reversed.
💰 Risk Management Parameters
Pair & Timeframe: BTC/USD (30-minute chart)
Capital (simulated): $30,00
Order size: `$100` per trade (realistic, low-risk sizing)
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 5%
Number of Trades (backtest period): 181
📊 Performance Overview
Symbol: BTC/USD
Timeframe: 30-minute chart
Date Range: January 1, 2024 – July 3, 2025
Win Rate: 47.8%
Profit Factor: 2.01
Net Profit: 173.16 (units not specified)
Max Drawdown: 5.77% or 24.91 (0.79%)
⚙️ Indicator Parameters
Indicator Name: RSI-Adaptive T3 + Squeeze Momentum
RSI Length: 14
T3 Min Length: 5
T3 Max Length: 50
T3 Volume Factor: 0.7
BB Length: 27 (Multiplier: 2.0)
KC Length: 20 (Multiplier: 1.5, TrueRange enabled)
🖼 Visual Support
T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart,
providing high clarity for quick trend analysis and execution.
🔧 Strategy Improvements & Uniqueness
Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear ,
this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system .
Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity .
✅ Summary
The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management.
With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use appropriate risk management when applying it.
Prakash and Vicky TrendPrakash and Vicky Trend
This indicator is designed to help traders identify potential trend changes and key price levels on the chart. It uses three weighted moving averages and the volume-weighted average price (VWAP) for a balanced view of short-term momentum, overall trend, and market value.
The fast and slow moving averages generate buy and sell signals when they cross over or under each other, signaling shifts in market momentum.
The longer-term moving average acts as a trend filter, helping traders see the bigger picture direction.
VWAP offers a benchmark level watched by institutions, highlighting areas of value and potential support or resistance.
This combination provides a simple yet effective framework for making trading decisions with a clear view of price action, trend strength, and key levels.
Dashboard TrendsDashboard Trends – Multi-Timeframe VWAP + EMA Bias Indicator
The Dashboard Trends indicator is a powerful market sentiment tool that visually displays trend biases across multiple timeframes using a combination of:
Anchored Session VWAP with Deviation Bands
EMA(22) vs EMA(200) Trend Comparison
Custom Neutral Zone Logic
Multi-Timeframe Dashboard Table
1-Minute Precision Bias and VWAP Positioning
This tool is designed for day traders, scalpers, and swing traders who want a clean and fast way to assess the market's trend structure at a glance.
📊 Features
✅ 1. Anchored Session VWAP
Custom VWAP that resets at the start of each daily session.
Displays ±1σ, ±2σ, ±3σ standard deviation bands.
Tracks real-time price positioning relative to VWAP.
✅ 2. EMA Trend Bias
Uses EMA(22) and EMA(200) across multiple timeframes (1m, 10m, 30m, 4h, 1D).
A trend is:
Bullish if EMA(22) > EMA(200) + threshold
Bearish if EMA(22) < EMA(200) - threshold
Neutral within buffer zone
Choose between:
Fixed Threshold (% based)
Dynamic ATR-based Threshold for volatility adaptation
✅ 3. VWAP Bias Calculation
Measures price deviation from session VWAP within normalized range
Color-coded output for:
Green: Bullish bias
Red: Bearish bias
Gray: Neutral zone
✅ 4. Real-Time Dashboard Table
Updates every 10 bars
Displays market bias for:
1m, 10m, 30m, 4h, 1D, and VWAP trend zones
Color-coded cells for instant decision-making
📈 Suggested Trading Strategy
You can build rules around trend alignment and VWAP zones for effective entries and exits.
📌 Entry Rules:
Long Entry:
1m, 10m, 30m, and VWAP all show Bullish (green)
Price is above VWAP and holding above +1σ
Optional: Use pullback to EMA(22) on the 1m or 10m chart as a trigger
Short Entry:
1m, 10m, 30m, and VWAP all show Bearish (red)
Price is below VWAP and holding below -1σ
Optional: Use rejection at EMA(22) on the 1m/10m as confirmation
📌 Exit / Take-Profit:
Take profit at ±2σ or ±3σ levels
Trail stops based on price moving back into Neutral or opposite bias
📌 Stop-Loss:
Just below VWAP or the opposite side of ±1σ band (depending on entry direction)
Or use fixed ATR-based stop for dynamic positioning
⚙️ Settings Recommendations
For volatile markets (crypto, small caps): Enable Dynamic ATR Threshold
For stable markets (indices, large caps): Use Fixed Threshold = 0.05–0.10%
For scalping: Set neutral zone buffer (1m) to a tighter value like 0.05
RSI + Divergence + Stochastic RSIsimple indicator combining RSI and STOCH
RSI indicator (with divergence detection, smoothing, and optional Bollinger Bands)
Stochastic RSI indicator (with %K and %D lines, bands, and background fill)
Market Maker Trap Reversal V1Market Maker Trap Reversal V1 is a lightweight, precision-focused tool designed to detect the same liquidity manipulation tactics used by institutional players and market makers.
This script identifies key liquidity sweeps of prior swing highs/lows and confirms trap reversals when price closes back inside the swept range — a signature move of smart money designed to trap retail breakout traders.
Built for disciplined execution, this tool includes:
✅ Sweep detection using custom swing lookbacks
✅ Convincing trap confirmation (strong candle body)
✅ Optional NY session filter for optimal timing
✅ Clean long/short alerts for seamless automation
✅ No indicators — just raw price action and intent
Use this strategy to mirror market maker logic, avoid false breakouts, and trade with real conviction around liquidity events.
**Coded with the help of Zero"
Volume Data Table (Real-time & Historical Volume Analysis)Volume Data Table (Real-time & Historical Volume Analysis)
Overview:
The Volume Data Table indicator is a powerful tool designed to provide concise, real-time, and historical volume insights directly on your chart. It aggregates critical volume metrics into an organized, customizable table, making it incredibly easy to identify unusual volume activity, sudden surges, or sustained interest in a particular asset.
This indicator is perfect for traders who rely on volume analysis to confirm price movements, spot potential reversals, or gauge market conviction.
Key Features & How It Works:
Real-time Volume Metrics:
The table prominently displays the volume data for the current (last) candle, including:
Time: The precise time of the current candle's close, formatted in IST (Indian Standard Time - UTC+5:30) for your convenience.
Volume: The total volume for the current candle, smartly formatted in K (Thousands) or M (Millions) for readability.
Change % (Chg%): The percentage change in volume compared to the immediately preceding candle. This helps you quickly spot sudden increases or decreases in trading activity.
Vs 4-Avg % (vs4Avg%): The percentage change in volume compared to the average volume of the last 4 preceding candles. This is crucial for identifying volume surges or drops relative to recent historical activity, which can signal significant market events.
Configurable Historical Data:
Beyond the current candle, you can customize how many previous candles' volume data you wish to display. A simple input setting allows you to choose from 1 to 20 historical rows, giving you flexibility to review recent volume trends. Each historical row also provides its own "Change %" and "Vs 4-Avg %" for detailed analysis of past candle activity.
Intuitive Color-Coding:
Percentage change values are intuitively color-coded for instant visual cues:
Green: Indicates a positive (increase) in volume percentage.
Red: Indicates a negative (decrease) in volume percentage.
Clean & Organized Table Display:
The indicator presents all this data in a neat, easy-to-read table positioned at the top-right of your chart. The table automatically adjusts its height based on the number of historical rows you choose, ensuring a compact and efficient use of screen space.
Ideal Use Cases:
Volume Confirmation: Quickly confirm the conviction behind price movements. A strong price move on high "Vs 4-Avg %" volume often indicates higher reliability.
Spotting Abnormal Volume: Identify candles with unusually high or low volume compared to their recent average, which can precede or accompany significant price action.
Momentum Analysis: Understand if buying/selling pressure is increasing or decreasing over recent periods.
Scalping & Day Trading: The real-time updates and concise format make it highly effective for fast-paced short-term decision-making.
Complements Other Indicators: Use it alongside price action, candlestick patterns, or other technical indicators for a more robust analysis.
Customization Options:
Number of Historical Rows: Adjust Number of Historical Rows from 1 to 20 to tailor the depth of your historical volume review.
Important Disclaimer:
This indicator is a technical analysis tool and should be used as part of a comprehensive trading strategy. It is not financial advice. Trading in financial markets involves substantial risk, and you could lose money. Always perform your own research and risk management.
MA5 — 四點高低 + H1/L1 水平線 + 突破/回買 + 月季線交叉//@version=5
indicator("MA5 — 四點高低 + H1/L1 水平線 + 突破/回買 + 月季線交叉", overlay=true)
// 1. 均線設定
ma5 = ta.sma(close, 5)
ma10 = ta.sma(close, 10)
ma20 = ta.sma(close, 20)
ma60 = ta.sma(close, 60) // ← 加上這一行
// 畫出均線
plot(ma5, title="MA5", color=color.red)
plot(ma10, title="MA10", color=color.orange)
plot(ma20, title="MA20", color=color.yellow)
plot(ma60, title="MA60", color=color.green)
// 2. 全域變數：方向、區段極值
var int direction = na
var float segHigh = na
var int segHighBar = na
var float segLow = na
var int segLowBar = na
// 3. 全域變數：儲存兩組高低
var float high1 = na
var int high1Bar = na
var float high2 = na
var int high2Bar = na
var float low1 = na
var int low1Bar = na
var float low2 = na
var int low2Bar = na
// 4. 全域變數：標籤與線段句柄
var label highLbl1 = na
var label highLbl2 = na
var label lowLbl1 = na
var label lowLbl2 = na
var line highLine = na
var line lowLine = na
var line h1Line = na
var line l1Line = na
// 5. 全域變數：回買訊號控制
var bool buyBackShown = false
// 6. 判斷當前段方向
currDir = close > ma5 ? 1 : close < ma5 ? -1 : direction
// 7. 首次初始化
if na(direction)
direction := currDir
segHigh := high
segHighBar := bar_index
segLow := low
segLowBar := bar_index
// 8. 同段內更新極值
if currDir == 1 and high > segHigh
segHigh := high
segHighBar := bar_index
if currDir == -1 and low < segLow
segLow := low
segLowBar := bar_index
// 9. 段落切換：推舊值→更新 H1/L1→刪舊標籤/線→畫新標籤/線→重置 seg*
if currDir != direction
high2 := high1
high2Bar := high1Bar
low2 := low1
low2Bar := low1Bar
if direction == 1
high1 := segHigh
high1Bar := segHighBar
else
low1 := segLow
low1Bar := segLowBar
buyBackShown := false
if not na(highLbl1)
label.delete(highLbl1)
if not na(highLbl2)
label.delete(highLbl2)
if not na(lowLbl1)
label.delete(lowLbl1)
if not na(lowLbl2)
label.delete(lowLbl2)
if not na(high2)
highLbl2 := label.new(high2Bar, high2, "H2", style=label.style_label_down, color=color.blue, textcolor=color.white)
if not na(high1)
highLbl1 := label.new(high1Bar, high1, "H1", style=label.style_label_down, color=color.blue, textcolor=color.white)
if not na(low2)
lowLbl2 := label.new(low2Bar, low2, "L2", style=label.style_label_up, color=color.purple, textcolor=color.white)
if not na(low1)
lowLbl1 := label.new(low1Bar, low1, "L1", style=label.style_label_up, color=color.purple, textcolor=color.white)
if not na(highLine)
line.delete(highLine)
if not na(high1) and not na(high2)
highLine := line.new(high2Bar, high2, high1Bar, high1, color=color.blue, width=2)
if not na(lowLine)
line.delete(lowLine)
if not na(low1) and not na(low2)
lowLine := line.new(low2Bar, low2, low1Bar, low1, color=color.purple, width=2)
if not na(h1Line)
line.delete(h1Line)
if not na(high1)
h1Line := line.new(high1Bar, high1, bar_index, high1, xloc=xloc.bar_index, extend=extend.right, color=color.green, style=line.style_dashed)
if not na(l1Line)
line.delete(l1Line)
if not na(low1)
l1Line := line.new(low1Bar, low1, bar_index, low1, xloc=xloc.bar_index, extend=extend.right, color=color.red, style=line.style_dashed)
segHigh := high
segHighBar := bar_index
segLow := low
segLowBar := bar_index
// 10. 更新方向
direction := currDir
// 11. 突破訊號：收盤首次突破 H1 且 ma5>ma10>ma20
buySignal = not na(high1) and ta.crossover(close, high1) and ma5 > ma10 and ma10 > ma20
if buySignal
label.new(bar_index, low, "突破", style=label.style_label_up, color=color.green, textcolor=color.white)
// 12. 回買訊號：L1 之後任一 K 棒，首次收盤突破 MA5，且高於 L1、漲幅>2%、ma5>ma10>ma20、且收盤>ma20
buyBackSignal = not na(low1) and bar_index > low1Bar and ta.crossover(close, ma5) and high > low1 and (close - open) / open > 0.02 and ma5 > ma10 and ma10 > ma20 and close > ma20 and not buyBackShown
if buyBackSignal
label.new(bar_index, low, "回買", style=label.style_label_up, color=color.green, textcolor=color.white)
buyBackShown := true
// 13. 月季線交叉且四線多頭排列時，在 K 棒正下方標示放大三角形
if ta.cross(ma20, ma60) and ma5 > ma10 and ma10 > ma20 and ma20 > ma60
label.new(bar_index, low, "▲", xloc=xloc.bar_index, yloc=yloc.belowbar, style=label.style_label_center, color=color.new(color.white, 100), textcolor=color.white, size=size.large)
👽 TIME PERIODS👽 TIME PERIODS v1.15
Visualize key time divisions and session levels on any chart:
• Timezone‐aware session shading
– Highlight active NY session (configurable HHMM–HHMM and days)
– Adjustable background opacity
• Weekly & Monthly Separators
– Toggle on/off
– Custom color, style (solid/dashed/dotted) & width
• Day-of-Week Labels
– Diamonds at session start for M–S
– Toggle on/off
• Session Open Line
– Horizontal line at each session’s open
– Configurable color, width & “distanceRight” in bars
– Always shows current session
• Midpoint Vertical Line
– Plots halfway between session open & close
– Custom color, style & width
– Toggle on/off
▶ All elements grouped for easy parameter tweaking
▶ Fully timezone-configurable (default America/New_York)
▶ Version 1.15 — added distanceRight feature & current session support
Use this to see exactly where your chosen session, weekly/monthly boundaries, and intraday pivot points fall—across any timeframe.
ZLMA Keltner ChannelThe ZLMA Keltner Channel uses a Zero-Lag Moving Average (ZLMA) as the centerline with ATR-based bands to track trends and volatility.
The ZLMA’s reduced lag enhances responsiveness for breakouts and reversals, i.e. it's more sensitive to pivots and trend reversals.
Unlike Bollinger Bands, which use standard deviation and are more sensitive to price spikes, this uses ATR for smoother volatility measurement.
Background:
Built on John Ehlers’ lag-reduction techniques, this indicator adapts the classic Keltner Channel for dynamic markets. It excels in trending (low-entropy) markets for breakouts and range-bound (high-entropy) markets for reversals.
How to Read:
ZLMA (Blue): Tracks price trends. Above = bullish, below = bearish.
Upper Band (Green): ZLMA + (Multiplier × ATR). Cross above signals breakout or overbought.
Lower Band (Red): ZLMA - (Multiplier × ATR). Cross below signals breakout or oversold.
Channel Fill (Gray): Shows volatility. Narrow = low volatility, wide = high volatility.
Signals (Optional): Enable to show “Buy” (green) on upper band crossovers, “Sell” (red) on lower band crossunders.
Strategies: Trade breakouts in trending markets, reversals in ranges, or use bands as trailing stops.
Settings:
ZLMA Period (20): Adjusts centerline responsiveness.
ATR Period (20): Sets volatility period.
Multiplier (2.0): Controls band width.
If you are still confused between the ZLMA Keltner Channels and Bollinger Bands:
Keltner Channel (ZLMA): Uses ATR for bands, which smooths volatility and is less reactive to sudden price spikes. The ZLMA centerline reduces lag for faster trend detection.
Bollinger Bands: Uses standard deviation for bands, making them more sensitive to price volatility and prone to wider swings in high-entropy markets. Typically uses an SMA centerline, which lags more than ZLMA.
BTCs RSI Dip & EMA Crossover AlertThis indicator helps you catch potential reversal opportunities after a stock or crypto asset becomes oversold.
🛠 How it works:
Watches RSI (Relative Strength Index)
First, it waits for RSI to dip below a level you choose (default is 30), which often signals the asset is oversold and due for a bounce.
Waits for Price Confirmation
After the RSI dip, the indicator watches for the first time price closes above both the 55 EMA and 200 EMA — a strong sign that momentum may be shifting upward.
Sends a “Buy” Signal
When that happens, the script:
Plots a green “Buy” label on the chart
Triggers an alert (labeled "Buy Indicator") so you’re notified immediately
⚙️ Customizable Inputs:
RSI threshold (e.g. 30 or 25)
RSI period (e.g. 14)
EMA lengths (default: 55 and 200)
✅ Designed to:
Avoid false signals by requiring both RSI weakness and price strength
Only trigger once per RSI dip, so you’re not spammed with repeat alerts
Use it to stay patient during downtrends and get alerted when the technicals show a possible turnaround. Great for swing traders and longer-term entries.
Indicador Strong Buy + Volume
Association of several bullish indicators with a trigger on a sudden increase in volume
TSLA Reversal Alert: Harmonic + VWAP + RSI DivergenceWorking on a Bearish Harmonic Alert, and Bullish Harmonic Alert
Price Extension from 8 EMAOverview
This indicator can be used to see how far away the price is from the 8 EMA. It compares this to the Average Daily Range % to see if the stock may be overextended. The "Extension Multiplier" represents how far the stock is extended away from the 8 EMA.
Core Concept
This indicator is best used for breakout trades that are trying to make sure they are not chasing the stock.
How to Use This Indicator
This tool is primarily intended for analyzing daily charts of individual stocks and is often used by breakout traders to evaluate potential entry areas.
If the stock is far away from the 8 EMA, it is likely not ready to break out. If it is close to the 8ema, it could be ready to move higher.
This indicator can also be used in the opposite way. For example, shorting or puts.
Understanding the colors
Green (Not Extended): Indicates the price is close to the 8 EMA. This often corresponds to periods of consolidation.
Yellow (Slightly Extended): The price is beginning to move away from the 8 EMA.
Orange (Extended): The price has moved a considerable distance from the 8 EMA.
Red (Very Extended): The price is at an extreme distance from the 8 EMA, historically increasing the likelihood of a pullback or consolidation.
Settings
Info Row Position: Adjusts the vertical position of the display table on the chart. Useful when using other indicators.
ADR Length: Sets the lookback period for calculating the Average Daily Range. Or the average range % for different timeframes.
Timeframe: Determines the timeframe for the EMA and ADR calculation (the default is Daily).
Breakout with ATR & Volume Filter🚀 Introducing Our New Breakout Strategy: Powerful Signals with ATR & Volume Filters
Designed specifically for the fast and volatile crypto markets, this breakout strategy delivers robust signals on Bitcoin’s 15-minute charts.
🌟 Key Features:
ATR filter ensures entries only during high volatility periods, reducing false signals.
Volume confirmation captures strong and reliable breakouts.
20-period support/resistance breakout levels identify early trend moves.
Scientifically optimized stop loss and take profit levels provide effective risk management.
Simple, clear, and effective — ideal for both beginners and professional traders.
🔥 Why Choose This Strategy?
It filters out market noise and focuses on genuine momentum moves, increasing your chances of success by leveraging real-time volatility and volume conditions.
📈 How to Use
Easily deploy on TradingView with customizable parameters. Perfect for traders who need quick, confident decisions in crypto markets.
Get closer to success in BTC trading with reliable signals and smart risk management!
Omori Law Recovery PhasesWhat is the Omori Law?
Originally a seismological model, the Omori Law describes how earthquake aftershocks decay over time. It follows a power law relationship: the frequency of aftershocks decreases roughly proportionally to 1/(t+c)^p, where:
t = time since the main shock
c = time offset constant
p = power law exponent (typically around 1.0)
Application to the markets
Financial markets experience "aftershocks" similar to earthquakes:
Market Crashes as Main Shocks: Major market declines (crashes) represent the initial shock event.
Volatility Decay: After a crash, market volatility typically declines following a power law pattern rather than a linear or exponential one.
Behavioral Components: The decay pattern reflects collective market psychology - initial panic gives way to uncertainty, then stabilization, and finally normalization.
The Four Recovery Phases
The Omori decay pattern in markets can be divided into distinct phases:
Acute Phase: Immediately after the crash, characterized by extreme volatility, panic selling, and sharp reversals. Trading is hazardous.
Reaction Phase: Volatility begins decreasing, but markets test previous levels. False rallies and retests of lows are common.
Repair Phase: Structure returns to the market. Volatility approaches normal levels, and traditional technical analysis becomes more reliable.
Recovery Phase: The final stage where market behavior normalizes completely. The impact of the original shock has fully decayed.
Why It Matters for Traders
Understanding where the market stands in this recovery cycle provides valuable context:
Risk Management: Adjust position sizing based on the current phase
Strategy Selection: Different strategies work in different phases
Psychological Preparation: Know what to expect based on the phase
Time Horizon Guidance: Each phase suggests appropriate time frames for trading
ROLLING-VWAP🔹 Session VWAP with Deviation Bands (±1σ, ±2σ, ±3σ)
This indicator plots a Volume-Weighted Average Price (VWAP) that resets daily, along with optional standard deviation bands (±1σ, ±2σ, ±3σ). It helps traders identify key dynamic support and resistance levels throughout the trading session.
Features:
Daily VWAP anchor resets at the start of each session.
Customizable standard deviation multiplier for precise volatility calibration.
Toggle visibility for ±1σ, ±2σ, and ±3σ bands independently.
Visual guidance for intraday trend strength, mean reversion, and volatility expansion.
Ideal For:
Intraday traders looking for mean-reversion or breakout opportunities.
Identifying overbought/oversold levels in real-time based on price's deviation from VWAP.
市场参与度宽度 (S&P/Nasdaq)指标功能和解读：
下拉菜单切换： 在指标的设置（点击指标名称旁边的小齿轮图标）中，您可以轻松地从 "S&P 500" 切换到 "Nasdaq 100"，指标会自动更新显示对应的数据。
同框显示： 蓝色的粗线代表50天市场参与度（中期健康度），橙色的细线代表20天市场参与度（短期情绪），两者在同一个副图中，方便您进行对比和观察。
关键水平线：
50%线 (灰色实线): 这是最重要的多空分界线。当指标线持续在50%以上时，表明市场处于强势；反之则处于弱势。
80%线 (红色虚线): 当短期指标（橙色线）进入80%以上时，可能意味着市场情绪过热，进入超买区。
20%线 (绿色虚线): 当短期指标进入20%以下时，可能意味着市场情绪过度悲观，进入超卖区，有时是机会的信号。
背离分析： 您可以观察当主图指数（如SPY）创出新高时，这个指标是否也创出新高。如果指数新高而指标没有，就形成了顶背离，是市场内部力量减弱的警示信号。
Indicator function and interpretation:
Drop-down menu switch: In the indicator settings (click the small gear icon next to the indicator name), you can easily switch from "S&P 500" to "Nasdaq 100", and the indicator will automatically update to display the corresponding data.
Same frame display: The thick blue line represents the 50-day market participation (medium-term health), and the thin orange line represents the 20-day market participation (short-term sentiment). Both are in the same sub-chart for your comparison and observation.
Key horizontal lines:
50% line (solid gray line): This is the most important dividing line between long and short. When the indicator line is continuously above 50%, it indicates that the market is strong; otherwise, it is weak.
80% line (dashed red line): When the short-term indicator (orange line) enters above 80%, it may mean that the market sentiment is overheated and enters the overbought zone.
20% line (dashed green line): When the short-term indicator enters below 20%, it may mean that the market sentiment is overly pessimistic and enters the oversold zone, which is sometimes a signal of opportunity.
Divergence analysis: You can observe whether this indicator also hits a new high when the main chart index (such as SPY) hits a new high. If the index hits a new high but the indicator does not, it forms a top divergence, which is a warning signal of weakening internal market forces.
SQZMOM Breakout Strategy📌 SQZMOM Breakout Strategy – Optimized for 15-Minute Intraday Trading
SQZMOM Breakout Strategy is a momentum and volatility-based algorithmic trading system, primarily built around the Squeeze Momentum (SQZMOM) indicator. It is specifically optimized for 15-minute timeframes to exploit intraday breakouts and trend continuations.
📊 Key Features:
✅ Breakout signals based on the Squeeze Momentum indicator
✅ Trend filter using 200-period WMA (visual only, not affecting entries)
✅ RSI filter to avoid trades in overbought/oversold zones
✅ Volume and ATR filters to confirm breakout quality
✅ Position sizing dynamically scales from 5% to 20% based on signal strength
✅ Trailing Stop Loss based on user-adjustable ATR multiple (default: 2.0 ATR)
✅ No fixed Take Profit: trades ride the trend using trailing stops
⚙️ Configurable Inputs:
Bollinger Band & Keltner Channel parameters
RSI thresholds (fixed at 40 to avoid early entries against momentum)
Trailing Stop distance defined by ATR Multiplier for Trailing Stop
All parameters are user-tunable for further optimization
🟢 When Does It Enter a Trade?
Long Entry:
SQZMOM fires bullish breakout + momentum increases + price above WMA200 + sufficient volume & ATR + RSI > 40
Short Entry:
SQZMOM fires bearish breakout + momentum decreases + price below WMA200 + sufficient volume & ATR + RSI < 40
Signal entries are deferred until all filters (especially RSI) align — no crossover logic is used
🎯 Trade Management:
Position Sizing: Adjusted according to momentum strength (val), from 5% to 20%
Exit Strategy: Trailing Stop only, no hard TP — lets profits run
TP/SL logic: Trailing SL moves dynamically with price, distance = ATR × multiplier
📚 Scientific & Practical Foundations:
The model is inspired by John Carter’s “TTM Squeeze” principle: volatility contraction followed by explosive momentum
Position sizing and ATR-based trailing logic follow Ernie Chan’s adaptive risk framework in Algorithmic Trading (2013)
RSI as a trend-quality gate is consistent with classic momentum confirmation rules
Omega Market Mood Meter [OmegaTools]The Omega Market Mood Meter is a precision-built sentiment oscillator that captures the market’s emotional intensity through a multi-layered RSI system. Designed for traders who seek to align with the market's true behavioral state, it blends momentum readings with a brand-new, rarely-seen innovation: the Sentiment-Weighted Moving Average (WMA-Ω)—a trend filter that dynamically adjusts to the market’s psychological tone.
🧠 Market Mood Oscillator
At its core, the Ω 3M oscillator aggregates three RSI-based components:
RSI(9) on close — captures short-term tension;
RSI(21) on HLC3 — balances medium-term positioning;
RSI(50) on HL2 — reflects long-term directional weight.
Each input is scaled and weighted to contribute to a final oscillator centered around zero, with ±50 and ±100 acting as key sentiment boundaries. When values exceed ±100, the market is likely reaching emotional extremes—zones that often precede reversals or require caution.
Visual features include:
Dynamic Background Highlighting: automatically emphasizes extreme sentiment zones.
Reference Lines: plotted at ±100, ±50, and 0 for fast sentiment interpretation.
🔥 WMA-Ω: Sentiment-Weighted Moving Average
The standout innovation of this tool is the Weighted Market Mood Moving Average, or WMA-Ω—a proprietary calculation that averages price using the absolute value of sentiment as its weighting force. This approach gives greater importance to price during periods of strong emotional conviction (either bullish or bearish), resulting in a context-aware trend filter that reacts only when sentiment truly matters.
This technique:
Filters noise during low-volatility or indecisive conditions;
Enhances reliability by reacting to meaningful sentiment surges;
Offers a more psychologically-adjusted trend baseline compared to traditional MAs.
Visually:
When price is above WMA-Ω, a semi-transparent bullish fill highlights underlying strength;
When below, a bearish fill reveals dominant downward sentiment.
This feature is unique among public TradingView tools and provides an edge in identifying trend quality with psychological context.
✅ How to Use
Extreme Sentiment Zones (±100): Use as contrarian warning zones or signal dampeners.
Crosses of WMA-Ω: Treat these as psychological trend confirmations; price above indicates structurally bullish sentiment and vice versa.
Range-bound Bias: Between ±50, sentiment may be indecisive; watch for breakout or alignment with WMA-Ω.
Advanced Confluence: Combine with other Omega tools (e.g., Ω Bias Forecaster, Ω IV Walls) for powerful regime-based strategies.
Omega Market Mood Meter is ideal for discretionary and systematic traders who want a clean, multi-timeframe sentiment readout and a cutting-edge weighted trend engine grounded in market psychology.
