Floor and Roof Indicator with SignalsFloor and Roof Indicator with Trading Signals
A comprehensive support and resistance indicator that identifies premium and discount zones with automated signal generation.
Key Features:
Dynamic Support/Resistance Zones: Calculates floor (support) and roof (resistance) levels using price action and volatility
Premium/Discount Zone Identification: Highlights areas where price may find resistance or support
Customizable Signal Frequency: Control how often signals are displayed (every Nth occurrence)
Visual Signal Table: Optional table showing the last 5 long and short signal prices
Multiple Timeframe Compatibility: Works across all timeframes
Technical Details:
Uses ATR-based calculations for dynamic zone width adjustment
Combines Bollinger Bands with highest/lowest price analysis
Smoothing options for cleaner signal generation
Fully customizable colors and display options
How to Use:
Floor Zones (Blue): Potential support areas where long positions may be considered
Roof Zones (Pink): Potential resistance areas where short positions may be considered
Signal Crosses: Visual markers when price interacts with key levels
Signal Table: Track recent signal prices for analysis
Settings:
Length: Period for calculations (default: 200)
Smooth: Smoothing factor for cleaner signals
Zone Width: Adjust the thickness of support/resistance zones
Signal Frequency: Control signal display frequency
Visual Options: Customize colors and table position
Alerts Available:
Long signal alerts when price touches discount zones
Short signal alerts when price reaches premium zones
Educational Purpose: This indicator is designed to help traders identify potential support and resistance areas. Always combine with proper risk management and additional analysis.
This description focuses on the technical aspects and educational value while avoiding any language that could be interpreted as financial advice or guaranteed profits.
Statistics
Jumping watermark# Jumping watermark
## Function description
- Dynamic watermark: Mainly used to add dynamic watermarks to prevent theft and transfer when recording videos.
- Static watermark: Sharing opinions can easily include information such as trading pairs, cycles, current time, and individual signatures.
### Static watermark:
Display the watermark related to the current trading pair in the center of the chart.
- Configuration items:
- You can choose to configure the display content: current trading pair code and name, cycle, date, time, and individual signature content
### Dynamic watermark
Display the configured watermark content in a dynamic random position.
- Configuration items:
- Turn on or off the display of watermark jumping
- Modify the display text content and style by yourself
----- 中文简介-----
# 跳动水印
## 功能描述
- 动态水印： 主要可用于视频录制时添加动态水印防盗、防搬运。
- 静态水印：观点分享是可方便的带上交易对、周期、当前时间、个签等信息。
### 静态水印：
在图表中心位置显示当前交易对相关信息水印。
- 配置项：
- 可选择配置显示内容：当前交易对代码及名称、周期、日期、时间、个签内容
### 动态水印
动态随机位置显示配置水印内容。
- 配置项：
- 开启或关闭显示水印跳动
- 自行修改配置显示文字内容和样式
Kelly Optimal Leverage IndicatorThe Kelly Optimal Leverage Indicator mathematically applies Kelly Criterion to determine optimal position sizing based on market conditions.
This indicator helps traders answer the critical question: "How much capital should I allocate to this trade?"
Note that "optimal position sizing" does not equal the position sizing that you should have. The Optima position sizing given by the indicator is based on historical data and cannot predict a crash, in which case, high leverage could be devastating.
Originally developed for gambling scenarios with known probabilities, the Kelly formula has been adapted here for financial markets to dynamically calculate the optimal leverage ratio that maximizes long-term capital growth while managing risk.
Key Features
Kelly Position Sizing: Uses historical returns and volatility to calculate mathematically optimal position sizes
Multiple Risk Profiles: Displays Full Kelly (aggressive), 3/4 Kelly (moderate), 1/2 Kelly (conservative), and 1/4 Kelly (very conservative) leverage levels
Volatility Adjustment: Automatically recommends appropriate Kelly fraction based on current market volatility
Return Smoothing: Option to use log returns and smoothed calculations for more stable signals
Comprehensive Table: Displays key metrics including annualized return, volatility, and recommended exposure levels
How to Use
Interpret the Lines: Each colored line represents a different Kelly fraction (risk tolerance level). When above zero, positive exposure is suggested; when below zero, reduce exposure. Note that this is based on historical returns. I personally like to increase my exposure during market downturns, but this is hard to illustrate in the indicator.
Monitor the Table: The information panel provides precise leverage recommendations and exposure guidance based on current market conditions.
Follow Recommended Position: Use the "Recommended Position" guidance in the table to determine appropriate exposure level.
Select Your Risk Profile: Conservative traders should follow the Half Kelly or Quarter Kelly lines, while more aggressive traders might consider the Three-Quarter or Full Kelly lines.
Adjust with Volatility: During high volatility periods, consider using more conservative Kelly fractions as recommended by the indicator.
Mathematical Foundation
The indicator calculates the optimal leverage (f*) using the formula:
f* = μ/σ²
Where:
μ is the annualized expected return
σ² is the annualized variance of returns
This approach balances potential gains against risk of ruin, offering a scientific framework for position sizing that maximizes long-term growth rate.
Notes
The Full Kelly is theoretically optimal for maximizing long-term growth but can experience significant drawdowns. You should almost never use full kelly.
Most practitioners use fractional Kelly strategies (1/2 or 1/4 Kelly) to reduce volatility while capturing most of the growth benefits
This indicator works best on daily timeframes but can be applied to any timeframe
Negative Kelly values suggest reducing or eliminating market exposure
The indicator should be used as part of a complete trading system, not in isolation
Enjoy the indicator! :)
P.S. If you are really geeky about the Kelly Criterion, I recommend the book The Kelly Capital Growth Investment Criterion by Edward O. Thorp and others.
Crypto Risk-Weighted Allocation SuiteCrypto Risk-Weighted Allocation Suite
This indicator is designed to help users explore dynamic portfolio allocation frameworks for the crypto market. It calculates risk-adjusted allocation weights across major crypto sectors and cash based on multi-factor momentum and volatility signals. Best viewed on INDEX:BTCUSD 1D chart. Other charts and timeframes may give mixed signals and incoherent allocations.
🎯 How It Works
This model systematically evaluates the relative strength of:
BTC Dominance (CRYPTOCAP:BTC.D)
Represents Bitcoin’s share of the total crypto market. Rising dominance typically indicates defensive market phases or BTC-led trends.
ETH/BTC Ratio (BINANCE:ETHBTC)
Gauges Ethereum’s relative performance versus Bitcoin. This provides insight into whether ETH is leading risk appetite.
SOL/BTC Ratio (BINANCE:SOLBTC)
Measures Solana’s performance relative to Bitcoin, capturing mid-cap layer-1 strength.
Total Market Cap excluding BTC and ETH (CRYPTOCAP:TOTAL3ES)
Represents Altcoins as a broad category, reflecting appetite for higher-risk assets.
Each of these series is:
✅ Converted to a momentum slope over a configurable lookback period.
✅ Standardized into Z-scores to normalize changes relative to recent behavior.
✅ Smoothed optionally using a Hull Moving Average for cleaner signals.
✅ Divided by ATR-based volatility to create a risk-weighted score.
✅ Scaled to proportionally allocate exposure, applying user-configured minimum and maximum constraints.
🪙 Dynamic Allocation Logic
All signals are normalized to sum to 100% if fully confident.
An overall confidence factor (based on total signal strength) scales the allocation up or down.
Any residual is allocated to cash (unallocated capital) for conservative exposure.
The script automatically avoids “all-in” bias and prevents negative allocations.
📊 Outputs
The indicator displays:
Market Phase Detection (which asset class is currently leading)
Risk Mode (Risk On, Neutral, Risk Off)
Dynamic Allocations for BTC, ETH, SOL, Alts, and Cash
Optional momentum plots for transparency
🧠 Why This Is Unique
Unlike simple dominance indicators or crossovers, this model:
Integrates multiple cross-asset signals (BTC, ETH, SOL, Alts)
Adjusts exposure proportionally to signal strength
Normalizes by volatility, dynamically scaling risk
Includes configurable constraints to reflect your own risk tolerance
Provides a cash fallback allocation when conviction is low
Is entirely non-repainting and based on daily closing data
⚠️ Disclaimer
This script is provided for educational and informational purposes only.
It is not financial advice and should not be relied upon to make investment decisions.
Past performance does not guarantee future results.
Always consult a qualified financial advisor before acting on any information derived from this tool.
🛠 Recommended Use
As a framework to visualize relative momentum and risk-adjusted allocations
For research and backtesting ideas on portfolio allocation across crypto sectors
To help build your own risk management process
This script is not a turnkey strategy and should be customized to fit your goals.
✅ Enjoy exploring dynamic crypto allocations responsibly!
Logistic Regression ICT FVG🚀 OVERVIEW
Welcome to the Logistic Regression Fair Value Gap (FVG) System — a next-gen trading tool that blends precision gap detection with machine learning intelligence.
Unlike traditional FVG indicators, this one evolves with each bar of price action, scoring and filtering gaps based on real market behavior.
🔧 CORE FEATURES
✨ Smart Gap Detection
Automatically identifies bullish and bearish Fair Value Gaps using volatility-aware candle logic.
📊 Probability-Based Filtering
Uses logistic regression to assign each gap a confidence score (0 to 1), showing only high-probability setups.
🔁 Real-Time Retest Tracking
Continuously watches how price interacts with each gap to determine if it deserves respect.
📈 Multi-Factor Assessment
Evaluates RSI, MACD, and body size at gap formation to build a full context snapshot.
🧠 Self-Learning Engine
The logistic regression model updates on each bar using gradient descent, refining its predictions over time.
📢 Built-In Alerts
Get instant alerts when a gap forms, gets retested, or breaks.
🎨 Custom Display Options
Control the color of bullish/bearish zones, and toggle on/off probability labels for cleaner charts.
🚩 WHAT MAKES IT DIFFERENT
This isn’t just another box-drawing indicator.
While others mark every imbalance, this system thinks before it draws — using statistical modeling to filter out noise and prioritize high-impact zones.
By learning from how price behaves around gaps (not just how they form), it helps you trade only what matters — not what clutters.
⚙️ HOW IT WORKS
1️⃣ Detection
FVGs are identified using ATR-based thresholds and sharp wick imbalances.
2️⃣ Behavior Monitoring
Every gap is tracked — and if respected enough times, it becomes part of the elite training set.
3️⃣ Context Capture
Each new FVG logs RSI, MACD, and body size to provide a feature-rich context for prediction.
4️⃣ Prediction (Logistic Regression)
The model predicts how likely the gap is to be respected and assigns it a probability score.
5️⃣ Classification & Alerts
Gaps above the threshold are plotted with score labels, and alerts trigger for entry/respect/break.
⚙️ CONFIGURATION PANEL
🔧 System Inputs
• Max Retests – How many times a gap must be respected to train the model
• Prediction Threshold – Minimum score to show a gap on the chart
• Learning Rate – Controls how fast the model adapts (default: 0.009)
• Max FVG Lifetime – Expiration duration for unused gaps
• Show Historic Gaps – Show/hide expired or invalidated gaps
🎨 Visual Options
• Bullish/Bearish Colors – Set gap colors to fit your chart style
• Confidence Labels – Show probability scores next to FVGs
• Alert Toggles – Enable alerts for:
– New FVG detected
– FVG respected (entry)
– FVG invalidated (break)
💡 WHY LOGISTIC REGRESSION?
Traditional FVG tools rely on candle shapes.
This system relies on probability — by training on RSI, MACD, and price behavior, it predicts whether a gap will act as a true liquidity zone.
Logistic regression lets the system continuously adapt using new data, making it more accurate the longer it runs.
That means smarter signals, fewer false positives, and a clearer view of where real opportunities lie.
EVaR Indicator and Position SizingThe Problem:
Financial markets consistently show "fat-tailed" distributions where extreme events occur with higher frequency than predicted by normal distributions (Gaussian or even log-normal). These fat tails manifest in sudden price crashes, volatility spikes, and black swan events that traditional risk measures like volatility can underestimate. Standard deviation and conventional VaR calculations assume normally distributed returns, leaving traders vulnerable to severe drawdowns during market stress.
Cryptocurrencies and volatile instruments display particularly pronounced fat-tailed behavior, with extreme moves occurring 5-10 times more frequently than normal distribution models would predict. This reality demands a more sophisticated approach to risk measurement and position sizing.
The Solution: Entropic Value at Risk (EVAR)
EVaR addresses these limitations by incorporating principles from statistical mechanics and information theory through Tsallis entropy. This advanced approach captures the non-linear dependencies and power-law distributions characteristic of real financial markets.
Entropy is more adaptive than standard deviations and volatility measures.
I was inspired to create this indicator after reading the paper " The End of Mean-Variance? Tsallis Entropy Revolutionises Portfolio Optimisation in Cryptocurrencies " by by Sana Gaied Chortane and Kamel Naoui.
Key advantages of EVAR over traditional risk measures:
Superior tail risk capture: More accurately quantifies the probability of extreme market moves
Adaptability to market regimes: Self-calibrates to changing volatility environments
Non-parametric flexibility: Makes less assumptions about the underlying return distribution
Forward-looking risk assessment: Better anticipates potential market changes (just look at the charts :)
Mathematically, EVAR is defined as:
EVAR_α(X) = inf_{z>0} {z * log(1/α * M_X(1/z))}
Where the moment-generating function is calculated using q-exponentials rather than conventional exponentials, allowing precise modeling of fat-tailed behavior.
Technical Implementation
This indicator implements EVAR through a q-exponential approach from Tsallis statistics:
Returns Calculation: Price returns are calculated over the lookback period
Moment Generating Function: Approximated using q-exponentials to account for fat tails
EVAR Computation: Derived from the MGF and confidence parameter
Normalization: Scaled to for intuitive visualization
Position Sizing: Inversely modulated based on normalized EVAR
The q-parameter controls tail sensitivity—higher values (1.5-2.0) increase the weighting of extreme events in the calculation, making the model more conservative during potentially turbulent conditions.
Indicator Components
1. EVAR Risk Visualization
Dynamic EVAR Plot: Color-coded from red to green normalized risk measurement (0-1)
Risk Thresholds: Reference lines at 0.3, 0.5, and 0.7 delineating risk zones
2. Position Sizing Matrix
Risk Assessment: Current risk level and raw EVAR value
Position Recommendations: Percentage allocation, dollar value, and quantity
Stop Parameters: Mathematically derived stop price with percentage distance
Drawdown Projection: Maximum theoretical loss if stop is triggered
Interpretation and Application
The normalized EVAR reading provides a probabilistic risk assessment:
< 0.3: Low risk environment with minimal tail concerns
0.3-0.5: Moderate risk with standard tail behavior
0.5-0.7: Elevated risk with increased probability of significant moves
> 0.7: High risk environment with substantial tail risk present
Position sizing is automatically calculated using an inverse relationship to EVAR, contracting during high-risk periods and expanding during low-risk conditions. This is a counter-cyclical approach that ensures consistent risk exposure across varying market regimes, especially when the market is hyped or overheated.
Parameter Optimization
For optimal risk assessment across market conditions:
Lookback Period: Determines the historical window for risk calculation
Q Parameter: Controls tail sensitivity (higher values increase conservatism)
Confidence Level: Sets the statistical threshold for risk assessment
For cryptocurrencies and highly volatile instruments, a q-parameter between 1.5-2.0 typically provides the most accurate risk assessment because it helps capturing the fat-tailed behavior characteristic of these markets. You can also increase the q-parameter for more conservative approaches.
Practical Applications
Adaptive Risk Management: Quantify and respond to changing tail risk conditions
Volatility-Normalized Positioning: Maintain consistent exposure across market regimes
Black Swan Detection: Early identification of potential extreme market conditions
Portfolio Construction: Apply consistent risk-based sizing across diverse instruments
This indicator is my own approach to entropy-based risk measures as an alterative to volatility and standard deviations and it helps with fat-tailed markets.
Enjoy!
BANKNIFTY Contribution Table [GSK-VIZAG-AP-INDIA]1. Overview
This indicator provides a real-time visual contribution table of the 12 constituent stocks in the BANKNIFTY index. It displays key metrics for each stock that help traders quickly understand how each component is impacting the index at any given moment.
2. Purpose / Trading Use Case
The tool is designed for intraday and short-term traders who rely on index movement and its internal strength or weakness. By seeing which stocks are contributing positively or negatively, traders can:
Confirm trend strength or divergence within the index.
Identify whether a BANKNIFTY move is broad-based or driven by a few heavyweights.
Detect reversals when individual components decouple from index direction.
3. Key Features and Logic
Live LTP: Current price of each BANKNIFTY stock.
Price Change: Difference between current LTP and previous day’s close.
% Change: Percentage move from previous close.
Weight %: Static weight of each stock within the BANKNIFTY index (user-defined).
This estimates how much each stock contributes to the BANKNIFTY’s point change.
Sorted View: The stocks are sorted by their weight (descending), so high-impact movers are always at the top.
4. User Inputs / Settings
Table Position (tableLocationOpt):
Choose where the table appears on the chart:
top_left, top_right, bottom_left, or bottom_right.
This helps position the table away from your price action or indicators.
5. Visual and Plotting Elements
Table Layout: 6 columns
Stock | Contribution | Weight % | LTP | Change | % Change
Color Coding:
Green/red for positive/negative price changes and contributions.
Alternating background rows for better visibility.
BANKNIFTY row is highlighted separately at the top.
Text & Background Colors are chosen for both readability and direction indication.
6. Tips for Effective Use
Use this table on 1-minute or 5-minute intraday charts to see near real-time market structure.
Watch for:
A few heavyweight stocks pulling the index alone (can signal weak internal breadth).
Broad green/red across all rows (signals strong directional momentum).
Combine this with price action or volume-based strategies for confirmation.
Best used during market hours for live updates.
7. What Makes It Unique
Unlike other contribution tables that show only static data or require paid feeds, this script:
Updates in real time.
Uses dynamic calculated contributions.
Places BANKNIFTY at the top and presents the entire internal structure clearly.
Doesn’t repaint or rely on lagging indicators.
8. Alerts / Additional Features
No alerts are added in this version.
(Optional: Alerts can be added to notify when a certain stock contributes above/below a threshold.)
9. Technical Concepts Used
request.security() to pull both 1-minute and daily close data.
Conditional color formatting based on price change direction.
Dynamic table rendering using table.new() and table.cell().
Static weights assigned manually for BANKNIFTY stocks (can be updated if index weights change).
10. Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice or a buy/sell recommendation.
Users should test and validate the tool on paper or demo accounts before applying it to live trading.
📌 Note: Due to internet connectivity, data delays, or broker feeds, real-time values (LTP, change, contribution, etc.) may slightly differ from other platforms or terminals. Use this indicator as a supportive visual tool, not a sole decision-maker.
Script Title: BANKNIFTY Contribution Table -
Author: GSK-VIZAG-AP-INDIA
Version: Final Public Release
Frahm Factor Position Size CalculatorThe Frahm Factor Position Size Calculator is a powerful evolution of the original Frahm Factor script, leveraging its volatility analysis to dynamically adjust trading risk. This Pine Script for TradingView uses the Frahm Factor’s volatility score (1-10) to set risk percentages (1.75% to 5%) for both Margin-Based and Equity-Based position sizing. A compact table on the main chart displays Risk per Trade, Frahm Factor, and Average Candle Size, making it an essential tool for traders aligning risk with market conditions.
Calculates a volatility score (1-10) using true range percentile rank over a customizable look-back window (default 24 hours).
Dynamically sets risk percentage based on volatility:
Low volatility (score ≤ 3): 5% risk for bolder trades.
High volatility (score ≥ 8): 1.75% risk for caution.
Medium volatility (score 4-7): Smoothly interpolated (e.g., 4 → 4.3%, 5 → 3.6%).
Adjustable sensitivity via Frahm Scale Multiplier (default 9) for tailored volatility response.
Position Sizing:
Margin-Based: Risk as a percentage of total margin (e.g., $175 for 1.75% of $10,000 at high volatility).
Equity-Based: Risk as a percentage of (equity - minimum balance) (e.g., $175 for 1.75% of ($15,000 - $5,000)).
Compact 1-3 row table shows:
Risk per Trade with Frahm score (e.g., “$175.00 (Frahm: 8)”).
Frahm Factor (e.g., “Frahm Factor: 8”).
Average Candle Size (e.g., “Avg Candle: 50 t”).
Toggles to show/hide Frahm Factor and Average Candle Size rows, with no empty backgrounds.
Four sizes: XL (18x7, large text), L (13x6, normal), M (9x5, small, default), S (8x4, tiny).
Repositionable (9 positions, default: top-right).
Customizable cell color, text color, and transparency.
Set Frahm Factor:
Frahm Window (hrs): Pick how far back to measure volatility (e.g., 24 hours). Shorter for fast markets, longer for chill ones.
Frahm Scale Multiplier: Set sensitivity (1-10, default 9). Higher makes the score jumpier; lower smooths it out.
Set Margin-Based:
Total Margin: Enter your account balance (e.g., $10,000). Risk auto-adjusts via Frahm Factor.
Set Equity-Based:
Total Equity: Enter your total account balance (e.g., $15,000).
Minimum Balance: Set to the lowest your account can go before liquidation (e.g., $5,000). Risk is based on the difference, auto-adjusted by Frahm Factor.
Customize Display:
Calculation Method: Pick Margin-Based or Equity-Based.
Table Position: Choose where the table sits (e.g., top_right).
Table Size: Select XL, L, M, or S (default M, small text).
Table Cell Color: Set background color (default blue).
Table Text Color: Set text color (default white).
Table Cell Transparency: Adjust transparency (0 = solid, 100 = invisible, default 80).
Show Frahm Factor & Show Avg Candle Size: Check to show these rows, uncheck to hide (default on).
Machine Learning Key Levels [AlgoAlpha]🟠 OVERVIEW
This script plots Machine Learning Key Levels on your chart by detecting historical pivot points and grouping them using agglomerative clustering to highlight price levels with the most past reactions. It combines a pivot detection, hierarchical clustering logic, and an optional silhouette method to automatically select the optimal number of key levels, giving you an adaptive way to visualize price zones where activity concentrated over time.
🟠 CONCEPTS
Agglomerative clustering is a bottom-up method that starts by treating each pivot as its own cluster, then repeatedly merges the two closest clusters based on the average distance between their members until only the desired number of clusters remain. This process creates a hierarchy of groupings that can flexibly describe patterns in how price reacts around certain levels. This offers an advantage over K-means clustering, since the number of clusters does not need to be predefined. In this script, it uses an average linkage approach, where distance between clusters is computed as the average pairwise distance of all contained points.
The script finds pivot highs and lows over a set lookback period and saves them in a buffer controlled by the Pivot Memory setting. When there are at least two pivots, it groups them using agglomerative clustering: it starts with each pivot as its own group and keeps merging the closest pairs based on their average distance until the desired number of clusters is left. This number can be fixed or chosen automatically with the silhouette method, which checks how well each point fits in its cluster compared to others (higher scores mean cleaner separation). Once clustering finishes, the script takes the average price of each cluster to create key levels, sorts them, and draws horizontal lines with labels and colors showing their strength. A metrics table can also display details about the clusters to help you understand how the levels were calculated.
🟠 FEATURES
Agglomerative clustering engine with average linkage to merge pivots into level groups.
Dynamic lines showing each cluster’s price level for clarity.
Labels indicating level strength either as percent of all pivots or raw counts.
A metrics table displaying pivot count, cluster count, silhouette score, and cluster size data.
Optional silhouette-based auto-selection of cluster count to adaptively find the best fit.
🟠 USAGE
Add the indicator to any chart. Choose how far back to detect pivots using Pivot Length and set Pivot Memory to control how many are kept for clustering (more pivots give smoother levels but can slow performance). If you want the script to pick the number of levels automatically, enable Auto No. Levels ; otherwise, set Number of Levels . The colored horizontal lines represent the calculated key levels, and circles show where pivots occurred colored by which cluster they belong to. The labels beside each level indicate its strength, so you can see which levels are supported by more pivots. If Show Metrics Table is enabled, you will see statistics about the clustering in the corner you selected. Use this tool to spot areas where price often reacts and to plan entries or exits around levels that have been significant over time. Adjust settings to better match volatility and history depth of your instrument.
Liquidity Break Probability [PhenLabs]📊 Liquidity Break Probability
Version: PineScript™ v6
The Liquidity Break Probability indicator revolutionizes how traders approach liquidity levels by providing real-time probability calculations for level breaks. This advanced indicator combines sophisticated market analysis with machine learning inspired probability models to predict the likelihood of high/low breaks before they happen.
Unlike traditional liquidity indicators that simply draw lines, LBP analyzes market structure, volume profiles, momentum, volatility, and sentiment to generate dynamic break probabilities ranging from 5% to 95%. This gives traders unprecedented insight into which levels are most likely to hold or break, enabling more confident trading decisions.
🚀 Points of Innovation
Advanced 6-factor probability model weighing market structure, volatility, volume, momentum, patterns, and sentiment
Real-time probability updates that adjust as market conditions change
Intelligent trading style presets (Scalping, Day Trading, Swing Trading) with optimized parameters
Dynamic color-coded probability labels showing break likelihood percentages
Professional tiered input system - from quick setup to expert-level customization
Smart volume filtering that only highlights levels with significant institutional interest
🔧 Core Components
Market Structure Analysis: Evaluates trend alignment, level strength, and momentum buildup using EMA crossovers and price action
Volatility Engine: Incorporates ATR expansion, Bollinger Band positioning, and price distance calculations
Volume Profile System: Analyzes current volume strength, smart money proxies, and level creation volume ratios
Momentum Calculator: Combines RSI positioning, MACD strength, and momentum divergence detection
Pattern Recognition: Identifies reversal patterns (doji, hammer, engulfing) near key levels
Sentiment Analysis: Processes fear/greed indicators and market breadth measurements
🔥 Key Features
Dynamic Probability Labels: Real-time percentage displays showing break probability with color coding (red >70%, orange >50%, white <50%)
Trading Style Optimization: One-click presets automatically configure sensitivity and parameters for your trading timeframe
Professional Dashboard: Live market state monitoring with nearest level tracking and active level counts
Smart Alert System: Customizable proximity alerts and high-probability break notifications
Advanced Level Management: Intelligent line cleanup and historical analysis options
Volume-Validated Levels: Only displays levels backed by significant volume for institutional-grade analysis
🎨 Visualization
Recent Low Lines: Red lines marking validated support levels with probability percentages
Recent High Lines: Blue lines showing resistance zones with break likelihood indicators
Probability Labels: Color-coded percentage labels that update in real-time
Professional Dashboard: Customizable panel showing market state, active levels, and current price
Clean Display Modes: Toggle between active-only view for clean charts or historical view for analysis
📖 Usage Guidelines
Quick Setup
Trading Style Preset
Default: Day Trading
Options: Scalping, Day Trading, Swing Trading, Custom
Description: Automatically optimizes all parameters for your preferred trading timeframe and style
Show Break Probability %
Default: True
Description: Displays percentage labels next to each level showing break probability
Line Display
Default: Active Only
Options: Active Only, All Levels
Description: Choose between clean active-only view or comprehensive historical analysis
Level Detection Settings
Level Sensitivity
Default: 5
Range: 1-20
Description: Lower values show more levels (sensitive), higher values show fewer levels (selective)
Volume Filter Strength
Default: 2.0
Range: 0.5-5.0
Description: Controls minimum volume threshold for level validation
Advanced Probability Model
Market Trend Influence
Default: 25%
Range: 0-50%
Description: Weight given to overall market trend in probability calculations
Volume Influence
Default: 20%
Range: 0-50%
Description: Impact of volume analysis on break probability
✅ Best Use Cases
Identifying high-probability breakout setups before they occur
Determining optimal entry and exit points near key levels
Risk management through probability-based position sizing
Confluence trading when multiple high-probability levels align
Scalping opportunities at levels with low break probability
Swing trading setups using high-probability level breaks
⚠️ Limitations
Probability calculations are estimations based on historical patterns and current market conditions
High-probability setups do not guarantee successful trades - risk management is essential
Performance may vary significantly across different market conditions and asset classes
Requires understanding of support/resistance concepts and probability-based trading
Best used in conjunction with other analysis methods and proper risk management
💡 What Makes This Unique
Probability-Based Approach: First indicator to provide quantitative break probabilities rather than simple S/R lines
Multi-Factor Analysis: Combines 6 different market factors into a comprehensive probability model
Adaptive Intelligence: Probabilities update in real-time as market conditions change
Professional Interface: Tiered input system from beginner-friendly to expert-level customization
Institutional-Grade Filtering: Volume validation ensures only significant levels are displayed
🔬 How It Works
1. Level Detection:
Identifies pivot highs and lows using configurable sensitivity settings
Validates levels with volume analysis to ensure institutional significance
2. Probability Calculation:
Analyzes 6 key market factors: structure, volatility, volume, momentum, patterns, sentiment
Applies weighted scoring system based on user-defined factor importance
Generates probability score from 5% to 95% for each level
3. Real-Time Updates:
Continuously monitors price action and market conditions
Updates probability calculations as new data becomes available
Adjusts for level touches and changing market dynamics
💡 Note: This indicator works best on timeframes from 1-minute to 4-hour charts. For optimal results, combine with proper risk management and consider multiple timeframe analysis. The probability calculations are most accurate in trending markets with normal to high volatility conditions.
Logarithmic Moving Average (LMA) [QuantAlgo]🟢 Overview
The Logarithmic Moving Average (LMA) uses advanced logarithmic weighting to create a dynamic trend-following indicator that prioritizes recent price action while maintaining statistical significance. Unlike traditional moving averages that use linear or exponential weights, this indicator employs logarithmic decay functions to create a more sophisticated price averaging system that adapts to market volatility and momentum conditions.
The indicator displays a smoothed signal line that oscillates around zero, with positive values indicating bullish momentum and negative values indicating bearish momentum. The signal incorporates trend quality assessment, momentum confirmation, and multiple filtering mechanisms to help traders and investors identify trend continuation and reversal opportunities across different timeframes and asset classes.
🟢 How It Works
The indicator's core innovation lies in its logarithmic weighting system, where weights are calculated using the formula: w = 1.0 / math.pow(math.log(i + steepness), 2) The steepness parameter controls how aggressively recent data is prioritized over historical data, creating a dynamic weight decay that can be fine-tuned for different trading styles. This logarithmic approach provides more nuanced weight distribution compared to exponential moving averages, offering better responsiveness while maintaining stability.
The LMA calculation combines multiple sophisticated components. First, it calculates the logarithmic weighted average of closing prices. Then it measures the slope of this average over a 10-period lookback: lmaSlope = (lma - lma ) / lma * 100 The system also incorporates trend quality assessment using R-squared correlation analysis of log-transformed prices, measuring how well the price data fits a linear trend model over the specified period.
The final signal generation uses the formula: signal = lmaSlope * (0.5 + rSquared * 0.5) which combines the LMA slope with trend quality weighting. When momentum confirmation is enabled, the indicator calculates annualized log-return momentum and applies a multiplier when the momentum direction aligns with the signal direction, strengthening confirmed signals while filtering out weak or counter-trend movements.
🟢 How to Use
1. Signal Interpretation and Threshold Zones
Positive Values (Above Zero): LMA slope indicating bullish momentum with upward price trajectory relative to logarithmic baseline
Negative Values (Below Zero): LMA slope indicating bearish momentum with downward price trajectory relative to logarithmic baseline
Zero Line Crosses: Signal transitions between bullish and bearish regimes, indicating potential trend changes
Long Entry Threshold Zone: Area above positive threshold (default 0.5) indicating confirmed bullish signals suitable for long positions
Short Entry Threshold Zone: Area below negative threshold (default -0.5) indicating confirmed bearish signals suitable for short positions
Extreme Values: Signals exceeding ±1.0 represent strong momentum conditions with higher probability of continuation
2. Momentum Confirmation and Visual Analysis
Signal Color Intensity: Gradient coloring shows signal strength, with brighter colors indicating stronger momentum
Bar Coloring: Optional price bar coloring matches signal direction for quick visual trend identification
Position Labels: Real-time position classification (Bullish/Bearish/Neutral) displayed on the latest bar
Momentum Weight Factor: When short-term log-return momentum aligns with LMA signal direction, the signal receives additional weight confirmation
Trend Quality Component: R-squared values weight the signal strength, with higher correlation indicating more reliable trend conditions
3. Examples: Preconfigured Settings
Default: Universally applicable configuration balanced for medium-term investing and general trading across multiple timeframes and asset classes.
Scalping: Highly responsive setup with shorter period and higher steepness for ultra-short-term trades on 1-15 minute charts, optimized for quick momentum shifts.
Swing Trading: Extended period with moderate steepness and increased smoothing for multi-day positions, designed to filter noise while capturing larger price swings on 1-4 hour and daily charts.
Trend Following: Maximum smoothing with lower steepness for established trend identification, generating fewer but more reliable signals optimal for daily and weekly timeframes.
Mean Reversion: Shorter period with high steepness for counter-trend strategies, more sensitive to extreme moves and reversal opportunities in ranging market conditions.
Avg daily rangeThe Average Daily Range (ADR) is a technical indicator that measures the average price movement of a financial instrument over a specific period.
Price Reaction Analysis by Day of WeekOverview
The "Price Reaction Analysis by Day of Week" indicator is a tool that enables traders to analyze historical price reaction patterns to technical indicator signals on a selected day of the week. It examines price behavior on a chosen candle (from 1 to 30) in the next day or subsequent days after a signal, depending on the timeframe, and provides success rate statistics to support data-driven trading decisions. The indicator is optimized for timeframes up to 1 day (e.g., 1D, 12H, 8H, 6H, 4H, 1H, 15M), as the analysis relies on day-of-week comparisons. Lower timeframes generate more signals due to the higher number of candles per day.
Key Features
1. Flexible Technical Indicator Selection
Users can choose one of four technical indicators: RSI, SMI, MA, or Bollinger Bands. Each indicator has configurable parameters, such as:
RSI length, oversold/overbought levels.
SMI length, %K and %D smoothing, signal levels.
MA length.
Bollinger Bands length and multiplier.
2. Day-of-Week Analysis
The indicator allows users to select a day of the week (Monday, Tuesday, Wednesday, Thursday, Friday) for generating signals. It analyzes price reactions on a selected candle (from 1 to 30) in the next day or subsequent days after the signal. Examples:
On a daily timeframe, a signal on Monday can be analyzed for the first, fourth, or later candle (up to 30) in subsequent days (e.g., Tuesday, Wednesday).
On timeframes lower than 1 day (e.g., 12H, 8H, 6H, 4H, 1H, 15M), the analysis targets the selected candle in the next day or subsequent days. For example, on a 4H timeframe, you can analyze the second Tuesday candle following a Monday signal. The maximum timeframe is 1 day to ensure consistent day-of-week analysis.
3. Visual Signals
Signals for the analysis period are marked with background highlights in real-time when the indicator’s conditions are met. The last highlighted candle of the selected day is always analyzed. Arrows are displayed on the chart at the candle specified by the “Candles to Compare” setting (e.g., the first candle if set to 1):
Green upward triangles (below the candle) for successful buy signals (the closing price of the selected candle is higher than the signal candle’s close).
Red downward triangles (above the candle) for successful sell signals (the closing price of the selected candle is lower than the signal candle’s close).
Gray “x” marks for unsuccessful signals (no price reversal in the expected direction). Arrow positions are intuitive: buy signals below the candle, sell signals above. Highlights and arrows do not require waiting for future signals but are essential for calculating statistics.
Note: The first candle of the next day may appear shifted on the chart due to timezone differences, which can affect the timing of signal appearance.
4. Signal Conditions (Highlights) for Each Indicator
RSI: The oscillator is in oversold (buy) or overbought (sell) zones.
SMI: SMI returns from oversold (buy) or overbought (sell) zones.
MA: Price crosses the MA (upward for buy, downward for sell).
Bollinger Bands: Price returns inside the bands (from below for buy, from above for sell).
5. Success Rate Statistics
A table in the top-right corner of the chart displays:
The number of buy and sell signals for the selected day of the week.
The percentage of cases where the price of the selected candle in the next day or subsequent days reversed as expected (e.g., rising after a buy signal). Statistics are based on comparing the closing price of the signal candle with the closing price of the selected candle (e.g., first, fourth) in the next day or subsequent days.
Important: Statistics do not account for price movements within the candle or after its close. The price on the selected candle (e.g., fourth) may be lower than earlier candles but still higher than the signal candle, counting as a positive buy signal, though it does not guarantee profit.
6. Date Range
Users can specify the analysis date range, enabling strategy testing on historical data from a chosen period. Ensure the start and end dates are set correctly.
Applications
The indicator is designed for traders who want to leverage historical patterns for position planning. Examples:
On a 4-hour timeframe: If a sell signal highlight appears on Monday and statistics show an 80% chance that the fourth Tuesday candle is bearish, traders may consider playing a correction at the open of that candle.
On a daily timeframe: If a highlight indicates market overheating, traders may consider entering a position at the open of the first candle after the signal (e.g., Tuesday), provided statistics suggest an edge. Users can analyze the signal on the first candle and check later candles to validate results, increasing confidence in consistent patterns.
Key Settings
Indicator Type: Choose between RSI, SMI, MA, or Bollinger Bands.
Selected Day: Monday, Tuesday, Wednesday, Thursday, or Friday.
Candles to Compare: The number of the candle in the next day or subsequent days (from 1 to 30).
Indicator Parameters: Lengths, levels (e.g., oversold/overbought for RSI).
Background Colors: Configurable highlights for buy and sell signals.
Notes
Timeframes: The indicator is optimized for timeframes up to 1 day (e.g., 1D, 12H, 8H, 6H, 4H, 1H, 15M), as the analysis relies on day-of-week patterns. Timeframes lower than 1 day generate more signals due to the higher number of candles per day.
Candle Shift: The first candle of the next day may appear shifted on the chart due to timezone differences, affecting the timing of signals across markets or platforms.
Statistical Limitations: Results are based on the closing prices of the selected candle, ignoring fluctuations in earlier candles, within the candle, or subsequent price movements. Traders must assess whether entering at the open or after the close of the selected candle is profitable.
Testing: Effectiveness depends on historical data and parameter settings. Testing different configurations across markets and timeframes is recommended.
Who Is It For?
Swing and position traders who base decisions on technical analysis and historical patterns.
Market analysts seeking patterns in price behavior by day of the week.
TradingView users of all experience levels, thanks to an intuitive interface and flexible settings.
Boomerang Trading Indicator# Boomerang News Trading Indicator
## Overview
The Boomerang Trading Indicator is designed to identify potential reversal opportunities following major economic news releases. This indicator analyzes the initial market reaction to news events and provides visual cues for potential counter-trend trading opportunities based on Fibonacci retracement levels.
## How It Works
### News Event Detection
- Automatically detects major news release times (NFP, CPI, FOMC, etc.)
- Analyzes the first significant price movement following news releases
- Requires minimum candle size threshold to filter out weak reactions
### First Move Analysis
The indicator employs multiple analytical methods to determine the initial market direction:
**Simple Analysis (High Confidence):**
- When the news candle has ≥70% body-to-total ratio, uses straightforward bullish/bearish classification
**Advanced Analysis (Complex Cases):**
- Volume-weighted direction analysis
- Momentum and wick pattern analysis
- Market structure and gap analysis
- Weighted voting system combining all methods
### Entry Signal Generation
Based on the "boomerang" concept where markets often reverse after initial news reactions:
**For Bullish First Moves (Price Up Initially):**
- Generates SHORT entry signals when price retraces to 1.25-1.5 Fibonacci levels
- Visual: Red triangles above price bars
**For Bearish First Moves (Price Down Initially):**
- Generates LONG entry signals when price retraces to -0.25 to -0.5 Fibonacci levels
- Visual: Green triangles below price bars
## Key Features
### Visual Elements
- **Fibonacci Levels**: Displays key retracement levels based on the initial reaction range
- **Entry Zones**: Clear visual marking of optimal entry areas
- **Direction Arrows**: Shows the initial market reaction direction
- **Target Levels**: Displays profit target zones at 50% and 100% retracement levels
### Information Panel
Real-time display showing:
- Current setup status
- First move direction and body percentage
- Recommended trade direction
- Key price levels (reaction high/low)
- Profit targets with historical success rates
### Alert System
- Pre-news warnings (customizable timing)
- News event notifications
- Setup activation alerts
- Entry signal notifications
### Success Tracking
- Visual "BOOM!" animations when targets are hit
- Target 1 (50% level): ~95% historical success rate
- Target 2 (Main target): ~80% historical success rate
## Configuration Options
### Time Settings
- News release hour and minute (customizable for different events)
- Pre-news alert timing
- Setup duration (default 60 bars after news)
### Fibonacci Levels
- Adjustable retracement percentages
- Customizable target levels
- Mid-level importance weighting
### Risk Management
- Minimum reaction candle size filter
- Maximum risk point setting
- Visual risk/reward display
### Display Options
- Toggle Fibonacci level visibility
- Toggle target level display
- Toggle animation effects
- Customizable alert preferences
## Applicable News Events
This indicator is designed for high-impact economic releases:
- Non-Farm Payrolls (NFP) - First Friday, 8:30 AM ET
- Consumer Price Index (CPI) - Monthly, 8:30 AM ET
- Producer Price Index (PPI) - Monthly, 8:30 AM ET
- Gross Domestic Product (GDP) - Quarterly, 8:30 AM ET
- FOMC Interest Rate Decisions - 8 times yearly, 2:00 PM ET
## Trading Strategy Framework
### Core Principle
Markets often overreact to news initially, then reverse toward more rational price levels. This "boomerang effect" creates short-term trading opportunities.
### Entry Strategy
1. Wait for significant initial reaction (>10 points minimum)
2. Identify the initial direction using multi-factor analysis
3. Trade opposite to the initial reaction when price reaches sweet spot zones
4. Use Fibonacci retracement levels as entry triggers
### Risk Management
- Always use appropriate position sizing
- Set stop losses beyond recent swing levels
- Consider market volatility and news importance
- Monitor for setup invalidation signals
## Important Notes
### Educational Purpose
This indicator is for educational and analytical purposes. Users should:
- Thoroughly test strategies in demo environments
- Understand the risks involved in news trading
- Consider market conditions and volatility
- Use proper risk management techniques
### Market Considerations
- High volatility during news events increases both opportunity and risk
- Spreads may widen significantly during news releases
- Different brokers may have varying execution conditions
- Economic calendar timing may vary between sources
### Limitations
- Past performance does not guarantee future results
- Market conditions can change, affecting strategy effectiveness
- News events may have unexpected outcomes affecting normal patterns
- Technical analysis should be combined with fundamental analysis
## Version Information
- Compatible with TradingView Pine Script v5
- Designed for 1-minute timeframe optimal performance
- Works on major forex pairs, indices, and commodities
- Regular updates based on market condition changes
---
**Disclaimer:** This indicator is provided for educational purposes only. Trading involves substantial risk and is not suitable for all investors. Past performance is not indicative of future results. Users should conduct their own research and consider their financial situation before making trading decisions.
Micro Futures Contract Calculator Micro Futures Contract Calculator
Synopsis: The Micro Futures Contract Calculator is a sleek, minimalist indicator that calculates the number of Micro E-mini Nasdaq-100 (MNQ) or S&P 500 (MES) contracts you can trade based on a fixed dollar risk and stop-loss (in ticks). Displayed in a compact, professional table in the top-right corner, it shows your risk, stop-loss, contract type, and calculated contracts, helping traders maintain consistent risk management.
How to Use:
Add the indicator to your chart (search “Micro Futures Contract Calculator”).
In settings, input:
Maximum Risk ($): Your total risk per trade (e.g., $100).
Stop-Loss (Ticks): Stop-loss size in ticks (e.g., 20 ticks = 5 points).
Contract Type: Select MNQ or MES.
Check the top-right table for:
Risk, stop-loss, contract type, and number of contracts (e.g., “10” for MNQ, “4” for MES).
Use the contract number to size trades, ensuring risk stays fixed.
Why Standardized Risk is Important:
Consistency: Fixed risk per trade (e.g., $100) prevents oversized losses, stabilizing long-term performance.
Discipline: Removes emotional guesswork, enforcing a systematic approach across MNQ/MES trades.
Capital Protection: Limits exposure, preserving your account during losing streaks and volatile markets.
Scalability: Aligns position sizing with your risk tolerance, enabling confident scaling as your account grows.
This indicator simplifies risk management, making it essential for disciplined futures trading.
OI Bahavior MapThis indicator visualizes Open Interest (OI) changes for Binance Futures and highlights the behavior of market participants — whether takers or makers are opening or closing positions.
📊 Supported display modes:
• Taker or Maker
• Longs or Shorts
• Cumulative or Per-Bar
• Displayed in USD or Coins
💡 Each candle color reflects the dominant trade direction (delta):
🟢 Green = Aggressive buying (Delta Buy)
🔴 Red = Aggressive selling (Delta Sell)
OI direction (↑/↓) determines whether positions are being opened or closed.
🛠️ Optional metrics:
• Moving average of OI (SMA, EMA, WMA, VWMA, LSMA)
• Volatility channels (Bollinger Bands or Extremums)
⚙️ How it works:
• Fetches OI data from the SYMBOL_OI ticker (e.g., BTCUSDT_OI)
• Compares current OI with the previous bar
• Uses signed volume delta (close - open) to infer intent
• Classifies bar as open/close, long/short, taker/maker
• Displays the net effect as a colored candle on a secondary chart
🤔 How to interpret Taker and Maker?
• Taker: The aggressive participant who removes liquidity (initiates the trade)
• Maker: The passive participant who provides liquidity (places resting orders)
You can choose to display the same event from either the Taker or Maker perspective — the chart will look the same, but the interpretation changes.
🧠 Core Logic Mapping
```
🟢 Green: Taker Longs (Buy, OI↑) | Maker Shorts (Buy, OI↓)
🔴 Red: Taker Shorts (Sell, OI↑) | Maker Longs (Sell, OI↓)
```
⚠️ Limitations:
• Works only for Binance Futures
• Requires existence of SYMBOL_OI ticker on TradingView
• Represents approximate intent based on OI + volume behavior
💬 Open Source
The script is open for the community. Suggestions and feedback are welcome in the comments!
__________________________________________________________________________________
Этот индикатор визуализирует изменения открытого интереса (OI) для Binance Futures и показывает поведение участников рынка — открывают или закрывают позиции тейкеры или мейкеры.
📊 Доступные режимы отображения:
• Taker или Maker
• Longs или Shorts
• Кумулятивный или по бару
• В USD или в монетах
💡 Каждый цвет свечи отражает преобладающее направление сделок (дельта):
🟢 Зеленый = Агрессивные покупки (Delta Buy)
🔴 Красный = Агрессивные продажи (Delta Sell)
Направление OI (↑/↓) показывает, открываются или закрываются позиции.
🛠️ Дополнительные метрики:
• Скользящая средняя OI (SMA, EMA, WMA, VWMA, LSMA)
• Волатильностные каналы (Bollinger Bands или экстремумы)
⚙️ Как работает:
• Получает данные OI из тикера SYMBOL_OI (например, BTCUSDT_OI)
• Сравнивает текущий OI с предыдущим баром
• Использует направленную дельту объема (close - open) для определения намерения
• Классифицирует бар как открытие/закрытие, лонг/шорт, тейкер/мейкер
• Отображает итог в виде цветной свечи на дополнительном графике
🤔 Как интерпретировать Taker и Maker?
• Taker: Агрессивный участник, который изымает ликвидность (инициирует сделку)
• Maker: Пассивный участник, который создает ликвидность (выставляет лимитные заявки)
Вы можете выбрать отображение события с позиции тейкера или мейкера — график будет одинаковым, но смысл меняется.
🧠 Схема логики
```
🟢 Зеленый: Taker Longs (Покупка, OI↑) | Maker Shorts (Покупка, OI↓)
🔴 Красный: Taker Shorts (Продажа, OI↑) | Maker Longs (Продажа, OI↓)
```
⚠️ Ограничения:
• Работает только для Binance Futures
• Требуется наличие тикера SYMBOL_OI на TradingView
• Показывает приблизительное намерение на основе OI и дельты объема
💬 Open Source
Скрипт открыт для сообщества. Предложения и обратная связь приветствуются в комментариях!
BTC/Fiat Divergence & Spread Monitor📄 BTC/Fiat Divergence & Spread Monitor
This indicator visualizes Bitcoin’s relative performance across multiple fiat currencies and highlights periods of unusual divergence. It helps traders assess which fiat pairs BTC has outperformed or underperformed over a configurable lookback period and monitor the dynamic spread between the strongest and weakest pairs.
Features:
Relative Performance Matrix:
Ranks BTC returns in 6 fiat pairs, displaying a color-coded table of percentage changes and ranks.
Divergence Spread Oscillator:
Calculates the spread between the top and bottom performing pairs and normalizes this using a Z-Score. The oscillator helps identify when fiat pricing divergence is unusually high or compressed.
Dynamic Smoothing:
Optional Hull Moving Average smoothing to reduce noise in the spread signal.
Customizable Inputs:
Lookback period for percent change.
Z-Score normalization window.
Smoothing length.
Symbol selection for each fiat pair.
Visual Mode Toggle:
Switch between relative performance lines and spread oscillator view.
Potential Use Cases:
Fiat Rotation:
Identify which fiat is relatively weak or strong to optimize your exit currency when taking BTC profits.
Volatility Detection:
Use the spread Z-Score to detect periods of high divergence across fiat pairs, signaling macro FX volatility or dislocations.
Regime Analysis:
Track when fiat spreads are converging or expanding, potentially signaling market regime shifts.
Risk Management:
When divergence is extreme (Z-Score > +1), consider reducing position sizing or waiting for reversion.
Disclaimer:
This indicator is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security or asset. Always do your own research and consult a qualified financial professional before making trading decisions. Use at your own risk.
Tip:
Experiment with different lookback periods and smoothing settings to adapt the indicator to your timeframe and trading style.
Uptrick: Universal Z-Score ValuationOverview
The Uptrick: Universal Z-Score Valuation is a tool designed to help traders spot when the market might be overreacting—whether that’s on the upside or the downside. It does this by combining the Z-scores of multiple key indicators into a single average, letting you see how far the current market conditions have stretched away from “normal.” This average is shown as a smooth line, supported by color-coded visuals, signal markers, optional background highlights, and a live breakdown table that shows the contribution of each indicator in real time. The focus here is on spotting potential reversals, not following trends. The indicator works well across all timeframes and asset classes, from fast intraday charts like the 1-minute and 5-minute, to higher timeframes such as the 4-hour, daily, or even weekly. Its universal design makes it suitable for any market — whether you're trading crypto, stocks, forex, or commodities.
Introduction
To understand what this indicator does, let’s start with the idea of a Z-score. In simple terms, a Z-score tells you how far a number is from the average of its recent history, measured in standard deviations. If the price of an asset is two standard deviations above its mean, that means it’s statistically “rare” or extended. That doesn’t guarantee a reversal—but it suggests the move is unusual enough to pay attention.
This concept isn’t new, but what this indicator does differently is apply the Z-score to a wide set of market signals—not just price. It looks at momentum, volatility, volume, risk-adjusted performance, and even institutional price baselines. Each of those indicators is normalized using Z-scores, and then they’re combined into one average. This gives you a single, easy-to-read line that summarizes whether the entire market is behaving abnormally. Instead of reacting to one indicator, you’re reacting to a statistically balanced blend.
Purpose
The goal of this script is to catch turning points—places where the market may be topping out or bottoming after becoming overstretched. It’s built for traders who want to fade sharp moves rather than follow trends. Think of moments when price explodes upward and starts pulling away from every moving average, volume spikes, volatility rises, and RSI shoots up. This tool is meant to spot those situations—not just when price is stretched, but when multiple different indicators agree that something is overdone.
Originality and Uniqueness
Most indicators that use Z-scores only apply them to one thing—price, RSI, or maybe Bollinger Bands. This one is different because it treats each indicator as a contributor to the full picture. You decide which ones to include, and the script averages them out. This makes the tool flexible but also deeply informative.
It doesn’t rely on complex or hidden math. It uses basic Z-score formulas, applies them to well-known indicators, and shows you the result. What makes it unique is the way it brings those signals together—statistically, visually, and interactively—so you can see what’s happening in the moment with full transparency. It’s not trying to be flashy or predictive. It’s just showing you when things have gone too far, too fast.
Inputs and Parameters
This indicator includes a wide range of configurable inputs, allowing users to customize which components are included in the Z-score average, how each indicator is calculated, and how results are displayed visually. Below is a detailed explanation of each input:
General Settings
Z-Score Lookback (default: 100): Number of bars used to calculate the mean and standard deviation for Z-score normalization. Larger values smooth the Z-scores; smaller values make them more reactive.
Bar Color Mode (default: None): Determines how bars are visually colored. Options include: None: No candle coloring applied. - Heat: Smooth gradient based on the Z-score value. - Latest Signal: Applies a solid color based on the most recent buy or sell signal
Boolean - General
Plot Universal Valuation Line (default: true): If enabled, plots the average Z-score (zAvg) line in the separate pane.
Show Signals (default: true): Displays labels ("𝓤𝓹" for buy, "𝓓𝓸𝔀𝓷" for sell) when zAvg crosses above or below user-defined thresholds.
Show Z-Score Table (default: true): Displays a live table listing each enabled indicator's Z-score and the current average.
Select Indicators
These toggles enable or disable each indicator from contributing to the Z-score average:
Use VWAP Z-Score (default: true)
Use Sortino Z-Score (default: true)
Use ROC Z-Score (default: true)
Use Price Z-Score (default: true)
Use MACD Histogram Z-Score (default: false)
Use Bollinger %B Z-Score (default: false)
Use Stochastic K Z-Score (default: false)
Use Volume Z-Score (default: false)
Use ATR Z-Score (default: false)
Use RSI Z-Score (default: false)
Use Omega Z-Score (default: true)
Use Sharpe Z-Score (default: true)
Only enabled indicators are included in the average. This modular design allows traders to tailor the signal mix to their preferences.
Indicator Lengths
These inputs control how each individual indicator is calculated:
MACD Fast Length (default: 12)
MACD Slow Length (default: 26)
MACD Signal Length (default: 9)
Bollinger Basis Length (default: 20): Used to compute the Bollinger %B.
Bollinger Deviation Multiplier (default: 2.0): Standard deviation multiplier for the Bollinger Band calculation.
Stochastic Length (default: 14)
ATR Length (default: 14)
RSI Length (default: 14)
ROC Length (default: 10)
Zones
These thresholds define key signal levels for the Z-score average:
Neutral Line Level (default: 0): Baseline for the average Z-score.
Bullish Zone Level (default: -1): Optional intermediate zone suggesting early bullish conditions.
Bearish Zone Level (default: 1): Optional intermediate zone suggesting early bearish conditions.
Z = +2 Line Level (default: 2): Primary threshold for bearish signals.
Z = +3 Line Level (default: 3): Extreme bearish warning level.
Z = -2 Line Level (default: -2): Primary threshold for bullish signals.
Z = -3 Line Level (default: -3): Extreme bullish warning level.
These zone levels are used to generate signals, fill background shading, and draw horizontal lines for visual reference.
Why These Indicators Were Merged
Each indicator in this script was chosen for a specific reason. They all measure something different but complementary.
The VWAP Z-score helps you see when price has moved far from the volume-weighted average, often used by institutions.
Sortino Ratio Z-score focuses only on downside risk, which is often more relevant to traders than overall volatility.
ROC Z-score shows how fast price is changing—strong momentum may burn out quickly.
Price Z-score is the raw measure of how far current price has moved from its mean.
RSI Z-score shows whether momentum itself is stretched.
MACD Histogram Z-score captures shifts in trend strength and acceleration.
%B (Bollinger) Z-score indicates how close price is to the upper or lower volatility envelope.
Stochastic K Z-score gives a sense of how high or low price is relative to its recent range.
Volume Z-score shows when trading activity is unusually high or low.
ATR Z-score gives a read on volatility, showing if price movement is expanding or contracting.
Sharpe Z-score measures reward-to-risk performance, useful for evaluating trend quality.
Omega Z-score looks at the ratio of good returns to bad ones, offering a more nuanced view of efficiency.
By normalizing each of these using Z-scores and averaging only the ones you turn on, the script creates a flexible, balanced view of the market’s statistical stretch.
Calculations
The core formula is the standard Z-score:
Z = (current value - average) / standard deviation
Every indicator uses this formula after it’s calculated using your chosen settings. For example, RSI is first calculated as usual, then its Z-score is calculated over your selected lookback period. The script does this for every indicator you enable. Then it averages those Z-scores together to create a single value: zAvg. That value is plotted and used to generate visual cues, signals, table values, background color changes, and candle coloring.
Sequence
Each selected indicator is calculated using your custom input lengths.
The Z-score of each indicator is computed using the shared lookback period.
All active Z-scores are added up and averaged.
The resulting zAvg value is plotted as a line.
Signal conditions check if zAvg crosses user-defined thresholds (default: ±2).
If enabled, the script plots buy/sell signal labels at those crossover points.
The candle color is updated using your selected mode (heatmap or signal-based).
If extreme Z-scores are reached, background highlighting is applied.
A live table updates with each individual Z-score so you know what’s driving the signal.
Features
This script isn’t just about stats—it’s about making them usable in real time. Every feature has a clear reason to exist, and they’re all there to give you a better read on market conditions.
1. Universal Z-Score Line
This is your primary reference. It reflects the average Z-score across all selected indicators. The line updates live and is color-coded to show how far it is from neutral. The further it gets from 0, the brighter the color becomes—cyan for deeply oversold conditions, magenta for overbought. This gives you instant feedback on how statistically “hot” or “cold” the market is, without needing to read any numbers.
2. Signal Labels (“𝓤𝓹” and “𝓓𝓸𝔀𝓷”)
When the average Z-score drops below your lower bound, you’ll see a "𝓤𝓹" label below the bar, suggesting potential bullish reversal conditions. When it rises above the upper bound, a "𝓓𝓸𝔀𝓷" label is shown above the bar—indicating possible bearish exhaustion. These labels are visually clear and minimal so they don’t clutter your chart. They're based on clear crossover logic and do not repaint.
3. Real-Time Z-Score Table
The table shows each indicator's individual Z-score and the final average. It updates every bar, giving you a transparent breakdown of what’s happening under the hood. If the market is showing an extreme average score, this table helps you pinpoint which indicators are contributing the most—so you’re not just guessing where the pressure is coming from.
4. Bar Coloring Modes
You can choose from three modes:
None: Keeps your candles clean and untouched.
Heat: Applies a smooth gradient color based on Z-score intensity. As conditions become more extreme, candle color transitions from neutral to either cyan (bullish pressure) or magenta (bearish pressure).
Latest Signal: Applies hard coloring based on the most recent signal—greenish for a buy, purple for a sell. This mode is great for tracking market state at a glance without relying on a gradient.
Every part of the candle is colored—body, wick, and border—for full visibility.
5. Background Highlighting
When zAvg enters an extreme zone (typically above +2 or below -2), the background shifts color to reflect the market’s intensity. These changes aren’t overwhelming—they’re light fills that act as ambient warnings, helping you stay aware of when price might be reaching a tipping point.
6. Customizable Zone Lines and Fills
You can define what counts as neutral, overbought, and oversold using manual inputs. Horizontal lines show your thresholds, and shaded regions highlight the most extreme zones (+2 to +3 and -2 to -3). These lines give you visual structure to understand where price currently stands in relation to your personal reversal model.
7. Modular Indicator Control
You don’t have to use all the indicators. You can enable or disable any of the 12 with a simple checkbox. This means you can build your own “blend” of market context—maybe you only care about RSI, price, and volume. Or maybe you want everything on. The script adapts accordingly, only averaging what you select.
8. Fully Customizable Sensitivity and Lengths
You can adjust the Z-score lookback length globally (default 100), and tweak individual indicator lengths separately. This lets you tune the indicator’s responsiveness to suit your trading style—slower for longer swings, faster for scalping.
9. Clean Integration with Any Chart Layout
All visual elements are designed to be informative without taking over your chart. The coloring is soft but clear, the labels are readable without being huge, and you can turn off any feature you don’t need. The indicator can work as a full dashboard or as a simple line with a couple of alerts—it’s up to you.
10. Precise, Real-Time Signal Logic
The crossover logic for signals is exact and only fires when the Z-score moves across your defined boundary. No estimation, no delay. Everything is calculated based on current and previous bar data, and nothing repaints or back-adjusts.
Conclusion
The Universal Z-Score Valuation indicator is a tool for traders who want a clear, unbiased way to detect overextension. Instead of relying on a single signal, you get a composite of several market perspectives—momentum, volatility, volume, and more—all standardized into a single view. The script gives you the freedom to control the logic, the visuals, and the components. Whether you use it as a confirmation tool or a primary signal source, it’s designed to give you clarity when markets become chaotic.
Disclaimer
This indicator is for research and educational use only. It does not constitute financial advice or guarantees of performance. All trading involves risk, and users should test any strategy thoroughly before applying it to live markets. Use this tool at your own discretion.
FastMetrixLibrary "FastMetrix"
This is a library I've been tweaking and working with for a while and I find it useful to get valuable technical analysis metrics faster (why its called FastMetrix). A lot of is personal to my trading style, so sorry if it does not have everything you want. The way I get my variables from library to script is by copying the return function into my new script.
TODO: Volatility and short term price analysis functions
slope(source, smoothing)
Parameters:
source (float)
smoothing (int)
integral(topfunction, bottomfunction, start, end)
Parameters:
topfunction (float)
bottomfunction (float)
start (int)
end (int)
deviation(x, y)
Parameters:
x (float)
y (float)
getema(len)
TODO: return important exponential long term moving averages and derivatives/variables
Parameters:
len (simple int)
getsma(len)
TODO: return requested sma
Parameters:
len (int)
kc(mult, len)
TODO: Return Keltner Channels variables and calculations
Parameters:
mult (simple float)
len (simple int)
bollinger(len, mult)
TODO: returns bollinger bands with optimal settings
Parameters:
len (int)
mult (simple float)
volatility(atrlen, smoothing)
TODO: Returns volatility indicators based on atr
Parameters:
atrlen (simple int)
smoothing (int)
premarketfib()
countinday(xcondition)
Parameters:
xcondition (bool)
countinsession(condition, n)
Parameters:
condition (bool)
n (int)
Open Interest Footprint IQ [TradingIQ]Hello Traders!
Th e Open Interest Footprint IQ indicator is an advanced visualization tool designed for cryptocurrency markets. It provides a granular, real-time breakdown of open interest changes across different price levels, allowing traders to see how aggressive market participation is distributed within each bar.
Unlike standard footprint charts that rely solely on volume, this indicator offers unique insights by focusing on the interaction between price action and changes in open interest (OI) — a leading metric often used to infer trader intent and positioning.
How it works
The Open Interest Footprint IQ processes lower timeframe price and open interest data to build a footprint-style chart that shows how traders are positioning themselves within each candle.
Here’s a breakdown of the process:
1. Granular OI & Price Sampling
The script retrieves lower-timeframe data (1-minute, 1-second, or 1-tick, based on your setting).
For each candle, it captures:
High and low prices
Price change direction
Change in open interest (OI)
2. Classifying Trader Behavior
For each lower-timeframe segment, the indicator determines the type of positioning occurring based on price movement and OI change:
If price is moving up and open interest is increasing, it suggests that long positions are being opened. This is considered a "Longs Opening" event, labeled as UU (Up/Up).
If price is moving up but open interest is decreasing, it indicates that short positions are being closed. This is referred to as UD (Up/Down), or "Shorts Closing."
If price is moving down and open interest is increasing, it signals that short positions are being opened. This is known as DU (Down/Up), or "Shorts Opening."
If price is moving down while open interest is also decreasing, it means that long positions are being closed. This is labeled as DD (Down/Down), or "Longs Closing."
These are stored in separate arrays and displayed at specific price levels.
It is particularly useful for identifying:
Where longs or shorts are opening/closing positions
Stacked imbalances (indicative of potential absorption or exhaustion)
Value area zones and POC (Point of Control) based on OI, not volume
This footprint runs on your choice of sub-bar granularity and is ideal for high-frequency trading, scalping, and entries based on order flow dynamics.
Key Features
Footprint Visualization
At each price level within a candle:
Long/short opening and closing behavior is broken down.
Delta (net open interest change) is displayed both numerically and color-coded.
Optional gradient coloring shows intensity and type of flow (longs/shorts opened/closed).
Cumulative or per-bar reset modes allow you to track OI evolution over time.
The image above explains the information that each Footprint box shows across a candlestick!
Each footprint box shows:
OI Delta
OI Delta %
Longs Opened (LO)
Longs Closed (LC)
Shorts Opened (SO)
Shorts Closed (SC)
The image above explains the color-coding feature of the indicator.
Boxes are color coded to show which position action
dominated at the price area.
For this example:
Green boxes = Long positions being opened dominated
Purple boxes = Long positions being closed dominated
Red boxes = Short positions being opened dominated
Yellow boxes = Short positions being closed dominated
All colors are customizable.
Additionally, for traders who are only interested in whether OI increased/decreased, a "two-color" option is available in the settings.
For the two-color option, footprint boxes can be one of two colors. Showing whether OI increased or decreased at the level.
Cumulative Levels
Open Interest Footprint IQ contains a "Cumulative Levels" feature that tracks/stores open interest change at tick levels over time, rather than resetting per bar.
With the "Cumulative Levels" feature enabled, traders can see open interest changes persist across all candlesticks. This feature is useful for determining whether longs opening, longs closing, shorts opening, or shorts closing are dominating at particular price areas over time rather than on a single bar.
A useful feature to see if shorts/longs are favoring certain price throughout the day, week, month, etc.
Input Settings Explained
Granularity (Dropdown: Granularity)
Options: 1-Minute, 1-Second, 1-Tick
Determines how finely the script samples the lower timeframe data to construct the footprint.
For precision:
1-Tick = Highest accuracy, but more resource-intensive.
1-Second/1-Minute = Suitable for broader or more zoomed-out analysis.
Tick Level Distance (Tick Level Distance (0 = Auto))
Defines the vertical spacing between levels in the footprint chart.
If 0, the script uses an automatic calculation based on ATR to adapt to volatility.
Set a manual value (e.g., 5) to control the height granularity of each level in ticks.
Cumulative Levels (Toggle)
If enabled, the footprint builds cumulatively over time, rather than resetting per candle.
Use case: Visualize ongoing buildup of OI activity across a session or day.
Cumulative Levels Reset TF (Timeframe)
Sets the reset interval for the cumulative view (e.g., reset daily, hourly, etc.)
Works only when Cumulative Levels is enabled.
Delta Box Display Settings
Show Delta Percentage
Toggles the display of the percentage change in OI across the footprint level.
Helpful to gauge how aggressive positioning is relative to total OI at that level.
Show Longs/Shorts (Opened/Closed)
Show Longs Opened: Displays OI increase in up candles (price ↑, OI ↑).
Show Longs Closed: Displays OI decrease in down candles (price ↓, OI ↓).
Show Shorts Opened: OI increase in down candles (price ↓, OI ↑).
Show Shorts Closed: OI decrease in up candles (price ↑, OI ↓).
These behaviors are color-coded to give traders instant context:
Blue-green for longs opening.
Purple for longs closing.
Red for shorts opening.
Yellow for shorts closing.
Value Area & POC
Value Area % (Value Area %)
Controls how much cumulative open interest is used to define the value area.
Example: 70% means the smallest range of prices that contains 70% of total OI in that bar will be marked.
Helps identify zones of interest, support/resistance, and institutional levels.
The image above explains how to identify the VAH/VAL/POC shown by Open Interest Footprint IQ.
VAH = Upper 🞂
POC = ●
VAL = Lower 🞂
Imbalances
Imbalance Percentage
Defines the minimum delta % required at a level to be marked as an imbalance.
If the net open interest change at a level exceeds this threshold, a visual marker appears.
Stacked Imbalance Count
If the number of consecutive imbalance levels meets this count, a “Stacked Imbalance” alert will trigger.
This can signal aggressive buying or selling pressure, potential breakout zones, or institutional absorption.
Color Settings
Longs Opened / Closed, Shorts Opened / Closed
Customize the color palette for each order flow behavior.
These colors appear in the background gradient of the footprint boxes.
Up/Down Only Mode
Toggle to override all behavior-based colors with a single Up Color and Down Color.
Useful if you prefer a simple bull/bear view.
Up Color / Down Color
If "Up/Down Only" is enabled, these two colors are used to represent all net positive or negative deltas.
Special Notes
Crypto only: This script works only with crypto tickers on TradingView.
For other assets (stocks, futures), a warning message will appear instead.
OI data must be available from the exchange (many perpetual pairs support this).
If the footprint is too small or invisible, increase your tick level spacing in the settings.
Alerts
When a stacked imbalance is detected, an alert is fired ("Stacked Imbalance").
This feature is useful for automated systems, bots, or simply staying informed of potential trade setups.
And that's all for now!
If you have any questions or features you'd like to see feel free to share them in the comments below!
Thank you traders!
Z Score Overlay [BigBeluga]🔵 OVERVIEW
A clean and effective Z-score overlay that visually tracks how far price deviates from its moving average. By standardizing price movements, this tool helps traders understand when price is statistically extended or compressed—up to ±4 standard deviations. The built-in scale and real-time bin markers offer immediate context on where price stands in relation to its recent mean.
🔵 CONCEPTS
Z Score Calculation:
Z = (Close − SMA) ÷ Standard Deviation
This formula shows how many standard deviations the current price is from its mean.
Statistical Extremes:
• Z > +2 or Z < −2 suggests statistically significant deviation.
• Z near 0 implies price is close to its average.
Standardization of Price Behavior: Makes it easier to compare volatility and overextension across timeframes and assets.
🔵 FEATURES
Colored Z Line: Gradient coloring based on how far price deviates—
• Red = oversold (−4),
• Green = overbought (+4),
• Yellow = neutral (~0).
Deviation Scale Bar: A vertical scale from −4 to +4 standard deviations plotted to the right of price.
Active Z Score Bin: Highlights the current Z-score bin with a “◀” arrow
Context Labels: Clear numeric labels for each Z-level from −4 to +4 along the side.
Live Value Display: Shows exact Z-score on the active level.
Non-intrusive Overlay: Can be applied directly to price chart without changing scaling behavior.
🔵 HOW TO USE
Identify overbought/oversold areas based on +2 / −2 thresholds.
Spot potential mean reversion trades when Z returns from extreme levels.
Confirm strong trends when price remains consistently outside ±2.
Use in multi-timeframe setups to compare strength across contexts.
🔵 CONCLUSION
Z Score Overlay transforms raw price action into a normalized statistical view, allowing traders to easily assess deviation strength and mean-reversion potential. The intuitive scale and color-coded display make it ideal for traders seeking objective, volatility-aware entries and exits.
Daily Trading Barometer (DTB) with DJIA OverlayThe "Daily Trading Barometer (DTB) with DJIA Overlay" is a custom technical indicator designed to identify intermediate-term overbought and oversold conditions in the stock market, inspired by Edson Gould's original DTB methodology. This indicator combines three key components:
A 7-day advance-decline oscillator, a 20-day volume oscillator, and a 28-day DJIA price ratio, normalized into a composite index scaled around 110–135. Values below 110 signal potential oversold conditions, while values above 135 indicate overbought territory, aiding in timing market reversals.
The overlay of a normalized DJIA plot allows for visual correlation with the broader market trend. Use this tool to anticipate turning points in oscillating markets, though it’s best combined with other indicators for confirmation. Ideal for traders seeking probabilistic insights into bear or bull market transitions.
How to use -
If the DTB line (blue) and normalized DJIA (orange) are under the green dashed line, high probability for a long and reversal.
Use with the symbol SPX/QQQ
Dow Jones Industrial Average - DJIA
Gap % Distribution Table (2% Bins)Description
This indicator displays a Gap % Distribution Table categorized in 2% bins ranging from `< -20%` to `> +20%`. It calculates the gap between today’s open and the previous day’s close, and groups occurrences into defined bins. The table includes:
Gap range, count, and percentage for each bin
A total row summarizing all entries
Customizable appearance including:
Font color, cell background fill (with transparency), and table border color
Column headers and full outer border
Date filtering using selectable start and end dates
Position control for placing the table on the chart area
Ideal for analyzing the historical behavior of opening gaps for any instrument.
