First FVG Directional Strategy (2:1 RR)This strategy captures directional momentum by trading the first confirmed Fair Value Gap (FVG) and holding that bias until an opposing FVG appears. It’s designed to align with ICT-style displacement logic, entering only when a clear imbalance is confirmed and exiting when the market structure shifts.
Key features:
✅ Directional bias lock: Trades only in the direction of the first FVG. No re-entries until reversal.
✅ FVG confirmation: Requires directional candle confirmation for valid gaps.
✅ 2:1 reward-to-risk targeting: Take profit is set at twice the distance of the stop loss.
✅ Clean, structure-driven logic: No indicators or overlays — just price action and delivery.
📈 Optimized for EURUSD on the 4-hour chart, where its structural logic and risk parameters are best aligned.
This strategy is ideal for traders seeking clarity, discipline, and directional conviction based on price imbalance and displacement.
Penunjuk dan strategi
MTG StochRSI+VWAPGreat buy and sell indicator. Works well on 3 min chart. Green Cross for buy Red Cross for sell. Uses StochRSI and VWAP. Happy Trading
Custom Horizontal Lines | Trade Symmetry📊 Custom Horizontal Lines
🔍 Overview
The Custom Horizontal Lines is a precision utility designed for traders who perform manual higher-timeframe analysis and want to preserve their marked price levels directly on the chart.
It doesn’t calculate or detect anything automatically — instead, it acts as your personal level memory, preserving your analyzed zones and reference prices throughout the session.
Ideal for traders who manually mark the High, Low, Open, Close, Mean Thresholds, and Quarter Levels of Order Blocks, Fair Value Gaps, Inversion Fair Value Gaps and Wicks before the trading day begins.
⚙️ Key Features
✅ Manual Level Entry — Input your analyzed price levels (OB, FVG, WICK,etc) directly into the indicator settings.
✅ Preserved Levels — Once entered, your lines stay visible and consistent — even after switching symbols, timeframes, or reloading the chart.
✅ Supports All Level Types — Store any kind of manually defined level: OB highs/lows, FVG boundaries, Wicks, Mean Thresholds, Quarter levels, or custom reference prices.
✅ Clean Visualization — Customize line color, style, and labels for easy visual organization.
✅ Session-Ready Workflow — Built for pre-market preparation — enter your HTF levels once, and trade around them all day.
✅ No Auto Calculations — 100% manual by design — ensuring only your analyzed levels are shown, exactly as you defined them.
💡 How to Use
Open the indicator’s settings and manually enter those price values.
The indicator will plot and preserve those exact levels on your chart.
Switch to your lower timeframe and observe how price reacts around them — without ever needing to redraw.
🎯 Why It’s Useful
Keeps your HTF levels organized and persistent across sessions.
Saves time by avoiding redrawing.
Fits perfectly into ICT / Smart Money trading workflows.
Ensures full manual control and precision over what’s displayed on your chart.
🧩 Ideal For
ICT and Smart Money traders
Institutional-style manual analysts
Traders marking Mean Thresholds, or Quarter Levels of OBs, FVGs, Wicks etc
Anyone who wants a clean, reliable way to preserve their manual analysis
Enhanced MA Crossover Pro📝 Strategy Summary: Enhanced MA Crossover Pro
This strategy is an advanced, highly configurable moving average (MA) crossover system designed for algorithmic trading. It uses the crossover of two customizable MAs (a "Fast" MA 1 and a "Slow" MA 2) as its core entry signal, but aggressively integrates multiple technical filters, time controls, and dynamic position management to create a robust and comprehensive trading system.
💡 Core Logic
Entry Signal: A bullish crossover (MA1 > MA2) generates a Long signal, and a bearish crossover (MA1 < MA2) generates a Short signal. Users can opt to use MA crossovers from a Higher Timeframe (HTF) for the entry signal.
Confirmation/Filters: The basic MA cross signal is filtered by several optional indicators (see Filters section below) to ensure trades align with a broader trend or momentum context.
Position Management: Trades are managed with a sophisticated system of Stop Loss, Take Profit, Trailing Stops, and Breakeven stops that can be fixed, ATR-based, or dynamically adjusted.
Risk Management: Daily limits are enforced for maximum profit/loss and maximum trades per day.
⚙️ Key Features and Customization
1. Moving Averages
Primary MAs (MA1 & MA2): Highly configurable lengths (default 8 & 20) and types: EMA, WMA, SMA, or SMMA/RMA.
Higher Timeframe (HTF) MAs: Optional MAs calculated on a user-defined resolution (e.g., "60" for 1-hour) for use as an entry signal or as a trend confirmation filter.
2. Multi-Filter System
The entry signal can be filtered by the following optional conditions:
SMA Filter: Price must be above a 200-period SMA for long trades, and below it for short trades.
VWAP Filter: Price must be above VWAP for long trades, and below it for short trades.
RSI Filter: Long trades are blocked if RSI is overbought (default 70); short trades are blocked if RSI is oversold (default 30).
MACD Filter: Requires the MACD Line to be above the Signal Line for long trades (and vice versa for short trades).
HTF Confirmation: Requires the HTF MA1 to be above HTF MA2 for long entries (and vice versa).
3. Dynamic Stop and Target Management (S/L & T/P)
The strategy provides extensive control over exits:
Stop Loss Methods:
Fixed: Fixed tick amount.
ATR: Based on a multiple of the Average True Range (ATR).
Capped ATR: ATR stop limited by a maximum fixed tick amount.
Exit on Close Cross MA: Position is closed if the price crosses back over the chosen MA (MA1 or MA2).
Breakeven Stop: A stop can be moved to the entry price once a trigger distance (fixed ticks or Adaptive Breakeven based on ATR%) is reached.
Trailing Stop: Can be fixed or ATR-based, with an optional feature to auto-tighten the trailing multiplier after the breakeven condition is met.
Profit Target: Can be a fixed tick amount or a dynamic target based on an ATR multiplier.
4. Time and Session Control
Trading Session: Trades are only taken between defined Start/End Hours and Minutes (e.g., 9:30 to 16:00).
Forced Close: All open positions are closed near the end of the session (e.g., 15:45).
Trading Days: Allows specific days of the week to be enabled or disabled for trading.
5. Risk and Position Limits
Daily Profit/Loss Limits: The strategy tracks daily realized and unrealized PnL in ticks and will close all positions and block new entries if the user-defined maximum profit or maximum loss is hit.
Max Trades Per Day: Limits the number of executed trades in a single day.
🎨 Outputs and Alerts
Plots: Plots the MA1, MA2, SMA, VWAP, and HTF MAs (if enabled) on the chart.
Shapes: Plots visual markers (BUY/SELL labels) on the bar where the MA crossover occurs.
Trailing Stop: Plots the dynamic trailing stop level when a position is open.
Alerts: Generates JSON-formatted alerts for entry ({"action":"buy", "price":...}) and exit ({"action":"exit", "position":"long", "price":...}).
Mean Reversion Scalping by XtramaskAvoid using this indicator in aggressively trending markets . Best in Non Treanding Markets
Opposing Candle V2🟩 OC (Opposing Candle) Multi–Timeframe Framework
🔍 Overview
The OC Indicator automatically detects and displays Opposing Candles (OCs) across up to three timeframes.
An Opposing Candle is a candle that fully engulfs the previous one, signaling a potential shift in control — either a trend continuation or a trend reversal.
This multi–timeframe framework gives traders a structured way to visualize displacement, pullbacks, and momentum shifts between timeframes.
⚙️ How It Works
Each OC is drawn as a box showing:
High & Low → The candle’s full range
Open Line (black) → Key control level
Midline (white) → Candle equilibrium
Optional labels for timeframe and session
You can enable up to 3 timeframes (e.g., 30m / 1H / 4H) and adjust how many OCs to display for each.
📈 Trading Framework
🔹 Continuation Setup (Trend Following)
1. 4H Bias → Bullish or Bearish
Identify clear trend structure (HH/HL = bullish, LH/LL = bearish).
Confirm strong displacement and visible gaps between OCs — signs of momentum and healthy trend continuation.
2. 1H Confirmation OC
OC forms in the direction of the 4H bias, confirming control.
3. 30min Pullback OC
Opposite–colored OC appears → represents the pullback.
4. Entry Trigger
A yellow candle closes beyond the 30min OC open line, confirming the end of the pullback.
→ Enter in trend direction.
🎯 Targets
Target 1: Next 1H OC high or low (in trend direction)
Target 2: Next 4H OC high or low
🛑 Stop: Beyond the 30min OC’s opposite wick
🔹 Reversal Setup (Trend Shift)
1. 4H Structure → Extended or Losing Momentum
When there are no higher–timeframe gaps and no displacement, momentum weakens — often a sign of potential reversal.
2. Opposing OC Forms on HTF
A strong engulfing OC appears against the previous trend at a key structural level.
3. Lower–Timeframe Alignment
1H and 30min OCs begin forming in the new direction, confirming control shift.
4. Entry Trigger
Break of the lower–timeframe OC open line signals the reversal confirmation.
🟢 Example: Bullish Reversal
4H downtrend shows compression (no displacement)
4H bullish OC forms at support
30min breaks above a bearish OC’s open line → Go long
🔴 Example: Bearish Reversal
4H uptrend stalls at resistance
4H bearish OC forms
30min breaks below a bullish OC’s open line → Go short
🎯 Targets
Target 1: Nearest opposing 1H OC high/low
Target 2: Major 4H structural high/low
🛑 Stop: Beyond the reversal OC wick
🧠 Key Concepts
Displacement = Strength. Strong, impulsive moves with clear gaps between OCs show continuation.
Compression = Weakness. Overlapping candles and no HTF displacement often hint at reversal.
OC = Control Candle. The open line is the “line in the sand” — when price breaks it, control flips.
Multi–TF Confluence = Precision. 4H → 1H → 30m gives you structure → confirmation → entry accuracy.
🎨 Features
✅ Multi–Timeframe OC detection (default: 30m / 1H / 4H)
✅ Bullish & Bearish boxes with open and midlines
✅ Break candles highlighted yellow
✅ Optional labels (timeframe + session)
✅ Session filters (Asia, London, NYAM, NYPM)
✅ Fully customizable visuals and extension lengths
SPY One-Direction Open Drive Detectorno open retracements meaning the chart will probably trend in a certain direction and probably never touch opening range again that day
Multi-Timeframe Supertrend [TCMaster]📊 SuperTrend Multi-Timeframe System (TCMaster)
This indicator combines multi-timeframe SuperTrend signals into a single overlay chart, allowing traders to visualize trend alignment across different timeframes instantly.
It’s designed to help identify high-probability trend continuation and reversal zones by synchronizing multiple SuperTrend layers.
🔍 Key Features
✅ Up to 4 independent SuperTrend layers, each with customizable parameters and timeframes
✅ Multi-timeframe analysis directly on the same chart (no need to switch timeframes)
✅ Instant alerts when a SuperTrend flips from uptrend to downtrend or vice versa
✅ Color-coded background for quick trend visualization
✅ Works on all markets and timeframes
⚙️ Inputs
ATR Length & Multiplier for each SuperTrend
Timeframe selection for each layer
Background color enable/disable toggle
Real-time alert options for trend change events
⚠️ Notes
The indicator is non-repainting and works in real time.
Use it as a trend confirmation tool combined with your existing trading strategy.
This script is for educational and informational purposes only, not financial advice.
💡 Recommended Use
Combine with oscillators (like RSI or Stochastic) or volume filters to improve entry confirmation.
Best for traders who follow multi-timeframe confluence and momentum-based setups.
ARVELOV MACD BubblesThis Pine Script is a customized Moving Average Convergence Divergence (MACD) indicator designed for TradingView. It plots the MACD signal line with a yellow color and a thicker line width for visibility, while visually highlighting bullish and bearish crossovers between the MACD and its signal line. When the MACD crosses above the signal line, a small green dot (bullish signal) is plotted, and when it crosses below, a small red dot (bearish signal) appears. These visual markers make it easier for traders to identify potential trend reversals or entry and exit points directly on the chart in real time.
Integrated Volatility Intelligence System (IVIS) AutoKVolMind™ AutoK — Integrated Volatility Intelligence System (IVIS)
IVIS AutoK
Author: © lfu
Public Description (for publication)
VolMind™ AutoK represents an institutional-grade open-source framework for adaptive volatility intelligence and probabilistic trade management.
This system fuses Kalman-inspired KAMA smoothing, CVD dynamics, Auto K-Means clustering, entropy-based regime analysis, and a Kolmogorov–Smirnov market normality test into a single modular platform.
Key Capabilities:
Adaptive ATR Stop Bands dynamically scale with volatility, entropy, and cluster variance.
Auto KMeans Intelligence automatically selects the optimal cluster count for price structure recognition (3–10 clusters).
Entropy Module quantifies structural uncertainty and information decay within price movement.
KS-Test Integration identifies non-normal distributions, signaling regime divergence and volatility inflection.
CVD Dynamics reveal real-time directional bias via cumulative volume delta.
MSI Composite Signal fuses multi-source indicators (ATR, CVD, entropy, clusters) to model market stress and adaptive risk.
Designed for forward-looking quant traders, IVIS serves as a volatility intelligence backbone for portfolio automation, volatility forecasting, and adaptive stop-loss scaling.
Fully open-source for research and applied strategy development. Not a financial advice. DYOR.
Dominus US Indici - Core4 (ES,NQ,YM,RTY) - EditabileOne-liner
“Dominus US Indici ranks ES, NQ, YM, RTY at the NY open using a blended Score (return from window start + VWAP delta) to highlight the strongest long/short and give clean BUY/SELL signals.”
Short paragraph
“Dominus US Indici analyzes the four core US indices (ES, NQ, YM, RTY) from the New York open. It builds a single Score by combining momentum from the window start with distance from VWAP, ranks the indices, and flags only the top, high-quality opportunity. Optional ‘Alpha vs S1’ (beta-neutral), macro gate (DXY & US10Y), editable symbols/timezone, and a freeze snapshot keep decisions consistent.”
Bullets
Core4: ES, NQ, YM, RTY (editable).
Score = Return from start + VWAP delta (weighted).
Live table + ranking; threshold → BUY/SELL signals.
Optional Alpha vs S1 and macro filter (DXY, US10Y).
Custom window/timezone + freeze at window end.
If you want, I can add a tighter IG caption + hashtags in your Dominus style.
FVG + CoSD Confirmation Strategy (6:1 RR, 2% Equity Risk)This strategy combines two powerful displacement signals — Fair Value Gaps (FVG) and Change of State of Delivery (CoSD) — to capture high-conviction directional moves. It sets a directional bias when either signal appears, but only enters a trade once both FVG and CoSD confirm in the same direction. This dual-filter approach helps reduce noise and improve entry precision.
Key features:
✅ Bias lock on first signal: Directional bias is set by either FVG or CoSD, but trades only trigger when both align.
✅ 6:1 reward-to-risk targeting: Take profit is set at sixtimes the stop distance, allowing for high-RR setups.
✅ Fixed stop buffer: SL is calculated using a static tick buffer for simplicity and consistency.
✅ Exit on opposing signal: Trades are closed when an opposite FVG or CoSD appears, signaling structural reversal.
📈 Optimized for EURUSD on the 4-hour timeframe, where its structural logic and risk parameters are best aligned with market rhythm and volatility.
This strategy is ideal for traders who want to combine price imbalance with structural confirmation, while maintaining disciplined risk management and directional clarity.
ATR + EMA + Sessions ProATR + EMA + Sessions Pro By Saeed Fadi to save indicator space, it,s for atr, emas, sessions etc.
MTG Real-Time RSI Momentum + Strength Great buy and sell indicator. Works well on the 3 min chart. Big Red and Green Flags for Strong Sell and Stong Buy. Smaller flags for not as strong sell or buy. Happy Trading
MTG EMA Cross + ATR FilterBeautiful buy and sell indicator that uses EMA cross and ATR Filter. Red Triangle for sell and Green for buy. Happy Trading
[Parth🇮🇳] Wall Street US30 Pro - Prop Firm Edition....Yo perfect! Here's the COMPLETE strategy in simple words:
***
## WALL STREET US30 TRADING STRATEGY - SIMPLE VERSION
### WHAT YOU'RE TRADING:
US30 (Dow Jones Index) on 1-hour chart using a professional indicator with smart money concepts.
---
### WHEN TO TRADE:
**6:30 PM - 10:00 PM IST every day** (London-NY overlap = highest volume)
***
### THE INDICATOR SHOWS YOU:
A table in top-right corner with 5 things:
1. **Signal Strength** - How confident (need 70%+)
2. **RSI** - Momentum (need OK status)
3. **MACD** - Trend direction (need UP for buys, DOWN for sells)
4. **Volume** - Real or fake move (need HIGH)
5. **Trend** - Overall direction (need UP for buys, DOWN for sells)
Plus **green arrows** (buy signals) and **red arrows** (sell signals).
---
### THE RULES:
**When GREEN ▲ arrow appears:**
- Wait for 1-hour candle to close (don't rush in)
- Check the table:
- Signal Strength 70%+ ? ✅
- Volume HIGH? ✅
- RSI okay? ✅
- MACD up? ✅
- Trend up? ✅
- If all yes = ENTER LONG (BUY)
- Set stop loss 40-50 pips below entry
- Set take profit 2x the risk (2:1 ratio)
**When RED ▼ arrow appears:**
- Wait for 1-hour candle to close (don't rush in)
- Check the table:
- Signal Strength 70%+ ? ✅
- Volume HIGH? ✅
- RSI okay? ✅
- MACD down? ✅
- Trend down? ✅
- If all yes = ENTER SHORT (SELL)
- Set stop loss 40-50 pips above entry
- Set take profit 2x the risk (2:1 ratio)
***
### REAL EXAMPLE:
**7:45 PM IST - Green arrow appears**
Table shows:
- Signal Strength: 88% 🔥
- RSI: 55 OK
- MACD: ▲ UP
- Volume: 1.8x HIGH
- Trend: 🟢 UP
All checks pass ✅
**8:00 PM - Candle closes, signal confirmed**
I check table again - still strong ✓
**I enter on prop firm:**
- BUY 0.1 lot
- Entry: 38,450
- Stop Loss: 38,400 (50 pips below)
- Take Profit: 38,550 (100 pips above)
- Risk: $50
- Reward: $100
- Ratio: 1:2 ✅
**9:30 PM - Price hits 38,550**
- Take profit triggered ✓
- +$100 profit
- Trade closes
**Done for that signal!**
***
### YOUR DAILY ROUTINE:
**6:30 PM IST** - Open TradingView + prop firm
**6:30 PM - 10 PM IST** - Watch for signals
**When signal fires** - Check table, enter if strong
**10:00 PM IST** - Close all trades, done
**Expected daily** - 1-3 signals, +$100-300 profit
***
### EXPECTED RESULTS:
**Win Rate:** 65-75% (most trades win)
**Signals per day:** 1-3
**Profit per trade:** $50-200
**Daily profit:** $100-300
**Monthly profit:** $2,000-6,000
**Monthly return:** 20-30% (on $10K account)
---
### WHAT MAKES THIS WORK:
✅ Uses 7+ professional filters (not just 1 indicator)
✅ Checks volume (real moves only)
✅ Filters overbought/oversold (avoids tops/bottoms)
✅ Aligns with 4-hour trend (higher timeframe)
✅ Only trades peak volume hours (6:30-10 PM IST)
✅ Uses support/resistance (institutional levels)
✅ Risk/reward 2:1 minimum (math works out)
***
### KEY DISCIPLINE RULES:
**DO:**
- ✅ Only trade 6:30-10 PM IST
- ✅ Wait for candle to close
- ✅ Check ALL 5 table items
- ✅ Only take 70%+ strength signals
- ✅ Always use stop loss
- ✅ Always 2:1 reward ratio
- ✅ Risk 1-2% per trade
- ✅ Close all trades by 10 PM
- ✅ Journal every trade
- ✅ Follow the plan
**DON'T:**
- ❌ Trade outside 6:30-10 PM IST
- ❌ Enter before candle closes
- ❌ Take weak signals (below 70%)
- ❌ Trade without stop loss
- ❌ Move stop loss (lock in loss)
- ❌ Hold overnight
- ❌ Revenge trade after losses
- ❌ Overleverge (more than 0.1 lot start)
- ❌ Skip journaling
- ❌ Deviate from plan
***
### THE 5-STEP ENTRY PROCESS:
**Step 1:** Arrow appears on chart ➜
**Step 2:** Wait for candle to close ➜
**Step 3:** Check table (all 5 items) ➜
**Step 4:** If all good = go to prop firm ➜
**Step 5:** Enter trade with SL & TP
Takes 30 seconds once you practice!
***
### MONEY MATH (Starting with $5,000):
**If you take 20 signals per month:**
- Win 15, Lose 5 (75% rate)
- Wins: 15 × $100 = $1,500
- Losses: 5 × $50 = -$250
- Net: +$1,250/month = 25% return
**Month 2:** $5,000 + $1,250 = $6,250 account
**Month 3:** $6,250 + $1,562 = $7,812 account
**Month 4:** $7,812 + $1,953 = $9,765 account
**Month 5:** $9,765 + $2,441 = $12,206 account
**Month 6:** $12,206 + $3,051 = $15,257 account
**In 6 months = $10,000 account → $15,000+ (50% growth)**
That's COMPOUNDING, baby! 💰
***
### START TODAY:
1. Copy indicator code
2. Add to 1-hour US30 chart on TradingView
3. Wait until 6:30 PM IST tonight (or tomorrow if late)
4. Watch for signals
5. Follow the rules
6. Trade your prop firm
**That's it! Simple as that!**
***
### FINAL WORDS:
This isn't get-rich-quick. This is build-wealth-steadily.
You follow the plan, take quality signals only, manage risk properly, you WILL make money. Not every trade wins, but the winners are bigger than losers (2:1 ratio).
Most traders fail because they:
- Trade too much (overtrading)
- Don't follow their plan (emotions)
- Risk too much per trade (blown account)
- Chase signals (FOMO)
- Don't journal (repeat mistakes)
You avoid those 5 things = you'll be ahead of 95% of traders.
**Start trading 6:30 PM IST. Let's go! 🚀**
Volume Weighted Linear Regression BandThe Volume-Weighted Linear Regression Band (VWLRBd) is a volatility channel that uses a Linear Regression line as its dynamic baseline. Its primary feature is the decomposition of total volatility into two distinct components, visualized as layered bands.
Key Features:
Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): The indicator functions as a standard (Volume-Weighted) Linear Regression Channel. It plots a single set of bands based on the standard deviation of the residuals (the error between the Source price and the regression line).
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used for the regression). This mode displays two sets of bands:
Inner Bands: Show only the contribution of the 'residual' (trend noise) volatility, calculated proportionally.
Outer Bands: Show the total volatility (the sum of residual and within-bar components).
Regression Baseline (Linear / Exponential): The central line is a (Volume-Weighted) Linear Regression curve. An optional 'Normalize' mode performs all calculations in logarithmic space, transforming the baseline into an Exponential Regression Curve and the bands into constant percentage deviations, suitable for analyzing growth assets.
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the regression baseline and the volatility decomposition, giving more influence to high-participation bars.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Includes a full set of built-in alerts for the source price crossing over or under the central regression line and the outermost calculated volatility band.
DISCLAIM_
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Scientific Correlation Testing FrameworkScientific Correlation Testing Framework - Comprehensive Guide
Introduction to Correlation Analysis
What is Correlation?
Correlation is a statistical measure that describes the degree to which two assets move in relation to each other. Think of it like measuring how closely two dancers move together on a dance floor.
Perfect Positive Correlation (+1.0): Both dancers move in perfect sync, same direction, same speed
Perfect Negative Correlation (-1.0): Both dancers move in perfect sync but in opposite directions
Zero Correlation (0): The dancers move completely independently of each other
In financial markets, correlation helps us understand relationships between different assets, which is crucial for:
Portfolio diversification
Risk management
Pairs trading strategies
Hedging positions
Market analysis
Why This Script is Special
This script goes beyond simple correlation calculations by providing:
Two different correlation methods (Pearson and Spearman)
Statistical significance testing to ensure results are meaningful
Rolling correlation analysis to track how relationships change over time
Visual representation for easy interpretation
Comprehensive statistics table with detailed metrics
Deep Dive into the Script's Components
1. Input Parameters Explained-
Symbol Selection:
This allows you to select the second asset to compare with the chart's primary asset
Default is Apple (NASDAQ:AAPL), but you can change this to any symbol
Example: If you're viewing a Bitcoin chart, you might set this to "NASDAQ:TSLA" to see if Bitcoin and Tesla are correlated
Correlation Window (60): This is the number of periods used to calculate the main correlation
Larger values (e.g., 100-500) provide more stable, long-term correlation measures
Smaller values (e.g., 10-50) are more responsive to recent price movements
60 is a good balance for most daily charts (about 3 months of trading days)
Rolling Correlation Window (20): A shorter window to detect recent changes in correlation
This helps identify when the relationship between assets is strengthening or weakening
Default of 20 is roughly one month of trading days
Return Type: This determines how price changes are calculated
Simple Returns: (Today's Price - Yesterday's Price) / Yesterday's Price
Easy to understand: "The asset went up 2% today"
Log Returns: Natural logarithm of (Today's Price / Yesterday's Price)
More mathematically elegant for statistical analysis
Better for time-additive properties (returns over multiple periods)
Less sensitive to extreme values.
Confidence Level (95%): This determines how certain we want to be about our results
95% confidence means we accept a 5% chance of being wrong (false positive)
Higher confidence (e.g., 99%) makes the test more strict
Lower confidence (e.g., 90%) makes the test more lenient
95% is the standard in most scientific research
Show Statistical Significance: When enabled, the script will test if the correlation is statistically significant or just due to random chance.
Display options control what you see on the chart:
Show Pearson/Spearman/Rolling Correlation: Toggle each correlation type on/off
Show Scatter Plot: Displays a scatter plot of returns (limited to recent points to avoid performance issues)
Show Statistical Tests: Enables the detailed statistics table
Table Text Size: Adjusts the size of text in the statistics table
2.Functions explained-
calcReturns():
This function calculates price returns based on your selected method:
Log Returns:
Formula: ln(Price_t / Price_t-1)
Example: If a stock goes from $100 to $101, the log return is ln(101/100) = ln(1.01) ≈ 0.00995 or 0.995%
Benefits: More symmetric, time-additive, and better for statistical modeling
Simple Returns:
Formula: (Price_t - Price_t-1) / Price_t-1
Example: If a stock goes from $100 to $101, the simple return is (101-100)/100 = 0.01 or 1%
Benefits: More intuitive and easier to understand
rankArray():
This function calculates the rank of each value in an array, which is used for Spearman correlation:
How ranking works:
The smallest value gets rank 1
The second smallest gets rank 2, and so on
For ties (equal values), they get the average of their ranks
Example: For values
Sorted:
Ranks: (the two 2s tie for ranks 1 and 2, so they both get 1.5)
Why this matters: Spearman correlation uses ranks instead of actual values, making it less sensitive to outliers and non-linear relationships.
pearsonCorr():
This function calculates the Pearson correlation coefficient:
Mathematical Formula:
r = (nΣxy - ΣxΣy) / √
Where x and y are the two variables, and n is the sample size
What it measures:
The strength and direction of the linear relationship between two variables
Values range from -1 (perfect negative linear relationship) to +1 (perfect positive linear relationship)
0 indicates no linear relationship
Example:
If two stocks have a Pearson correlation of 0.8, they have a strong positive linear relationship
When one stock goes up, the other tends to go up in a fairly consistent proportion
spearmanCorr():
This function calculates the Spearman rank correlation:
How it works:
Convert each value in both datasets to its rank
Calculate the Pearson correlation on the ranks instead of the original values
What it measures:
The strength and direction of the monotonic relationship between two variables
A monotonic relationship is one where as one variable increases, the other either consistently increases or decreases
It doesn't require the relationship to be linear
When to use it instead of Pearson:
When the relationship is monotonic but not linear
When there are significant outliers in the data
When the data is ordinal (ranked) rather than interval/ratio
Example:
If two stocks have a Spearman correlation of 0.7, they have a strong positive monotonic relationship
When one stock goes up, the other tends to go up, but not necessarily in a straight-line relationship
tStatistic():
This function calculates the t-statistic for correlation:
Mathematical Formula: t = r × √((n-2)/(1-r²))
Where r is the correlation coefficient and n is the sample size
What it measures:
How many standard errors the correlation is away from zero
Used to test the null hypothesis that the true correlation is zero
Interpretation:
Larger absolute t-values indicate stronger evidence against the null hypothesis
Generally, a t-value greater than 2 (in absolute terms) is considered statistically significant at the 95% confidence level
criticalT() and pValue():
These functions provide approximations for statistical significance testing:
criticalT():
Returns the critical t-value for a given degrees of freedom (df) and significance level
The critical value is the threshold that the t-statistic must exceed to be considered statistically significant
Uses approximations since Pine Script doesn't have built-in statistical distribution functions
pValue():
Estimates the p-value for a given t-statistic and degrees of freedom
The p-value is the probability of observing a correlation as strong as the one calculated, assuming the true correlation is zero
Smaller p-values indicate stronger evidence against the null hypothesis
Standard interpretation:
p < 0.01: Very strong evidence (marked with **)
p < 0.05: Strong evidence (marked with *)
p ≥ 0.05: Weak evidence, not statistically significant
stdev():
This function calculates the standard deviation of a dataset:
Mathematical Formula: σ = √(Σ(x-μ)²/(n-1))
Where x is each value, μ is the mean, and n is the sample size
What it measures:
The amount of variation or dispersion in a set of values
A low standard deviation indicates that the values tend to be close to the mean
A high standard deviation indicates that the values are spread out over a wider range
Why it matters for correlation:
Standard deviation is used in calculating the correlation coefficient
It also provides information about the volatility of each asset's returns
Comparing standard deviations helps understand the relative riskiness of the two assets.
3.Getting Price Data-
price1: The closing price of the primary asset (the chart you're viewing)
price2: The closing price of the secondary asset (the one you selected in the input parameters)
Returns are used instead of raw prices because:
Returns are typically stationary (mean and variance stay constant over time)
Returns normalize for price levels, allowing comparison between assets of different values
Returns represent what investors actually care about: percentage changes in value
4.Information Table-
Creates a table to display statistics
Only shows on the last bar to avoid performance issues
Positioned in the top right of the chart
Has 2 columns and 15 rows
Populating the Table
The script then populates the table with various statistics:
Header Row: "Metric" and "Value"
Sample Information: Sample size and return type
Pearson Correlation: Value, t-statistic, p-value, and significance
Spearman Correlation: Value, t-statistic, p-value, and significance
Rolling Correlation: Current value
Standard Deviations: For both assets
Interpretation: Text description of the correlation strength
The table uses color coding to highlight important information:
Green for significant positive results
Red for significant negative results
Yellow for borderline significance
Color-coded headers for each section
=> Practical Applications and Interpretation
How to Interpret the Results
Correlation Strength
0.0 to 0.3 (or 0.0 to -0.3): Weak or no correlation
The assets move mostly independently of each other
Good for diversification purposes
0.3 to 0.7 (or -0.3 to -0.7): Moderate correlation
The assets show some tendency to move together (or in opposite directions)
May be useful for certain trading strategies but not extremely reliable
0.7 to 1.0 (or -0.7 to -1.0): Strong correlation
The assets show a strong tendency to move together (or in opposite directions)
Can be useful for pairs trading, hedging, or as a market indicator
Statistical Significance
p < 0.01: Very strong evidence that the correlation is real
Marked with ** in the table
Very unlikely to be due to random chance
p < 0.05: Strong evidence that the correlation is real
Marked with * in the table
Unlikely to be due to random chance
p ≥ 0.05: Weak evidence that the correlation is real
Not marked in the table
Could easily be due to random chance
Rolling Correlation
The rolling correlation shows how the relationship between assets changes over time
If the rolling correlation is much different from the long-term correlation, it suggests the relationship is changing
This can indicate:
A shift in market regime
Changing fundamentals of one or both assets
Temporary market dislocations that might present trading opportunities
Trading Applications
1. Portfolio Diversification
Goal: Reduce overall portfolio risk by combining assets that don't move together
Strategy: Look for assets with low or negative correlations
Example: If you hold tech stocks, you might add some utilities or bonds that have low correlation with tech
2. Pairs Trading
Goal: Profit from the relative price movements of two correlated assets
Strategy:
Find two assets with strong historical correlation
When their prices diverge (one goes up while the other goes down)
Buy the underperforming asset and short the outperforming asset
Close the positions when they converge back to their normal relationship
Example: If Coca-Cola and Pepsi are highly correlated but Coca-Cola drops while Pepsi rises, you might buy Coca-Cola and short Pepsi
3. Hedging
Goal: Reduce risk by taking an offsetting position in a negatively correlated asset
Strategy: Find assets that tend to move in opposite directions
Example: If you hold a portfolio of stocks, you might buy some gold or government bonds that tend to rise when stocks fall
4. Market Analysis
Goal: Understand market dynamics and interrelationships
Strategy: Analyze correlations between different sectors or asset classes
Example:
If tech stocks and semiconductor stocks are highly correlated, movements in one might predict movements in the other
If the correlation between stocks and bonds changes, it might signal a shift in market expectations
5. Risk Management
Goal: Understand and manage portfolio risk
Strategy: Monitor correlations to identify when diversification benefits might be breaking down
Example: During market crises, many assets that normally have low correlations can become highly correlated (correlation convergence), reducing diversification benefits
Advanced Interpretation and Caveats
Correlation vs. Causation
Important Note: Correlation does not imply causation
Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but one doesn't cause the other
Implication: Just because two assets move together doesn't mean one causes the other to move
Solution: Look for fundamental economic reasons why assets might be correlated
Non-Stationary Correlations
Problem: Correlations between assets can change over time
Causes:
Changing market conditions
Shifts in monetary policy
Structural changes in the economy
Changes in the underlying businesses
Solution: Use rolling correlations to monitor how relationships change over time
Outliers and Extreme Events
Problem: Extreme market events can distort correlation measurements
Example: During a market crash, many assets may move in the same direction regardless of their normal relationship
Solution:
Use Spearman correlation, which is less sensitive to outliers
Be cautious when interpreting correlations during extreme market conditions
Sample Size Considerations
Problem: Small sample sizes can produce unreliable correlation estimates
Rule of Thumb: Use at least 30 data points for a rough estimate, 60+ for more reliable results
Solution:
Use the default correlation length of 60 or higher
Be skeptical of correlations calculated with small samples
Timeframe Considerations
Problem: Correlations can vary across different timeframes
Example: Two assets might be positively correlated on a daily basis but negatively correlated on a weekly basis
Solution:
Test correlations on multiple timeframes
Use the timeframe that matches your trading horizon
Look-Ahead Bias
Problem: Using information that wouldn't have been available at the time of trading
Example: Calculating correlation using future data
Solution: This script avoids look-ahead bias by using only historical data
Best Practices for Using This Script
1. Appropriate Parameter Selection
Correlation Window:
For short-term trading: 20-50 periods
For medium-term analysis: 50-100 periods
For long-term analysis: 100-500 periods
Rolling Window:
Should be shorter than the main correlation window
Typically 1/3 to 1/2 of the main window
Return Type:
For most applications: Log Returns (better statistical properties)
For simplicity: Simple Returns (easier to interpret)
2. Validation and Testing
Out-of-Sample Testing:
Calculate correlations on one time period
Test if they hold in a different time period
Multiple Timeframes:
Check if correlations are consistent across different timeframes
Economic Rationale:
Ensure there's a logical reason why assets should be correlated
3. Monitoring and Maintenance
Regular Review:
Correlations can change, so review them regularly
Alerts:
Set up alerts for significant correlation changes
Documentation:
Keep notes on why certain assets are correlated and what might change that relationship
4. Integration with Other Analysis
Fundamental Analysis:
Combine correlation analysis with fundamental factors
Technical Analysis:
Use correlation analysis alongside technical indicators
Market Context:
Consider how market conditions might affect correlations
Conclusion
This Scientific Correlation Testing Framework provides a comprehensive tool for analyzing relationships between financial assets. By offering both Pearson and Spearman correlation methods, statistical significance testing, and rolling correlation analysis, it goes beyond simple correlation measures to provide deeper insights.
For beginners, this script might seem complex, but it's built on fundamental statistical concepts that become clearer with use. Start with the default settings and focus on interpreting the main correlation lines and the statistics table. As you become more comfortable, you can adjust the parameters and explore more advanced applications.
Remember that correlation analysis is just one tool in a trader's toolkit. It should be used in conjunction with other forms of analysis and with a clear understanding of its limitations. When used properly, it can provide valuable insights for portfolio construction, risk management, and pair trading strategy development.
EMA100 Breakout by shubhThis indicator is a clean, price-action-based breakout system designed for disciplined trend trading on any timeframe — especially for Nifty and Bank Nifty spot, futures, and options charts.
It uses a single 100-period EMA to define trend direction and waits for decisive candle closes across the EMA to trigger potential entries.
The logic ensures only one active trade at a time, enforcing patience and clarity in decision-making.
⚙️ Core Logic
Buy Setup
A bullish candle closes above the 100 EMA while its open was below the EMA.
Entry occurs at candle close.
Stop-Loss (SL): Low of the signal candle.
Target (TP): 4 × the SL distance (Risk : Reward = 1 : 4).
Sell Setup
A bearish candle closes below the 100 EMA while its open was above the EMA.
Entry occurs at candle close.
Stop-Loss (SL): High of the signal candle.
Target (TP): 4 × the SL distance.
Trade Management
Only one trade may run at a time (either long or short).
New signals are ignored until the current position hits SL or TP.
Transparent labels show Entry, SL, and TP levels on chart.
Dotted lines visualize active Stop-Loss (red) and Target (green).
Exit markers:
✅ Target Hit
❌ Stop Loss Hit
🧠 Key Advantages
Simple and transparent trend-following logic.
Enforces disciplined “one-trade-at-a-time” behavior.
High risk-to-reward (1 : 4).
Works across timeframes — 5 min to Daily.
Ideal for intraday and positional setups.
📊 Suggested Use
Apply on Nifty / Bank Nifty spot or futures charts.
Works on any instrument with clear momentum swings.
Best confirmation when EMA 100 acts as dynamic support/resistance.
⚠️ Disclaimer
This script is for educational and research purposes only.
It is not financial advice or an invitation to trade.
Always backtest thoroughly and manage risk responsibly before applying in live markets.
Volume Weighted Keltner ChannelThis indicator provides a customizable implementation of Keltner Channels (KC), a volatility-based envelope designed to identify trend direction and potential reversal or breakout zones. It allows deep control over its core components and calculation methods.
Key Features:
Customizable Components: This implementation allows for full control over the channel's construction:
Basis Line: Choose from a wide range of moving average types (e.g., EMA, SMA, WMA) for the central line.
Volatility Bands: Select the volatility measure used to construct the bands: Average True Range (ATR), True Range (TR), or bar Range (High-Low).
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the basis moving average and the selected volatility measure (e.g., creating a Volume-Weighted ATR). This makes the channel more responsive to moves backed by high market participation.
Logarithmic Scaling: The indicator includes an optional 'Normalize' mode that calculates the channel on a logarithmic scale. This creates bands that represent a constant percentage distance from the basis, making it a suitable tool for analyzing long-term trends in exponential markets.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Includes a full set of built-in alerts for the source price crossing over or under the upper band, lower band, and the central basis line.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Price Trend Indicator+🧠 What it does
It measures the ratio between average price change and average volatility, showing how strong and directional the trend is.
Higher positive values = steady uptrend, negative = downtrend
📊 How to interpret
P value Signal Meaning
P > +0.5 🟢 Strong Uptrend Steady upward movement
0 < P < +0.5 🟡 Mild Uptrend Weak upward bias
P ≈ 0 ⚪ Sideways No clear direction
-0.5 < P < 0 🟠 Mild Downtrend Slight downward bias
P < -0.5 🔴 Strong Downtrend Consistent decline
