Futures Sizing Calculator (NQ,MGC,MES)Clean simple, risk indicator that will allow you to see risk before entering trade. This will allow you to use it on MES, MGC and MNQ.
For any ideas or improvements, don't hesitate to contact me.
Chỉ báo và chiến lược
BoS/CHoCH + FakeoutRMI • BoS / CHoCH + Fakeout Detector
This indicator identifies true market structure breaks based on Break of Structure (BoS) and Change of Character (CHoCH), combined with a precise Fakeout / Liquidity Sweep detector to filter false breakouts.
The logic is built on Smart Money Concepts (SMC) and ICT market structure, using close-confirmation only instead of wick-based signals.
Key Features
BoS & CHoCH Detection (Major Structure)
– Clear distinction between trend continuation (BoS) and trend reversal (CHoCH)
– Bullish and bearish structures are visually separated by color
Fakeout / Liquidity Sweep Detection
– Detects wick sweeps above highs and below lows
– Fakeouts are automatically removed once a valid structure break occurs
– No overlap between Fakeouts and BoS / CHoCH
Close-Only Confirmation (Institutional Logic)
– Structure is considered broken only after candle close
– Reduces noise and false signals caused by stop hunts
Split-Line Design (Clean Chart)
– Structure lines with centered text gap
– Extremely clean and readable, even on lower timeframes
Potential Next Break (Optional)
– Displays potential next major highs and lows
– Ideal for liquidity targeting and trade planning
Why This Indicator?
This tool is designed for traders who:
want non-repainting structure logic
focus on price action & market structure, not lagging indicators
need a clear distinction between fakeouts and real breaks
trade using SMC / ICT concepts
Perfect for scalping, day trading, and swing trading across Forex, Indices, Crypto, and Commodities.
Disclaimer
This indicator is an analysis tool, not an automated trading system.
For best results, combine it with Order Blocks, Fair Value Gaps (FVG), Liquidity Pools, and session bias.
One-Sided Hodrick-Prescott FilterTechnical & Mathematical Architecture
This indicator represents a significant departure from standard Moving Averages or traditional Hodrick-Prescott (HP) filter implementations found on Trading View. It utilizes a State-Space Model approach to decompose time-series data into trend and cyclical components, solved recursively via a Kalman Filter (Forward Pass) and a Rauch-Tung-Striebel (RTS) Smoother (Backward Pass). Furthermore, it introduces a proprietary Maximum Likelihood Estimation (MLE) loop to adapt the smoothing parameter (λ) dynamically in response to market regimes.
1.1 The State-Space Formulation
The standard HP filter minimizes a specific loss function involving the sum of squared deviations and the sum of squared second differences. While typically solved via batch matrix inversion, this script reformulates the problem as a Local Linear Trend (LLT) model, a stochastic structural model defined by:
Measurement Equation:
y = μ + ε
(Where ε is normally distributed noise)
State Transition Equations:
μ = μ + β + η
β = β + ζ
Where μ represents the stochastic level (trend) and β represents the stochastic slope (drift). The crucial link to the HP filter is the signal-to-noise ratio. By setting the variance of η to 0 (smooth trend) and defining λ as the ratio of measurement variance to slope variance, the Kalman Filter solution converges exactly to the One-Sided HP Filter.
1.2 The Forward Pass: Kalman Filter
The script executes a recursive estimation loop for real-time (causal) filtering:
Prediction Step: Projects the state mean and error covariance forward based on the transition matrix.
Innovation: Calculates the measurement residual (v = y - predicted y).
Update Step: Computes the Kalman Gain. The posterior state is updated based on how much the prediction missed the actual price.
Stability: The covariance update utilizes the Joseph Form subtraction to ensure the covariance matrix remains positive semi-definite, preventing numerical instability inherent in high-precision floating-point calculations over long durations.
1.3 Adaptive λ via Maximum Likelihood
Standard filters use a static λ (e.g., 1600 for quarterly data), which fails in crypto/FX markets exhibiting changing volatility. This script implements an Adaptive ML Loop.
The Kalman Filter assumes innovations are normally distributed with a specific theoretical variance (S). We compute a running variance ratio test:
Ratio = Actual Innovation Variance / Theoretical Variance
Ratio > 1: The model is "surprised" by volatility. The filter is under-fitting. The script dynamically decreases λ to increase responsiveness (reduce lag).
Ratio < 1: The model is over-fitting noise. The script increases λ to enforce a smoother trend.
This allows the filter to function as a low-lag trend follower during impulses and a robust noise filter during consolidation, automatically.
1.4 The Backward Pass: Rauch-Tung-Striebel (RTS) Smoother
This is the most complex feature of the script. While the Forward Pass provides the optimal estimate based on past data, the Backward Pass computes the optimal estimate based on all data.
The RTS algorithm runs purely on historical arrays stored in memory:
It iterates backward from the last bar to the past. It computes a "Smoother Gain" matrix based on future information. It updates the past estimates to correct them based on what happened afterwards. This results in a Minimum Mean Squared Error (MMSE) estimator. Note: This smoothed line is for analytical hindsight and back testing theoretical limits; it is distinct from the real-time filtered line used for live signaling.
Usage Guide:
This indicator is designed for precision trend following and mean-reversion trading. It separates the market price into a Trend Component (Signal) and a Cycle Component (Noise/Oscillation).
The Two Trend Lines:
The Filtered Trend (Real-Time): This is the filled/shaded line on your chart. It calculates the trend using only past data. It does not repaint. Use this for entering and exiting live trades.
Green Fill: Price is above the trend (Bullish bias).
Red Fill: Price is below the trend (Bearish bias).
The Smoothed Trend (Hindsight): (Optional, enabled via settings). This is the "God mode" line. It uses future data to show you exactly where the trend was.
WARNING: This line repaints. Do not trade the tip of this line. Its purpose is to show you the ideal path for training your eye or optimizing parameters.
Mean Reversion Signals:
The script calculates the "Cycle," which is the percentage deviation of price from the HP Trend.
Bands: The Upper and Lower bands represent the Cycle Threshold.
Long Signal (L): Triggered when the Cycle is Oversold (below lower band) AND begins to turn up, while the Filtered Drift (slope) is positive. This suggests a "dip buy" in an uptrend.
Short Signal (S): Triggered when the Cycle is Overbought (above upper band) AND begins to turn down, while the Filtered Drift is negative. This suggests selling a rally in a downtrend.
Adaptive Lambda Panel:
Enable the "Lambda Panel" to see the engine under the hood.
Rising Lambda (Blue): The market is noisy or consolidating. The filter is becoming "stiffer" to ignore the chop.
Falling Lambda (Orange): The market is trending impulsively. The filter is becoming "looser" to track the price closely and reduce lag.
Strategy: You can use low Lambda values as a confirmation of high-volatility breakout regimes.
Performance Table:
A dashboard in the bottom right corner displays the efficiency of the Kalman Filter:
MSE Filtered vs. Smoothed: Shows the Mean Squared Error of the real-time prediction vs. the hindsight-optimal smooth.
Improvement %: A higher percentage indicates that the RTS Smoother is extracting significantly more noise than the real-time filter (common in choppy markets).
Kalman Gains (K1, K2): These display the current weight the filter assigns to new price data for updating the Level and Slope respectively.
Summary of Settings
Base Lambda: The starting stiffness. Higher = smoother (long-term trend). Lower = responsive (short-term trend).
Adaptation Speed: Recommended between 0.01 and 0.05. Controls how fast λ reacts to volatility shocks.
Smoother Lookback: How far back (in bars) the RTS algorithm re-optimizes the historical line.
Best Practice: Use the Filtered Trend for execution. Use the Smoothed Trend to analyze past price action and determine if your Base Lambda setting is appropriate for the asset's volatility profile.
AMN Zones The AMN Model Indicator streamlines your trading by:
-Displaying all active AMN 6 tap opportunities directly on the chart.
-Helps you analyze structure and establish bias
-Highlights 50% of the optimal zone for precision entries.
Additionally, it marks setups that haven’t been mitigated and provides real-time alerts whenever a new setup presents itself. Ideal for traders aiming for clarity, consistency, and efficiency in identifying high-probability zones for entries and exits.
PFA_Futures-Spot Divergence IndicatorPFA Futures-Spot Divergence Indicator™
The PFA Futures-Spot Divergence Indicator™ is a proprietary analytical tool designed to provide traders with real-time insights into the pricing gap between futures contracts and their underlying spot indices. By measuring the premium or discount for key indices, the indicator highlights potential market sentiment, arbitrage opportunities, and short-term positioning pressure.
Unlike conventional indicators that focus on price trends alone, this tool emphasizes inter-market dynamics, showing how futures are behaving relative to the cash market. It calculates the differential for selected indices and visualizes it via:
Line plots: showing the live futures-spot gap
Color-coded zones: highlighting premium (positive) vs discount (negative)
Dashboard values: indicating the exact spread and relative intensity
Key Benefits:
Detect market overbought/oversold conditions due to excessive premium or discount
Identify potential arbitrage or rollover opportunities
Gauge market participant sentiment in real time
Complement trend, momentum, and volatility strategies
Use Cases:
NIFTY, BANKNIFTY, and other major Indian indices
Short-term trading and hedging strategies
Risk management and intraday market positioning
Disclaimer: The indicator is for analytical and educational purposes only. It does not provide buy/sell signals or guarantee future returns. Traders should apply independent judgment and proper risk management before taking positions.
Whale Flow PRO [Institutional Grade Trend System]Whale Flow PRO is an advanced market analysis algorithm designed to align retail traders with institutional liquidity cycles. Unlike standard lagging indicators, Whale Flow focuses on detecting the underlying phase of the market: Liquidity Building (Consolidation) vs. Institutional Expansion (Whale Runs).
This tool was engineered to solve the biggest problem in trading: getting trapped in choppy markets ("Whipsaws") and missing the true explosive moves.
⚙️ How It Works
The algorithm utilizes a proprietary volatility-adjusted volume model combined with dynamic price-action pivots. By analyzing the rate of change relative to historical volatility compression, the script identifies key "Pivot Lines" where liquidity is likely to flow.
Trend Filtering: It automatically filters out noise by calculating a custom "Consolidation Index". When the market is in a building phase, signals are suppressed to protect capital.
Whale Runs: When volatility expands beyond a specific threshold in the direction of the dominant trend, the system triggers a "Whale Run" mode, signaling high-probability entry zones.
📊 Key Features
Smart Dashboard (HUD): A real-time professional panel displaying the current Trend Direction, Market Phase (Run vs. Build), and active Pivot Levels.
Dynamic Heatmap: A visual ribbon at the bottom of the chart that tracks the historical strength of the trend flow.
Context-Aware Coloring:
Neon Green: Confirmed Bullish Flow (Whale Run).
Neon Red: Confirmed Bearish Flow (Dump).
Silver/Gray: Consolidation Zone (Safety Mode - No Trades).
Protection System: The "Liquidity Build" filter prevents entries during sideways movement, significantly increasing the win rate of the signals.
🔒 Access
This is an Invite-Only script dedicated to professional traders and community members. It is strictly protected to maintain the edge of its users.
To obtain access: Please visit the link in my signature or send me a private message (PM) here on TradingView for licensing details.
Disclaimer: This tool is for informational purposes only and does not constitute financial advice. Past performance (even of whales) is not indicative of future results.
PFA Regime & Structure EnginePFA बाज़ार दर्शन™ is a proprietary market regime and structure indicator designed to provide traders with a comprehensive view of market dynamics. Unlike traditional indicators that focus solely on price direction, this tool evaluates both momentum and structural context to determine the underlying market condition.
It calculates a Regime Score (0–100) by combining momentum energy from MACD pivots, fast and slow structural pivots, and market stress factors. Based on this score, the market is classified into actionable regimes such as Trend Dominant, Selective Phase, or Capital Protection.
The indicator features a live dashboard showing the current regime and score, along with visual structural zones directly on the chart. It acts as an early-warning system for potential market transitions, helping traders manage risk, identify high-probability trend phases, and make informed position-sizing decisions.
Disclaimer: PFA बाज़ार दर्शन™ is for analytical and educational purposes only. It does not provide buy/sell signals or guarantee future performance. Users should combine it with their own trading strategy, risk management, and confirmation tools.
Premium Volume Divergence Signals [Stansbooth]Advanced Divergence Indicator
This indicator is designed to uncover the hidden relationship between price action and momentum. By accurately detecting when price and momentum move in different directions, it highlights bullish and bearish divergences at critical market points — often before reversals or strong continuations occur.
🔹 Key Features:
Precise detection of Regular and Hidden Divergence
Helps identify early market reversals
Clean, clear, and easy-to-read visual signals
Works across Forex, Crypto, and Stock markets
Suitable for all timeframes and trading styles
This indicator empowers traders to make smarter entries, confident exits, and better risk management decisions. Instead of chasing the market, it allows you to anticipate price movement with confidence.
Trade smarter, not harder — let divergence reveal the real market strength.
UK Public Oneside V2This strategy combines RSI, Stochastic Oscillator, and a 50 EMA trend filter to identify moderate-risk trading opportunities in trending markets.
How it works:
Long entries occur when RSI and Stochastic are in oversold conditions while price is above the 50 EMA.
Short entries occur when RSI and Stochastic are in overbought conditions while price is below the 50 EMA.
Trades are confirmed on the previous candle, avoiding premature entries and exits.
Risk management is handled using fixed percentage stop-loss with configurable risk-to-reward targets.
Optional RSI-based exits close positions early during overbought or oversold conditions.
Key Features:
Trend-filtered entries using EMA 50
Non-repainting logic (confirmed candle signals)
Configurable stop-loss and reward ratio
Works well for scalping and intraday trading
Suitable for crypto, forex, and indices
Recommended Timeframes:
5m, 15m, 30m
Note:
This strategy is designed for educational and research purposes. Always forward-test and apply proper risk management before using in live trading.
CoreHedge : Pivots(Main) + Manual RR Monitor
You can fInd Mainly Target Point of Support and Resistance
1. Finding Tipping Point
2. Strategy Build
3. RR Caculator
Custom Study 4402This custom indicator acts as a comprehensive technical analysis suite designed to visualize market structure and trend alignment for intraday analysis. The primary purpose of this script is to automate the calculation of significant price levels based on historical data points, specifically focusing on the relationship between previous day's price action and current momentum.
**Key Features:**
1. **Automated Level Plotting:** The script calculates and renders key support and resistance zones derived from standard volatility metrics and historical high/low data. These levels serve as static references throughout the trading session.
2. **Trend Confluence:** It incorporates Volume Weighted Average Price (VWAP) logic to filter price action, helping to identify whether the asset is in a bullish or bearish phase relative to the average volume-weighted price.
3. **Signal Visualization:** The script utilizes visual markers (shapes and lines) to highlight specific conditions where price action aligns with the calculated levels.
4. **Dashboard Display:** A data table is provided to numerically display the calculated values for quick reference.
**Usage:**
This tool is intended for studying price behavior around calculated pivot zones. It is a "Protected" script designed to maintain the integrity of the specific calculation parameters used in this study. The logic combines multi-timeframe analysis to ensure that the plotted levels remain consistent regardless of the intraday timeframe being viewed.
**Disclaimer:**
This script is for educational and research purposes only. It visualizes data based on past performance and does not guarantee future results.
Bullish Breakout Finder by St0icTraderThis breakout finder is for PSEI. Buy on breakout candle close with stop loss of 5%.
PFA_Cumulative VolumeComplex Technical Summary – PFA_Cumulative Volume Indicator
The PFA_Cumulative Volume indicator implements a session-normalized volume aggregation framework that conditionally resets at each daily time boundary, thereby isolating intraday participation dynamics from multi-day carryover noise. By cumulatively summing raw traded volume from the session open, the script constructs a real-time proxy for directional conviction and liquidity absorption across the trading day.
In parallel, the indicator captures the immediate microstructure context by explicitly retaining the volume of the last two completed candles, enabling short-horizon comparative analysis of participation decay, acceleration, or stalling. This dual-layer design—macro session accumulation coupled with micro candle-level volume comparison—allows traders to infer whether price movement is being structurally supported by expanding market involvement or merely drifting due to transient order flow.
The visualization layer, implemented via a dynamically updated table overlay, prioritizes informational density over graphical plots. By segregating cumulative session volume, last-candle volume, and second-last-candle volume into discrete cells, the indicator facilitates rapid regime assessment without distorting price charts. Functionally, the tool does not assert directional bias; instead, it acts as a participation integrity monitor, highlighting divergence between price action and underlying volume commitment, which is critical for detecting distribution, exhaustion, or false continuation scenarios.
In essence, the indicator operationalizes volume as a state variable rather than a trigger, framing trades around the sustainability of market effort rather than isolated price events.
Anchored VWAP: Monthly / Weekly / SessionsPlots up to five VWAP lines using the chart’s exchange timezone:
Monthly anchored VWAP: resets on the first bar at/after your chosen month start day + time.
Weekly anchored VWAP: resets on the first bar at/after your chosen weekday + time.
Up to 3 session anchored VWAPs: each resets on the first bar that enters its configured TradingView session window; optionally hides the line outside the session).
All VWAPs are computed from a selectable price source (default hlc3) and traded volume.
Rule-Based Elliott Wave Strategy by xitaxutaStrategy Description
This is a rule-based Elliott Wave–inspired trading strategy designed for lower timeframes (e.g., 1-minute).
The strategy converts Elliott Wave concepts into objective, testable rules using swing pivots, Fibonacci retracements, and momentum confirmation.
The core idea is to trade Wave-3 continuation moves after a valid Wave-1 impulse and Wave-2 corrective pullback have been identified.
How it works
Wave 1 Detection
Identifies an impulsive move using pivot structure and a minimum ATR size filter to avoid noise.
Wave 2 Validation
Waits for a corrective structure (A–B–C–like behavior) and validates it using Fibonacci retracement rules (default ~38%–78%).
Entry Logic
Trades are triggered only on confirmation, not anticipation:
Longs: break above corrective resistance (Wave B)
Shorts: break below corrective support (Wave B)
Risk Management
Stops are placed at the true Wave-2 extreme, invalidating the Elliott count if hit.
Position sizing is based on a fixed percentage of account risk.
Targets
Partial profits are taken at R-based levels, with optional continuation targets using Wave-3 Fibonacci extensions.
Momentum Filter
RSI is used as a confirmation filter to align momentum with the expected Wave-3 direction.
Design Philosophy
No subjective wave drawing
No prediction of tops or bottoms
Structure → confirmation → execution
Focused on high-momentum continuation, not reversals
This strategy is best suited for active intraday trading and performs optimally in markets with sufficient volatility.
Important Notes
Elliott Wave concepts are approximated using objective rules.
The strategy waits for confirmation and may appear “late” by design.
Results depend on market conditions, timeframe, and parameter selection.
Quantum Algo Matrix Quantum Algo Matrix
Multi-Layer Market Intelligence
🔹 Overview
Quantum Algo Matrix is a multi-dimensional market analysis system designed to identify high-probability reversal and continuation zones by combining momentum, volatility, trend structure, multi-timeframe correlation, and AI-based confirmation into a single, coherent framework.
Instead of relying on a single indicator, this script cross-validates signals across independent methodologies, significantly reducing noise and false positives.
It is best suited for active traders, swing traders, and systematic traders who value confirmation, structure, and context over single-trigger signals.
🧠 Core Components & How They Work Together
1️⃣ WaveTrend Engine (Market Structure & Extremes)
At the heart of the system lies a WaveTrend oscillator, which identifies overbought and oversold market conditions with multiple graded levels:
Level 1 (L1) → Primary extreme zones
Level 2 (L2) → Secondary confirmation zones
Level 0 (L0) → Extended exhaustion zones beyond normal extremes
Signals are only considered when WaveTrend momentum confirms a structural extreme, ensuring trades are taken where risk-reward is asymmetric, not mid-range.
Visual differentiation (lines, dots, and crosses) clearly communicates signal strength and hierarchy.
2️⃣ WVF – Volatility Reversal Detection
The WVF module tracks volatility expansion and contraction relative to historical extremes:
Identifies panic selling and emotional spikes
Uses percentile-based thresholds, not fixed values
Optional standard deviation & range filters reduce noise
WVF reversal signals are gated by WaveTrend zones, meaning volatility alone is never enough — price must also be in a statistically significant location.
This avoids the common pitfall of chasing volatility in trending or neutral conditions.
3️⃣ Squeeze Momentum (SQZ) – Pressure & Energy Release
The Squeeze Momentum module measures volatility compression vs expansion, highlighting when the market is:
Building pressure (compression)
Releasing energy (expansion)
Unlike traditional implementations, SQZ is scaled to the WaveTrend range, allowing it to visually integrate with the rest of the system.
The result is a clear momentum context that confirms whether a signal occurs:
Into expansion (higher probability)
Or during decay (lower probability)
4️⃣ Multi-Timeframe Correlation (MTF Filter)
One of the most powerful features of Quantum Algo Matrix is its Multi-Timeframe WaveTrend Correlation Filter.
When enabled, the script checks WaveTrend conditions across multiple higher timeframes (user-selectable):
45m
60m
120m
(optional lower / higher frames)
A signal is only validated when current timeframe conditions align with higher-timeframe momentum, ensuring:
Trades are with the broader market context
Lower-timeframe noise is filtered out
Counter-trend signals are reduced
This is especially effective in volatile or choppy markets.
5️⃣ AI SuperTrend Clustering (Advanced Confirmation Layer)
The AI module introduces a machine-learning-inspired clustering approach:
Multiple SuperTrend variations are generated
Their behavior is clustered using K-means logic
Bullish, bearish, and neutral consensus streams are extracted
Output is normalized and scaled to the WaveTrend environment
Rather than predicting price, the AI acts as a confidence validator:
Confirms strength
Filters weak setups
Prevents entries during indecision
This layer dramatically improves signal quality consistency, especially during transitions and regime changes.
🎯 Final Signal Logic (Why It’s Accurate)
A final LONG or SHORT signal is only produced when:
✔ WaveTrend confirms a valid extreme
✔ Volatility (WVF) shows a qualified reversal or memory condition
✔ Momentum (SQZ) supports expansion or pressure release
✔ Multi-Timeframe structure is aligned (optional)
✔ AI consensus confirms directional confidence (optional)
Because each component is independent, the probability of random alignment is low — this is what makes the system robust and statistically sound.
🧩 Customization & Flexibility
Every module can be enabled or disabled
Visuals are clean and user-controlled
Works on all markets (crypto, forex, indices, stocks)
Optimized for intraday to swing timeframes
No repainting logic in signal generation
⚠️ Important Notes
This script is a decision-support system, not a prediction tool.
It is designed to help traders identify high-quality opportunities, manage risk more effectively, and avoid emotional trading.
Always combine with:
Proper risk management
Market structure awareness
Personal trading rules
⭐ Summary
Quantum Algo Matrix is not a single indicator —
it is a complete market intelligence framework.
By blending structure, volatility, momentum, correlation, and AI-based confirmation, it delivers clearer signals, fewer false positives, and stronger contextual awareness across all timeframes.
PFA_ATR Locha:Clean Volatility RegimeCondensed Abstract (Advanced)
ATR Locha functions as a non-directional volatility-regime discriminator, operationalizing ATR normalized by price to detect latent shifts in market stress dynamics. By stratifying volatility into compression, equilibrium, and expansion states, it isolates pre-trend instability and post-trend exhaustion without invoking directional bias. The indicator is structurally anticipatory rather than predictive, serving as a probabilistic risk-state lens that contextualizes price behavior, enhances temporal positioning, and mitigates regime-mismatch errors when integrated with structural or trend-confirmatory frameworks.
N Days Back Session DividerThis Pine Script acts as a smart vertical marker that identifies exactly where a trading day began a specific number of sessions ago. It is designed to ignore "dead time" (like weekends or holidays) by focusing on actual market activity.
PDH/PDL + Alerts + Liquidity Sweep ReversalThis indicator is designed for traders who utilize Price Action to identify high-probability reversal zones at daily liquidity levels. It automatically plots the Previous Day High (PDH) and Previous Day Low (PDL) and monitors them for institutional "fake-outs" or liquidity sweeps.
Core Functionality
Daily Liquidity Levels: Automatically fetches and plots the PDH and PDL with custom labels and line styles.
Strict Reversal Logic: Unlike standard breakout indicators, this script looks for specific "trap" behavior where price pierces a level and is immediately rejected.
Institutional Precision Tooltips: Includes built-in precision guides for Wick Percentages and Lookback counts based on professional trading standards.
The "Strict Reversal" Setup
The indicator only triggers a Buy/Sell label when three specific criteria are met:
The Lookback: The level must have been respected as a boundary for a user-defined number of candles (Default: 7), confirming its strength.
The Sequence: The candle must open on the "safe" side of the level, pierce through it to grab liquidity, and then close back on the original side.
The Rejection (Wick %): The candle must leave a significant wick (Default: 72%). This 72% threshold aligns with the 2.5x Wick-to-Body ratio, signaling a violent institutional rejection.
Alert Options
The script features four consolidated alert conditions for seamless automation:
Sell Signal (Rejection): Triggers on strict bearish wick sweeps at key levels.
Buy Signal (Rejection): Triggers on strict bullish wick sweeps at key levels.
Price Cross Up: Alerts when price breaks above either PDH or PDL.
Price Cross Down: Alerts when price breaks below either PDH or PDL.
How to Use
Scalping: Use a 3–5 candle lookback on the 1m or 5m timeframe.
Intraday Reversals: Use the 7–10 candle lookback on the 5m or 15m timeframe for standard SMC setups.
Swing Trading: Use the 15+ candle lookback on the 1h or 4h timeframe to target major daily liquidity pools.
SS Critical Advanced Swing Trading Decision Matrix
📊 How to Use the SS Critical Advanced Swing Trading Decision Matrix Indicator
Installation & Setup
Adding to TradingView
Open TradingView and Click "Add to Chart"
The indicator will load with the dashboard on your selected position
Recommended Timeframes
Daily charts: Primary timeframe for swing trading signals
4-hour charts: For fine-tuning entry/exit points
Weekly charts: For confirming long-term trends
Interpreting the Decision Matrix Scores
Final Score Ranges
Component Breakdown
Trend (25%): MA alignment + SuperTrend direction + ADX strength
Momentum (30%): RSI + MACD + Stochastic + ROC + MFI
Volume (20%): Volume surge + MFI confirmation
Volatility (15%): Bollinger Bands position + ATR
Oscillators (10%): CCI + Williams %R + ADX
Trading Signals
BUY Signal
Triggers when Final Score crosses above 65
Confirms bullish momentum building
Enter within 1-2 bars of signal for best results
SELL Signal
Triggers when Final Score drops below 35
Indicates bearish pressure intensifying
Exit or consider shorting opportunities
Signal Quality Validation
Check Previous Close score for trend confirmation
Higher previous score = stronger continuation
Diverging scores = potential reversal or consolidation
Customisation for Your Strategy
Adjusting Signal Weights
Trending Markets: Increase Trend Weight to 30-35%
Volatile Markets: Increase Volatility Weight to 20-25%
Low Volume Stocks: Decrease Volume Weight to 10-15%
High Volume Stocks: Increase Volume Weight to 25-30%
Parameter Optimization
Fast MA (9): For aggressive entries, reduce to 5-7
Slow MA (50/200): For longer holds, keep standard
RSI Length (14): Increase to 21 for smoother signals
Profit Target: Set based on stock volatility (6-7% default)
Best Practices
Entry Strategy
Wait for score ≥ 65 (STRONG or EXCELLENT)
Confirm trend on higher timeframe (weekly)
Check volume is above average
Enter on price pullback or breakout
Exit Strategy
Target: Achieve 6-7% profit within timeframe
Stop-loss: When score drops below 50 (MODERATE)
Trailing stop: Move to breakeven at 3% profit
Risk Management
Never risk more than 2% of capital per trade
Use position sizing based on signal quality:
EXCELLENT: 100% of planned position
STRONG: 75% of planned position
MODERATE: 25% or skip
Avoiding False Signals
Use multiple timeframe confirmation (daily + weekly)
Avoid trading during low volume periods
Check fundamentals for stocks with EXCELLENT scores
Don't overtrade - wait for quality setups
Dashboard Interpretation
Current Bar Section
Shows real-time analysis of ongoing candle
Component scores color-coded (Green/Yellow/Red)
Weighted column shows actual contribution to final score
Previous Close Section
Displays confirmed signal from last closed bar
Use for backtesting and strategy validation
Compare with current to spot trend changes
Alerts Setup
Create alerts for Buy/Sell signals
Set notifications for EXCELLENT quality signals
Combine with price alerts for automated monitoring
Practical Example
EXCELLENT Signal (Score 85)
All 5 components show green (>60 points)
Strong uptrend with high volume
Action: Enter full position, target 6-7% in 5 -15 days
WEAK Signal (Score 40)
Mixed indicators, declining momentum
Action: Avoid new entries, monitor existing positions
Pro Tip: Backtest this indicator on your favorite stocks using historical data before live trading. Adjust weights and parameters based on which components work best for your specific market/timeframe.
© Dr Shantanu Samanta - This indicator combines proven swing trading indicators into a single decision matrix for clearer trade execution.
For Educational purposes only
PFA_ATR LochaCondensed Abstract (Advanced)
ATR Locha functions as a non-directional volatility-regime discriminator, operationalizing ATR normalized by price to detect latent shifts in market stress dynamics. By stratifying volatility into compression, equilibrium, and expansion states, it isolates pre-trend instability and post-trend exhaustion without invoking directional bias. The indicator is structurally anticipatory rather than predictive, serving as a probabilistic risk-state lens that contextualizes price behavior, enhances temporal positioning, and mitigates regime-mismatch errors when integrated with structural or trend-confirmatory frameworks.
Candle Pattern Library [1CG]Candle Pattern Library
A comprehensive and easy-to-use Pine Script™ library for detecting single, two, and three-candle patterns. This library provides detailed pattern analysis including size classification, direction validation, and specific pattern identification.
Quick Start
1. Import the Library
import OneCleverGuy/CandlePatternLibrary/1 as CPL
2. Analyze Candles
Use the main analysis functions to detect patterns. You can analyze the current forming candle or confirmed historical candles.
// 1. Analyze candles (Current , Previous , and the one before )
// Note: We use full variable names for clarity.
CandleData candleNewest = CPL.analyzeCandle(open, high, low, close, 250, 50, 10, 50, 85)
CandleData candleMiddle = CPL.analyzeCandle(open , high , low , close , 250, 50, 10, 50, 85)
CandleData candleOldest = CPL.analyzeCandle(open , high , low , close , 250, 50, 10, 50, 85)
// 2. Analyze multi-candle patterns
// Pass candles in chronological order: Oldest -> Newest
var twoCandleData = CPL.analyzeTwoCandlePattern(candleMiddle, candleNewest, 10, 85)
var threeCandleData = CPL.analyzeThreeCandlePattern(candleOldest, candleMiddle, candleNewest)
Enums Reference
These are the Enum Types exported by the library. When checking results, use the pattern Alias.EnumType.Value (e.g., CPL.CandlePattern.Hammer).
CandlePattern
Enum Type for single-candle formations.
Usage: CPL.CandlePattern.
Values:
Unknown : No specific pattern detected.
RegularBullish : A standard bullish candle.
RegularBearish : A standard bearish candle.
BullishMarubozu : Bullish candle with little to no wicks.
BearishMarubozu : Bearish candle with little to no wicks.
Hammer : Small body at the top of the range (bullish reversal).
ShootingStar : Small body at the bottom of the range (bearish reversal).
SpinningTop : Small body centered in the range.
Doji : Open and close are effectively equal.
LongLeggedDoji : Doji with long upper and lower wicks.
CrossDoji : Doji with the body in the upper section.
DragonflyDoji : Doji where open/close are at the high.
InvertedCrossDoji : Doji with the body in the lower section.
GravestoneDoji : Doji where open/close are at the low.
FourPriceDoji : Open, High, Low, and Close are all equal.
TwoCandlePattern
Enum Type for two-candle formations.
Usage: CPL.TwoCandlePattern.
Values:
None : No two-candle pattern detected.
BullishEngulfingWeak : Bullish candle engulfs the previous body (close does not engulf range).
BullishEngulfingStrong : Bullish candle completely engulfs the previous body close outside range.
BearishEngulfingWeak : Bearish candle engulfs the previous body.
BearishEngulfingStrong : Bearish candle completely engulfs the previous body.
InsideBar : The second candle is completely contained within the first.
TweezerTop : Two candles with matching highs (bearish reversal).
TweezerBottom : Two candles with matching lows (bullish reversal).
BullishRailRoad : Two opposite Marubozus (Down -> Up).
BearishRailRoad : Two opposite Marubozus (Up -> Down).
ThreeCandlePattern
Enum Type for three-candle formations.
Usage: CPL.ThreeCandlePattern.
Values:
None : No three-candle pattern detected.
ThreeWhiteSoldiers : Three consecutive bullish candles.
ThreeBlackCrows : Three consecutive bearish candles.
ThreeWhiteSoldiersWithBullishFVG : Three White Soldiers containing a Bullish FVG.
ThreeWhiteSoldiersWithBearishFVG : Three White Soldiers containing a Bearish FVG.
ThreeBlackCrowsWithBullishFVG : Three Black Crows containing a Bullish FVG.
ThreeBlackCrowsWithBearishFVG : Three Black Crows containing a Bearish FVG.
MorningStar : Bearish -> Small/Doji -> Bullish (Bullish Reversal).
EveningStar : Bullish -> Small/Doji -> Bearish (Bearish Reversal).
BullishAbandonedBaby : Morning Star with gaps between all candles.
BearishAbandonedBaby : Evening Star with gaps between all candles.
EngulfingSandwich : Bearish -> Bullish (Engulfing) -> Bearish (Inside).
BullishFairValueGap : A gap between Candle 1 High and Candle 3 Low.
BearishFairValueGap : A gap between Candle 1 Low and Candle 3 High.
CandleSize
Enum Type for candle size classification.
Usage: CPL.CandleSize.
Values:
Short
Normal
Long
CandleDirection
Enum Type for candle direction classification.
Usage: CPL.CandleDirection.
Values:
Bearish
Neutral
Bullish
Function Reference
Analysis Functions
analyzeCandle(_open, _high, _low, _close, _avgSize, _sizeThresholdPct, _equivTolerance, _bodyTolerance, _positionThreshold)
analyzeCandle - Analyzes a single candle's OHLC data to determine its size, direction, and single-candle pattern.
Parameters:
_open (float) : (float) - Candle open price.
_high (float) : (float) - Candle high price.
_low (float) : (float) - Candle low price.
_close (float) : (float) - Candle close price.
_avgSize (float) : (float) - Baseline size (wick range) to compare against.
_sizeThresholdPct (float) : (float) - % difference from average to be considered Long/Short (e.g., 50.0).
_equivTolerance (float) : (float) - Absolute price diff for Close to equal Open (Doji checks).
_bodyTolerance (float) : (float) - Absolute price diff for "Small Body" checks.
_positionThreshold (int) : (int) - Int (0-100) determining valid wick ratios for Hammers/Shooting Stars (e.g., 85).
Returns: (CandleData) - CandleData object containing CandlePattern, CandleSize, CandleDirection.
analyzeTwoCandlePattern(_candle1, _candle2, _equivTolerance, _positionThreshold)
analyzeTwoCandlePattern - Analyzes two consecutive candles to find pairs like Engulfing, Tweezers, or Inside Bars.
Parameters:
_candle1 (CandleData) : (CandleData) - The first (older) candle data (previous).
_candle2 (CandleData) : (CandleData) - The second (newer) candle data (current).
_equivTolerance (float) : (float) - Price tolerance for matching highs/lows (Tweezers).
_positionThreshold (int) : (int) - Threshold for wick validations.
Returns: (TwoCandleData) - TwoCandleData object containing TwoCandlePattern.
analyzeThreeCandlePattern(_candle1, _candle2, _candle3)
analyzeThreeCandlePattern - Analyzes three consecutive candles to find complex patterns like Morning Stars, Abandoned Babies, or Three White Soldiers.
Parameters:
_candle1 (CandleData) : (CandleData) - The first (oldest) candle data.
_candle2 (CandleData) : (CandleData) - The second (middle) candle data.
_candle3 (CandleData) : (CandleData) - The third (newest) candle data.
Returns: (ThreeCandleData) - ThreeCandleData object containing ThreeCandlePattern.
Naming Utilities
getPatternName(_pattern)
getPatternName - Returns the string name of a candle pattern.
Parameters:
_pattern (CandlePattern) : (CandlePattern) - The candle pattern enum value.
Returns: (string) - Human-readable pattern name (e.g., "Hammer").
getTwoCandlePatternName(_pattern)
getTwoCandlePatternName - Returns the string name of a two-candle pattern.
Parameters:
_pattern (TwoCandlePattern) : (TwoCandlePattern) - The two-candle pattern enum value.
Returns: (string) - Human-readable pattern name (e.g., "Bullish Engulfing").
getThreeCandlePatternName(_pattern)
getThreeCandlePatternName - Returns the string name of a three-candle pattern.
Parameters:
_pattern (ThreeCandlePattern) : (ThreeCandlePattern) - The three-candle pattern enum value.
Returns: (string) - Human-readable pattern name (e.g., "Morning Star").
getSizeName(_size)
getSizeName - Returns the string name of a candle size.
Parameters:
_size (CandleSize) : (CandleSize) - The candle size enum value.
Returns: (string) - Human-readable size name ("Short", "Normal", or "Long").
getDirectionName(_direction)
getDirectionName - Returns the string name of a candle direction.
Parameters:
_direction (CandleDirection) : (CandleDirection) - The candle direction enum value.
Returns: (string) - Human-readable direction name ("Bullish", "Bearish", or "Neutral").
PFA_EMA ComboEMA Combo Chart – Multi-Timeframe Trend & Momentum Framework
The EMA Combo Chart is a comprehensive trend-analysis setup that plots 10, 20, 50, 100, and 200 Exponential Moving Averages (EMAs) on a single price chart. By visualizing all meaningful combinations of these EMAs, the chart helps traders and investors quickly assess short-term momentum, medium-term structure, and long-term trend direction in one view.
How the EMA Combo Works
• 10 & 20 EMA
Ultra-short-term momentum – useful for identifying early trend shifts, pullbacks, and fast entries.
• 20 & 50 EMA
Short-to-medium trend confirmation – commonly used for swing trading and trend continuation setups.
• 50 & 100 EMA
Intermediate trend strength – filters noise and highlights sustained directional moves.
• 100 & 200 EMA
Long-term trend & regime identification – widely followed by institutions to define bullish vs bearish structure.
• Cross-EMA Alignment (Stacking)
When EMAs are aligned in order (10 > 20 > 50 > 100 > 200), it signals a strong bullish trend .
Reverse alignment indicates a strong bearish trend .
Why Use EMA Instead of SMA
1. Faster Response to Price
EMAs give more weight to recent prices, making them more responsive than Simple Moving Averages (SMA).
2. Early Signal Generation
EMA crossovers and slope changes occur earlier, helping traders capture moves closer to the start of a trend .
3. Better for Volatile Markets
In fast-moving or news-driven markets, EMAs adapt quicker and reduce lag compared to SMA.
4. Institutional Preference
Many professional and algorithmic strategies rely on EMAs, especially 50, 100, and 200 EMA, making them self-fulfilling reference levels .
5. Cleaner Trend Structure
EMA combinations help distinguish between pullbacks vs reversals more effectively than SMA.
Key Use-Cases
• Trend identification across multiple timeframes
• Dynamic support and resistance zones
• Entry-exit timing using EMA crossovers
• Filtering false breakouts in range-bound markets
• Aligning short-term trades with long-term trend
Disclaimer
This EMA Combo Chart is a technical analysis tool intended for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or an assurance of returns. Financial markets involve risk, and past performance is not indicative of future results. Users should conduct their own analysis and consult a qualified financial advisor before making any trading or investment decisions.
