Moving Average Consecutive Up/Down Strategy (by ChartArt)This simple strategy goes long (or short) if there are several consecutive increasing (or decreasing) moving average values in a row in the same direction. The bars can be colored using the raw moving average trend. And the background can be colored using the consecutive moving average trend setting. In addition a experimental line of the moving average change can be drawn.
The strategy is based upon the "Consecutive Up/Down Strategy" which was created by Tradingview.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Cerca negli script per "liquidity"
MACD + SMA 200 Strategy (by ChartArt)Here is a combination of the classic MACD (moving average convergence divergence indicator) with the classic slow moving average SMA with period 200 together as a strategy.
This strategy goes long if the MACD histogram and the MACD momentum are both above zero and the fast MACD moving average is above the slow MACD moving average. As additional long filter the recent price has to be above the SMA 200. If the inverse logic is true, the strategy goes short. For the worst case there is a max intraday equity loss of 50% filter.
Save another $999 bucks with my free strategy.
This strategy works in the backtest on the daily chart of Bitcoin, as well as on the S&P 500 and the Dow Jones Industrial Average daily charts. Current performance as of November 30, 2015 on the SPX500 CFD daily is percent profitable: 68% since the year 1970 with a profit factor of 6.4. Current performance as of November 30, 2015 on the DOWI index daily is percent profitable: 51% since the year 1915 with a profit factor of 10.8.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Forex Session OverlapApplies gray background coloring for each major active Forex session, the more sessions active the lighter the background. Adjusted coloring for low (Sydney, Tokyo) and high (Frankfurt, London, New York) liquidity. Market opening hours for Sydney, Tokyo, Frankfurt, London and New York have been set to 08:00 - 17:00 local time and are converted to EST while taking daylight saving time into account across regions (REMEMBER: configure manually!). Sessions can be turned on or off separately. By default this indicator hides itself in larger time-frames (>30min by default). Enabling session breaks or daily pivots helps distinguish between sessions.
ICT – Sweep + FVG + Displacement The ICT (Inner Circle Trader) strategy is a sophisticated trading philosophy rooted in institutional market behavior. It revolves around understanding how large players manipulate price to trigger retail stop-losses, create liquidity, and execute their orders. At its core, ICT focuses on market structure, identifying Higher Highs, Lower Lows, and shifts that signal potential reversals. Key concepts include Order Blocks—zones where institutions placed significant orders—and Fair Value Gaps (FVG), untraded areas that price tends to return to. The Liquidity Grab is a crucial phase: price sweeps through key levels to trap retail traders before reversing. Traders use higher timeframes (H4/H1) for structure analysis and lower ones (M15/M5) for precise entries. Entries occur after a Market Structure Shift, confirmed by FVG fill or OB retest, with strict risk management. A minimum 3:1 risk-reward ratio ensures long-term profitability. The strategy demands deep market awareness, patience, and discipline. It’s not about indicators, but about reading the "invisible hand" of the market—where supply and demand meet, and where smart money moves. For advanced traders, ICT offers a window into the true mechanics of price action, transforming trading from speculation into strategic insight. It’s not just a method—it’s a mindset.
ICT Advanced Entry Models & Market Analysis# ICT Advanced Entry Models & Market Analysis
**🏆 The Most Comprehensive ICT (Inner Circle Trader) Indicator Available**
Transform your trading with this institutional-grade Pine Script that combines **12 advanced ICT entry models** with professional risk management and multi-timeframe analysis. Developed for serious traders who want confluence-based signals with complete market context.
## 🎯 **Core Features**
### **12 Enhanced ICT Entry Models**
- ✅ **Optimal Trade Entry (OTE)** - Enhanced Fibonacci retracements with volume confirmation
- ✅ **Silver Bullet** - London/NY session directional moves with regime filtering
- ✅ **Unicorn Model** - Liquidation + FVG + Order Block triple confluence
- ✅ **Fair Value Gap (FVG) Entry** - Gap mitigation tracking with confluence zones
- ✅ **Order Block Entry** - Enhanced with mitigation levels and volume validation
- ✅ **Breaker Block Entry** - Failed order blocks with trend confirmation
- ✅ **Stop Hunt Entry** - Institutional liquidity grabs with volume spikes
- ✅ **Liquidity Grab Entry** - Equal highs/lows with multiple touch confirmation
- ✅ **Market Maker Model** - AMD cycle with session-based phases
- ✅ **Power of 3** - Distribution phase entries with volume validation
- ✅ **Judas Swing** - False breakout reversals in first hour
- ✅ **Asian Range Breakout** - London session range expansion
### **Advanced Confluence System**
- 🎯 **Weighted Model Scoring** - Customize importance of each model
- 📊 **Multi-Factor Analysis** - Structure + trend + volatility alignment
- ⭐ **Signal Quality Ratings** - HIGH/MEDIUM/LOW probability assessments
- 🎪 **Threshold Filtering** - Only shows signals above your confidence level
### **Professional Risk Management**
- 💰 **Dynamic Position Sizing** - Automatic calculation based on account risk
- 🛑 **Structure-Based Stops** - Intelligent stop placement beyond swing points
- 🎯 **Multiple Take Profits** - 1.5R, 2.5R, and 4R targets
- 📈 **Risk-Reward Filtering** - Only signals with acceptable R:R ratios
- 💹 **Visual Trade Planning** - Entry, stop, and target levels on chart
### **Multi-Timeframe Analysis**
- 📅 **Higher Timeframe Structure** - 4H bias confirmation
- ⏱️ **Lower Timeframe Entries** - 15min precision timing
- 🎯 **Structure Alignment** - Only trade when timeframes agree
- 📊 **Cross-Timeframe Confluence** - Enhanced signal validation
## 🧠 **Market Intelligence**
### **Market Regime Detection**
- 📈 **Trending vs Ranging** - ADX-based market state analysis
- 🌊 **Volatility Regimes** - High/low/normal volatility identification
- 🎛️ **Adaptive Strategies** - Different model weights for different conditions
- 🎯 **Session Momentum** - Volume-based session strength analysis
### **Enhanced Market Structure**
- 🔍 **BOS vs CHoCH** - Precise break of structure vs change of character
- ⚡ **Swing Failures** - Failed high/low attempts (reversal signals)
- 📐 **Internal Structure** - Lower timeframe confirmation
- 🎪 **Premium/Discount Zones** - Enhanced with extreme levels
### **Fair Value Gap Innovation**
- 📦 **Mitigation Tracking** - Gaps become invalid when filled
- 🎯 **Confluence Zones** - Multiple overlapping gaps identified
- 📏 **Size Filtering** - Only significant gaps (customizable pip size)
- 🔄 **Real-Time Updates** - Dynamic gap management with arrays
## 📊 **Visual Excellence**
### **Professional Chart Display**
- 🎨 **Color-Coded Confluence** - Visual strength indicators
- 📋 **Comprehensive Info Table** - All key market data at a glance
- 🎯 **Signal Quality Labels** - Clear HIGH/MEDIUM/LOW ratings
- 📊 **Risk Management Display** - Entry, stop, targets on chart
### **Session & Time Analysis**
- 🌏 **Kill Zone Backgrounds** - Asian/London/NY sessions
- ⏰ **Macro Time Highlighting** - Key institutional activity periods
- 🥈 **Silver Bullet Times** - High-probability directional moves
- 🌐 **DST Auto-Adjustment** - Accurate timing year-round
### **Enhanced Visual Elements**
- 📦 **Order Block Tracking** - Active vs mitigated blocks
- 📊 **FVG Visualization** - Confluence zones with thickness indication
- 📈 **Structure Labels** - BOS/CHoCH/SF clearly marked
- 🎯 **Probability Heatmap** - High-frequency price zones
## 🎛️ **Customization & Control**
### **Model Weighting System**
- ⚖️ **Individual Weights** - Customize each model's importance
- 🎯 **Confluence Threshold** - Set minimum score for signals
- 📊 **Quality Control** - Filter signals by your criteria
- 🎪 **Strategy Adaptation** - Adjust weights based on backtesting
### **Risk Management Settings**
- 💰 **Account Size Input** - Set your trading capital
- 📊 **Risk Per Trade** - Percentage risk (0.1% to 5%)
- 🎯 **Minimum R:R** - Only show trades above your threshold
- 📈 **Position Size Display** - Automatic lot size calculation
## 📈 **Performance Tracking**
### **Built-in Analytics**
- 📊 **Win Rate Monitoring** - Track success over time
- 💹 **Average Return** - R:R performance tracking
- 📉 **Maximum Drawdown** - Risk assessment metrics
- 🎯 **Model Performance** - See which models work best
### **Advanced Alerts**
- 🚨 **Tiered Alert System** - High/Medium/Low probability
- 🎯 **Model-Specific Alerts** - Individual setup notifications
- 📊 **Structure Change Alerts** - BOS/CHoCH notifications
- ⚠️ **Risk Management Warnings** - Poor R:R alerts
## 🚀 **Why This Indicator is Different**
### **Institutional Approach**
- 🏦 Built using **actual ICT concepts** from institutional trading
- 📊 **Multi-model confluence** instead of single-indicator reliance
- 🎯 **Risk-first mentality** with position sizing integration
- 📈 **Professional-grade** market structure analysis
### **Complete Trading System**
- 🎪 Not just signals - complete **market analysis framework**
- 💰 **Integrated risk management** for proper position sizing
- 📊 **Performance tracking** to refine your approach
- 🎯 **Multi-timeframe** analysis for institutional-level precision
### **Proven ICT Methodology**
- ✅ **Optimal Trade Entry** zones for high-probability entries
- 🥈 **Silver Bullet** setups during institutional activity times
- 🦄 **Unicorn Model** for maximum confluence trades
- 📦 **Order Block** and **Fair Value Gap** precision timing
## 📚 **Perfect For**
- 💼 **Serious Forex Traders** using ICT methodology
- 📈 **Indices Traders** (ES, NQ, etc.) seeking institutional setups
- 🎯 **Swing Traders** wanting multi-timeframe confluence
- 📊 **Day Traders** needing precise entry timing
- 🏦 **Anyone learning** institutional trading concepts
## ⚙️ **Easy Setup**
1. **Add to Chart** - Works on any timeframe (15min recommended)
2. **Set Risk Parameters** - Account size and risk percentage
3. **Customize Weights** - Adjust model importance to your style
4. **Enable Alerts** - Get notified of high-probability setups
5. **Start Trading** - Use confluence scoring for better decisions
## 🎓 **Educational Value**
- 📚 **Learn ICT Concepts** - Visual representation of all key models
- 🎯 **Understand Confluence** - See how multiple factors align
- 💰 **Risk Management Training** - Learn proper position sizing
- 📊 **Market Structure Education** - Identify BOS, CHoCH, and more
---
**⚡ Transform your trading today with the most advanced ICT indicator available. Stop guessing and start trading with institutional-level market analysis and risk management.**
*Compatible with all markets: Forex, Indices, Commodities, Crypto*
*Recommended timeframes: 15min to 4H for optimal performance*
---
**🔥 Don't just trade - trade with institutional intelligence and proper risk management. Your account will thank you.**
HorizonSigma Pro [CHE]HorizonSigma Pro
Disclaimer
Not every timeframe will yield good results . Very short charts are dominated by microstructure noise, spreads, and slippage; signals can flip and the tradable edge shrinks after costs. Very high timeframes adapt more slowly, provide fewer samples, and can lag regime shifts. When you change timeframe, you also change the ratios between horizon, lookbacks, and correlation windows—what works on M5 won’t automatically hold on H1 or D1. Liquidity, session effects (overnight gaps, news bursts), and volatility do not scale linearly with time. Always validate per symbol and timeframe, then retune horizon, z-length, correlation window, and either the neutral band or the z-threshold. On fast charts, “components” mode adapts quicker; on slower charts, “super” reduces noise. Keep prior-shift and calibration enabled, monitor Hit Rate with its confidence interval and the Brier score, and execute only on confirmed (closed-bar) values.
For example, what do “UP 61%” and “DOWN 21%” mean?
“UP 61%” is the model’s estimated probability that the close will be higher after your selected horizon—directional probability, not a price target or profit guarantee. “DOWN 21%” still reports the probability of up; here it’s 21%, which implies 79% for down (a short bias). The label switches to “DOWN” because the probability falls below your short threshold. With a neutral-band policy, for example ±7%, signals are: Long above 57%, Short below 43%, Neutral in between. In z-score mode, fixed z-cutoffs drive the call instead of percentages. The arrow length on the chart is an ATR-scaled projection to visualize reach; treat it as guidance, not a promise.
Part 1 — Scientific description
Objective.
The indicator estimates the probability that price will be higher after a user-defined horizon (a chosen number of bars) and emits long, short, or neutral decisions under explicit thresholds. It combines multi‑feature, z‑normalized inputs, adaptive correlation‑based weighting, a prior‑shifted sigmoid mapping, optional rolling probability calibration, and repaint‑safe confirmation. It also visualizes an ATR‑scaled forward projection and prints a compact statistics panel.
Data and labeling.
For each bar, the target label is whether price increased over the past chosen horizon. Learning is deliberately backward‑looking to avoid look‑ahead: features are associated with outcomes that are only known after that horizon has elapsed.
Feature engineering.
The feature set includes momentum, RSI, stochastic %K, MACD histogram slope, a normalized EMA(20/50) trend spread, ATR as a share of price, Bollinger Band width, and volume normalized by its moving average. All features are standardized over rolling windows. A compressed “super‑feature” is available that aggregates core trend and momentum components while penalizing excessive width (volatility). Users can switch between a “components” mode (weighted sum of individual features) and a “super” mode (single compressed driver).
Weighting and learning.
Weights are the rolling correlations between features (evaluated one horizon ago) and realized directional outcomes, smoothed by an EMA and optionally clamped to a bounded range to stabilize outliers. This produces an adaptive, regime‑aware weighting without explicit machine‑learning libraries.
Scoring and probability mapping.
The raw score is either the weighted component sum or the weighted super‑feature. The score is standardized again and passed through a sigmoid whose steepness is user‑controlled. A “prior shift” moves the sigmoid’s midpoint to the current base rate of up moves, estimated over the evaluation window, so that probabilities remain well‑calibrated when markets drift bullish or bearish. Probabilities and standardized scores are EMA‑smoothed for stability.
Decision policy.
Two modes are supported:
- Neutral band: go long if the probability is above one half plus a user‑set band; go short if it is below one half minus that band; otherwise stay neutral.
- Z‑score thresholds: use symmetric positive/negative cutoffs on the standardized score to trigger long/short.
Repaint protection.
All values used for decisions can be locked to confirmed (closed) bars. Intrabar updates are available as a preview, but confirmed values drive evaluation and stats.
Calibration.
An optional rolling linear calibration maps past confirmed probabilities to realized outcomes over the evaluation window. The mapping is clipped to the unit interval and can be injected back into the decision logic if desired. This improves reliability (probabilities that “mean what they say”) without necessarily improving raw separability.
Evaluation metrics.
The table reports: hit rate on signaled bars; a Wilson confidence interval for that hit rate at a chosen confidence level; Brier score as a measure of probability accuracy; counts of long/short trades; average realized return by side; profit factor; net return; and exposure (signal density). All are computed on rolling windows consistent with the learning scheme.
Visualization.
On the chart, an arrowed projection shows the predicted direction from the current bar to the chosen horizon, with magnitude scaled by ATR (optionally scaled by the square‑root of the horizon). Labels display either the decision probability or the standardized score. Neutral states can display a configurable icon for immediate recognition.
Computational properties.
The design relies on rolling means, standard deviations, correlations, and EMAs. Per‑bar cost is constant with respect to history length, and memory is constant per tracked series. Graphical objects are updated in place to obey platform limits.
Assumptions and limitations.
The method is correlation‑based and will adapt after regime changes, not before them. Calibration improves probability reliability but not necessarily ranking power. Intrabar previews are non‑binding and should not be evaluated as historical performance.
Part 2 — Trader‑facing description
What it does.
This tool tells you how likely price is to be higher after your chosen number of bars and converts that into Long / Short / Neutral calls. It learns, in real time, which components—momentum, trend, volatility, breadth, and volume—matter now, adjusts their weights, and shows you a probability line plus a forward arrow scaled by volatility.
How to set it up.
1) Choose your horizon. Intraday scalps: 5–10 bars. Swings: 10–30 bars. The default of 14 bars is a balanced starting point.
2) Pick a feature mode.
- components: granular and fast to adapt when leadership rotates between signals.
- super: cleaner single driver; less noise, slightly slower to react.
3) Decide how signals are triggered.
- Neutral band (probability based): intuitive and easy to tune. Widen the band for fewer, higher‑quality trades; tighten to catch more moves.
- Z‑score thresholds: consistent numeric cutoffs that ignore base‑rate drift.
4) Keep reliability helpers on. Leave prior shift and calibration enabled to stabilize probabilities across bullish/bearish regimes.
5) Smoothing. A short EMA on the probability or score reduces whipsaws while preserving turns.
6) Overlay. The arrow shows the call and a volatility‑scaled reach for the next horizon. Treat it as guidance, not a promise.
Reading the stats table.
- Hit Rate with a confidence interval: your recent accuracy with an uncertainty range; trust the range, not only the point.
- Brier Score: lower is better; it checks whether a stated “70%” really behaves like 70% over time.
- Profit Factor, Net Return, Exposure: quick triage of tradability and signal density.
- Average Return by Side: sanity‑check that the long and short calls each pull their weight.
Typical adjustments.
- Too many trades? Increase the neutral band or raise the z‑threshold.
- Missing the move? Tighten the band, or switch to components mode to react faster.
- Choppy timeframe? Lengthen the z‑score and correlation windows; keep calibration on.
- Volatility regime change? Revisit the ATR multiplier and enable square‑root scaling of horizon.
Execution and risk.
- Size positions by volatility (ATR‑based sizing works well).
- Enter on confirmed values; use intrabar previews only as early signals.
- Combine with your market structure (levels, liquidity zones). This model is statistical, not clairvoyant.
What it is not.
Not a black‑box machine‑learning model. It is transparent, correlation‑weighted technical analysis with strong attention to probability reliability and repaint safety.
Suggested defaults (robust starting point).
- Horizon 14; components mode; weight EMA 10; correlation window 500; z‑length 200.
- Neutral band around seven percentage points, or z‑threshold around one‑third of a standard deviation.
- Prior shift ON, Calibration ON, Use calibrated for decisions OFF to start.
- ATR multiplier 1.0; square‑root horizon scaling ON; EMA smoothing 3.
- Confidence setting equivalent to about 95%.
Disclaimer
No indicator guarantees profits. HorizonSigma Pro is a decision aid; always combine with solid risk management and your own judgment. Backtest, forward test, and size responsibly.
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Enhance your trading precision and confidence 🚀
Best regards
Chervolino
BTC Macro Composite Index -Offsettingthis is an indicator using Howell's Thesis of BTC moved by liquidity :
instead of using global M2, it composes :
Global Liquidity (41%) = USD-adjusted CB balance sheets (WALCL, EUCBBS, JPCBBS, CNCBBS)
Investor Risk Appetite (22%)=Copper/Gold ratio, inverted VIX (risk-on), HY vs IG OAS
Gold-related factors(15-20%)= XAUUSD + BTC/Gold ratio (Gold influence on Bitcoin)
All of it offset foward 90 days , and it does a better job on identifying where the btc price will be headed .....
Trapped Traders [ScorsoneEnterprises]This indicator identifies and visualizes trapped traders - market participants caught on the wrong side of price movements with significant volume imbalances. By analyzing volume delta at specific price levels, it reveals where traders are likely experiencing unrealized losses and may be forced to exit their positions.
The point of this tool is to identify where the liquidity in a trend may be.
var lowerTimeframe = switch
useCustomTimeframeInput => lowerTimeframeInput
timeframe.isseconds => "1S"
timeframe.isintraday => "1"
timeframe.isdaily => "5"
=> "60"
= ta.requestVolumeDelta(lowerTimeframe)
price_quantity = map.new()
is_red_candle = close < open
is_green_candle = close > open
for i=0 to lkb-1 by 1
current_vol = price_quantity.get(close)
new_vol = na(current_vol) ? lastVolume : current_vol + lastVolume
price_quantity.put(close, new_vol)
if is_green_candle and new_vol < 0
price_quantity.put(close, new_vol)
else if is_red_candle and new_vol > 0
price_quantity.put(close, new_vol)
We see in this snippet, the lastVolume variable is the most recent volume delta we can receive from the lower timeframe, we keep updating the price level we're keeping track of with that lastVolume from the lower timeframe.
This is the bulk of the concept as this level and size gives us the idea of how many traders were on the wrong side of the trend, and acting as liquidity for the profitable entries. The more, the stronger.
There are 3 ways to visualize this. A basic label, that will display the size and if positive or negative next to the bar, a gradient line that goes 10 bars to the future to be used as a support or resistance line that includes the quantity, and a bubble chart with the quantity. The larger the quantity, the bigger the bubble.
We see in this example on NYMEX:CL1! that there are lines plotted throughout this price action that price interacts with in meaningful way. There are consistently many levels for us.
Here on CME_MINI:ES1! we see the labels on the chart, and the size set to large. It is the same concept just another way to view it.
This chart of CME_MINI:RTY1! shows the bubble chart visualization. It is a way to view it that is pretty non invasive on the chart.
Every timeframe is supported including daily, weekly, and monthly.
The included settings are the display style, like mentioned above. If the user would like to see the volume numbers on the chart. The text size along with the transparency percentage. Following that is the settings for which lower timeframe to calculate the volume delta on. Finally, if you would like to see your inputs in the status line.
No indicator is 100% accurate, use "Trapped Traders" along with your own discretion.
Advanced Price Ranges ICTThis indicator automatically divides price into fixed ranges (configurable in points or pips) and plots important reference levels such as the high, low, 50% midpoint, and 25%/75% quarters. It is designed to help traders visualize structured price movement, spot confluence zones, and frame their trading bias around clean range-based levels.
🔹 Key Features
Custom Range Size: Define ranges in points (e.g., 100, 50, 25, 10) or in Forex pips.
Forex Mode: Automatically adapts pip size (0.0001 or 0.01 for JPY pairs).
Dynamic Anchoring: Price ranges automatically align to the current price, snapping into blocks.
Multiple Ranges: Option to extend visualization above and below the current active block for a complete grid.
Level Types:
High / Low of the range
50% midpoint
25% and 75% quarters
Custom Styling: Adjustable line colors and widths for each level type.
Labels: Optional right-edge labels showing level type and exact price.
Alerts: Built-in alerts for when price crosses the range high, low, or 50% midpoint.
🔹 Use Cases
Quickly map out 100/50/25/10 point structures like Zeussy’s advanced price range method.
Identify key reaction levels where liquidity is often built or swept.
Support ICT-style concepts like range-based bias, fair value gaps, and liquidity pools.
Works for indices, futures, crypto, and forex.
🔹 Customization
Range increments can be set to any size (default 100).
Toggle which levels are shown (High/Low, Midpoint, Quarters).
Adjustable line widths, colors, and label visibility.
Extend ranges above and below for broader market context.
BOS FVG IndicatorBOS FVG Indicator (Smart Market Structure Tool)
🔎 Overview
The BOS FVG Indicator is a smart price-action–based tool that combines Break of Structure (BOS), Change of Character (CHoCH), Fair Value Gaps (FVG), Supertrend, and ADX strength into one powerful indicator.
It helps traders identify market structure shifts, imbalances, and high-probability trade setups while also highlighting no-trade zones (NTZ) where the market is choppy or lacks trend strength.
This indicator is designed for intraday and swing traders who follow ICT-style concepts or price-action based trading.
⚡ Key Features
Break of Structure (BOS) & CHoCH Detection
Labels bullish BOS (📈 BOS↑) and bearish BOS (📉 BOS↓).
Highlights structure shifts for trend confirmation.
Fair Value Gaps (FVG)
Auto-detects bullish and bearish FVGs.
Draws transparent boxes with labels where imbalances appear.
Supertrend Confirmation
Adaptive supertrend line with dynamic coloring (green = bullish, red = bearish).
No Trade Zone (NTZ)
Automatically shades background gray when ADX is weak or no BOS detected.
Helps avoid false signals in sideways/choppy markets.
Multi-Timeframe Context
Previous 4H candle range plotted as a dotted yellow box.
Useful for intraday traders tracking HTF liquidity zones.
Signal Strength
Regular and Strong Buy/Sell signals based on ADX confirmation.
Labels include entry info, RR (2:1), and trend strength.
Market Info Dashboard
Table on chart showing ADX strength, current trend, and trade zone status.
🛠 How to Use
Add to Chart → Apply the indicator to any timeframe (works best on 5m–1H for intraday, 4H–Daily for swing).
Choose Mode
Indicator Mode → Shows visual signals, BOS, FVG, NTZ zones, and dashboard.
Strategy Mode → Displays trade entry labels with RR info for backtesting setups.
Filters
Only trade signals when ADX > threshold and NTZ is inactive.
Confirm with Supertrend direction + BOS + FVG alignment.
Entries & Exits
Long Entry → Bullish BOS + Bullish FVG + Trend bullish.
Short Entry → Bearish BOS + Bearish FVG + Trend bearish.
Stop Loss: Recent swing high/low.
Take Profit: Auto-suggested 2:1 RR.
🔔 Alerts
Set alerts to never miss key signals:
✅ Bullish / Bearish BOS
✅ Bullish / Bearish FVG
✅ Strong Buy / Sell
✅ Regular Buy / Sell
✅ Long / Short Entries
✅ No Trade Zone active
Alerts are pre-configured with clear messages (📈, 📉, 🚀, 🟢, 🔴, ⚪).
📌 Best Use Cases
ICT-style liquidity and FVG traders.
Intraday traders filtering strong vs weak signals.
Swing traders using multi-timeframe confirmation.
Traders who want an all-in-one market structure toolkit.
👉 This script is not financial advice. Always backtest before using in live markets.
TURNOVER FOR THE DAY TURNOVER FOR THE DAY
1. Turnover in Volume Terms (Share Turnover)
This refers to the total number of shares traded in a stock or the whole market during a day.
It includes both buy and sell transactions (since every buy has a corresponding sell, exchanges count the total traded quantity).
Example:
If Reliance Industries had 50 lakh shares traded today, then its turnover in volume = 50,00,000 shares.
This shows liquidity and activity level of the stock.
2. Turnover in Stock Market Terms (Value Turnover / Trading Value)
This refers to the total money value of shares traded in a stock or the market during a day.
Formula:
Turnover (Value)
=
Total Shares Traded
×
Average/Trade Price
Turnover (Value)=Total Shares Traded×Average/Trade Price
🔑 Difference
Volume turnover = Quantity traded (in shares).
Value turnover = Amount of money involved (in ₹ / $).
Both are used:
Volume turnover helps measure liquidity (how actively a stock is traded).
Value turnover helps gauge the capital flow or market participation in money terms.
FlowStateTrader FlowState Trader - Advanced Time-Filtered Strategy
## Overview
FlowState Trader is a sophisticated algorithmic trading strategy that combines precision entry signals with intelligent time-based filtering and adaptive risk management. Built for traders seeking to achieve their optimal performance state, FlowState identifies high-probability trading opportunities within user-defined time windows while employing dynamic trailing stops and partial position management.
## Core Strategy Philosophy
FlowState Trader operates on the principle that peak trading performance occurs when three elements align: **Focus** (precise entry signals), **Flow** (optimal time windows), and **State** (intelligent position management). This strategy excels at finding reversal opportunities at key support and resistance levels while filtering out suboptimal trading periods to keep traders in their optimal flow state.
## Key Features
### 🎯 Focus Entry System
**Support/Resistance Zone Trading**:
- Dynamic identification of key price levels using configurable lookback periods
- Entry signals triggered when price interacts with these critical zones
- Volume confirmation ensures genuine breakout/reversal momentum
- Trend filter alignment prevents counter-trend disasters
**Entry Conditions**:
- **Long Signals**: Price closes above support buffer, touches support level, with above-average volume
- **Short Signals**: Price closes below resistance buffer, touches resistance level, with above-average volume
- Optional trend filter using EMA or SMA for directional bias confirmation
### ⏰ FlowState Time Filtering System
**Comprehensive Time Controls**:
- **12-Hour Format Trading Windows**: User-friendly AM/PM time selection
- **Multi-Timezone Support**: UTC, EST, PST, CST with automatic conversion
- **Day-of-Week Filtering**: Trade only weekdays, weekends, or both
- **Lunch Hour Avoidance**: Automatically skips low-volume lunch periods (12-1 PM)
- **Visual Time Indicators**: Background coloring shows active/inactive trading periods
**Smart Time Features**:
- Handles overnight trading sessions seamlessly
- Prevents trades during historically poor performance periods
- Customizable trading hours for different market sessions
- Real-time trading window status in dashboard
### 🛡️ Adaptive Risk Management
**Multi-Level Take Profit System**:
- **TP1**: First profit target with optional partial position closure
- **TP2**: Final profit target for remaining position
- **Flexible Scaling**: Choose number of contracts to close at each level
**Dynamic Trailing Stop Technology**:
- **Three Operating Modes**:
- **Conservative**: Earlier activation, tighter trailing (protect profits)
- **Balanced**: Optimal risk/reward balance (recommended)
- **Aggressive**: Later activation, wider trailing (let winners run)
- **ATR-Based Calculations**: Adapts to current market volatility
- **Automatic Activation**: Engages when position reaches profitability threshold
### 📊 Intelligent Position Sizing
**Contract-Based Management**:
- Configurable entry quantity (1-1000 contracts)
- Partial close quantities for profit-taking
- Clear position tracking and P&L monitoring
- Real-time position status updates
### 🎨 Professional Visualization
**Enhanced Chart Elements**:
- **Entry Zone Highlighting**: Clear visual identification of trading opportunities
- **Dynamic Risk/Reward Lines**: Real-time TP and SL levels with price labels
- **Trailing Stop Visualization**: Live tracking of adaptive stop levels
- **Support/Resistance Lines**: Key level identification
- **Time Window Background**: Visual confirmation of active trading periods
**Dual Dashboard System**:
- **Strategy Dashboard**: Real-time position info, settings status, and current levels
- **Performance Scorecard**: Live P&L tracking, win rates, and trade statistics
- **Customizable Sizing**: Small, Medium, or Large display options
### ⚙️ Comprehensive Customization
**Core Strategy Settings**:
- **Lookback Period**: Support/resistance calculation period (5-100 bars)
- **ATR Configuration**: Period and multipliers for stops/targets
- **Reward-to-Risk Ratios**: Customizable profit target calculations
- **Trend Filter Options**: EMA/SMA selection with adjustable periods
**Time Filter Controls**:
- **Trading Hours**: Start/end times in 12-hour format
- **Timezone Selection**: Four major timezone options
- **Day Restrictions**: Weekend-only, weekday-only, or unrestricted
- **Session Management**: Lunch hour avoidance and custom periods
**Risk Management Options**:
- **Trailing Stop Modes**: Conservative/Balanced/Aggressive presets
- **Partial Close Settings**: Enable/disable with custom quantities
- **Alert System**: Comprehensive notifications for all trade events
### 📈 Performance Tracking
**Real-Time Metrics**:
- Net profit/loss calculation
- Win rate percentage
- Profit factor analysis
- Maximum drawdown tracking
- Total trade count and breakdown
- Current position P&L
**Trade Analytics**:
- Winner/loser ratio tracking
- Real-time performance scorecard
- Strategy effectiveness monitoring
- Risk-adjusted return metrics
### 🔔 Alert System
**Comprehensive Notifications**:
- Entry signal alerts with price and quantity
- Take profit level hits (TP1 and TP2)
- Stop loss activations
- Trailing stop engagements
- Position closure notifications
## Strategy Logic Deep Dive
### Entry Signal Generation
The strategy identifies high-probability reversal points by combining multiple confirmation factors:
1. **Price Action**: Looks for price interaction with key support/resistance levels
2. **Volume Confirmation**: Ensures sufficient market interest and liquidity
3. **Trend Alignment**: Optional filter prevents counter-trend positions
4. **Time Validation**: Only trades during user-defined optimal periods
5. **Zone Analysis**: Entry occurs within calculated buffer zones around key levels
### Risk Management Philosophy
FlowState Trader employs a three-tier risk management approach:
1. **Initial Protection**: ATR-based stop losses set at strategy entry
2. **Profit Preservation**: Trailing stops activate once position becomes profitable
3. **Scaled Exit**: Partial profit-taking allows for both security and potential
### Time-Based Edge
The time filtering system recognizes that not all trading hours are equal:
- Avoids low-volume, high-spread periods
- Focuses on optimal liquidity windows
- Prevents trading during news events (lunch hours)
- Allows customization for different market sessions
## Best Practices and Optimization
### Recommended Settings
**For Scalping (1-5 minute charts)**:
- Lookback Period: 10-20
- ATR Period: 14
- Trailing Stop: Conservative mode
- Time Filter: Major session hours only
**For Day Trading (15-60 minute charts)**:
- Lookback Period: 20-30
- ATR Period: 14-21
- Trailing Stop: Balanced mode
- Time Filter: Extended trading hours
**For Swing Trading (4H+ charts)**:
- Lookback Period: 30-50
- ATR Period: 21+
- Trailing Stop: Aggressive mode
- Time Filter: Disabled or very broad
### Market Compatibility
- **Forex**: Excellent for major pairs during active sessions
- **Stocks**: Ideal for liquid stocks during market hours
- **Futures**: Perfect for index and commodity futures
- **Crypto**: Effective on major cryptocurrencies (24/7 capability)
### Risk Considerations
- **Market Conditions**: Performance varies with volatility regimes
- **Timeframe Selection**: Lower timeframes require tighter risk management
- **Position Sizing**: Never risk more than 1-2% of account per trade
- **Backtesting**: Always test on historical data before live implementation
## Educational Value
FlowState serves as an excellent learning tool for:
- Understanding support/resistance trading
- Learning proper time-based filtering
- Mastering trailing stop techniques
- Developing systematic trading approaches
- Risk management best practices
## Disclaimer
This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly backtest the strategy and understand all risks before live trading. Always use proper position sizing and never risk more than you can afford to lose.
---
*FlowState Trader represents the evolution of systematic trading - combining classical technical analysis with modern risk management and intelligent time filtering to help traders achieve their optimal performance state through systematic, disciplined execution.*
STOCK EXCHANGE + SILVER BULLET FRAMESThis script is an updated version of the " NY/LDN/TOK Stock Exchange Opening Hours " script.
Objective
Displays global stock exchange sessions (New York, London, Tokyo) with session frames, highs/lows, and opening lines. Includes ICT Silver Bullet windows (NY, London, Tokyo) with configurable shading. Past sessions are frozen at close, ongoing sessions update dynamically until closure, and upcoming sessions are pre-drawn. Fully customizable with options for weekends, labels, padding, opacity, and individual session toggles.
It is designed to help traders quickly interpret market context, liquidity zones, and session-based price behavior.
Main Features
Past sessions (historical data)
• Session Frames:
• Each box is frozen at the session’s close.
• The left edge aligns with the opening time, while the right edge is fixed at the closing time.
• The top and bottom reflect the highest and lowest prices during the session.
• Session Labels:
• Names (NY, LDN, TOK) displayed above the frame, aligned left, in the same color as the frame.
• Opening Lines:
• Vertical dotted lines mark the start of each session.
Ongoing and upcoming sessions (live market)
• Dynamic Session Frames:
• The right edge is locked at the future close time.
• The top and bottom update in real time as new highs and lows form.
• Labels and Lines:
• The session label is visible above the active frame.
• Opening lines are drawn as soon as the session begins.
Silver Bullet Time Windows (ICT concept)
• Highlights key liquidity windows within sessions:
• New York: 10:00–11:00 and 14:00–15:00
• London: 08:00–09:00
• Tokyo: 09:00–10:00
• Silver Bullet zones are shaded with configurable opacity (default 5%).
Customization and Options
• Enable or disable individual sessions (NY, London, Tokyo).
• Toggle weekend display (frames and Silver Bullets).
• Adjust label size, padding, and text visibility.
• Control frame opacity (default 0%).
• Optimized memory management with automatic pruning of old graphical objects.
Smart Moving Concepts [GILDEX]This all-in-one indicator displays real-time market structure (internal & swing BOS / CHoCH), order blocks, premium & discount zones, equal highs & lows, and much more...allowing traders to automatically mark up their charts with widely used price action methodologies. Following the release of our Fair Value Gap script, we received numerous requests from our community to release more features in the same category.
"Smart Money Concepts" (SMC) is a fairly new yet widely used term amongst price action traders looking to more accurately navigate liquidity & find more optimal points of interest in the market. Trying to determine where institutional market participants have orders placed (buy or sell side liquidity) can be a very reasonable approach to finding more practical entries & exits based on price action.
The indicator includes alerts for the presence of swing structures and many other relevant conditions.
Features
This indicator includes many features relevant to SMC, these are highlighted below:
Full internal & swing market structure labeling in real-time
Break of Structure (BOS)
Change of Character (CHoCH)
Order Blocks (bullish & bearish)
Equal Highs & Lows
Fair Value Gap Detection
Previous Highs & Lows
Premium & Discount Zones as a range
Options to style the indicator to more easily display these concepts
Settings
Mode: Allows the user to select Historical (default) or Present, which displays only recent data on the chart.
Style: Allows the user to select different styling for the entire indicator between Colored (default) and Monochrome.
Color Candles: Plots candles based on the internal & swing structures from within the indicator on the chart.
Internal Structure: Displays the internal structure labels & dashed lines to represent them. (BOS & CHoCH).
Confluence Filter: Filter non-significant internal structure breakouts.
Swing Structure: Displays the swing structure labels & solid lines on the chart (larger BOS & CHoCH labels).
Swing Points: Displays swing points labels on chart such as HH, HL, LH, LL.
Internal Order Blocks: Enables Internal Order Blocks & allows the user to select how many most recent Internal Order Blocks appear on the chart.
Swing Order Blocks: Enables Swing Order Blocks & allows the user to select how many most recent Swing Order Blocks appear on the chart.
Equal Highs & Lows: Displays EQH/EQL labels on chart for detecting equal highs & lows.
Bars Confirmation: Allows the user to select how many bars are needed to confirm an EQH/EQL symbol on chart.
Fair Value Gaps: Displays boxes to highlight imbalance areas on the chart.
Auto Threshold: Filter out non-significant fair value gaps.
Timeframe: Allows the user to select the timeframe for the Fair Value Gap detection.
Extend FVG: Allows the user to choose how many bars to extend the Fair Value Gap boxes on the chart.
Highs & Lows MTF: Allows the user to display previous highs & lows from daily, weekly, & monthly timeframes as significant levels.
Premium/Discount Zones: Allows the user to display Premium, Discount, and Equilibrium zones on the chart
Cheat CodeWhy Monday & Friday
Monday evening (NY): frequently seeds the weekly expansion. Its DR/IDR often acts as a weekly “starter envelope,” useful for breakout continuation or fade back into the box plays as liquidity builds.
Friday evening (NY): often exposes end-of-week traps (run on stops into the close) and sets expectation boundaries into the following week. Carry these levels forward to catch Monday’s reaction to Friday’s closing structure.
Typical use-cases
Breakout & retest:
Price closes outside the Monday DR/IDR → look for retests of the band edge for continuation.
Liquidity sweep (“trap”) recognition:
Friday session wicks briefly beyond Friday DR/IDR then closes back inside → watch for mean reversion early next week.
Bias filter:
Above both Monday DR midline and Friday DR midline → bias long until proven otherwise; the inverse for shorts.
Session open confluence:
Reactions at the open line frequently mark decision points for momentum vs. fade setups.
(This is a levels framework, not a signals engine. Combine with your execution model: orderflow, S/R, session timing, or higher-TF bias.)
Inputs & styling (quick reference)
Display toggles (per day):
Show DR / IDR / Middle DR / Middle IDR
Show Opening Line
Show DR/IDR Box (choose DR or IDR as box source)
Show Price Labels
Style controls (per day):
Line width (1–4), style (Solid/Dashed/Dotted)
Independent colors for DR, IDR, midlines, open line
Box background opacity
Timezone:
Default America/New_York (changeable).
Optional on-chart warning if your chart TZ differs.
Practical notes
Works on intraday charts; levels are anchored using weekly timestamps for accuracy on any symbol.
Live updating: During the Mon/Fri calc windows, DR/IDR highs/lows and midlines keep updating until the session ends.
Clean drawings: Lines, box, and labels are created once per session and then extended/updated—efficient on resources even with long display windows.
Max elements: Script reserves ample line/box/label capacity for stability across weeks.
Engulfing + Sweep (Confirmed Only) v6 — bars onlyMarks bullish/bearish engulfing candles with liquidity sweeps and confirms them on the next candle — no repaint.
✳️ Features:
• 🟩 Bullish Engulfing + Low Sweep
• 🟥 Bearish Engulfing + High Sweep
• 🎛 Require opposite-color previous candle (optional)
• 📏 Min body-to-range filter
• 🔔 Alerts on confirmation candle
🎯 Best for:
• Price action & reversal traders
• Liquidity sweep confluence setups
Nifty50 Swing Trading Super Indicator# 🚀 Nifty50 Swing Trading Super Indicator - Complete Guide
**Created by:** Gaurav
**Date:** August 8, 2025
**Version:** 1.0 - Optimized for Indian Markets
---
## 📋 Table of Contents
1. (#quick-start-guide)
2. (#indicator-overview)
3. (#installation-instructions)
4. (#parameter-settings)
5. (#signal-interpretation)
6. (#trading-strategy)
7. (#risk-management)
8. (#optimization-tips)
9. (#troubleshooting)
---
## 🎯 Quick Start Guide
### What You Get
✅ **2 Complete Pine Script Indicators:**
- `swing_trading_super_indicator.pine` - Universal version for all markets
- `nifty_optimized_super_indicator.pine` - Specifically optimized for Nifty50 & Indian stocks
✅ **Key Features:**
- Multi-component signal confirmation system
- Optimized for daily and 3-hour timeframes
- Built-in risk management with dynamic stops and targets
- Real-time signal strength monitoring
- Gap analysis for Indian market characteristics
### Immediate Setup
1. Copy the Pine Script code from `nifty_optimized_super_indicator.pine`
2. Paste into TradingView Pine Editor
3. Add to chart on daily or 3-hour timeframe
4. Look for 🚀BUY and 🔻SELL signals
5. Use the information table for signal confirmation
---
## 🔍 Indicator Overview
### Core Components Integration
**🎯 Range Filter (35% Weight)**
- Primary trend identification using adaptive volatility filtering
- Optimized sampling period: 21 bars for Indian market volatility
- Enhanced range multiplier: 3.0 to handle market gaps
- Provides trend direction and strength measurement
**⚡ PMAX (30% Weight)**
- Volatility-adjusted trend confirmation using ATR-based calculations
- Dynamic multiplier adjustment based on market volatility
- 14-period ATR with 2.5 multiplier for swing trading sensitivity
- Offers trailing stop functionality
**🏗️ Support/Resistance (20% Weight)**
- Dynamic level identification using pivot point analysis
- Tighter channel width (3%) for precise Indian market levels
- Enhanced strength calculation with historical interaction weighting
- Provides entry/exit timing and breakout signals
**📊 EMA Alignment (15% Weight)**
- Multi-timeframe moving average confirmation
- Key EMAs: 9, 21, 50, 200 (popular in Indian markets)
- Hierarchical alignment scoring for trend strength
- Additional trend validation layer
### Advanced Features
**🌅 Gap Analysis**
- Automatic detection of significant price gaps (>2%)
- Gap strength measurement and impact on signals
- Specific optimization for Indian market overnight gaps
- Visual gap markers on chart
**⏰ Multi-Timeframe Integration**
- Higher timeframe bias from daily/weekly data
- Configurable daily bias weight (default 70%)
- 3-hour confirmation for precise entry timing
- Prevents counter-trend trades against major timeframe
**🛡️ Risk Management**
- Dynamic stop-loss calculation using multiple methods
- Automatic profit target identification
- Position sizing guidance based on signal strength
- Anti-whipsaw logic to prevent false signals
---
## 📥 Installation Instructions
### Step 1: Access TradingView
1. Open TradingView.com
2. Navigate to Pine Editor (bottom panel)
3. Create a new indicator
### Step 2: Copy the Code
**For Nifty50 & Indian Stocks (Recommended):**
```pinescript
// Copy entire content from nifty_optimized_super_indicator.pine
```
**For Universal Use:**
```pinescript
// Copy entire content from swing_trading_super_indicator.pine
```
### Step 3: Configure and Apply
1. Click "Add to Chart"
2. Select daily or 3-hour timeframe
3. Adjust parameters if needed (defaults are optimized)
4. Enable alerts for signal notifications
### Step 4: Verify Installation
- Check that all components are visible
- Confirm information table appears in top-right
- Test with known trending stocks for signal validation
---
## ⚙️ Parameter Settings
### 🎯 Range Filter Settings
```
Sampling Period: 21 (optimized for Indian market volatility)
Range Multiplier: 3.0 (handles overnight gaps effectively)
Source: Close (most reliable for swing trading)
```
### ⚡ PMAX Settings
```
ATR Length: 14 (standard for daily/3H timeframes)
ATR Multiplier: 2.5 (balanced for swing trading sensitivity)
Moving Average Type: EMA (responsive to price changes)
MA Length: 14 (matches ATR period for consistency)
```
### 🏗️ Support/Resistance Settings
```
Pivot Period: 8 (shorter for Indian market dynamics)
Channel Width: 3% (tighter for precise levels)
Minimum Strength: 3 (higher quality levels only)
Maximum Levels: 4 (focus on strongest levels)
Lookback Period: 150 (sufficient historical data)
```
### 🚀 Super Indicator Settings
```
Signal Sensitivity: 0.65 (balanced for swing trading)
Trend Strength Requirement: 0.75 (high quality signals)
Gap Threshold: 2.0% (significant gap detection)
Daily Bias Weight: 0.7 (strong higher timeframe influence)
```
### 🎨 Display Options
```
Show Range Filter: ✅ (trend visualization)
Show PMAX: ✅ (trailing stops)
Show S/R Levels: ✅ (key price levels)
Show Key EMAs: ✅ (trend confirmation)
Show Signals: ✅ (buy/sell alerts)
Show Trend Background: ✅ (visual trend state)
Show Gap Markers: ✅ (gap identification)
```
---
## 📊 Signal Interpretation
### 🚀 BUY Signals
**Requirements for BUY Signal:**
- Price above Range Filter with upward trend
- PMAX showing bullish direction (MA > PMAX line)
- Support/resistance breakout or favorable positioning
- EMA alignment supporting upward movement
- Higher timeframe bias confirmation
- Overall signal strength > 75%
**Signal Strength Indicators:**
- **90-100%:** Extremely strong - Maximum position size
- **80-89%:** Very strong - Large position size
- **75-79%:** Strong - Standard position size
- **65-74%:** Moderate - Reduced position size
- **<65%:** Weak - Wait for better opportunity
### 🔻 SELL Signals
**Requirements for SELL Signal:**
- Price below Range Filter with downward trend
- PMAX showing bearish direction (MA < PMAX line)
- Resistance breakdown or unfavorable positioning
- EMA alignment supporting downward movement
- Higher timeframe bias confirmation
- Overall signal strength > 75%
### ⚖️ NEUTRAL Signals
**Characteristics:**
- Conflicting signals between components
- Low overall signal strength (<65%)
- Range-bound market conditions
- Wait for clearer directional bias
### 📈 Information Table Guide
**Component Status:**
- **BULL/BEAR:** Current signal direction
- **Strength %:** Component contribution strength
- **Status:** Additional context (STRONG/WEAK/ACTIVE/etc.)
**Overall Signal:**
- **🚀 STRONG BUY:** All systems aligned bullish
- **🔻 STRONG SELL:** All systems aligned bearish
- **⚖️ NEUTRAL:** Mixed or weak signals
---
## 💼 Trading Strategy
### Daily Timeframe Strategy
**Setup:**
1. Apply indicator to daily chart of Nifty50 or Indian stocks
2. Wait for 🚀BUY or 🔻SELL signal with >75% strength
3. Confirm higher timeframe bias alignment
4. Check for significant support/resistance levels
**Entry:**
- Enter on signal bar close or next bar open
- Use 3-hour chart for precise entry timing
- Avoid entries during major news events
- Consider gap analysis for overnight positions
**Position Sizing:**
- **>90% Strength:** 3-4% of portfolio
- **80-89% Strength:** 2-3% of portfolio
- **75-79% Strength:** 1-2% of portfolio
- **<75% Strength:** Avoid or minimal size
### 3-Hour Timeframe Strategy
**Setup:**
1. Confirm daily timeframe bias first
2. Apply indicator to 3-hour chart
3. Look for signals aligned with daily trend
4. Use for entry/exit timing optimization
**Entry Refinement:**
- Wait for 3H signal confirmation
- Enter on pullbacks to key levels
- Use tighter stops for better risk/reward
- Monitor intraday support/resistance
### Risk Management Rules
**Stop Loss Placement:**
1. **Primary:** Use indicator's dynamic stop level
2. **Secondary:** Below/above nearest support/resistance
3. **Maximum:** 2-3% of portfolio per trade
4. **Trailing:** Move stops with PMAX line
**Profit Taking:**
1. **Target 1:** First resistance/support level (50% position)
2. **Target 2:** Second resistance/support level (30% position)
3. **Runner:** Trail remaining 20% with PMAX
**Position Management:**
- Review positions at daily close
- Adjust stops based on new signals
- Exit if trend changes to opposite direction
- Reduce size during high volatility periods
---
## 🎯 Optimization Tips
### For Nifty50 Trading
- Use daily timeframe for primary signals
- Monitor sector rotation impact
- Consider index futures for better liquidity
- Watch for RBI policy and global cues impact
### For Individual Stocks
- Verify stock follows Nifty correlation
- Check sector-specific news and events
- Ensure adequate liquidity for position size
- Monitor earnings calendar for volatility
### Market Condition Adaptations
**Trending Markets:**
- Increase position sizes for strong signals
- Use wider stops to avoid whipsaws
- Focus on trend continuation signals
- Reduce counter-trend trading
**Range-Bound Markets:**
- Reduce position sizes
- Use tighter stops and quicker profits
- Focus on support/resistance bounces
- Increase signal strength requirements
**High Volatility Periods:**
- Reduce overall exposure
- Use smaller position sizes
- Increase stop-loss distances
- Wait for clearer signals
### Performance Monitoring
- Track win rate and average profit/loss
- Monitor signal quality over time
- Adjust parameters based on market changes
- Keep trading journal for pattern recognition
---
## 🔧 Troubleshooting
### Common Issues
**Q: Signals appear too frequently**
A: Increase "Trend Strength Requirement" to 0.8-0.9
**Q: Missing obvious trends**
A: Decrease "Signal Sensitivity" to 0.5-0.6
**Q: Too many false signals**
A: Enable "3H Confirmation" and increase strength requirements
**Q: Indicator not loading**
A: Check Pine Script version compatibility (requires v5)
### Parameter Adjustments
**For More Sensitive Signals:**
- Decrease Signal Sensitivity to 0.5-0.6
- Decrease Trend Strength Requirement to 0.6-0.7
- Increase Range Filter multiplier to 3.5-4.0
**For More Conservative Signals:**
- Increase Signal Sensitivity to 0.7-0.8
- Increase Trend Strength Requirement to 0.8-0.9
- Enable all confirmation features
### Performance Issues
- Reduce lookback periods if chart loads slowly
- Disable some visual elements for better performance
- Use on liquid stocks/indices for best results
---
## 📞 Support & Updates
This super indicator combines the best of Range Filter, PMAX, and Support/Resistance analysis specifically optimized for Indian market swing trading. The multi-component approach significantly improves signal quality while the built-in risk management features help protect capital.
**Remember:** No indicator is 100% accurate. Always combine with proper risk management, market analysis, and your trading experience for best results.
**Happy Trading! 🚀**
HTFSweep – Structure & ResolveThis indicator isolates higher timeframe Open, High, Low, and Close levels and projects them onto lower timeframes.
It is designed as a structural lens, not a trading signal — a tool for experienced operators who study how intraday price interacts with higher‑timeframe liquidity anchors.
Key Features:
Selectable higher timeframe (default: Daily).
Plots Open, High, Low, Close lines across intraday charts.
Bullish/Bearish candle bodies shaded for context.
Background fill between High and Low for zone visualization.
Purpose:
This script is not a “buy/sell” tool. It is a scope, intentionally minimal, highlighting a repeating place of structural and liquidity significance. Use it to track sweeps of higher‑timeframe levels and confirm structural shifts intraday.
⚠️ Disclaimer: This script provides market structure visualization only. It does not generate trading signals or financial advice.
COMEX_MINI:MGC1!
Titan Wick Zone IndicatorThe Titan Wick Zone Indicator visually highlights the upper and lower wick regions of each candlestick on your chart, helping traders instantly identify areas where price was aggressively rejected (top wick) or absorbed (bottom wick). The indicator fills the area above the candle body to the wick high in red (sell zone), and the area below the candle body to the wick low in green (buy zone), both with adjustable opacity for clear visibility.
How to Use:
Spot Rejection and Absorption:
The red-filled upper wick zone marks where upward price moves were sharply rejected by sellers, often indicating supply, resistance, or “stop hunt” zones.
The green-filled lower wick zone marks where downward price moves were absorbed by buyers, pointing to potential demand, support, or accumulation zones.
Enhance Price Action Analysis:
Use these zones to avoid entering trades at price extremes, spot potential reversals, and find areas of confluence with support/resistance, Fibonacci levels, or order blocks.
Risk Management:
The indicator helps visualize where liquidity hunts or false breakouts may occur, so you can better place stop losses outside of volatile wick zones.
Ideal For:
Price action traders, scalpers, and swing traders seeking a visual edge in spotting supply/demand dynamics, liquidity zones, and wick-driven traps.
AymaN Entry Signal – With HTF + Pin Bar + Multi TP + BE + V1Ayman Entry Signal – Indicator Description
Overview
Ayman Entry Signal – With HTF + Pin Bar + Multi TP + BE + Stats Panel (V1)
This is a professional-grade Pine Script indicator designed for scalping and intraday trading, with full trade management, multi-confirmation logic, and advanced visualization. The tool is ideal for traders focused on XAUUSD (Gold), Forex, and other volatile instruments who seek both precision entries and structured exits with dynamic risk control.
Main Features
Advanced Entry Logic:
- EMA fast/slow crossovers (configurable)
- Optional conditions: Break of Structure (BoS), Order Block (OB), Fair Value Gap (FVG), Liquidity sweeps, Pin Bars
- HTF confirmation using EMA or BoS
- Real-time entry condition display
Trade Management:
- Dynamic calculation of Entry, SL (with ATR buffer), TP1, TP2
- Supports Partial Close and Break Even logic after TP1
- Visual PnL label (dynamic and color-coded)
Statistics Panel:
- Shows total trades, win/loss/breakeven count, cumulative PnL
- Filter by custom date or session
- Fully customizable panel appearance
Trade Visualization:
- Trade box includes all trade levels (Entry, SL, TP1, TP2)
- Visual display of trade conditions and PnL result
- Option to keep previous trades on chart
Alert System:
- Alerts for Buy and Sell entries
- Compatible with webhook automation systems like MT5/MT4
Customization & Inputs
- Capital & risk per trade
- Value per pip/point
- SL buffer (ATR-based)
- Manual EMA override
- Enable/disable: EMA, BoS, OB, FVG, Liquidity, Pin Bars
- HTF: timeframe + confirmation logic
- Trade box/labels visibility
- Full color customization
- PnL label position: top, center, or bottom
Recommended Use
- Ideal for Gold scalping (XAUUSD), also effective for Forex
- Best on 1m–15m charts; use HTF confirmation from 15m–4H
- Pairs well with semi-automated systems using alerts and webhooks
Disclaimer
Note: This is a non-executing indicator. It does not place trades but provides visual and statistical guidance for professional manual or semi-automated trading.
Drawdown Distribution Analysis (DDA) ACADEMIC FOUNDATION AND RESEARCH BACKGROUND
The Drawdown Distribution Analysis indicator implements quantitative risk management principles, drawing upon decades of academic research in portfolio theory, behavioral finance, and statistical risk modeling. This tool provides risk assessment capabilities for traders and portfolio managers seeking to understand their current position within historical drawdown patterns.
The theoretical foundation of this indicator rests on modern portfolio theory as established by Markowitz (1952), who introduced the fundamental concepts of risk-return optimization that continue to underpin contemporary portfolio management. Sharpe (1966) later expanded this framework by developing risk-adjusted performance measures, most notably the Sharpe ratio, which remains a cornerstone of performance evaluation in financial markets.
The specific focus on drawdown analysis builds upon the work of Chekhlov, Uryasev and Zabarankin (2005), who provided the mathematical framework for incorporating drawdown measures into portfolio optimization. Their research demonstrated that traditional mean-variance optimization often fails to capture the full risk profile of investment strategies, particularly regarding sequential losses. More recent work by Goldberg and Mahmoud (2017) has brought these theoretical concepts into practical application within institutional risk management frameworks.
Value at Risk methodology, as comprehensively outlined by Jorion (2007), provides the statistical foundation for the risk measurement components of this indicator. The coherent risk measures framework developed by Artzner et al. (1999) ensures that the risk metrics employed satisfy the mathematical properties required for sound risk management decisions. Additionally, the focus on downside risk follows the framework established by Sortino and Price (1994), while the drawdown-adjusted performance measures implement concepts introduced by Young (1991).
MATHEMATICAL METHODOLOGY
The core calculation methodology centers on a peak-tracking algorithm that continuously monitors the maximum price level achieved and calculates the percentage decline from this peak. The drawdown at any time t is defined as DD(t) = (P(t) - Peak(t)) / Peak(t) × 100, where P(t) represents the asset price at time t and Peak(t) represents the running maximum price observed up to time t.
Statistical distribution analysis forms the analytical backbone of the indicator. The system calculates key percentiles using the ta.percentile_nearest_rank() function to establish the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of the historical drawdown distribution. This approach provides a complete picture of how the current drawdown compares to historical patterns.
Statistical significance assessment employs standard deviation bands at one, two, and three standard deviations from the mean, following the conventional approach where the upper band equals μ + nσ and the lower band equals μ - nσ. The Z-score calculation, defined as Z = (DD - μ) / σ, enables the identification of statistically extreme events, with thresholds set at |Z| > 2.5 for extreme drawdowns and |Z| > 3.0 for severe drawdowns, corresponding to confidence levels exceeding 99.4% and 99.7% respectively.
ADVANCED RISK METRICS
The indicator incorporates several risk-adjusted performance measures that extend beyond basic drawdown analysis. The Sharpe ratio calculation follows the standard formula Sharpe = (R - Rf) / σ, where R represents the annualized return, Rf represents the risk-free rate, and σ represents the annualized volatility. The system supports dynamic sourcing of the risk-free rate from the US 10-year Treasury yield or allows for manual specification.
The Sortino ratio addresses the limitation of the Sharpe ratio by focusing exclusively on downside risk, calculated as Sortino = (R - Rf) / σd, where σd represents the downside deviation computed using only negative returns. This measure provides a more accurate assessment of risk-adjusted performance for strategies that exhibit asymmetric return distributions.
The Calmar ratio, defined as Annual Return divided by the absolute value of Maximum Drawdown, offers a direct measure of return per unit of drawdown risk. This metric proves particularly valuable for comparing strategies or assets with different risk profiles, as it directly relates performance to the maximum historical loss experienced.
Value at Risk calculations provide quantitative estimates of potential losses at specified confidence levels. The 95% VaR corresponds to the 5th percentile of the drawdown distribution, while the 99% VaR corresponds to the 1st percentile. Conditional VaR, also known as Expected Shortfall, estimates the average loss in the worst 5% of scenarios, providing insight into tail risk that standard VaR measures may not capture.
To enable fair comparison across assets with different volatility characteristics, the indicator calculates volatility-adjusted drawdowns using the formula Adjusted DD = Raw DD / (Volatility / 20%). This normalization allows for meaningful comparison between high-volatility assets like cryptocurrencies and lower-volatility instruments like government bonds.
The Risk Efficiency Score represents a composite measure ranging from 0 to 100 that combines the Sharpe ratio and current percentile rank to provide a single metric for quick asset assessment. Higher scores indicate superior risk-adjusted performance relative to historical patterns.
COLOR SCHEMES AND VISUALIZATION
The indicator implements eight distinct color themes designed to accommodate different analytical preferences and market contexts. The EdgeTools theme employs a corporate blue palette that matches the design system used throughout the edgetools.org platform, ensuring visual consistency across analytical tools.
The Gold theme specifically targets precious metals analysis with warm tones that complement gold chart analysis, while the Quant theme provides a grayscale scheme suitable for analytical environments that prioritize clarity over aesthetic appeal. The Behavioral theme incorporates psychology-based color coding, using green to represent greed-driven market conditions and red to indicate fear-driven environments.
Additional themes include Ocean, Fire, Matrix, and Arctic schemes, each designed for specific market conditions or user preferences. All themes function effectively with both dark and light mode trading platforms, ensuring accessibility across different user interface configurations.
PRACTICAL APPLICATIONS
Asset allocation and portfolio construction represent primary use cases for this analytical framework. When comparing multiple assets such as Bitcoin, gold, and the S&P 500, traders can examine Risk Efficiency Scores to identify instruments offering superior risk-adjusted performance. The 95% VaR provides worst-case scenario comparisons, while volatility-adjusted drawdowns enable fair comparison despite varying volatility profiles.
The practical decision framework suggests that assets with Risk Efficiency Scores above 70 may be suitable for aggressive portfolio allocations, scores between 40 and 70 indicate moderate allocation potential, and scores below 40 suggest defensive positioning or avoidance. These thresholds should be adjusted based on individual risk tolerance and market conditions.
Risk management and position sizing applications utilize the current percentile rank to guide allocation decisions. When the current drawdown ranks above the 75th percentile of historical data, indicating that current conditions are better than 75% of historical periods, position increases may be warranted. Conversely, when percentile rankings fall below the 25th percentile, indicating elevated risk conditions, position reductions become advisable.
Institutional portfolio monitoring applications include hedge fund risk dashboard implementations where multiple strategies can be monitored simultaneously. Sharpe ratio tracking identifies deteriorating risk-adjusted performance across strategies, VaR monitoring ensures portfolios remain within established risk limits, and drawdown duration tracking provides valuable information for investor reporting requirements.
Market timing applications combine the statistical analysis with trend identification techniques. Strong buy signals may emerge when risk levels register as "Low" in conjunction with established uptrends, while extreme risk levels combined with downtrends may indicate exit or hedging opportunities. Z-scores exceeding 3.0 often signal statistically oversold conditions that may precede trend reversals.
STATISTICAL SIGNIFICANCE AND VALIDATION
The indicator provides 95% confidence intervals around current drawdown levels using the standard formula CI = μ ± 1.96σ. This statistical framework enables users to assess whether current conditions fall within normal market variation or represent statistically significant departures from historical patterns.
Risk level classification employs a dynamic assessment system based on percentile ranking within the historical distribution. Low risk designation applies when current drawdowns perform better than 50% of historical data, moderate risk encompasses the 25th to 50th percentile range, high risk covers the 10th to 25th percentile range, and extreme risk applies to the worst 10% of historical drawdowns.
Sample size considerations play a crucial role in statistical reliability. For daily data, the system requires a minimum of 252 trading days (approximately one year) but performs better with 500 or more observations. Weekly data analysis benefits from at least 104 weeks (two years) of history, while monthly data requires a minimum of 60 months (five years) for reliable statistical inference.
IMPLEMENTATION BEST PRACTICES
Parameter optimization should consider the specific characteristics of different asset classes. Equity analysis typically benefits from 500-day lookback periods with 21-day smoothing, while cryptocurrency analysis may employ 365-day lookback periods with 14-day smoothing to account for higher volatility patterns. Fixed income analysis often requires longer lookback periods of 756 days with 34-day smoothing to capture the lower volatility environment.
Multi-timeframe analysis provides hierarchical risk assessment capabilities. Daily timeframe analysis supports tactical risk management decisions, weekly analysis informs strategic positioning choices, and monthly analysis guides long-term allocation decisions. This hierarchical approach ensures that risk assessment occurs at appropriate temporal scales for different investment objectives.
Integration with complementary indicators enhances the analytical framework. Trend indicators such as RSI and moving averages provide directional bias context, volume analysis helps confirm the severity of drawdown conditions, and volatility measures like VIX or ATR assist in market regime identification.
ALERT SYSTEM AND AUTOMATION
The automated alert system monitors five distinct categories of risk events. Risk level changes trigger notifications when drawdowns move between risk categories, enabling proactive risk management responses. Statistical significance alerts activate when Z-scores exceed established threshold levels of 2.5 or 3.0 standard deviations.
New maximum drawdown alerts notify users when historical maximum levels are exceeded, indicating entry into uncharted risk territory. Poor risk efficiency alerts trigger when the composite risk efficiency score falls below 30, suggesting deteriorating risk-adjusted performance. Sharpe ratio decline alerts activate when risk-adjusted performance turns negative, indicating that returns no longer compensate for the risk undertaken.
TRADING STRATEGIES
Conservative risk parity strategies can be implemented by monitoring Risk Efficiency Scores across a diversified asset portfolio. Monthly rebalancing maintains equal risk contribution from each asset, with allocation reductions triggered when risk levels reach "High" status and complete exits executed when "Extreme" risk levels emerge. This approach typically results in lower overall portfolio volatility, improved risk-adjusted returns, and reduced maximum drawdown periods.
Tactical asset rotation strategies compare Risk Efficiency Scores across different asset classes to guide allocation decisions. Assets with scores exceeding 60 receive overweight allocations, while assets scoring below 40 receive underweight positions. Percentile rankings provide timing guidance for allocation adjustments, creating a systematic approach to asset allocation that responds to changing risk-return profiles.
Market timing strategies with statistical edges can be constructed by entering positions when Z-scores fall below -2.5, indicating statistically oversold conditions, and scaling out when Z-scores exceed 2.5, suggesting overbought conditions. The 95% VaR serves as a stop-loss reference point, while trend confirmation indicators provide additional validation for position entry and exit decisions.
LIMITATIONS AND CONSIDERATIONS
Several statistical limitations affect the interpretation and application of these risk measures. Historical bias represents a fundamental challenge, as past drawdown patterns may not accurately predict future risk characteristics, particularly during structural market changes or regime shifts. Sample dependence means that results can be sensitive to the selected lookback period, with shorter periods providing more responsive but potentially less stable estimates.
Market regime changes can significantly alter the statistical parameters underlying the analysis. During periods of structural market evolution, historical distributions may provide poor guidance for future expectations. Additionally, many financial assets exhibit return distributions with fat tails that deviate from normal distribution assumptions, potentially leading to underestimation of extreme event probabilities.
Practical limitations include execution risk, where theoretical signals may not translate directly into actual trading results due to factors such as slippage, timing delays, and market impact. Liquidity constraints mean that risk metrics assume perfect liquidity, which may not hold during stressed market conditions when risk management becomes most critical.
Transaction costs are not incorporated into risk-adjusted return calculations, potentially overstating the attractiveness of strategies that require frequent trading. Behavioral factors represent another limitation, as human psychology may override statistical signals, particularly during periods of extreme market stress when disciplined risk management becomes most challenging.
TECHNICAL IMPLEMENTATION
Performance optimization ensures reliable operation across different market conditions and timeframes. All technical analysis functions are extracted from conditional statements to maintain Pine Script compliance and ensure consistent execution. Memory efficiency is achieved through optimized variable scoping and array usage, while computational speed benefits from vectorized calculations where possible.
Data quality requirements include clean price data without gaps or errors that could distort distribution analysis. Sufficient historical data is essential, with a minimum of 100 bars required and 500 or more preferred for reliable statistical inference. Time alignment across related assets ensures meaningful comparison when conducting multi-asset analysis.
The configuration parameters are organized into logical groups to enhance usability. Core settings include the Distribution Analysis Period (100-2000 bars), Drawdown Smoothing Period (1-50 bars), and Price Source selection. Advanced metrics settings control risk-free rate sourcing, either from live market data or fixed rate specification, along with toggles for various risk-adjusted metric calculations.
Display options provide flexibility in visual presentation, including color theme selection from eight available schemes, automatic dark mode optimization, and control over table display, position lines, percentile bands, and standard deviation overlays. These options ensure that the indicator can be adapted to different analytical workflows and visual preferences.
CONCLUSION
The Drawdown Distribution Analysis indicator provides risk management tools for traders seeking to understand their current position within historical risk patterns. By combining established statistical methodology with practical usability features, the tool enables evidence-based risk assessment and portfolio optimization decisions.
The implementation draws upon established academic research while providing practical features that address real-world trading requirements. Dynamic risk-free rate integration ensures accurate risk-adjusted performance calculations, while multiple color schemes accommodate different analytical preferences and use cases.
Academic compliance is maintained through transparent methodology and acknowledgment of limitations. The tool implements peer-reviewed statistical techniques while clearly communicating the constraints and assumptions underlying the analysis. This approach ensures that users can make informed decisions about the appropriate application of the risk assessment framework within their broader trading and investment processes.
BIBLIOGRAPHY
Artzner, P., Delbaen, F., Eber, J.M. and Heath, D. (1999) 'Coherent Measures of Risk', Mathematical Finance, 9(3), pp. 203-228.
Chekhlov, A., Uryasev, S. and Zabarankin, M. (2005) 'Drawdown Measure in Portfolio Optimization', International Journal of Theoretical and Applied Finance, 8(1), pp. 13-58.
Goldberg, L.R. and Mahmoud, O. (2017) 'Drawdown: From Practice to Theory and Back Again', Journal of Risk Management in Financial Institutions, 10(2), pp. 140-152.
Jorion, P. (2007) Value at Risk: The New Benchmark for Managing Financial Risk. 3rd edn. New York: McGraw-Hill.
Markowitz, H. (1952) 'Portfolio Selection', Journal of Finance, 7(1), pp. 77-91.
Sharpe, W.F. (1966) 'Mutual Fund Performance', Journal of Business, 39(1), pp. 119-138.
Sortino, F.A. and Price, L.N. (1994) 'Performance Measurement in a Downside Risk Framework', Journal of Investing, 3(3), pp. 59-64.
Young, T.W. (1991) 'Calmar Ratio: A Smoother Tool', Futures, 20(1), pp. 40-42.
Smart Order Blocks [Pro Version]Here’s a **clear, detailed "How It Works" explanation** for this indicator:
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## ✅ **Smart Order Blocks \ – How It Works**
### **Purpose**
This indicator detects **Order Blocks (OBs)** based on **pivot highs and lows**, and automatically marks **Bullish** and **Bearish OB zones** on the chart with optional extensions and alerts. It is designed to help traders identify **institutional price levels** where liquidity is often engineered for future price moves.
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### **Customization Options**
✔ **Source** → Choose between Wicks or Bodies for OB calculation.
✔ **Pivot Settings** → Adjust sensitivity for detecting pivots.
✔ **Extend OBs** → Keep zones visible until tapped, or fix a specific width.
✔ **Show Labels** → Displays OB type and strength on chart.
✔ **Colors** → Configure Bullish, Bearish, and Invalid OB colors.
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### **Practical Usage**
* **Entry Strategy**:
* Wait for price to **revisit a Bullish OB** in an uptrend → Long entry.
* Wait for price to **revisit a Bearish OB** in a downtrend → Short entry.
* Combine with:
* **Market Structure (HH/HL or LH/LL)**.
* **Confirmation signals** (e.g., candlestick pattern, break of structure).
* **Risk Management** → Stop loss outside OB zone.
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### ✅ **Summary in One Sentence**
The indicator automatically identifies **institutional OB zones**, shows their strength, extends them until mitigated, and alerts you when price interacts with these key liquidity levels, helping you trade like Smart Money.
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Smart Trap Candle Detector [Pro]Purpose
The Smart Trap Candle Detector is designed to identify common fakeout scenarios in the market, where price breaks a key swing high or low and quickly reverses. These “trap candles” often mislead breakout traders and are commonly used by smart money to induce liquidity before reversing.
How It Works
The script detects potential trap candles using these conditions:
A bearish trap is identified when price breaks above a recent swing high and closes back below it.
A bullish trap is identified when price breaks below a recent swing low and closes back above it.
Optional confirmation from the previous candle’s direction can be enabled.
Swing highs/lows are calculated dynamically using a configurable lookback window.
Once a trap candle is confirmed, a signal is displayed on the chart along with optional labels and alert conditions.
Features
Detects fake breakouts of swing highs and lows
Configurable swing lookback period
Optional confirmation candle filter
Optional label display on trap bars
Built-in alerts for bullish and bearish trap signals
Lightweight, real-time signal detection
Usage Tips
Best used on intraday timeframes such as 15m, 30m, or 1H
Use around key support/resistance zones or liquidity areas
Combine with other confluence signals such as order blocks or RSI divergence
Adjust the swing lookback period depending on the volatility of the asset
