Alpha Hunter Integrated MACD & Oscillator [wjdtks255]Indicator Title: Alpha Hunter Integrated MACD & Oscillator Pro
Short Description
A high-precision hybrid oscillator that integrates MACD dynamics with a secondary-smoothed histogram to eliminate market noise and capture trend reversals with minimal lag.
Detailed Description
Overview
The Alpha Hunter Integrated MACD & Oscillator is designed to overcome the inherent lag of standard MACD indicators. By applying an exponential moving average (EMA) filter to the histogram itself and incorporating a momentum direction check, this tool identifies high-probability entry points while filtering out "whipsaws" commonly found in choppy markets.
Key Technical Pillars
Dual-Smoothed Histogram: Unlike standard oscillators, this script smooths the raw histogram values using a secondary filtering period. This reveals the true underlying momentum before price action fully shifts.
Momentum Directional Filter: Entry signals are only triggered when the MACD line’s slope aligns with the crossover, ensuring you don't enter against a stalling trend.
Dynamic Trend Clouds: The visual fill between the MACD and Signal lines acts as a "Trend Cloud," providing immediate visual feedback on the strength and duration of the current trend.
The Winning Trading Strategy (How to Use)
To maximize win rates, it is highly recommended to use this indicator as a Confirmation Oscillator alongside a Long-term Trend Filter (like a 200 EMA) on your main chart.
1. Long Setup (Buy)
Context: Price must be trading above the 200 EMA on the main chart.
Signal: A green "BUY" triangle and label appear on the oscillator.
Confirmation: The Histogram should be green and rising.
Exit: Exit at a pre-defined Take Profit (TP) box or when a bearish MACD crossunder occurs.
2. Short Setup (Sell)
Context: Price must be trading below the 200 EMA on the main chart.
Signal: A red "SELL" triangle and label appear on the oscillator.
Confirmation: The Histogram should be red and falling.
Exit: Exit at the designated Stop Loss (SL) or when a bullish MACD crossover occurs.
Input Parameters & Optimization
Fast/Slow/Signal: Default 12, 26, 9. (Standard for most markets).
Signal Smoothing: Set to 5 for a balance of speed and reliability. Increase to 8+ for swing trading on higher timeframes.
Recommended Timeframes: 15m, 1h, and 4h for the best signal-to-noise ratio.
Author's Note
This indicator is a "No-Repaint" script. Signals are confirmed at the close of the candle to ensure reliability during live trading. Always use proper risk management.
Strategy
Prism Band Dynamics [JOAT]Prism Band Dynamics - Bollinger-Style Bands with Force Detection
Introduction and Purpose
Prism Band Dynamics is an open-source overlay indicator that creates dynamic Bollinger-style bands with an innovative "force detection" system. The core problem this indicator solves is that standard Bollinger Bands show volatility but don't indicate directional momentum. When all three band components (upper, lower, basis) move in the same direction, it indicates strong directional force that standard bands don't highlight.
This indicator addresses that by detecting when all band components align directionally, providing a clear signal of market force.
Why Force Detection Matters
Standard Bollinger Bands expand and contract based on volatility, but they don't tell you about directional momentum. Force detection adds this dimension:
1. Bullish Force - Upper band, lower band, AND basis all moving up together. This indicates strong upward momentum where even the lower support level is rising.
2. Bearish Force - Upper band, lower band, AND basis all moving down together. This indicates strong downward momentum where even the upper resistance level is falling.
3. Neutral - Mixed movement indicates consolidation or uncertainty.
How Force Detection Works
bool upperUp = upper > upper
bool lowerUp = lower > lower
bool basisUp = basis > basis
int forceFull = if upperUp and lowerUp and basisUp
1 // Bullish force
else if upperDn and lowerDn and basisDn
-1 // Bearish force
else
0 // Neutral
Additional Features
Squeeze Detection - Identifies when band width contracts below threshold, often preceding large moves
Gradient Fills - Color intensity reflects force strength
Direction Change Arrows - Visual markers when force direction shifts
Dashboard Information
Force - Current force status (BULLISH/BEARISH/NEUTRAL)
Position - Price location within bands (Upper/Mid/Lower Zone)
Band Width - Current width percentage with expansion/contraction label
Volatility - Squeeze status (SQUEEZE/NORMAL)
Force Count - Bars since last force change
How to Use This Indicator
For Trend Following:
1. Enter long when force turns BULLISH
2. Enter short when force turns BEARISH
3. Exit or reduce when force turns NEUTRAL
For Squeeze Breakouts:
1. Watch for SQUEEZE status in dashboard
2. Prepare for breakout in either direction
3. Enter when force confirms direction after squeeze
For Mean Reversion:
1. Only trade mean-reversion when force is NEUTRAL
2. Avoid fading moves when force is active
3. Use band touches as entry points during neutral force
Input Parameters
Length (20) - Period for basis and standard deviation
Multiplier (2.0) - Standard deviation multiplier for bands
MA Type (SMA) - Basis calculation method
Squeeze Threshold (0.5) - Band width percentage for squeeze detection
Timeframe Recommendations
4H-Daily: Cleanest force signals
1H: Good balance of signals and reliability
15m: More signals but more noise
Limitations
Force detection can lag during rapid reversals
Squeeze breakouts can fail (false breakouts)
Works best in markets with clear trending/ranging phases
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Force detection does not guarantee trend continuation. Always use proper risk management.
- Made with passion by officialjackofalltrades
End Of MooveINDICATOR: END OF MOOVE (EOM)
1. Overview
The EndOfMoove (EOM) is a specialized volatility analysis tool designed to detect market exhaustion and potential price reversals. By utilizing a modified Williams Vix Fix (WVF) logic, it identifies when fear or selling pressure has reached a statistical extreme relative to recent history.
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2. Core Logic & Calculation
The script functions by measuring the "synthetic" volatility created during sharp price drops and momentum shifts.
* Williams Vix Fix (WVF) Logic: It calculates the distance between the current low and the highest close over a specific lookback period ( 20 bars by default ). This creates a volatility spike during market bottoms or rapid corrections.
* Dynamic Normalization: The indicator continuously tracks the Historical Maximum of this volatility over a long window ( 250 bars ).
* Statistical Thresholding: It sets a "Danger Zone" at a specific percentage ( 75% ) of that historical maximum to filter out noise and isolate significant exhaustion events.
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3. Adaptive Intelligence (Detection & Smoothing)
The EOM adapts to different market conditions through its detection engine:
1. Spike Confirmation: To avoid premature entries, the script uses a confirmation window ( 3 bars ). A signal is only "confirmed" if the current volatility spike is the highest within this local window.
2. Variable Smoothing: Traders can apply an internal SMA smoothing to the raw volatility data to filter out erratic price action on lower timeframes.
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4. Visual Anatomy
The interface uses a high-contrast design to highlight institutional exhaustion:
* The Histogram:
* Faded Gray: Represents standard market volatility. The transparency is dynamic ; it darkens as volatility rises, signaling a buildup in pressure.
* Bright White: Activates when the volatility crosses the Dynamic Threshold , marking a high-probability exhaustion zone.
* The Threshold Line: A continuous horizontal boundary that represents the 75% of historical max , acting as the "Trigger Line."
* Signal Triangles: A small white triangle appears at the top of the indicator when a Volatility Spike is statistically confirmed.
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5. How to Trade with EndOfMoove
* Spotting Bottoms: Large white columns often coincide with "capitulation" phases. When the histogram reaches these levels, the current downward move is likely overextended.
* Divergence Watch: If price makes a new low but the EOM histogram shows a lower spike than the previous one, it indicates that selling pressure is drying up.
* Volatility Breakouts: A sudden transition from faded gray to bright white suggests an impulse move that is reaching its peak velocity.
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6. Technical Parameters
* WVF Period: Controls the sensitivity of the raw volatility calculation.
* Historical Max Period: Determines the depth of the statistical database (50 to 500 bars).
* Threshold %: Allows the trader to tighten or loosen the "Extreme" zone (set to 75% for balanced results).
15-Minute Squeeze Scalper (Traffic Light Edition)Overview This is a highly optimized version of the famous Squeeze Momentum Indicator, customized specifically for 15-minute scalping .
While the original indicator is powerful, the default colors can be confusing for new traders. I have recoded this to function as a simple "Traffic Light" system to help you identify periods of inaction vs. periods of high-probability breakouts.
How it Works This tool identifies when the market is "quiet" (low volatility) and getting ready to explode. It uses Bollinger Bands and Keltner Channels to measure this energy.
The "Traffic Light" Visuals
🔴 RED Cross (Center Line): STOP / WAIT
Meaning: The Squeeze is ON. The market is coiling tight.
Action: Do not trade yet. Wait for the energy to release. The longer the line of red dots, the bigger the potential move.
🟢 GREEN Cross (Center Line): GO / ACTION
Meaning: The Squeeze has FIRED. Volatility is expanding.
Action: Look at the Histogram to determine the direction of the trade.
📊 Histogram Bars:
Lime/Green: Bullish Momentum (Trade Long).
Red/Maroon: Bearish Momentum (Trade Short).
The 15-Minute Scalping Strategy
Identify the Squeeze: Look for a series of Red Crosses on the zero line.
Wait for the Fire: Wait for the first Green Cross to appear.
Confirm Direction:
If the Cross turns Green AND the Histogram is above zero: LONG.
If the Cross turns Green AND the Histogram is below zero: SHORT.
Alerts Included I have added custom alerts so you don't have to stare at the screen:
"Squeeze Fired": Alerts you instantly when the Red Cross changes to Green.
"Momentum Long/Short": Alerts you when momentum flips direction.
Multi-indicator Signal Builder [Skyrexio]Overview
Multi-Indicator Signal Builder is a versatile, all-in-one script designed to streamline your trading workflow by combining multiple popular technical indicators under a single roof.
It features a single-entry, single-exit logic, intrabar stop-loss/take-profit handling, an optional time filter, a visually accessible condition table, and a built-in statistics label.
Traders can choose any combination of 12+ indicators (RSI, Ultimate Oscillator, Bollinger %B, Moving Averages, ADX, Stochastic, MACD, PSAR, MFI, CCI, Heikin Ashi, and a “TV Screener” placeholder) to form entry or exit conditions.
This script aims to simplify strategy creation and analysis , making it a powerful toolkit for technical traders.
Indicators Overview
RSI (Relative Strength Index)
Measures recent price changes to evaluate overbought or oversold conditions on a 0–100 scale.
Ultimate Oscillator (UO)
Uses weighted averages of three different timeframes, aiming to confirm price momentum while avoiding false divergences.
Bollinger %B
Expresses price relative to Bollinger Bands, indicating whether price is near the upper band (overbought) or lower band (oversold).
Moving Average (MA)
Smooths price data over a specified period. The script supports both SMA and EMA to help identify trend direction and potential crossovers.
ADX (Average Directional Index)
Gauges the strength of a trend (0–100). Higher ADX signals stronger momentum, while lower ADX indicates a weaker trend.
Stochastic
Compares a closing price to a price range over a given period to identify momentum shifts and potential reversals.
MACD (Moving Average Convergence/Divergence)
Tracks the difference between two EMAs plus a signal line, commonly used to spot momentum flips through crossovers.
PSAR (Parabolic SAR)
Plots a trailing stop-and-reverse dot that moves with the trend. Often used to signal potential reversals when price crosses PSAR.
MFI (Money Flow Index)
Similar to RSI but incorporates volume data. A reading above 80 can suggest overbought conditions, while below 20 may indicate oversold.
CCI (Commodity Channel Index)
Identifies cyclical trends or overbought/oversold levels by comparing current price to an average price over a set timeframe.
Heikin Ashi
A type of candlestick charting that filters out market noise. The script uses a streak-based approach (multiple consecutive bullish or bearish bars) to gauge mini-trends.
TV Screener
A placeholder condition designed to integrate external buy/sell logic (like a TradingView “Buy” or “Sell” rating). Users can override or reference external signals if desired.
Unique Features
Multi-Indicator Entry and Exit
You can selectively enable any subset of 12+ classic indicators, each with customizable parameters and conditions. A position opens only if all enabled entry conditions are met, and it closes only when all enabled exit conditions are satisfied, helping reduce false triggers.
Single-Entry / Single-Exit with Intrabar SL/TP
The script supports a single position at a time. Once a position is open, it monitors intrabar to see if the price hits your stop-loss or take-profit levels before the bar closes, making results more realistic for fast-moving markets.
Time Window Filter
Users may specify a start/end date range during which trades are allowed, making it convenient to focus on specific market cycles for backtesting or live trading.
Condition Table and Statistics
A table at the bottom of the chart lists all active entry/exit indicators. Upon each closed trade, an integrated statistics label displays net profit, total trades, win/loss count, average and median PnL, etc.
Seamless Alerts and Automation
• Configure alerts in TradingView using “Any alert() function call.”
• The script sends JSON alert messages you can route to your own webhook.
• The indicator can be integrated with Skyrexio alert bots to automate execution on major cryptocurrency exchanges.
Optional MA/PSAR Plots
For added visual clarity, optionally plot the chosen moving averages or PSAR on the chart to confirm signals without stacking multiple indicators.
Methodology
Multi-Indicator Entry Logic
When multiple entry indicators are enabled (e.g., RSI + Stochastic + MACD), the script requires all signals to align before generating an entry. Each indicator can be set for crossovers, crossunders, thresholds (above/below), etc. This “AND” logic aims to filter out low-confidence triggers.
Single-Entry Intrabar SL/TP
• One Position At a Time: Once an entry signal triggers, a trade opens at the bar’s close.
• Intrabar Checks: Stop-loss and take-profit levels (if enabled) are monitored on every tick. If either is reached, the position closes immediately, without waiting for the bar to end.
Exit Logic
All Conditions Must Agree: If the trade is still open (SL/TP not triggered), then all enabled exit indicators must confirm a closure before the script exits on the bar’s close.
Time Filter
Optional Trading Window: You can activate a date/time range to constrain entries and exits strictly to that interval.
Justification of Methodology
Indicator Confluence: Combining multiple tools (RSI, MACD, etc.) can reduce noise and false signals.
Intrabar SL/TP: Capturing real-time spikes or dips provides a more precise reflection of typical live trading scenarios.
Single-Entry Model: Straightforward for both manual and automated tracking (especially important in bridging to bots).
Custom Date Range: Helps refine backtesting for specific market conditions or to avoid known irregular data periods.
How to Use
Add the Script to Your Chart
• In TradingView, open Indicators , search for “Multi-indicator Signal Builder” .
• Click to add it to your chart.
Configure Inputs
• Time Filter: Set a start and end date for trades.
• Alerts Messages: Input any JSON or text payload needed by your external service or bot.
• Entry Conditions: Enable and configure any indicators (e.g., RSI, MACD) for a confluence-based entry.
• Close Conditions: Enable exit indicators, along with optional SL (negative %) and TP (positive %) levels.
Set Up Alerts
• In TradingView, select “Create Alert” → Condition = “Any alert() function call” → choose this script.
• Entry Alert: Triggers on the script’s entry signal.
• Close Alert: Triggers on the script’s close signal (or if SL/TP is hit).
• Skyrexio Alert Bots: You can route these alerts via webhook to Skyrexio alert bots to automate order execution on major crypto exchanges (or any other supported broker).
Visual Reference
• A condition table at the bottom summarizes active signals.
• Statistics Label updates automatically as trades are closed, showing PnL stats and distribution metrics.
Backtesting Guidelines
Symbol/Timeframe: Works on multiple assets and timeframes; always do thorough testing.
Realistic Costs: Adjust commissions and potential slippage to match typical exchange conditions.
Risk Management: If using the built-in stop-loss/take-profit, set percentages that reflect your personal risk tolerance.
Longer Test Horizons: Verify performance across diverse market cycles to gauge reliability.
Example of statistic calculation
Test Period: 2023-01-01 to 2025-12-31
Initial Capital: $1,000
Commission: 0.1%, Slippage ~5 ticks
Trade Count: 680 (varies by strategy conditions)
Win rate: 75.44% (varies by strategy conditions)
Net Profit: +90.14% (varies by strategy conditions)
Disclaimer
This indicator is provided strictly for informational and educational purposes.
It does not constitute financial or trading advice.
Past performance never guarantees future results.
Always test thoroughly in demo environments before using real capital.
Enjoy exploring the Multi-Indicator Signal Builder! Experiment with different indicator combinations and adjust parameters to align with your trading preferences, whether you trade manually or link your alerts to external automation services. Happy trading and stay safe!
Quantum Reversal Detector [JOAT]
Quantum Reversal Detector - Multi-Factor Reversal Probability Analysis
Introduction and Purpose
Quantum Reversal Detector is an open-source overlay indicator that combines multiple reversal detection methods into a unified probability-based framework. The core problem this indicator addresses is the unreliability of single-factor reversal signals. A price touching support means nothing without momentum confirmation; an RSI oversold reading means nothing without price structure context.
This indicator solves that by requiring multiple independent factors to align before generating reversal signals, then expressing the result as a probability score rather than a binary signal.
Why These Components Work Together
The indicator combines five analytical approaches, each addressing a different aspect of reversal detection:
1. RSI Extremes - Identifies momentum exhaustion (overbought/oversold)
2. MACD Crossovers - Confirms momentum direction change
3. Support/Resistance Proximity - Ensures price is at a significant level
4. Multi-Depth Momentum - Analyzes momentum across multiple timeframes
5. Statistical Probability - Quantifies reversal likelihood using Bayesian updating
These components are not randomly combined. Each filter catches reversals that others miss:
RSI catches momentum exhaustion but misses structural reversals
MACD catches momentum shifts but lags price action
S/R proximity catches structural levels but ignores momentum
Multi-depth momentum catches divergences across timeframes
Probability scoring combines all factors into actionable confidence levels
How the Detection System Works
Step 1: Pattern Detection
The indicator first identifies potential reversal conditions:
// Check if price is at support/resistance
float lowestLow = ta.lowest(low, period)
float highestHigh = ta.highest(high, period)
bool atSupport = low <= lowestLow * 1.002
bool atResistance = high >= highestHigh * 0.998
// Check RSI conditions
float rsi = ta.rsi(close, 14)
bool oversold = rsi < 30
bool overbought = rsi > 70
// Check MACD crossover
float macd = ta.ema(close, 12) - ta.ema(close, 26)
float signal = ta.ema(macd, 9)
bool macdBullish = ta.crossover(macd, signal)
bool macdBearish = ta.crossunder(macd, signal)
// Combine for reversal detection
if atSupport and oversold and macdBullish
bullishReversal := true
Step 2: Multi-Depth Momentum Analysis
The indicator calculates momentum across multiple periods to detect divergences:
calculateQuantumMomentum(series float price, simple int period, simple int depth) =>
float totalMomentum = 0.0
for i = 0 to depth - 1
int currentPeriod = period * (i + 1)
float momentum = ta.roc(price, currentPeriod)
totalMomentum += momentum
totalMomentum / depth
This creates a composite momentum reading that smooths out noise while preserving genuine momentum shifts.
Step 3: Bayesian Probability Calculation
The indicator uses Bayesian updating to calculate reversal probability:
bayesianProbability(series float priorProb, series float likelihood, series float evidence) =>
float posterior = evidence > 0 ? (likelihood * priorProb) / evidence : priorProb
math.min(math.max(posterior, 0.0), 1.0)
The prior probability starts at 50% and updates based on:
RSI extreme readings increase likelihood
MACD crossovers increase likelihood
S/R proximity increases likelihood
Momentum divergence increases likelihood
Step 4: Confidence Intervals
Using Monte Carlo simulation concepts, the indicator estimates price distribution:
monteCarloSimulation(series float price, series float volatility, simple int iterations) =>
float sumPrice = 0.0
float sumSqDiff = 0.0
for i = 0 to iterations - 1
float randomFactor = (i % 10 - 5) / 10.0
float simulatedPrice = price + volatility * randomFactor
sumPrice += simulatedPrice
float avgPrice = sumPrice / iterations
// Calculate standard deviation for confidence intervals
This provides 95% and 99% confidence bands around the current price.
Signal Classification
Signals are classified by confirmation level:
Confirmed Reversal : Pattern detected for N consecutive bars (default 3)
High Probability : Confirmed + Bayesian probability > 70%
Ultra High Probability : High probability + PDF above average
Dashboard Information
The dashboard displays:
Bayesian Probability - Updated reversal probability (0-100%)
Quantum Momentum - Multi-depth momentum average
RSI - Current RSI value with overbought/oversold status
Volatility - Current ATR as percentage of price
Reversal Signal - BULLISH, BEARISH, or NONE
Divergence - Momentum divergence detection
MACD - Current MACD histogram value
S/R Zone - AT SUPPORT, AT RESISTANCE, or NEUTRAL
95% Confidence - Price range with 95% probability
Bull/Bear Targets - ATR-based reversal targets
Visual Elements
Quantum Bands - ATR-based upper and lower channels
Probability Field - Circle layers showing probability distribution
Confidence Bands - 95% and 99% confidence interval circles
Reversal Labels - REV markers at confirmed reversals
High Probability Markers - Star diamonds at high probability setups
Reversal Zones - Boxes around confirmed reversal areas
Divergence Markers - Triangles at momentum divergences
How to Use This Indicator
For Reversal Trading:
1. Wait for Bayesian Probability to exceed 70%
2. Confirm price is at S/R zone (dashboard shows AT SUPPORT or AT RESISTANCE)
3. Check that RSI is in extreme territory (oversold for longs, overbought for shorts)
4. Enter when REV label appears with high probability marker
For Risk Management:
1. Use the 95% confidence band as a stop-loss reference
2. Use Bull/Bear Targets for take-profit levels
3. Higher probability readings warrant larger position sizes
For Filtering False Signals:
1. Increase Confirmation Bars to require more consecutive signals
2. Only trade when probability exceeds 70%
3. Require divergence confirmation for highest conviction
Input Parameters
Reversal Period (21) - Lookback for S/R and momentum calculations
Quantum Depth (5) - Number of momentum layers for multi-depth analysis
Confirmation Bars (3) - Consecutive bars required for confirmation
Detection Sensitivity (1.2) - Band width and target multiplier
Bayesian Probability (true) - Enable probability calculation
Monte Carlo Simulation (true) - Enable confidence interval calculation
Normal Distribution (true) - Enable PDF calculation
Confidence Intervals (true) - Enable confidence bands
Timeframe Recommendations
1H-4H: Best for swing trading reversals
Daily: Fewer but more significant reversal signals
15m-30m: More signals, requires higher probability threshold
Limitations
Statistical concepts are simplified implementations for Pine Script
Monte Carlo uses deterministic pseudo-random factors, not true randomness
Bayesian probability uses simplified prior/likelihood model
Reversal detection does not guarantee actual reversals will occur
Confirmation bars add lag to signal generation
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each component works.
This indicator does not constitute financial advice. Reversal detection is probabilistic, not predictive. The probability scores represent statistical likelihood based on historical patterns, not guaranteed outcomes. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses.
- Made with passion by officialjackofalltrades
Adaptive Bull Ratio Strategy█ Overview: Why This Strategy
Most option strategies fall into two traps:
They are too rigid: A "Call Ratio Spread" works great in slow markets but gets destroyed if the market rallies hard.
They are too simple: A simple "Buy Call" suffers from time decay (Theta) if the market chops sideways.
The Adaptive Bull Ratio Strategy solves both . It is a living strategy that "shifts gears" based on price action.
It is called "Adaptive" because it morphs its structure three times during a trade. It starts conservative to harvest Time Decay, but if the market explodes upwards, it "uncaps" itself to ride the trend aggressively.
█ The Entry Philosophy: Why Supertrend?
The default setting uses the Supertrend indicator as the trigger. This is intentional:
Volatility Awareness: Supertrend adapts to market noise using ATR. In high volatility, bands widen to prevent false entries.
Trend Confirmation: Since Phase 1 involves selling options, entering "too early" against a falling market is dangerous. Supertrend forces patience, waiting for a confirmed reversal (Close > Trend Line), ensuring the momentum is actually in your favor before you commit capital.
The "Drift" Benefit: This strategy excels in markets that "drift" upwards. Supertrend identifies these trends while filtering out short-term chop.
Flexibility with External Sources:
While Supertrend is the default, the strategy is designed to be flexible. You can enable the 'Enable External Source' option in the settings to plug in any custom indicator (e.g., Moving Averages, Parabolic SAR, or a proprietary trendline).
The Golden Rule for External Sources: The script interprets a Bullish Signal whenever your External Source line is below the Close price (Ext Source < Close).
Compatibility: As long as your custom indicator behaves like a support line in an uptrend (plotting below the candles), it will work seamlessly with this strategy's logic.
█ The "Long Only" Rationale: Avoiding the Volatility Trap
Why not trade this on the short side (Puts) during crashes?
The Volatility Trap (Vega Risk): In Bull markets, Implied Volatility (IV) usually drops, helping your sold options decay faster. In Bear markets, IV explodes (panic). Selling OTM Puts during a crash is dangerous as their value skyrockets, neutralizing gains.
Velocity Risk: Bear markets crash fast ("Elevator Down"). Prices can blow through adjustment levels faster than the strategy can safely roll down, causing slippage.
Structural Skew: OTM Puts are inherently more expensive. Buying expensive ITM Puts and selling expensive OTM Puts shifts the breakeven further away, making V-shape recoveries painful.
█ How It Works & Stands Out
This strategy actively transforms risk profiles based on market movement:
Phase 1: The "Safe" Start (Entry)
Setup: Initiates a Call Ratio Spread (Buy 2 ITM, Sell 4 OTM) + Protective Puts.
Logic: Profits from sideways drift or slow rallies via Time Decay (Theta). The sold options finance the trade.
Phase 2: The "Shift" (Adjustment Level 1)
Trigger: Market moves above Leg 2 (3 OTM Call).
Action: Rolls Up the position. Exits initial legs, enters new higher legs, and adds a Short Put to finance the roll.
Impact: Aggressive. You bet the trend is strong enough to support the added downside risk of the short put.
Phase 3: The "Uncap" (Adjustment Level 2)
Trigger: Market moves above Leg 3 (4 OTM Call).
Action: Exits all Sold Calls.
Impact: Uncaps profit potential. The trade becomes a Net Long position (Long Calls + Short Puts), allowing you to ride a massive rally without a ceiling.
Phase 4: The "Lock-In" (Optional Trail Adjustment)
Trigger: The market goes parabolic (price rises X levels above Leg 3, configurable in settings).
Action (If Enabled):
Call Adj: Exits the Phase 3 calls and buys fresh 1-OTM calls (Rolling Up to lock profits).
Put Adj: Exits all Put legs (Removing downside risk completely).
Impact: Maximum Safety. This phase is about "banking" the windfall from a massive rally and leaving a smaller, risk-free runner to capture any final extension.
█ How to Start: A Quick Setup Guide
Step 1: Map Expiry Dates
Manually input your trading expiry dates in Settings -> Expiry Management.
Format: YYYY-MM-DD (e.g., 2025-12-25). Strict adherence required for DhanHQ.
Step 2: Configure Symbol & Size
Exchange/Symbol: Enter NSE and NIFTY (or your ticker).
Lot Multiplier: Default is 1. Set to 2 to double all quantities (e.g., Buy 2 becomes Buy 4).
Step 3: Understand Visuals
Entry Window (Light Blue): Strategy is scanning for new trades.
Non-Entry Window (Dark Blue): Trading blocked (Day before Expiry & Expiry Day). Only management allowed.
Green Box: Valid Late Entry Zone.
Red Dashed Line: Invalidation Level (if price touches this, no late entry).
Fuchsia Line: Trigger level for Special Trail Adjustments (Phase 4).
IMPORTANT: Broker & Technology Heads-Up:
The alerts generated by this script ({"secret": "...", "alertType": "multi_leg_order"...}) are specifically formatted for the DhanHQ webhook structure.
Dhan Users: Plug-and-play.
Other Brokers: You need middleware (NextLevelBot, Quantiply) to parse the JSON.
█ Risk Disclaimer & Advice
Trading options involves substantial risk.
The Whipsaw Risk: In Phase 2, you are Long Calls and Short Puts. A sharp reversal causes losses on both sides.
Margin: Selling options requires significant margin. Keep a 15-20% cash buffer to handle adjustments instantly.
Testing: This strategy is optimized for NIFTY Weekly Options. Effectiveness on BankNifty or Stocks is untested and may require parameter tuning.
Advice:
Backtest: Use TradingView Replay.
Paper Trade: Run for at least one expiry cycle before live deployment.
Consult: Seek professional financial advice before trading.
Practical Tips for Smooth Execution
For a new trader deploying this system, these operational tips are vital:
Capital Buffer: Do not trade at your limit. Always keep 10-15% free cash in your broker account. Adjustments (specifically Phase 2, where you sell an extra Put) require additional margin instantly. If margin is short, the order fails, and your hedge breaks.
Liquidity Awareness : The script trades "Far Deep OTM" options (Leg 4) to reduce margin. On indices like Nifty/BankNifty, this is fine. On individual stocks, these deep strikes might be illiquid. Check the option chain volume before deploying on stocks.
Trust the Process (but Verify) : While the algo drives, you are the pilot.
Check your API connection every morning.
Ensure the "Entry Window" background color on the chart matches your real-world date.
Verify that your broker executed all legs of a multi-leg order (partial fills are rare but possible).
The "Human" Stop: If major news breaks (e.g., unexpected election results, war announcements), volatility can expand faster than any algo can react. It is acceptable—and smart—to pause the strategy during known "Black Swan" events or earnings releases.
█ Timeframe Selection: The 30-Minute Standard
Critical Requirement: This indicator must be applied to a 30-minute chart.
Why?
Noise Filtering: The Supertrend logic is tuned to capture multi-day trends. Lower timeframes (5m, 15m) are full of "noise"—random fluctuations that look like trend changes but aren't.
Execution Logic (The Hybrid Engine): The script has a built-in "Dual Timeframe" architecture.
Decision Layer (30m): Uses the chart timeframe to decide when to be Bullish or Bearish.
Execution Layer (5m): Internally fetches 5-minute data to manage the how (Adjustments, Late Entries, and precise invalidation).
The Risk of Lower Timeframes: If you run the main chart on 5-minutes, you destroy this hierarchy. You will get too many signals, pay too much brokerage, and the internal logic may behave erratically.
Recommendation: Always keep your TradingView chart interval at 30m. Do not switch to lower timeframes expecting "faster" signals; you will likely just get "false" signals.
█ Testing Scope, Feedback
⚠️ Important Note on Asset Classes:
This strategy logic and the associated strike step calculations have been rigorously tested ONLY on NIFTY Index Options with Weekly Expiry.
BankNifty / Sensex / FinNifty: The volatility characteristics (ATR) and strike intervals of these instruments differ significantly from NIFTY. The effectiveness of this strategy on these other scripts has not been verified and may require different parameter tuning (e.g., strike_step or ATR Length).
Stocks: Individual stock options often lack the liquidity required for the "Deep OTM" legs, leading to potential execution failures.
We encourage traders to backtest this logic on other indices and share their findings! If you find a robust parameter set for BankNifty or observe unique behaviors on other scripts, please let us know in the comments below so we can improve the algorithm for everyone. Your feedback is appriciated.
Max Pain Options [QuantLabs] v5 (Balanced)Institutional Grade Options Analysis: Max Pain, Gamma & Pin Risk
For years, TradingView users have been flying blind without access to Options Chain data. QuantLabs: Max Pain & Gamma Exposure changes that. This is not just a support/resistance indicator—it is a sophisticated, algorithmic model that reverse-engineers the incentives of Market Makers using synthetic Black-Scholes logic.
This tool visualizes the "invisible hand" of the market: the hedging requirements of large dealers who are forced to buy or sell to keep their books neutral.
CORE FEATURES:
🔴 Max Pain Gravity Model The bright red line represents the "Max Pain" strike—the price level where the maximum amount of Options Open Interest (Calls + Puts) expires worthless.
Theory: As OpEx (Expiration) approaches, Market Makers maximize profits by pinning the price to this level.
Strategy: Use this as a mean-reversion target. If price is far away, look for a snap-back to the red line.
🟣 Gamma Exposure Profiles (The Purple Lines) These neon histograms show you the estimated "Gamma Walls."
Long Gamma: Dealers trade against the trend (stabilizing price).
Short Gamma: Dealers trade with the trend (accelerating volatility).
Visual: The larger the purple bar, the harder it will be for price to break through that level.
📦 Algorithmic "Pin Risk" Zones The dashed red box highlights the "Kill Zone." When price enters this area near expiration, volatility often dies as dealers pin the asset to kill retail premiums.
Warning: Do not expect breakouts while inside the Pin Zone.
📊 Institutional HUD A clean, non-intrusive dashboard provides real-time Greeks and risk analysis:
Pin Risk: High/Medium/Low probability of a pinned close.
Exp Mode: Detects if the market is in "Short Gamma" (Squeeze territory) or "Long Gamma" (Chop territory).
HOW IT WORKS (The Math): Since live options data is not available via Pine Script, this engine uses a proprietary Synthetic OI Distribution Model. It inputs Volume, Volatility (IV), and Time-to-Expiry into a modified Black-Scholes equation to probability-map where the heavy open interest likely sits.
SETTINGS & CUSTOMIZATION:
Responsiveness: Tuned for the "Goldilocks Zone" (Spread: 12, Decay: 22) to catch local liquidity walls without over-fitting.
Visuals: Designed for Dark Mode. High-contrast Neon aesthetics for maximum readability.
Selected Days Indicator V3-TrDoes the stock drop every Wednesday? Do March months always move similarly? Does the 1st week of the month behave differently?
Do you ever say "it always makes this move in these months"? Don't you want to see more clearly whether it actually makes this move or not? Don't you want to see and test periodically repeating price patterns?
Hisse her Çarşamba düşüyor mu? Mart ayları hep benzer mi hareket ediyor? Ayın 1. haftası farklı mı davranıyor?
Bazen "bu aylarda hep bu hareketi yapıyor" dediğiniz oluyor mu? Gerçekten de bu hareketi yapıp yapmadığını daha net görmek istemez misiniz? Periyodik tekrarlayan fiyat kalıplarını görmek ve test etmek istemiyor musunuz?
1. Problem
Some stocks or crypto assets exhibit systematic behaviors on certain days, weeks, or months. But it's hard to see - everything is mixed together on the chart. This indicator isolates the days/weeks/months you want and shows only them. Hides everything else.
2. How It Works
Three-layer filter: Day (Monday, Tuesday...), Week (1st, 2nd, 3rd week of the month), Month (January, February...). Select what you want, let the rest disappear. Example: Show only Thursdays of March-June-September. Or compare every 1st week of the month. View as candlestick, line, or column chart.
3. What's It Good For?
Test "end-of-month effect". Find "day-of-the-week anomaly". Analyze crypto volatility by days. See seasonality in commodities. Discover patterns specific to your own strategy. Past data doesn't guarantee the future but provides statistical advantage.
Volatility Targeting: Single Asset [BackQuant]Volatility Targeting: Single Asset
An educational example that demonstrates how volatility targeting can scale exposure up or down on one symbol, then applies a simple EMA cross for long or short direction and a higher timeframe style regime filter to gate risk. It builds a synthetic equity curve and compares it to buy and hold and a benchmark.
Important disclaimer
This script is a concept and education example only . It is not a complete trading system and it is not meant for live execution. It does not model many real world constraints, and its equity curve is only a simplified simulation. If you want to trade any idea like this, you need a proper strategy() implementation, realistic execution assumptions, and robust backtesting with out of sample validation.
Single asset vs the full portfolio concept
This indicator is the single asset, long short version of the broader volatility targeted momentum portfolio concept. The original multi asset concept and full portfolio implementation is here:
That portfolio script is about allocating across multiple assets with a portfolio view. This script is intentionally simpler and focuses on one symbol so you can clearly see how volatility targeting behaves, how the scaling interacts with trend direction, and what an equity curve comparison looks like.
What this indicator is trying to demonstrate
Volatility targeting is a risk scaling framework. The core idea is simple:
If realized volatility is low relative to a target, you can scale position size up so the strategy behaves like it has a stable risk budget.
If realized volatility is high relative to a target, you scale down to avoid getting blown around by the market.
Instead of always being 1x long or 1x short, exposure becomes dynamic. This is often used in risk parity style systems, trend following overlays, and volatility controlled products.
This script combines that risk scaling with a simple trend direction model:
Fast and slow EMA cross determines whether the strategy is long or short.
A second, longer EMA cross acts as a regime filter that decides whether the system is ACTIVE or effectively in CASH.
An equity curve is built from the scaled returns so you can visualize how the framework behaves across regimes.
How the logic works step by step
1) Returns and simple momentum
The script uses log returns for the base return stream:
ret = log(price / price )
It also computes a simple momentum value:
mom = price / price - 1
In this version, momentum is mainly informational since the directional signal is the EMA cross. The lookback input is shared with volatility estimation to keep the concept compact.
2) Realized volatility estimation
Realized volatility is estimated as the standard deviation of returns over the lookback window, then annualized:
vol = stdev(ret, lookback) * sqrt(tradingdays)
The Trading Days/Year input controls annualization:
252 is typical for traditional markets.
365 is typical for crypto since it trades daily.
3) Volatility targeting multiplier
Once realized vol is estimated, the script computes a scaling factor that tries to push realized volatility toward the target:
volMult = targetVol / vol
This is then clamped into a reasonable range:
Minimum 0.1 so exposure never goes to zero just because vol spikes.
Maximum 5.0 so exposure is not allowed to lever infinitely during ultra low volatility periods.
This clamp is one of the most important “sanity rails” in any volatility targeted system. Without it, very low volatility regimes can create unrealistic leverage.
4) Scaled return stream
The per bar return used for the equity curve is the raw return multiplied by the volatility multiplier:
sr = ret * volMult
Think of this as the return you would have earned if you scaled exposure to match the volatility budget.
5) Long short direction via EMA cross
Direction is determined by a fast and slow EMA cross on price:
If fast EMA is above slow EMA, direction is long.
If fast EMA is below slow EMA, direction is short.
This produces dir as either +1 or -1. The scaled return stream is then signed by direction:
avgRet = dir * sr
So the strategy return is volatility targeted and directionally flipped depending on trend.
6) Regime filter: ACTIVE vs CASH
A second EMA pair acts as a top level regime filter:
If fast regime EMA is above slow regime EMA, the system is ACTIVE.
If fast regime EMA is below slow regime EMA, the system is considered CASH, meaning it does not compound equity.
This is designed to reduce participation in long bear phases or low quality environments, depending on how you set the regime lengths. By default it is a classic 50 and 200 EMA cross structure.
Important detail, the script applies regime_filter when compounding equity, meaning it uses the prior bar regime state to avoid ambiguous same bar updates.
7) Equity curve construction
The script builds a synthetic equity curve starting from Initial Capital after Start Date . Each bar:
If regime was ACTIVE on the previous bar, equity compounds by (1 + netRet).
If regime was CASH, equity stays flat.
Fees are modeled very simply as a per bar penalty on returns:
netRet = avgRet - (fee_rate * avgRet)
This is not realistic execution modeling, it is just a simple turnover penalty knob to show how friction can reduce compounded performance. Real backtesting should model trade based costs, spreads, funding, and slippage.
Benchmark and buy and hold comparison
The script pulls a benchmark symbol via request.security and builds a buy and hold equity curve starting from the same date and initial capital. The buy and hold curve is based on benchmark price appreciation, not the strategy’s asset price, so you can compare:
Strategy equity on the chart symbol.
Buy and hold equity for the selected benchmark instrument.
By default the benchmark is TVC:SPX, but you can set it to anything, for crypto you might set it to BTC, or a sector index, or a dominance proxy depending on your study.
What it plots
If enabled, the indicator plots:
Strategy Equity as a line, colored by recent direction of equity change, using Positive Equity Color and Negative Equity Color .
Buy and Hold Equity for the chosen benchmark as a line.
Optional labels that tag each curve on the right side of the chart.
This makes it easy to visually see when volatility targeting and regime gating change the shape of the equity curve relative to a simple passive hold.
Metrics table explained
If Show Metrics Table is enabled, a table is built and populated with common performance statistics based on the simulated daily returns of the strategy equity curve after the start date. These include:
Net Profit (%) total return relative to initial capital.
Max DD (%) maximum drawdown computed from equity peaks, stored over time.
Win Rate percent of positive return bars.
Annual Mean Returns (% p/y) mean daily return annualized.
Annual Stdev Returns (% p/y) volatility of daily returns annualized.
Variance of annualized returns.
Sortino Ratio annualized return divided by downside deviation, using negative return stdev.
Sharpe Ratio risk adjusted return using the risk free rate input.
Omega Ratio positive return sum divided by negative return sum.
Gain to Pain total return sum divided by absolute loss sum.
CAGR (% p/y) compounded annual growth rate based on time since start date.
Portfolio Alpha (% p/y) alpha versus benchmark using beta and the benchmark mean.
Portfolio Beta covariance of strategy returns with benchmark returns divided by benchmark variance.
Skewness of Returns actually the script computes a conditional value based on the lower 5 percent tail of returns, so it behaves more like a simple CVaR style tail loss estimate than classic skewness.
Important note, these are calculated from the synthetic equity stream in an indicator context. They are useful for concept exploration, but they are not a substitute for professional backtesting where trade timing, fills, funding, and leverage constraints are accurately represented.
How to interpret the system conceptually
Vol targeting effect
When volatility rises, volMult falls, so the strategy de risks and the equity curve typically becomes smoother. When volatility compresses, volMult rises, so the system takes more exposure and tries to maintain a stable risk budget.
This is why volatility targeting is often used as a “risk equalizer”, it can reduce the “biggest drawdowns happen only because vol expanded” problem, at the cost of potentially under participating in explosive upside if volatility rises during a trend.
Long short directional effect
Because direction is an EMA cross:
In strong trends, the direction stays stable and the scaled return stream compounds in that trend direction.
In choppy ranges, the EMA cross can flip and create whipsaws, which is where fees and regime filtering matter most.
Regime filter effect
The 50 and 200 style filter tries to:
Keep the system active in sustained up regimes.
Reduce exposure during long down regimes or extended weakness.
It will always be late at turning points, by design. It is a slow filter meant to reduce deep participation, not to catch bottoms.
Common applications
This script is mainly for understanding and research, but conceptually, volatility targeting overlays are used for:
Risk budgeting normalize risk so your exposure is not accidentally huge in high vol regimes.
System comparison see how a simple trend model behaves with and without vol scaling.
Parameter exploration test how target volatility, lookback length, and regime lengths change the shape of equity and drawdowns.
Framework building as a reference blueprint before implementing a proper strategy() version with trade based execution logic.
Tuning guidance
Lookback lower values react faster to vol shifts but can create unstable scaling, higher values smooth scaling but react slower to regime changes.
Target volatility higher targets increase exposure and drawdown potential, lower targets reduce exposure and usually lower drawdowns, but can under perform in strong trends.
Signal EMAs tighter EMAs increase trade frequency, wider EMAs reduce churn but react slower.
Regime EMAs slower regime filters reduce false toggles but will miss early trend transitions.
Fees if you crank this up you will see how sensitive higher turnover parameter sets are to friction.
Final note
This is a compact educational demonstration of a volatility targeted, long short single asset framework with a regime gate and a synthetic equity curve. If you want a production ready implementation, the correct next step is to convert this concept into a strategy() script, add realistic execution and cost modeling, test across multiple timeframes and market regimes, and validate out of sample before making any decision based on the results.
Alphabet Long Trigger (Björn)Alphabet Trigger Dezember 2025:
Kurs 267–269 €
grüne Kerze mit höherem Tief
Volumen-Lebenszeichen
Nasdaq nicht im Abwärtsmodus
Alphabet Momentum Pullback Strategy — Brief Description
This strategy targets high-quality pullbacks within a confirmed uptrend and enters a long position only when price, structure, volume, and market context align.
A trade is triggered when:
Price enters the buy zone between €267–€269, signaling a controlled pullback.
The chart forms the first green candle with a higher low, indicating buyers are returning.
Volume shows a positive uptick (at least above the recent average), confirming real demand.
The Nasdaq is not falling, ensuring the broader tech market is stable and not in risk-off mode.
The strategy avoids entries triggered solely by price and waits for multi-factor confirmation, reducing false breakouts and momentum traps. It is designed for disciplined swing traders who prioritize trend alignment, volume confirmation, and market context before entering a position.
OBV + WaveTrend Volume Scalper [GratefulFutures]This script is a combination script of three different strategies that provides buy and sell signals based on the change of volume with momentum confirmations.
Sources used:
This script relies on the outstanding scripts of the great script writer LazyBear: LazyBear
The following scripts were used in this publication:
1. A modified "On-Balance Volume Oscillator" modified from LazyBear's original script:
2. Wavetrend Oscillator with crosses, Author: LazyBear
3. Squeeze Momentum Oscillator, Author: LazyBear
This script functions based on the following criteria being true:
1. On balance volume oscillator turning from negative to positive (buy) or positive to negative (sell)
2. Squeeze Momentum value is increasing (buy) or decreasing (sell)
3. Wavetrend 1 (wt1) is greater than wavetrend 2 (wt2) (buy)/ Wavetrend 1 (wt1) is less than wavetrend 2 (wt2) (sell)
By combining these factors the indicator is able to signal exactly when net buying turns to net selling (OBV) and when this change is most advantageous to continue based on the momentum and price action of the underlying asset (SQMOMO and Wavetrend).
This allows you to pair volume and price action for a powerful tool to identify where price will reverse or continue providing exceptional entries for short term trades, especially when combined with other aspects such as support and resistance, or volume profile.
How to use:
Simply adjust the settings to your preference and read the given signals as generated.
Settings
There are multiple ways to tune the signals generated. It is set standard for my preferred use on a 1 minute chart.
OBV Oscillator Settings
The first 4 dropdowns in the Inputs section tune the On Balance Volume Oscillator (OBVO) portion of the indicator. You can choose if you want it to calculate based on close, open, high, low, or other value.
The most impactful in the entire settings is going to be the length and smoothing of the OBVO EMA. Making this number lower increasing the sensitivity to changes in volume, making the signals come quicker but is more susceptible to quick fluctuations. A value of between (5-20) is reasonable for the OBVO EMA length. There is a separate smoothing factor titled OBV Smoothing Length and below that, OBV Smoothing Type , a value of (2) is standard with "SMA" for smoothing type with a value of between 2-10 being reasonable. You may also play with these values to see what you like for your trading style.
Wavetrend Settings
The next 3 options are to modify the wavetrend portion of the indicator. I do not modify these from standard, and feel that they work appropriately on all time frames at the following values: n1 length (10), n2 length (20), Wavetrend Signal SMA length (4)
Squeeze Momentum Settings
The following 5 options through the end modify the Squeeze momentum portion of the indicator. The only one that modifies the signals generated is the KC Length , Making this number lower increasing the sensitivity to changes in price action, making the signals come quicker but is more susceptible to quick fluctuations. A value of between (18-25) is reasonable for KC Length .
Style Setting
You may select if you want to see the buy and sell signals. The following 5 options Raw OBV Osc through Squeeze Momentum allow you to see where each specific requirement was met, posted as a vertical line, but for live use it is recommended to turn all of these vertical lines off and only use the buy and sell signals.
Time Frames:
While this script is most effective on shorter time frames (1 minute for scalping and daytrading) it is also viable to use it on longer timeframes, due to the nature of its components being independent of time frame.
Examples of use - (Green and red vertical lines are for visualization purpose and are not part of the script)
SPY 1 Minute (Factory Settings):
SPX 15 minutes (Factory Settings):
Considerations
This script is meant primarily for short term trading, trades on the basis of seconds to minutes primarily. While they can be a good indication of volume lining up with momentum, it is always wise to use them in combination with other factors such as support, resistance, market structure, volume levels, or the many other techniques out there...
As Always... Happy Trading.
-Not_A_Mad_Scientist (GreatfulFutures Trade University)
Smart Money Setup 08 [TradingFinder] Binary Options Gold Scalper🔵 Introduction
In the Smart Money methodology, the market is understood as a structure driven by liquidity flow. This structure forms through the movement of large orders, the accumulation of liquidity, and the reactions that occur around key price zones. The logic of Smart Money is based on the idea that price movement is not random and usually evolves with the intention of collecting liquidity and creating price inefficiencies known as imbalances.
Within this framework, several important stages including the liquidity sweep, the formation of a point of interest, the appearance of an imbalance and the transition of market structure play major roles and collectively define the broader direction of price.
In many bullish scenarios, the market begins by sweeping sell side liquidity and targeting important lows in order to collect the liquidity resting below them. This liquidity collection often becomes the starting point for creating a point of interest which usually marks the area where Smart Money begins to enter the market.
After price moves away from this point, it breaks a structural high and forms a change of character. This shift marks a transition in the balance of power between buyers and sellers and is considered the first clear signal that the market structure is changing.
After the change of character, new institutional order flow often creates a strong and rapid movement that leaves behind an imbalance. This imbalance is one of the most important elements in Smart Money analysis because price tends to return to this area in order to complete structure and restore balance.
The return into the imbalance becomes meaningful when it occurs together with the liquidity sweep, the presence of a validated point of interest and a confirmed structural transition. These conditions frequently mark the beginning of powerful movements within the Smart Money cycle.
Understanding the sequence of liquidity, point of interest, imbalance, change of character and market structure builds the foundation of Smart Money analysis and provides a clear view of the true direction of institutional strength.
Bullish Setup :
Bearish Setup :
🔵 How to Use
To use this framework effectively, the trader must analyze the market through the principles of Smart Money and observe how liquidity drives price. A trade becomes valid only when several essential components appear together in a clear and consistent order.
These components include the liquidity sweep, the formation of a point of interest, the confirmation of a change of character, the transition of market structure and the return of price into an imbalance. The method is built on the understanding that the market first collects liquidity, then shifts order flow and finally provides an entry opportunity inside an inefficient area or inside a point of interest.
For this reason, the trader must follow the path of liquidity from the moment the sweep occurs, through the point of interest and the change of character and finally into the return of price toward the imbalance. When applied correctly, this approach creates entries that are more precise, more structural and more aligned with the real behavior of the market rather than with superficial signals.
🟣 Long Position
A bullish setup in Smart Money structure begins with a liquidity sweep on the sell side. The market first targets the areas where sell side liquidity is located and collects the stops and resting liquidity under previous lows. This collection is the condition that Smart Money requires to begin creating a new order flow. After this liquidity has been taken, a point of interest forms which is usually the last bearish candle or the effective demand zone that initiated the upward movement.
Price then moves away from the point of interest and breaks a structural high which creates a change of character. This event confirms that the market structure has moved from a bearish state to a bullish one and that buying pressure has taken control of the order flow. Following this shift, a strong upward movement often occurs and creates an imbalance between candles. This imbalance reflects the entrance of strong Smart Money orders and is seen as an important confirmation of bullish strength.
When price returns to this imbalance after the displacement, the market enters a phase where Smart Money aims to complete the corrective movement and continue the upward direction. The reaction inside the imbalance when combined with the liquidity sweep, the confirmed point of interest and the change of character completes the bullish setup and forms a structure that often leads to a continuation of the bullish trend.
🟣 Short Position
A bearish setup follows the same Smart Money logic but in the opposite direction. The market begins by collecting buy side liquidity and targets the highs where buy side liquidity and resting stops are located. This liquidity sweep on the buy side becomes the starting phase for Smart Money to initiate a downward order flow. After the liquidity is collected, a bearish point of interest forms which is usually the last bullish candle or the supply zone that created the initial drop.
Price then moves away from this point and breaks the first structural low. This creates a change of character to the downside which confirms that the market structure has transitioned from bullish to bearish and that selling pressure has gained control. After this shift, a strong downward displacement appears and leaves behind a bearish imbalance that clearly shows the dominance of sellers.
As price returns to this imbalance and corrects the inefficient movement, the bearish setup becomes complete as long as the market structure remains bearish. The combination of the buy side liquidity sweep, the bearish point of interest, the change of character, the imbalance and the corrective return creates the ideal structure that Smart Money uses to continue the downward movement and develop a reliable selling opportunity.
🔵 Settings
🟣 Logic Settings
Pivot Period : Defines how many bars are analyzed to identify swing highs and lows. Higher values detect larger, slower structures, while lower values respond to faster patterns. The default value of 5 offers a balanced sensitivity.
🟣 Alert Settings
Alert : Enables alerts for SMS08.
Message Frequency : Determines the frequency of alerts. Options include 'All' (every function call), 'Once Per Bar' (first call within the bar), and 'Once Per Bar Close' (final script execution of the real-time bar). Default is 'Once per Bar'.
Show Alert Time by Time Zone : Configures the time zone for alert messages. Default is 'UTC'.
🔵 Conclusion
The Smart Money approach demonstrates that price movement is not random or based on surface level patterns. Instead, it develops through a clear cycle of liquidity collection, structural transition and corrective movement toward key price zones. By recognizing events such as the liquidity sweep, the formation of the point of interest, the change of character and the return into the imbalance, the trader gains the ability to understand order flow more accurately and identify the true direction of market structure.
Both bullish and bearish setups show that the alignment of these elements creates a transparent view of institutional behavior and reveals the source of strong movements in the market. When the trader correctly identifies this sequence, entry points become more reliable and more aligned with liquidity flow. The combination of liquidity, structure and imbalance provides a consistent framework that removes guesswork and guides decisions through the real logic of the market.
APEX TREND: Macro & Hard Stop SystemAPEX TREND: Macro & Hard Stop System
The APEX TREND System is a composite trend-following strategy engineered to solve the "Whipsaw" problem inherent in standard breakout systems. It orchestrates four distinct technical theories—Macro Trend Filtering, Volatility Squeeze, Momentum, and Volatility Stop-Loss—into a single, hierarchical decision-making engine.
This script is not merely a collection of indicators; it is a rules-based trading system designed for Swing Traders (Day/Week timeframes) who aim to capture major trend extensions while strictly managing downside risk through a "Hard Stop" mechanism.
🧠 Underlying Concepts & Originality
Many trend indicators fail because they treat all price movements equally. The APEX TREND differentiates itself by applying an "Institutional Filter" logic derived from classic Dow Theory and Modern Volatility Analysis.
1. The Macro Hard Stop (The 200 EMA Logic)
Origin: Based on the institutional mandate that “Nothing good happens below the 200-day moving average.”
Function: Unlike standard super trends that flip constantly in sideways markets, this system integrates a 200-period Exponential Moving Average (EMA) as a non-negotiable "Hard Stop."
Synergy: This acts as the primary gatekeeper. Even if the volatility engine signals a "Buy," the system suppresses the signal if the price is below the Macro Baseline, effectively filtering out counter-trend traps.
2. The Volatility Engine (Squeeze Theory)
Origin: Derived from John Carter’s TTM Squeeze concept.
Function: The script identifies periods where Bollinger Bands (Standard Deviation) contract inside Keltner Channels (ATR). This indicates a period of potential energy build-up.
Synergy: The system only triggers an entry when this energy is released (Breakout) AND coincides with Linear Regression Momentum, ensuring the breakout is genuine.
3. Anti-Chop Filter (ADX Integration)
Origin: J. Welles Wilder’s Directional Movement Theory.
Function: A common failure point for trend systems is low-volatility chop. This script utilizes the Average Directional Index (ADX).
Synergy: If the ADX is below the threshold (Default: 20), the market is deemed "Choppy." The script visually represents this by painting candles GRAY, signaling a "No-Trade Zone" regardless of price action.
4. The "Run Trend" Stop Loss (Factor 4.0 ATR)
Origin: Adapted from the Turtle Trading rules regarding volatility-based stops.
Function: Standard Trailing Stops (usually Factor 3.0) are too tight for crypto or volatile equities on daily timeframes.
Optimization: This system employs a wider ATR Multiplier of 4.0. This allows the asset to fluctuate naturally within a trend without triggering a premature exit, maximizing the "Run Trend" potential.
🛠 How It Works (The Algorithm)
The script processes data in a specific order to generate a signal:
Check Macro Trend: Is Price > EMA 200? (If No, Longs are disabled).
Check Volatility: Is ADX > 20? (If No, all signals are disabled).
Check Volume: Is Current Volume > 1.2x Average Volume? (Confirmation of institutional participation).
Trigger: Has a Volatility Breakout occurred in the direction of the Macro Trend?
Execution: If ALL above are true -> Generate Signal.
🎯 Strategy Guide
1. Long Setup (Bullish)
Signal: Look for the Green "APEX LONG" Label.
Condition: The price must be ABOVE the White Line (EMA 200).
Execution: Enter at the close of the signal candle.
Stop Loss: Initial stop at the Green Trailing Line.
2. Short Setup (Bearish)
Signal: Look for the Red "APEX SHORT" Label.
Condition: The price must be BELOW the White Line (EMA 200).
Execution: Enter at the close of the signal candle.
Stop Loss: Initial stop at the Red Trailing Line.
3. Exit Rules (Crucial)
This system employs a Dual-Exit Mechanism:
Soft Exit (Profit Taking): Close the position if the price crosses the Trailing Stop Line (Green/Red line). This locks in profits during a trend reversal.
Hard Exit (Emergency): Close the position IMMEDIATELY if the price crosses the White EMA 200 Line against your trade. This prevents holding a position during a major market regime change.
⚙️ Settings
Momentum Engine: Adjust Bollinger Band/Keltner Channel lengths to tune breakout sensitivity.
Apex Filters: Toggle the EMA 200 or ADX filters on/off to adapt to different asset classes.
Risk Management: The ATR Multiplier (Default 4.0) controls the width of the trailing stop. Lower values = Tighter stops (Scalping); Higher values = Looser stops (Swing).
Disclaimer: This script is designed for trend-following on higher timeframes (4H, 1D, 1W). Please backtest on your specific asset before live trading.
Slope Rank ReversalThis tool is designed to solve the fundamental problem of "buying low and selling high" by providing objective entry/exit signals based on momentum extremes and inflection points.
The System employs three core components:
Trend Detection (PSAR): The Parabolic SAR is used as a filter to confirm that a trend reversal or transition is currently underway, isolating actionable trade setups.
Dynamic Momentum Ranking: The indicator continuously measures the slope of the price action. This slope is then ranked against historical data to objectively identify when an asset is in an extreme state (overbought or oversold).
Signal Generation (Inflection Points):
Oversold/Buy: A 🟢 Green X is generated only when the slope ranking indicates the market is steeply negative (oversold), and the slope value begins to tick upwards (the inflection point), signaling potential mean reversion.
Overbought/Sell: A 🔴 Red X is generated only when the slope ranking indicates the market is steeply positive (overbought), and the slope value begins to tick downwards, signaling momentum exhaustion.
The core philosophy is simple: Enter only when the market is exhausted and has started to turn.
Risk-On / Risk-Off Toolkit [SB1] (NQ, RTY, YM) VIXDescription:
The Risk-On / Risk-Off Toolkit is a professional-grade market context indicator designed to help traders quickly identify broad market sentiment shifts and gauge risk appetite. By combining major US equity futures (NQ, RTY, YM) with VIX dynamics, this toolkit provides clear visual signals of “Risk-On” (bullish, lower volatility environment) and “Risk-Off” (bearish, higher volatility environment) conditions. This is ideal for traders using discretionary analysis, swing strategies, intraday scalping, or portfolio positioning decisions.
My Personal Thoughts: Utilize all 3 charts to Identify which is Leading and who is lagging between the 3 (NQ, RTY, YM) Key Features:
Futures Trend Analysis:
Monitors the Nasdaq 100 (NQ), Russell 2000 (RTY), and Dow Jones (YM) futures in real-time.
Determines bullish/bearish bias based on each futures contract’s current close relative to its open.
Identifies when all three indices are moving in sync, highlighting broad market directional alignment.
VIX Confirmation:
Integrates the CBOE Volatility Index (VIX) to gauge market risk sentiment.
Confirms Risk-On conditions when VIX is falling while all three futures are bullish.
Confirms Risk-Off conditions when VIX is rising while all three futures are bearish.
Optional background shading visually highlights Risk-On (green) and Risk-Off (red) conditions for quick, intuitive assessment.
Strong Body Candle Signals:
Detects high conviction candlestick moves where the body represents at least 85% of the total range.
Confirms whether the candle closes near its extreme (top for bullish, bottom for bearish) within 15% of the range.
Plots arrows for strong bullish or bearish candles:
Green triangle-up for bullish strong candles
Red triangle-down for bearish strong candles
Provides a visual cue for intraday or swing traders to confirm trend momentum without cluttering the chart with labels.
Alert System:
Alerts can be set for Risk-On alignment: all monitored futures are bullish and VIX is falling.
Alerts can also be set for Risk-Off alignment: all monitored futures are bearish and VIX is rising.
Ensures traders never miss shifts in broad market sentiment, suitable for both intraday and end-of-day review.
Table Summary:
Provides a top-right summary table of each monitored market and VIX:
Displays Index Name and Current Bias (Bullish/Bearish/Neutral).
Highlights bullish conditions in green and bearish conditions in red.
Includes VIX status as “↓ Falling”, “↑ Rising”, or “Flat”, providing a quick visual reference of volatility trends.
Customizable Visuals:
Control the visibility of strong candle arrows.
Maintains dynamic bar coloring for strong candle moves (green for bullish, red for bearish).
How to Use the Risk-On / Risk-Off Toolkit:
Trend Confirmation: Use the alignment of NQ, RTY, and YM to determine whether the overall market environment is bullish or bearish.
Risk Sentiment Filter: Use VIX confirmation to identify if traders are in a risk-on or risk-off sentiment. This is especially useful for adjusting position sizing, hedging, or timing entries.
Momentum Validation: Strong candle arrows indicate decisive moves, providing additional confirmation for trade entries, breakouts, or trend continuation.
Alerts & Visual Cues: Set alerts to be notified whenever Risk-On or Risk-Off conditions are met, helping you act in real-time.
Quick Reference: Use the summary table for a bird’s-eye view of market alignment across indices and VIX, avoiding the need to track multiple charts simultaneously.
Why This Indicator is Unique:
Combines three major US indices with volatility confirmation to identify true macro market sentiment shifts.
Provides both visual and alert-based signals for actionable insights.
The inclusion of strong candle arrows gives intraday and swing traders a clear, low-latency cue for high-probability moves.
Perfect for multi-timeframe analysis and adaptable to both short-term and long-term strategies.
Indicator Name Justification:
The name “Risk-On / Risk-Off Toolkit ” accurately reflects the core function: identifying broad market risk appetite and sentiment alignment across key indices with volatility confirmation. It communicates instantly that the tool helps traders understand when the market is favoring risk-taking (Risk-On) versus risk-aversion (Risk-Off).
AI Bot Regime Feed (v6) — stableThis indicator generates real-time, structured JSON alerts for external trading bots or automation systems.
It combines multiple technical layers to identify market regimes and high-probability buy/sell events, and sends them to any webhook endpoint (e.g., a FastAPI or Zapier listener).
Volume Profile Auto POC📌 Overview
Volume Profile Auto POC is a trend-following strategy that uses the automatically calculated Point of Control (POC) from the volume profile, combined with ATR zones, to capture reversals and breakouts.
By basing decisions on volume concentration, it dynamically visualizes the price levels most watched by market participants.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
Automatically detect the volume concentration area (POC) to improve entry accuracy
Optimize risk management through ATR-based volatility adjustment
Provide early and consistent signals when trends emerge
✨ Key Features
Automatic POC Detection : Updates the volume profile over a defined lookback window in real time
ATR Zone Integration : Defines a POC ± 0.5 ATR zone to clarify potential reversals/breakouts
Visual Support : Plots the POC line and zones on the chart for intuitive decision-making
📊 Trading Rules
Long Entry:
Price breaks above the POC + 0.5 ATR zone
Volume is above average to support the breakout
Short Entry:
Price breaks below the POC - 0.5 ATR zone
Volume is above average to support the downside move
Exit (or Reverse Position):
Price returns to the POC area
Or touches the ATR band
⚙️ Trading Parameters & Considerations
Indicator Name: Volume Profile Auto POC
Parameters:
Lookback Bars: 50
Bins for Volume Profile: 24
ATR Length: 14
ATR Multiplier: 2.0
🖼 Visual Support
POC line plotted in red
POC ± 0.5 ATR zone displayed as a semi-transparent box
ATR bands plotted in blue for confirmation
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by traditional Volume Profile + ATR analysis,
while adding the improvement of a sliding-window mechanism for automatic POC updates.
Compared with conventional trend-following approaches,
its strength lies in combining both price and volume perspectives for decision-making.
✅ Summary
Volume Profile Auto POC automatically extracts key market levels (POC) and combines them with ATR-based zones,
providing a responsive trend-following method.
It balances clarity with practicality, aiming for both usability and reproducibility.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use proper risk management when applying it.
MomentumScriptThis is Momentum Tracker based on Richard Driehaus' research:
1) 12–1 momentum (return from t-12 months to t-1 month
2) FIP / path efficiency (many small up days > one big gap)
3) Proximity to 52-week high/low
Cnagda Liquidit Trading SystemCnagda Liquidit Trading System helps spot where price is likely to trap traders and reverse, then gives simple, actionable Level to entry, place SL, and take profits with confidence. It blends imbalance zones, trend bias, order blocks, liquidity pools, high-probability fake Signal, and context-aware candle patterns into one clean workflow.
🟩🟥 Imbalance boxes: “Crowd rushed, gaps left”
What it is: Green/red boxes mark fast, one-sided moves where price “skipped” orders—think FVG-like zones that often get revisited.
Why it helps: Price frequently pulls back to “fill” these zones, creating clean retest entries with logical stops.
⏩How to use:
Green box = potential demand retest; Red box = potential supply retest. Enter on pullback into box, not on first impulse. Put stop on far side of box and aim first targets at recent swing points.
↕️ Swing bias (HH/HL vs LH/LL): “Which way is the road?”
What it is: Higher-highs/higher-lows = up-bias; Lower-highs/lower-lows = down-bias. system plots Buy/Sell OB levels aligned with that bias.
Why it helps: Trading with the broader flow reduces “hero trades” against institutions. Bias gives clearer entries and cleaner drawdowns.
⏩How to use:
Up-bias: look for long on Buy OB retests. Down-bias: look for short on Sell OB retests. Wait for a small rejection/engulfing to confirm before triggering.
🧱Order blocks: “Where big players remember”
What it is: last opposite-colored candle before an impulsive move—these zones often hold memory and reaction. system plots these as Buy/Sell OB lines.
Why it helps: Many breakouts pull back to the origin. Good entries often happen on retest, not on the breakout chase.
⏩ How to use:
Let price return into the OB, show wick rejection, and decent volume. Enter with stop beyond OB; define risk-reward before entry.
📊Volume coloring: “How Volume is move?”
What it is: Bar color reflects relative volume; inside bars are black. The dashboard also shows Volume and “Volume vs Prev.”
Why it helps: Patterns without volume often fade; volume validates strength and intent of moves.
⏩ How to use:
Favor entries where imbalance/OB/liquidity-grab coincide with higher volume. If volume is weak, reduce size or skip.
🧲 BSL/SSL liquidity pools: “Fishing for stops”
What it is: Equal highs cluster stops above (BSL); equal lows cluster stops below (SSL). system plots these and highlights the nearest one (“magnet”).
Why it helps: Price often sweeps these pools to trigger stops before reversing. This is a prime trap-reversal location.
⏩ How to use:
Watch nearest BSL/SSL. If price wicks through and closes back inside, anticipate a reversal. Trade reaction, not first poke. When price closes beyond, consider that pool mitigated and move on.
🟢🔴 Advanced liquidity grab: “Catch fakeout”
What it is: Bullish grab = makes a new low beyond a prior low but closes back above it, with a long lower wick, small body, and higher volume. Bearish is mirror. Labeled automatically.
Why it helps: It exposes trap moves (stop hunts) and often precedes true direction.
⏩ How to use:
Best when it aligns with a nearby imbalance/OB and supportive volume. Enter on reversal candle break or on retest. Stop goes beyond sweep wick.
🧠 Smart candlestick patterns (only in right place)
What it is: Engulfing, Hammer, Shooting Star, Hanging Man, Doji (with high volume), Morning/Evening Star, Piercing—but marked “effective” only if context (swing/trend/location) agrees.
Why it helps: same pattern in the wrong place is noise; in the right place, it’s signal.
⏩ How to use:
Location first (BSL/SSL/OB/imbalance), then pattern. Treat pattern as trigger/confirmation—one fresh label shows to keep chart clean.
🧭 Dashboard: “Context in a glance”
⏩ Reversal Level: current swing anchor—expect turns or reactions nearby; great for alerts and planning.
⏩ Volume vs Prev + Volume: Strength meter for signal candle—higher adds conviction.
⏩ Nearest Pool: next “magnet” area—look for sweeps/rejections there.
🧩Step-by-step trading flow (with mindset)
⏩ Set bias: HH/HL = long bias, LH/LL = short bias. Counter-trend only on clean sweeps with strong confirmation.
⏩ Find magnet: Check Nearest Pool (BSL/SSL). Focus attention there; it saves screen time.
⏩ Wait for event: Look for a sweep/grab label, or sharp rejection at pool/OB/imbalance. Avoid FOMO.
⏩ Add confluence: Stack 2–3 of these—imbalance box, OB, contextual pattern, supportive volume.
⏩Plan entry: Bullish: trigger above reversal candle high or take retest of FVG/OB. Stop below sweep wick/zone. Target at least 1:1.5–1:2.
Bearish: mirror above.
⏩Manage smartly: Take partials, move to breakeven or trail thoughtfully. Don’t drag stops inside zone out of emotion.
🎛️ Parameter tuning (to reduce human error)
⏩ swingLen: Smaller = faster but noisier; larger = cleaner but slower. Backtest first, then go live.
⏩ Tolerance (ATR or percent): ATR tolerance adapts to volatility (good for fast markets and lower TFs). Start around 0.15–0.30. In calm markets, try percent 0.05–0.15%.
⏩ minBarsGap: Start with 3–5 so equal highs/lows are truly equal—reduces false pools.
❌Common mistakes → ✅ Better habits
⏩Chasing every breakout → Wait for sweep/rejection, then confirm.
⏩Ignoring volume → Validate strength; cut size or skip on weak volume.
⏩Losing history of pools → If reviewing/backtesting, keep mitigated pools visible (dashed/faded).
⏩Over-tight tolerance/too small swingLen → Increases false signals; backtest to find balance.
📝 checklist (before entry)
⏩ Is there a nearby BSL/SSL and did a sweep/grab happen there?
⏩ Is there a close imbalance/OB that price can retest?
⏩ Do we have an effective pattern plus supportive volume?
⏩Is the stop beyond the wick/zone and RR ≥ 1:1.5?
•?((¯°·._.• 🎀 𝐻𝒶𝓅𝓅𝓎 𝒯𝓇𝒶𝒹𝒾𝓃𝑔 🎀 •._.·°¯((?•
TrendBreaks & MA Divergence v1.3 — couleurs perso (panel)clean and easy predictive mouvements and swing stratagy
Straddle Charts - Live (Enhanced)Track options straddles with ease using the Straddle Charts - Live (Enhanced) indicator! Originally inspired by @mudraminer, this Pine Script v5 tool visualizes live call, put, and straddle prices for instruments like BANKNIFTY. Plotting call (green), put (red), and straddle (black) prices in a separate pane, it offers real-time insights for straddle strategy traders.
Key Features:
Live Data: Fetches 1-minute (customizable) option prices with error handling for invalid symbols.
Price Table: Displays call, put, straddle prices, and percentage change in a top-left table.
Volatility Alerts: Highlights bars with straddle price changes above a user-defined threshold (default 5%) with a yellow background and concise % labels.
Robust Design: Prevents plot errors with na checks and provides clear error messages.
How to Use: Input your call/put option symbols (e.g., NSE:NIFTY250814C24700), set the timeframe, and adjust the volatility threshold. Monitor straddle costs and volatility for informed trading decisions.
Perfect for options traders seeking a simple, reliable tool to track straddle performance. Check it out and share your feedback!
Hassi XAUUSD STRATEGY BOTGold (XAUUSD) 15m trend+momentum based signals with EMA(9/21/200), RSI, custom ADX, ATR-based SL/TP & alerts
Works on XAUUSD 15m.
Entry: EMA9/21 cross + price relative to EMA200 + RSI filter + custom ADX trend strength.
Risk: default SL=1.5×ATR, TP=2×ATR (editable).
Notes: No financial advice. Backtest before live use. Avoid high-impact news whipsaws.
