Liquidity Hunter Pro v11.9 โ TQI EditionLiquidity Hunter Pro v12 is built for intraday traders who want structure, clarity, and precision without unnecessary clutter. The tool blends market structure, momentum, trend alignment, volatility regime analysis, and liquidity mapping into a single unified model.
This version focuses on three core goals:
1. Identify only high-quality, directional market conditions.
The engine filters through HTF bias, short-term structure shifts, RSI momentum, and volatility compression/expansion. The idea is simple: wait for the market to become clean, aligned, and directional before considering an entry.
2. Map liquidity and detect sweeps in real time.
Major highs and lows are tracked using extended pivots, and the system highlights key areas where stop hunts or sweeps may occur. Sweeps and pressure zones are evaluated and factored directly into the quality score.
3. Grade every potential setup with a single, objective metric (TQI).
The Trade Quality Index (0โ5โญ) compresses all signals into one reading so the trader can quickly judge whether a setup has enough quality to act on.
The script includes:
โข Trend + Momentum + Structure detection
โข HTF bias (optional)
โข Volatility regime analysis
โข Liquidity sweeps + pressure zones
โข Micro-confirmation engine
โข PQI (0โ100%)
โข TQI (0โ5โญ)
โข Clean HUD and Driverโs Guide
โข Auto-cleaning labels and signal management
โข Optional session filtering (London/NY)
This tool is designed for traders who value confirmation over noise.
It will not fire constantly.
It will wait patiently for clean, directional, aligned markets โ and only then issue a signal.
How to Use Liquidity Hunter Pro v12
1. Check the HUD (top-right by default)
The HUD is your dashboard. Before doing anything:
A. HTF Bias
This is your map. Only trade in the direction of the bias.
B. Trend / Momentum / Structure
These should ideally all match the direction of the bias.
If they donโt line up โ wait. No alignment = low probability.
C. Liquidity + Volatility Regime
โSweep โโโโ or โSweep โโโโ = potential reversal points
โExpansionโ = clean conditions
โCompressionโ = choppy, avoid
You donโt need to overthink any of this โ just think:
โAre the ingredients lined up?โ
2. Wait for a valid signal
The indicator will only trigger a BUY or SELL when:
โ HTF bias aligns
โ Trend & momentum align
โ Structure supports the move
โ Micro-confirmation kicks in
โ PQI โฅ 75
โ Sessions are open (optional)
Signals are rare on purpose.
When one prints, you know the market conditions are stacked.
3. Read the label
Each signal prints a small block next to the candle containing:
โข Entry price
โข SL (based on structure)
โข TP(2R) suggestion
โข Liquidity context (e.g., sweep or pressure)
โข Volatility regime
โข TQI โญ rating (0โ5)
This helps you judge the setup instantly.
A simple rule for beginners:
Trade only if TQI โฅ โญโญโญ
Lower than that = more noise, less edge.
4. Use the liquidity zones
The script plots subtle boxes at recent liquidity highs/lows.
These mark:
โข Where the market may hunt stops
โข Where reversals often start
โข Where signals are more meaningful
When a signal happens near liquidity โ higher quality.
5. Follow the session filter (optional but recommended)
By default the tool focuses on:
โข London session
โข New York session
That removes 70% of low-volatility garbage.
You can turn this off if you trade crypto or indices overnight, but beginners usually benefit from keeping it on.
Recommended Settings
These are the settings used by most testers and early users.
Everything is configurable, but start with this:
Core Settings
โข Fast EMA: 21
โข Slow EMA: 55
โข RSI Length: 14
โข Pivot Lookback: 2
These settings create balanced structure detection and smooth trend signals.
HTF Bias
โข Use HTF Bias: ON
โข HTF Timeframe: 240 (H4)
H4 bias keeps you out of counter-trend traps.
Sessions
โข Use London/NY Filter: ON
โข London: 08:00โ17:00
โข New York: 13:30โ21:00
Perfect for FX, indices, and metals.
Crypto traders: turn sessions OFF.
HUD + Guide
โข HUD: ON
โข Guide: ON
โข Linger Bars: 12
This keeps things readable and prevents clutter.
Trading Tips for Beginners
These help keep you out of trouble:
1. Donโt fade the bias.
If HTF says bearish โ avoid buys.
2. Donโt trade in compression regimes.
It saves you from chop.
3. Donโt chase signals that fire far from structure.
If the signal candle is huge, let it go.
4. Donโt trade without at least โญโญโญ.
Youโll thank yourself later.
Final Thoughts
Liquidity Hunter Pro v12 isnโt meant to spam signals.
Itโs meant to filter hard, highlight clean conditions, and help new traders avoid the traps the market throws every day.
Treat it as a trading assistant that tells you:
โThe environment is right. Now you decide.โ
Search in scripts for "bias"
Market Outlook Score (MOS)Overview
The "Market Outlook Score (MOS)" is a custom technical indicator designed for TradingView, written in Pine Script version 6. It provides a quantitative assessment of market conditions by aggregating multiple factors, including trend strength across different timeframes, directional movement (via ADX), momentum (via RSI changes), volume dynamics, and volatility stability (via ATR). The MOS is calculated as a weighted score that ranges typically between -1 and +1 (though it can exceed these bounds in extreme conditions), where positive values suggest bullish (long) opportunities, negative values indicate bearish (short) setups, and values near zero imply neutral or indecisive markets.
This indicator is particularly useful for traders seeking a holistic "outlook" score to gauge potential entry points or market bias. It overlays on a separate pane (non-overlay mode) and visualizes the score through horizontal threshold lines and dynamic labels showing the numeric MOS value along with a simple trading decision ("Long", "Short", or "Neutral"). The script avoids using the plot function for compatibility reasons (e.g., potential TradingView bugs) and instead relies on hline for static lines and label.new for per-bar annotations.
Key features:
Multi-Timeframe Analysis: Incorporates slope data from 5-minute, 15-minute, and 30-minute charts to capture short-term trends.
Trend and Strength Integration: Uses ADX to weight trend bias, ensuring stronger signals in trending markets.
Momentum and Volume: Includes RSI momentum impulses and volume deviations for added confirmation.
Volatility Adjustment: Factors in ATR changes to assess market stability.
Customizable Inputs: Allows users to tweak periods for lookback, ADX, and ATR.
Decision Labels: Automatically classifies the MOS into actionable categories with visual labels.
This indicator is best suited for intraday or swing trading on volatile assets like stocks, forex, or cryptocurrencies. It does not generate buy/sell signals directly but can be combined with other tools (e.g., moving averages or oscillators) for comprehensive strategies.
Inputs
The script provides three user-configurable inputs via TradingView's input panel:
Lookback Period (lookback):
Type: Integer
Default: 20
Range: Minimum 10, Maximum 50
Purpose: Defines the number of bars used in slope calculations for trend analysis. A shorter lookback makes the indicator more sensitive to recent price action, while a longer one smooths out noise for longer-term trends.
ADX Period (adxPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Sets the smoothing period for the Average Directional Index (ADX) and its components (DI+ and DI-). Standard value is 14, but shorter periods increase responsiveness, and longer ones reduce false signals.
ATR Period (atrPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Determines the period for the Average True Range (ATR) calculation, which measures volatility. Adjust this to match your trading timeframeโshorter for scalping, longer for positional trading.
These inputs allow customization without editing the code, making the indicator adaptable to different market conditions or user preferences.
Core Calculations
The MOS is computed through a series of steps, blending trend, momentum, volume, and volatility metrics. Here's a breakdown:
Multi-Timeframe Slopes:
The script fetches data from higher timeframes (5m, 15m, 30m) using request.security.
Slope calculation: For each timeframe, it computes the linear regression slope of price over the lookback period using the formula:
textslope = correlation(close, bar_index, lookback) * stdev(close, lookback) / stdev(bar_index, lookback)
This measures the rate of price change, where positive slopes indicate uptrends and negative slopes indicate downtrends.
Variables: slope5m, slope15m, slope30m.
ATR (Average True Range):
Calculated using ta.atr(atrPeriod).
Represents average volatility over the specified period. Used later to derive volatility stability.
ADX (Average Directional Index):
A detailed, manual implementation (not using built-in ta.adx for customization):
Computes upward movement (upMove = high - high ) and downward movement (downMove = low - low).
Derives +DM (Plus Directional Movement) and -DM (Minus Directional Movement) by filtering non-relevant moves.
Smooths true range (trur = ta.rma(ta.tr(true), adxPeriod)).
Calculates +DI and -DI: plusDI = 100 * ta.rma(plusDM, adxPeriod) / trur, similarly for minusDI.
DX: dx = 100 * abs(plusDI - minusDI) / max(plusDI + minusDI, 0.0001).
ADX: adx = ta.rma(dx, adxPeriod).
ADX values above 25 typically indicate strong trends; here, it's normalized (divided by 50) to influence the trend bias.
Volume Delta (5m Timeframe):
Fetches 5m volume: volume_5m = request.security(syminfo.tickerid, "5", volume, lookahead=barmerge.lookahead_on).
Computes a 12-period SMA of volume: avgVolume = ta.sma(volume_5m, 12).
Delta: (volume_5m - avgVolume) / avgVolume (or 0 if avgVolume is zero).
This measures relative volume spikes, where positive deltas suggest increased interest (bullish) and negative suggest waning activity (bearish).
MOS Components and Final Calculation:
Trend Bias: Average of the three slopes, normalized by close price and scaled by 100, then weighted by ADX influence: (slope5m + slope15m + slope30m) / 3 / close * 100 * (adx / 50).
Emphasizes trends in strong ADX conditions.
Momentum Impulse: Change in 5m RSI(14) over 1 bar, divided by 50: ta.change(request.security(syminfo.tickerid, "5", ta.rsi(close, 14), lookahead=barmerge.lookahead_on), 1) / 50.
Captures short-term momentum shifts.
Volatility Clarity: 1 - ta.change(atr, 1) / max(atr, 0.0001).
Measures ATR stability; values near 1 indicate low volatility changes (clearer trends), while lower values suggest erratic markets.
MOS Formula: Weighted average:
textmos = (0.35 * trendBias + 0.25 * momentumImpulse + 0.2 * volumeDelta + 0.2 * volatilityClarity)
Weights prioritize trend (35%) and momentum (25%), with volume and volatility at 20% each. These can be adjusted in code for experimentation.
Trading Decision:
A variable mosDecision starts as "Neutral".
If mos > 0.15, set to "Long".
If mos < -0.15, set to "Short".
Thresholds (0.15 and -0.15) are hardcoded but can be modified.
Visualization and Outputs
Threshold Lines (using hline):
Long Threshold: Horizontal dashed green line at +0.15.
Short Threshold: Horizontal dashed red line at -0.15.
Neutral Line: Horizontal dashed gray line at 0.
These provide visual reference points for MOS interpretation.
Dynamic Labels (using label.new):
Placed at each bar's index and MOS value.
Text: Formatted MOS value (e.g., "0.2345") followed by a newline and the decision (e.g., "Long").
Style: Downward-pointing label with gray background and white text for readability.
This replaces a traditional plot line, showing exact values and decisions per bar without cluttering the chart.
The indicator appears in a separate pane below the main price chart, making it easy to monitor alongside price action.
Usage Instructions
Adding to TradingView:
Copy the script into TradingView's Pine Script editor.
Save and add to your chart via the "Indicators" menu.
Select a symbol and timeframe (e.g., 1-minute for intraday).
Interpretation:
Long Signal: MOS > 0.15 โ Consider bullish positions if supported by other indicators.
Short Signal: MOS < -0.15 โ Potential bearish setups.
Neutral: Between -0.15 and 0.15 โ Avoid trades or wait for confirmation.
Watch for MOS crossings of thresholds for momentum shifts.
Combine with price patterns, support/resistance, or volume for better accuracy.
Limitations and Considerations:
Lookahead Bias: Uses barmerge.lookahead_on for multi-timeframe data, which may introduce minor forward-looking bias in backtesting (use with caution).
No Alerts Built-In: Add custom alerts via TradingView's alert system based on MOS conditions.
Performance: Tested for compatibility; may require adjustments for illiquid assets or extreme volatility.
Backtesting: Use TradingView's strategy tester to evaluate historical performance, but remember past results don't guarantee future outcomes.
Customization: Edit weights in the MOS formula or thresholds to fit your strategy.
This indicator distills complex market data into a single score, aiding decision-making while encouraging users to verify signals with additional analysis. If you need modifications, such as restoring plot functionality or adding features, provide details for further refinement.
Monte Carlo Future Moves [ChartPrime]ORIGINS AND HISTORICAL BACKGROUND:
Prior to the the advent of the Monte Carlo method, examining well-understood deterministic problems via simulation generally utilized statistical sampling to gauge uncertainty estimations. The Monte Carlo (MC) approach inverts this paradigm by modeling with probabilistic metaheuristics to address deterministic problems. Addressing Buffon's needle problem, an early form of the Monte Carlo method estimated ฯ (3.14159) by dropping needles on a floor. Later, the modern MC inception primarily began when Stanislaw Ulam was playing solitaire games while experiencing illness and recovery.
Ulam further developed, applied, and ascribed "Monte Carlo" as a classified code name to maintain a level of secrecy for the modern method applications during collaborative investigations on neutron diffusion and collision intricacies with John von Neumann. Despite having relevant data, physicist's conventional deterministic mathematical methods were unable to solve mysterious "neutronion problems". Monte Carlo filled in the gaps necessary to resolve this perplexing neutron problem with innovative statistics, and the resilient MC continues onward to have diverse application in many fields of science. MC also extends into the realm of relevance within finance.
APPLICATION IN FINANCE:
Building on its historical roots, the Monte Carlo method's transition into finance opened new avenues for risk assessment and predictive analysis. In financial markets, characterized by uncertainty and complex variables, this method offers a powerful tool for simulating a wide range of scenarios and assessing probabilities of different outcomes. By employing probabilistic models to predict price movements, the Monte Carlo method helps in creating more resilient and informed trading strategies. This approach is particularly valuable in options pricing, portfolio management, and risk assessment, where understanding the range of potential outcomes is crucial for making sound investment decisions. Our indicator utilizes this methodology, blending traditional financial analysis with advanced statistical techniques.
THE INDICATOR:
The Monte Carlo Future Moves (ChartPrime) indicator is designed to predict future price movements. It simulates various possible price paths, showing the likelihood of different outcomes. We have designed it to be simple to use and understand by displaying lines indicating the most likely bullish and bearish outcomes. The arrows point to these areas making it intuitive to understand. Also included is extreme price levels shown in blue and yellow. This is the most likely extreme range that the price will move to. The outcome distribution is there to show you the range of outcomes along with a visual representation of the possible future outcomes. To make things more user friendly we have also included a representation of this distribution as a background heatmap. The brighter the price level, the more likely the price will end at that level. Finally, we have also included a market bias indication on the side that shows you the general bullish/bearish probabilities.
HOW TO USE:
To use this indicator you want to first assess the market bias. From there you want to target the most likely polar outcome. You can use the range of outcomes to assess your risk and set a stop within a reasonable range of the desired target. By default the indicator projects 10 steps into the future, however this can be easily adjusted in the settings. Generally this indicator excels at mid-term estimations and may yield inconclusive results if the prediction period is too short or too long. You can change the granularity of the outcomes to give you a more or less detailed view of the future. That being said, a lower resolution can make the predictions less useful while a higher resolution can give you a less useful picture. If you decide to use a higher resolution we have included an option to smooth the final result. This is intended to reduce the uncertainty and noise in the predicted outcomes. It is advised to use the minimum level of smoothing possible as a high level of smoothing will greatly reduce the accuracy.
INPUT SECTION:
Derivative Source changes how the indicator sees the price movements. When you set this to Candle it will use the difference between the open and close of each candle. If set to Move, it will use the difference between closing prices. If you are in a market with gaps, you might want to use Candle as this will prevent the indicator from seeing gaps.
Number of Simulations is a crucial setting as it is the core of this indicator. This determines the number of simulations the indicator will use to get its final result. By default it is set to 1000 as we feel like that is around the minimum number of simulations required to get a reasonable output while maintaining stability. In tests the maximum number of simulations we have been able to consistently achieve is 2000.
Lookback is the number of historical candles to account for. A lookback that is too short will not have enough data to accurately assess the likelihood of a price movement, while a period that is too large can make the data less relevant. By default this is set to 1000 as we feel like this is a reasonable tradeoff between volume of data and relevance.
Steps Into Future is the prediction period. By default we have picked a period of 10 steps as this has a good balance between accuracy and usability. The more steps into the future you go, the more uncertain the future outcome will be.
Outcome Granularity controls the precision of the simulated outcomes. By default this is set to 40 as its a good balance between resolution and accuracy.
Outcome Smoothing allows you to smooth the outcome distribution. By default this is set to 0 as it is generally not needed for lower resolutions. Smoothing levels beyond 2 are not recommended as it will negatively impact the output.
Returns Granularity controls the level of definition in the collected price movements. This directly impacts indicator performance and is set to 50 by default because its a good balance between fidelity and usability. When this number is too small, the simulations will be less accurate while numbers too large will negatively impact the probabilities of the movements.
Drift is the trend component in the simulation. This adds the directionality of the simulations by biasing the movements in the current direction of the market. We have included both the standard formula for drift and linear regression. Both methods are well suited for simulating future price movements and have their own advantages. The drift period is set to 100 by default as its a good balance between current and historical directionality. You may want to increase or decrease this number depending on the current market conditions but it is advised to use a period that isn't too small. If your period is too small it can skew the outcomes too much resulting in poor performance. When this is set to 0 it will use the same period as your lookback.
Volatility Adjust , adjusts the simulation to include current volatility. This makes sure that the price movements in the simulation reflects the current market conditions better by making sure that each price move is at least a minimum size.
Returns Style allows you to pick between using percent moves and log returns. We have opted to make percent move the default as it is more intuitive for beginners however both settings yield similar results. Log returns can be less cpu intensive so it might be desirable for longer term predictions.
Precision adjusts the rounding of used when collecting the frequency of price movement sizes. By default this is set to 4 as its is fairly accurate without impacting performance too much. A larger number will make the indicator more precise but at the cost of cpu time. Precision levels that are too small can greatly reduce the accuracy of the simulation and even break the indicator all together.
Update Every Bar allows you to recalculate the prediction every bar and is there for you if you want to strictly use the market bias. It is not recommended to enable this feature but it is there for flexibility.
Side of Chart allows you to pick what side of the price action you want the visuals to be on. When its set to the right everything will be to the right of the starting point and when its set to Left it will position everything to the left of the starting point.
Move Visualization is there to give you an arrow to the most likely bullish and bearish moves. It is meant as a visual aid and visualization tool. The color of these arrows use the same colors as the distribution.
Most Likely Move is a horizontal line that indicates the most likely move. It is positioned in the same location as the Move Visualization.
Standard Deviation is horizontal lines at the extremities of the simulated price action. These represent the most likely range of the future outcomes. You can adjust the multiplier of the standard deviation but by default it is set to 2.
Most Likely Direction is a vertical bar that shows you the sum of the up and down probabilities. It is there to show you the bias of the outcomes and guide you in decision making.
Max Probability Zone is a horizontal line that highlights the location of the highest probability move. You can think of it almost like the POC in a volume distribution but in this case it is the "most likely" single outcome.
Outcome Distribution allows you to toggle the distribution on or off. This is the distribution of all of the simulated outcomes. You can toggle the scale width of the distribution to fit your visual style.
Distribution Text toggles the probability text inside of the distribution bars. When you have a large number for the outcome granularity this text may not be visible and you may want to disable this feature.
Background is a heatmap of the outcome distribution. This allows you to visualize the underlying distribution without the need for the distribution histogram. The brighter the color, the more likely the outcome is for that level. It can be useful for visualizing the range of possible outcomes.
Starting Line is simply a horizontal line indicating the starting point of the simulation. It just the opening price for the starting position.
Extend Lines allows you to extend the lines and background past the prediction period.
CONCLUSION:
With its intuitive visuals and flexible settings, the Monte Carlo Future Moves (ChartPrime) indicator is practice and easy to use. It brings clarity to price movement predictions, helping you to build confidence in your strategies. This indicator not only reflects the evolution of technical analysis but also touches on data-driven insights.
Enjoy
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
โฆ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
โฆ Magenta/Pink Flow: Strong Bearish Trend.
โฆ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
โ๏ธ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensionsโMomentum, Volatility, and Trend Structureโinto a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
โข Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
โข Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
โข Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" โ specifically, the divergence between short-term and long-term volatility baselinesโprior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
โข Concept: This visualization represents the aggregate strength and consistency of the trend.
โข Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
๐ Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
โฆ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
โฆ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
โฆ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
โข Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
โข Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
โข Signal Generation:
โฆ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
โฆ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
โข Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
โข State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
โข Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
โข Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
โข Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
โข Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
๐ฆ Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
โข ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
โฆ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
โฆ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
โข Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweepsโdriving prices briefly below key support levels to accumulate inventory.
โฆ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
โฆ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
โข Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
โฆ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
โฆ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
โข Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
โฆ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
โฆ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
โข 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
โข 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
โข 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
๐จ Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
โข Visuals:
โฆ Cyan/Blue Ribbon: Indicates Bullish Momentum.
โฆ Pink/Magenta Ribbon: Indicates Bearish Momentum.
โข Interpretation:
โฆ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
โฆ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
โฆ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
โข Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
โข Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
โข Visuals: Labeled signals appear above/below specific candles.
โข Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
โข Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
โข Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
โข Visuals: Triangle or circle glows near the price bars.
โข Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
โข Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
โข Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
๐ฅ๏ธ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
โข Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
โข Interpretation:
โฆ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
โฆ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
โฆ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
โข Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
โข Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0โ7.0 / 3.0โ5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
โข Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
โข Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
โข Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
โข Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
โข Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
โข Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
โข Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
โข Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
โข Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
โข Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
โข Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
โ๏ธ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
๐ LANGUAGE SETTINGS (Localization)
โฆ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
โก IMPULSE CORE SETTINGS (Volatility Engine)
โฆ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
โฆ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
โฆ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
๐ฏ TP/SL SETTINGS (Risk Management)
โฆ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
โฆ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
โฆ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
โฆ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
๐ RIBBON SETTINGS (Momentum Visualization)
โฆ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
โฆ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
โฆ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
๐ DISPLAY OPTIONS
โฆ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
โฆ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
๐ TREND BASELINE (Structural Filter)
โฆ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
โฆ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
โฆ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
๐ง SMART EXIT (Dynamic Liquidity)
โฆ Use Smart Exit: Enables the momentum exhaustion logic.
โฆ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
โฆ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
๐ก๏ธ TRAILING STOP (Step)
โฆ Use Trailing Stop: Activates the step-function trailing mechanism.
โฆ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
โฆ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
๐ SAR & MACD SETTINGS (Secondary Confirmation)
โฆ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
โฆ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
โฆ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
๐ ANTI-GREED LOGIC (Behavioral Bias)
โฆ Strict Entry after Win: Enables the negative feedback loop.
โฆ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
๐ HTF FILTER (Multi-Timeframe)
โฆ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
โฆ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
๐ RSI PEAK & CHOPPINESS
โฆ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
โฆ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
๐ SLOPE TRIGGER LOGIC
โฆ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
โฆ Slope Sensitivity (1.5): The angle required to trigger this override.
โ FLAT MARKET FILTER (ADX & ATR)
โฆ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
โฆ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
๐ Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
๐ Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
๐ฏ Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
๐ก๏ธ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
๐ก Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
โ ๏ธ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components โ Volatility, Momentum, and Structure โ and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
โฆ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
โฆ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
โฆ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
โฆ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
Support & Resistance Zone Hunter [BOSWaves]Support & Resistance Zone Hunter - Dynamic Structural Zones with Real-Time Breakout Intelligence
Overview
The Support & Resistance Zone Hunter is a professional-grade structural mapping framework designed to automatically detect high-probability support and resistance areas in real time. Unlike traditional static levels or manually drawn zones, this system leverages pivot detection, range thresholds, and optional volume validation to create dynamic zones that reflect the true structural architecture of the market.
Zones evolve as price interacts with their boundaries. The first touch of a zone determines its bias - bullish, bearish, or neutral - and the system tracks the full lifecycle of each zone from formation, testing, and bias establishment to potential breakout events. Diamond-shaped breakout signals highlight structurally significant price expansions while filtering noise using a configurable cooldown period.
By visualizing market structure in this way, traders gain a deeper understanding of price behavior, trend momentum, and areas where liquidity and reactive forces are concentrated.
Theoretical Foundation
The Support & Resistance Zone Hunter is built on the premise that meaningful structural zones arise from two core principles:
Pivot-Based Turning Points : Only significant highs and lows that represent actual swings in price are considered.
Contextual Validation : Zones must pass minimum range criteria and optional volume thresholds to ensure their relevance.
Markets naturally generate numerous micro-pivots that do not carry predictive significance. By filtering out minor swings and validating zones against volume and range, the system isolates levels that are more likely to attract future price interaction or act as catalysts for breakout moves.
This framework captures not only where price is likely to react but also the direction of potential pressure, providing a statistically grounded, visually intuitive representation of market structure.
How It Works
The Support & Resistance Zone Hunter constructs zones through a multi-layered process that blends pivot logic, range validation, and real-time bias determination:
1. Pivot Detection Core
The indicator identifies pivot highs and pivot lows using a configurable lookback period. Zones are only considered valid when both a top and bottom pivot are present.
2. Zone Qualification Engine
Prospective zones must satisfy two conditions:
Range Threshold : The distance between pivot high and low must exceed the minimum percentage set by the user.
Volume Requirement : If enabled, the current volume must exceed the 50-period moving average.
Only zones meeting these criteria are drawn, reducing noise and emphasizing high-probability structural levels.
3. Zone Lifecycle
Once a valid top and bottom pivot exist:
The zone is created starting from the pivot formation bar.
Zones remain active until both boundaries have been touched by price.
The first boundary touched establishes bias: resistance first โ bullish bias ,support first โ bearish bias, neither โ neutral.
Inactive zones stop expanding but remain visible historically to maintain a clear structural context.
4. Visual Rendering
Active zones are displayed as filled boxes with color corresponding to their bias. Top, bottom, and midpoint lines are drawn for reference. Once a zone becomes inactive, its lines are removed while the filled box remains as a historical footprint.
5. Breakout Detection
Breakout signals occur when price closes above the top boundary or below the bottom boundary of an active zone. The system applies a cooldown period and requires price to return to the zone since the previous breakout to prevent signal spam. Bullish and bearish breakouts are visually represented by diamond-shaped markers with configurable colors.
Interpretation
The Support & Resistance Zone Hunter provides a structural view of market balance:
Bullish Zones : Form when resistance is tested first, indicating upward pressure and potential continuation.
Bearish Zones : Form when support is tested first, reflecting downward pressure and continuation risk.
Neutral Zones : Fresh zones that have not yet been interacted with, representing undiscovered liquidity.
Breakout Diamonds : Highlight significant structural price expansions, helping traders identify confirmed continuation moves while filtering noise.
Zones do not simply indicate past levels; they dynamically reflect the evolving battle between buyers and sellers, providing actionable context for both trend continuation and reversion strategies.
Strategy Integration
The Support & Resistance Zone Hunter is versatile and can be applied across multiple trading approaches:
Trend Continuation : Use bullish and bearish zones to confirm directional bias. Breakout diamonds indicate structural continuation opportunities.
Reversion Entries : Neutral zones often act as magnets in ranging markets, allowing for high-probability mean-reversion setups.
Breakout Trading : Diamonds mark true structural expansions, reducing false breakout risk and guiding stop placement or momentum entries.
Liquidity Zone Alignment : Combining the indicator with order block, breaker, or volume-based tools helps validate zones against broader market participation.
Technical Implementation Details
Pivot Engine : Two-sided pivot detection based on configurable lookback.
Zone Qualification : Minimum range requirement and optional volume filter.
Bias Logic : Determined by the first boundary touched.
Zone Lifecycle : Active until both boundaries are touched, historical visibility retained.
Breakout Signals : Diamond markers with cooldown filtering and price-return validation.
Visuals : Transparent filled zones with live top, bottom, and midpoint lines.
Suggested Optimal Parameters
Pivot Lookback : 10 - 30 for intraday, 20 - 50 for swing trading.
Minimum Range % : 0.5 - 2% for crypto or indices, 1 - 3% for metals or forex.
Volume Filter : Enable for assets with inconsistent liquidity; disable for consistently liquid markets.
Breakout Cooldown : 5 - 20 bars depending on volatility.
These suggested parameters should be used as a baseline; their effectiveness depends on the asset and timeframe, so fine-tuning is expected for optimal performance.
Performance Characteristics
High Effectiveness:
Markets with clear pivot structure and reliable volume.
Trending symbols with consistent retests.
Assets where zones attract repeated price interaction.
Reduced Effectiveness:
Random walk markets lacking structural pivots.
Low-volatility periods with minimal price reaction.
Assets with irregular volume distribution or erratic price action.
Integration Guidelines
Use zone color as contextual bias rather than a standalone signal.
Combine with structural tools, order blocks, or volume-based indicators for confluence.
Validate zones on higher timeframes to refine lower timeframe entries.
Treat breakout diamonds as confirmation of continuation rather than independent triggers.
Disclaimer
The Support & Resistance Zone Hunter provides structural zone mapping and breakout analytics. It does not predict price movement or guarantee profitability. Success requires disciplined risk management, proper parameter calibration, and integration into a comprehensive trading strategy.
Dynamic Support and Resistance with Trend LinesDynamic Support and Resistance with Trend Lines (DSRTL)
1. Introduction & Methodology
The DSRTL indicator is designed to provide a multidimensional analysis of market structure. Unlike traditional tools that rely solely on price pivots, this script combines Static Volume-based Zones with Dynamic Trend Lines to evaluate the price's position relative to critical market components.
The S/R Identification Technique
Instead of standard pivot points, DSRTL utilizes Volume Analysis to highlight areas of significant trader participation:
- Strategy A:
Matrix Climax: Identifies candles within the lookback period that are near price extremes (Highs/Lows) and coincide with significant buying or selling volume.
- Strategy B:
Volume Extremes: Detects candles with the absolute highest buy/sell volumes within the selected lookback window, creating extreme volume-based S/R zones.
- Result:
This creates Support/Resistance (S/R) zones that are validated by actual market activity, not just price geometry.
Dynamic Trend Lines
To complement the static zones, the indicator employs two adaptive channel methods:
- Pivot Span: Connects recent significant pivots for a fast, reactive trend corridor.
- 5-Point Channel: Segments the lookback period into 5 parts to perform a linear regression analysis, creating a stable and statistically significant channel.
2. Volume Calculation Methodology
Accurate S/R detection requires distinguishing Buy Volume from Sell Volume. DSRTL offers two calculation modes:
- Geometry (Source File): Estimates buy/sell volume based on the Close price's position relative to the High/Low of the candle.
Note: This is an approximation that works on all plan types as it does not require intrabar data.
- Intrabar (Precise): Analyzes historical lower-timeframe data (e.g., 15S) to calculate intrabar-based volume deltas with higher precision compared to the geometric method.
Note: This offers superior accuracy. It requires access to historical intrabar data (depending on your plan limits). For the best analytical results, use this mode if available.
3. The Smart Matrix Engine (3D Analysis)
The core of DSRTL is its dashboard, powered by the "Smart Matrix Engine." This engine evaluates the current price in a multi-layer market structure context (Static Volume Zones + Dynamic Channels + Volume Metrics).:
A. S-State (Static): Where is the price relative to the Volume S/R zones?
B. D-State (Dynamic): Where is the price relative to the Trend Channels?
How to read the Matrix Map:
The dashboard displays a 5x5 grid representing 25 possible market scenarios.
- Rows (S1-S5): Represent the Static State (S1=Breakout, S3=Mid-Range, S5=Breakdown).
- Columns (D1-D5): Represent the Dynamic State (D1=Overextended Up, D3=Neutral, D5=Overextended Down).
- Active Cell: Marked with a dot, indicating the specific intersection of price action and market structure.
4. Matrix Interpretations (The 25 Scenarios)
Below is the detailed logic for every possible state displayed on the dashboard, explaining the Title, Bias, and actionable Signal.
Section I: S1 - Static Breakout (Price > Static Resistance)
The price has cleared the static volume resistance zone.
- S1 / D1: HYPER EXTENSION
Bias: Extreme Bullish
Signal: Caution: Exhaustion Risk. Trail stops tight.
- S1 / D2: RESISTANCE CLASH
Bias: Bullish
Signal: Breakout confirmed but facing immediate dynamic resistance.
- S1 / D3: CHANNEL BREAKOUT
Bias: Strong Bullish
Signal: Ideal Trend Continuation. Look to buy dips.
- S1 / D4: SMART PULLBACK
Bias: Bullish (Pullback)
Signal: A pullback occurring after a breakout. Strong buy opportunity.
- S1 / D5: CONFLICT (DIV)
Bias: Conflict/Reversal
Signal: Major Divergence. Static breakout is failing against dynamic structure. High Risk.
Section II: S2 - Inside Static Resistance
The price is currently testing the overhead resistance zone.
- S2 / D1: WEAK SPIKE
Bias: Neutral/Bullish
Signal: Testing resistance, but short-term overextended.
- S2 / D2: IRON FORTRESS (R)
Bias: Rejection Risk
Signal: Double Resistance (Static + Dynamic). High probability of rejection.
- S2 / D3: TESTING RES
Bias: Neutral
Signal: Consolidating at resistance. Wait for a clear break or rejection.
- S2 / D4: COMPRESSION (UP)
Bias: Conflict (Squeeze)
Signal: Squeezed between Static Resistance and Dynamic Support. Volatility imminent.
- S2 / D5: RES vs DOWN-TREND
Bias: Bearish
Signal: Strong downtrend meeting static resistance. Potential Short entry.
Section III: S3 - Mid-Range
The price is floating between significant Static Support and Resistance.
- S3 / D1: OVERBOUGHT RANGE
Bias: Rejection Risk (OB)
Signal: Overextended within the range. Potential fade (short).
- S3 / D2: RANGE HIGH LIMIT
Bias: Neutral/Bearish
Signal: At the top of the dynamic channel. Look for rejection signs.
- S3 / D3: NEUTRAL / CHOPPY
Bias: Neutral
Signal: Dead Center. Low probability environment. Avoid trading.
- S3 / D4: RANGE DIP BUY
Bias: Neutral/Bullish
Signal: At the bottom of the dynamic channel. Look for bounce signs.
- S3 / D5: WEAK RANGE (OS)
Bias: Bounce Risk (OS)
Signal: Oversold within the range. Potential fade (long).
Section IV: S4 - Inside Static Support
The price is currently testing the floor support zone.
- S4 / D1: SUP vs UP-TREND
Bias: Bullish
Signal: Strong uptrend meeting static support. Potential Long entry.
- S4 / D2: COMPRESSION (DN)
Bias: Conflict (Squeeze)
Signal: Squeezed between Static Support and Dynamic Resistance. Volatility imminent.
- S4 / D3: TESTING SUPPORT
Bias: Neutral
Signal: Consolidating at support. Wait for a bounce or breakdown.
- S4 / D4: IRON FLOOR (S)
Bias: Bounce Risk
Signal: Double Support (Static + Dynamic). High probability of a bounce.
- S4 / D5: WEAK DIP
Bias: Neutral/Bearish
Signal: Testing support, but short-term oversold.
Section V: S5 - Static Breakdown (Price < Static Support)
The price has dropped below the static volume support zone.
- S5 / D1: CONFLICT (DIV)
Bias: Conflict/Reversal
Signal: Major Divergence. Static breakdown is failing. High Risk.
- S5 / D2: BEAR PULLBACK
Bias: Bearish (Pullback)
Signal: A pullback occurring after a breakdown. Strong selling opportunity.
- S5 / D3: CHANNEL BREAKDOWN
Bias: Strong Bearish
Signal: Ideal Trend Continuation (Down). Sell rallies.
- S5 / D4: SUPPORT CLASH
Bias: Bearish
Signal: Breakdown confirmed but facing immediate dynamic support.
- S5 / D5: HYPER DROP (VOID)
Bias: Extreme Bearish
Signal: Caution: Climax risk. Trail stops for shorts.
DISCLAIMER & EDUCATIONAL PURPOSE
This indicator is strictly an educational tool designed to visualize complex market structure concepts. Its primary purpose is to help traders "bridge the gap" between academic theory and real-time market behavior by providing a visual representation of support, resistance, and volume dynamics.
Please Note:
1. Not a Trading Strategy: This script is an analytical assistant, not a standalone "Black Box" trading system. It does not generate buy or sell signals that should be followed blindly.
2. No Financial Advice: The data provided by this tool is for informational purposes only. It is not a recommendation to buy or sell any asset.
3. Risk Warning: Trading involves significant risk. Always use your own judgment, perform your own technical analysis, and use proper risk management. Do not use this tool as the sole basis for your trading decisions.
4. Data Precision & Platform Limits: The "Intrabar (Precise)" calculation mode relies on high-resolution historical data to provide exact results. Access to this specific data depth depends entirely on your platform's subscription capabilities. If your plan does not support this level of historical intrabar data, the Precise mode may have limited coverage. In that case, you should switch to "Geometry" mode for a fully populated view.
DTFX Algo Zones [SamuraiJack Mod]CME_MINI:NQ1!
Credits
This indicator is a modified version of an open-source tool originally developed by Lux Algo. I literally modded their indicator to create the DTFX Algo Zones version, incorporating additional features and refinements. Special thanks to Lux Algo for their original work and for providing the open-source code that made this development possible.
Introduction
DTFX Algo Zones is a technical analysis indicator designed to automatically identify key supply and demand zones on your chart using market structure and Fibonacci retracements. It helps traders spot high-probability reversal areas and important support/resistance levels at a glance. By detecting shifts in market structure (such as Break of Structure and Change of Character) and highlighting bullish or bearish zones dynamically, this tool provides an intuitive framework for planning trades. The goal is to save traders time and improve decision-making by focusing attention on the most critical price zones where market bias may confirm or reverse.
Logic & Features
โข Market Structure Shift Detection (BOS & CHoCH): The indicator continuously monitors price swings and marks significant structure shifts. A Break of Structure (BOS) occurs when price breaks above a previous swing high or below a swing low, indicating a continuation of the current trend. A Change of Character (ChoCH) is detected when price breaks in the opposite direction of the prior trend, often signaling an early trend reversal. These moments are visually marked on the chart, serving as anchor points for new zones. By identifying BOS and ChoCH in real-time, the DTFX Algo Zones indicator ensures youโre aware of key trend changes as they happen.
โข Auto-Drawn Fibonacci Supply/Demand Zones: Upon a valid structure shift, the indicator plots a Fibonacci-based zone between the breakout point and the preceding swing high/low (the source of the move). This creates a shaded area or band of Fibonacci retracement levels (for example 38.2%, 50%, 61.8%, etc.) representing a potential support zone in an uptrend or resistance zone in a downtrend. These supply/demand zones are derived from the natural retracement of the breakout move, highlighting where price is likely to pull back. Each zone is essentially an auto-generated Fibonacci retracement region tied to a market structure event, which traders can use to anticipate where the next pullback or bounce might occur.
โข Dynamic Bullish and Bearish Zones: The DTFX Algo Zones indicator distinguishes bullish vs. bearish zones and updates them dynamically as new price action unfolds. Bullish zones (formed after bullish BOS/ChoCH) are typically highlighted in one color (e.g. green or blue) to indicate areas of demand/support where price may bounce upward. Bearish zones (formed after bearish BOS/ChoCH) are shown in another color (e.g. red/orange) to mark supply/resistance where price may stall or reverse downward. This color-coding and real-time updating allow traders to instantly recognize the market bias: for instance, a series of bullish zones implies an uptrend with multiple support levels on pullbacks, while consecutive bearish zones indicate a downtrend with resistance overhead. As old zones get invalidated or new ones appear, the chart remains current with the latest key levels, eliminating clutter from outdated levels.
โข Flexible Customization: The indicator comes with several options to tailor the zones to your trading style. You can filter which zones to display โ for example, show only the most recent N zones or limit to only bullish or only bearish zones โ helping declutter the chart and focus on recent, relevant levels. There are settings to control zone extension (how far into the future the zones are drawn) and to automatically invalidate zones once theyโre no longer relevant (for instance, if price fully breaks through a zone or a new structure shift occurs that supersedes it). Additionally, the Fibonacci retracement levels within each zone are customizable: you can choose which retracement percentages to plot, adjust their colors or line styles, and decide whether to fill the zone area for visibility. This flexibility ensures the DTFX Algo Zones can be tuned for different markets and strategies, whether you want a clean minimalist look or detailed zones with multiple internal levels.
Best Use Cases
DTFX Algo Zones is a versatile indicator that can enhance various trading strategies. Some of its best use cases include:
โข Identifying High-Probability Reversal Zones: Each zone marks an area where price has a higher likelihood of stalling or reversing because it reflects a significant prior swing and Fibonacci retracement. Traders can watch these zones for entry opportunities when the market approaches them, as they often coincide with order block or strong supply/demand areas. This is especially useful for catching trend reversals or pullbacks at points where risk is lower and potential reward is higher.
โข Spotting Key Support and Resistance: The automatically drawn zones act as dynamic support (below price) and resistance (above price) levels. Instead of manually drawing Fibonacci retracements or support/resistance lines, you get an instant map of the key levels derived from recent price action. This helps in quickly identifying where the next bounce (support) or rejection (resistance) might occur. Swing traders and intraday traders alike can use these zones to set alerts or anticipate reaction areas as the market moves.
โข Trend-Following Entries: In a trending market, the indicatorโs zones provide ideal areas to join the trend on pullbacks. For example, in an uptrend, when a new bullish zone is drawn after a BOS, it indicates a fresh demand zone โ buying near the lower end of that zone on a pullback can offer a low-risk entry to ride the next leg up. Similarly, in a downtrend, selling rallies into the highlighted supply zones can position you in the direction of the prevailing trend. The zones effectively serve as a roadmap of the trendโs structure, allowing trend traders to buy dips and sell rallies with greater confidence.
โข Mean-Reversion and Range Trading: Even in choppy or range-bound markets, DTFX Algo Zones can help find mean-reversion trades. If price is oscillating sideways, the zones at extremes of the range might mark where momentum is shifting (ChoCH) and price could swing back toward the mean. A trader might fade an extended move when it reaches a strong zone, anticipating a reversion. Additionally, if multiple zones cluster in an area across time (creating a zone overlap), it often signifies a particularly robust support/resistance level ideal for range trading strategies.
In all these use cases, the indicatorโs ability to filter out noise and highlight structurally important levels means traders can focus on higher-probability setups and make more informed trading decisions.
Strategy โ Pullback Trading with DTFX Algo Zones
One of the most effective ways to use the DTFX Algo Zones indicator is trading pullbacks in the direction of the trend. Below is a step-by-step strategy to capitalize on pullbacks using the zones, combining the indicatorโs signals with sound price action analysis and risk management:
1. Identify a Market Structure Shift and Trend Bias: First, observe the chart for a recent BOS or ChoCH signal from the indicator. This will tell you the current trend bias. For instance, a bullish BOS/ChoCH means the market momentum has shifted upward (bullish bias), and a new demand zone will be drawn. A bearish structure break indicates downward momentum and creates a supply zone. Make sure the broader context supports the bias (e.g., if multiple higher timeframe zones are bullish, focus on long trades).
2. Wait for the Pullback into the Zone: Once a new zone appears, donโt chase the price immediately. Instead, wait for price to retrace back into that highlighted zone. Patience is key โ let the market come to you. For a bullish setup, allow price to dip into the Fibonacci retracement zone (demand area); for a bearish setup, watch for a rally into the supply zone. Often, the middle of the zone (around the 50% retracement level) can be an optimal area where price might slow down and pivot, but itโs wise to observe price behavior across the entire zone.
3. Confirm the Entry with Price Action & Confluence: As price tests the zone, look for confirmation signals before entering the trade. This can include bullish reversal candlestick patterns (for longs) or bearish patterns (for shorts) such as engulfing candles, hammers/shooting stars, or doji indicating indecision turning to reversal. Additionally, incorporate confluence factors to strengthen the setup: for example, check if the zone overlaps with a key moving average, a round number price level, or an old support/resistance line from a higher timeframe. You might also use an oscillator (like RSI or Stochastic) to see if the pullback has reached oversold conditions in a bullish zone (or overbought in a bearish zone), suggesting a bounce is likely. The more factors aligning at the zone, the more confidence you can have in the trade. Only proceed with an entry once you see clear evidence of buyers defending a demand zone or sellers defending a supply zone.
4. Enter the Trade and Manage Risk: When youโre satisfied with the confirmation (e.g., price starts to react positively off a demand zone or shows rejection wicks in a supply zone), execute your entry in the direction of the original trend. Immediately set a stop-loss order to control risk: for a long trade, a common placement is just below the demand zone (a few ticks/pips under the swing low that formed the zone); for a short trade, place the stop just above the supply zoneโs high. This way, if the zone fails and price continues beyond it, your loss is limited. Position size the trade so that this stop-loss distance corresponds to a risk you are comfortable with (for example, 1-2% of your trading capital).
5. Take Profit Strategically: Plan your take-profit targets in advance. A conservative approach is to target the origin of the move โ for instance, in a long trade, you might take profit as price moves back up to the swing high (the 0% Fibonacci level of the zone) or the next significant zone or resistance level above. This often yields at least a 1:1 reward-to-risk ratio if you entered around mid-zone. More aggressive trend-following traders may leave a portion of the position running beyond the initial target, aiming for a larger move in line with the trend (for example, new higher highs in an uptrend). You can also trail your stop-loss upward behind new higher lows (for longs) or lower highs (for shorts) as the trend progresses, locking in profit while allowing for further gains.
6. Monitor Zone Invalidation: Even after entering, keep an eye on the behavior around the zone and any new zones that may form. If price fails to bounce and instead breaks decisively through the entire zone, respect that as an invalidation โ the market may be signaling a deeper reversal or that the signal was false. In such a case, itโs better to exit early or stick to your stop-loss than to hold onto a losing position. The indicator will often mark or no longer highlight zones that have been invalidated by price, guiding you to shift focus to the next opportunity.
Risk Management Tips:
โข Always use a stop-loss and donโt move it farther out in hope. Placing the stop just beyond the zoneโs far end (the swing point) helps protect you if the pullback turns into a larger reversal.
โข Aim for a favorable risk-to-reward ratio. With pullback entries near the middle or far end of a zone, you can often achieve a reward that equals or exceeds your risk. For example, risking 20 pips to make 20+ pips (1:1 or better) is a prudent starting point. Adjust targets based on market structure โ if the next resistance is 50 pips away, consider that upside against your risk.
โข Use confluence and context: Donโt take every zone signal in isolation. The highest probability trades come when the DTFX Algo Zone aligns with other analysis (trend direction, chart patterns, higher timeframe support/resistance, etc.). This filtered approach will reduce trades taken in weak zones or counter-trend traps.
โข Embrace patience and selectivity: Not all zones are equal. It can be wise to skip very narrow or insignificant zones and wait for those that form after a strong BOS/ChoCH (indicating a powerful move). Larger zones or zones formed during high-volume times tend to produce more reliable pullback opportunities.
โข Review and adapt: After each trade, note how price behaved around the zone. If you notice certain Fib levels (like 50% or 61.8%) within the zone consistently provide the best entries, you can refine your approach to focus on those. Similarly, adjust the indicatorโs settings if needed โ for example, if too many minor zones are cluttering your screen, limit to the last few or increase the structure length parameter to capture only more significant swings.
โธป
By combining the DTFX Algo Zones indicator with disciplined confirmation and risk management, traders can improve their timing on pullback entries and avoid chasing moves. This indicator shines in helping you trade what you see, not what you feel โ the clearly marked zones and structure shifts keep you grounded in price action reality. Whether youโre a trend trader looking to buy the dip/sell the rally, or a reversal trader hunting for exhaustion points, DTFX Algo Zones provides a robust visual aid to elevate your trading decisions. Use it as a complementary tool in your analysis to stay on the right side of the marketโs structure and enhance your trading performance.
Donchian ForecastDonchian Forecast โ multi-timeframe Donchian/ATR bias with ADX regime blending
Donchian Forecast is a multi-timeframe bias tool that turns classic Donchian channels into a normalized trend/mean-reversion โforecastโ and a single bias value in .
It projects a short polyline path from the current price and shows how that path adapts when the market shifts from ranging to trending (via ADX).
---
Concept
1. Donchian position โ direction
For each timeframe, the script measures where price sits inside its Donchian channel:
-1 = near channel low
0 = middle
+1 = near channel high
This Donchian position is multiplied by ATR to create a **price delta** (how far the forecast moves from current price).
2. Local behavior: trend vs mean-reversion around Donchian
The indicator treats the edges vs middle of the Donchian channel differently:
* By default, edges behave more โtrend-likeโ, middle more โmean-revertingโ.
* If you enable the reversed option, this logic flips (edges = mean-reverting, middle = trend-
like).
* This โlocalโ behavior is controlled smoothly by the absolute Donchian position |pos| (not by hard zone switches).
3. Global ADX modulation (regime aware)
ADX is mapped from your chosen low โ high thresholds into a signed factor in :
* ADX โค low โ -1 (fully reversed behavior, more range/mean-reversion oriented)
* ADX โฅ high โ +1 (fully normal behavior, more trend oriented)
* Values in between create a **smooth transition**.
* This global factor can:
* Keep the local behavior as is (trending regime),
* Flip it (range regime), or
* Neutralize it (indecisive regime).
4. Multi-timeframe aggregation (1xโ12x chart timeframe)
* The script repeats the same logic across 12 horizons:
* 1x = chart timeframe
* 2x..12x = multiples of the chart timeframe (e.g., 5m โ 10m, 15m, โฆ; 1h โ 2h, 3h, โฆ).
* For each horizon it builds:
* Donchian position
* ATR-scaled delta (in price units)
* Locally + globally blended delta (after Donchian + ADX logic).
* These blended deltas are ATR-weighted and summed into a single bias in , which is then shown as Bias % in the on-chart table.
---
### What you see on the chart
* Forecast polyline
* Starting at the current close, the indicator draws a short chain of **up to 12 segments**:
* Segment 1: from current price โ 1x projection
* Segment 2: 1x โ 2x projection
* โฆ up to 12x.
* Each segment is:
* Green when its blended delta is โฅ 0 (upward bias)
* Red when its blended delta is < 0 (downward bias)
* This is not future price, but a synthetic path showing how the Donchian/ATR/ADX model โexpectsโ price to drift across multiple horizons.
* Bias table (top-center)
* `Bias: X.Y%`
* > 0% (green) โ net upward bias across horizons
* < 0% (red) โ net downward bias
* Magnitude (e.g., ยฑ70โ100%) โ strength of the directional skew.
* `ADX:` current ADX value (from your DMI settings).
* `ADXBlend:` the signed ADX factor in :
* +1 โ fully โtrend-interpretationโ of Donchian behavior
* 0 โ neutral / mixed regime
* -1 โ fully โreversed/mean-reversion interpretationโ
---
Inputs & settings
Core Donchian / ATR
* Donchian Length โ lookback for Donchian high/low on each horizon.
* Price Source โ input series used for position inside the Donchian channel (default: close).
* ATR Length โ ATR lookback for all horizons.
* ATR Multiplier โ scales the size of each forecast step in price units (higher = longer segments / more aggressive forecast).
*Local behavior at high ADX
* Reversed local blend at high ADX?
* Off (default) โ edges behave more trend-like, middle more mean-reverting.
* On โ flips that logic (edges more mean-reverting, middle more trend-like).
* The actual effect is always modulated by the global ADX factor, so you can experiment with how the regime logic feels in different markets.
Global ADX blending
* DMI DI Length โ period for the DI+ and DI- components.
* ADX Smoothing โ smoothing length for ADX.
* ADX low (mean-rev zone) โ below this level, the global factor pushes behavior toward reversal/range logic .
* ADX high (trend zone) โ above this level, the global factor pushes behavior toward **trend logic**.
* Values between low and high create a smooth blend rather than a hard on/off switch.
---
How to use it (examples)
* Directional bias dashboard
* Use the Bias % as a compact summary of multi-horizon Donchian/ATR/ADX conditions:
* Consider only trades aligned with the sign of Bias (e.g., longs only when Bias > 0).
* Use the magnitude to filter for **strong vs weak** directional contexts.
* Regime-aware context
* Watch ADX and ADXBlend:
* High ADX & ADXBlend โ +1 โ favor trend-continuation ideas.
* Low ADX & ADXBlend โ -1 โ favor range/mean-reversion ideas.
* Around 0 โ mixed/transition regimes; forecasts will be more muted.
* Visual sanity check for systems
* Overlay Donchian Forecast on your usual entries/exits to see:
* When your system trades **with** the multi-TF Donchian bias.
* When it trades **against** it (possible fade setups or no-trade zones).
This script does not generate entry or exit signals by itself. It is a contextual/forecast tool meant to sit on top of your own trading logic.
---
Notes
* Works on most symbols and timeframes; higher-timeframe multiples are built from the chart timeframe.
* The forecast line is a model-based projection, not a prediction or guarantee of future price.
* Always combine this with your own risk management, testing, and judgement. This is for educational and analytical purposes only and is not financial advice.
Averaging Down Strategy1. Averaging Down:
Definition: "Averaging Down" is a strategy in which an investor buys more shares of a declining asset, thus lowering the average purchase price. The main idea is that, by averaging down, the investor can recover faster when the price eventually rebounds.
Risk Considerations: This strategy assumes that the asset will recover in value. If the price continues to decline, however, the investor may suffer larger losses. Academic research highlights the psychological bias of loss aversion that often leads investors to engage in averaging down, despite the increased risk (Barberis & Huang, 2001).
2. RSI (Relative Strength Index):
Definition: The RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is commonly used to identify overbought or oversold conditions. A reading below 30 (or in this case, 35) typically indicates an oversold condition, which might suggest a potential buying opportunity (Wilder, 1978).
Risk Considerations: RSI-based strategies can produce many false signals in range-bound or choppy markets, where prices do not exhibit strong trends. This can lead to multiple losing trades and an overall negative performance (Gencay, 1998).
3. Combination of RSI and Price Movement:
Approach: The combination of RSI for entry signals and price movement (previous day's high) for exit signals aims to capture short-term market reversals. This hybrid approach attempts to balance momentum with price confirmation.
Risk Considerations: While this combination can work well in trending markets, it may struggle in volatile or sideways markets. Additionally, a significant risk of averaging down is that the trader may continue adding to a losing position, which can exacerbate losses if the price keeps falling.
Risk Warnings:
Increased Losses Through Averaging Down:
Averaging down involves buying more of a falling asset, which can increase exposure to downside risk. Studies have shown that this approach can lead to larger losses when markets continue to decline, especially during prolonged bear markets (Statman, 2004).
A key risk is that this strategy may lead to significant capital drawdowns if the price of the asset does not recover as expected. In the worst-case scenario, this can result in a total loss of the invested capital.
False Signals with RSI:
RSI-based strategies are prone to generating false signals, particularly in markets that do not exhibit strong trends. For example, Gencay (1998) found that while RSI can be effective in certain conditions, it often fails in choppy or range-bound markets, leading to frequent stop-outs and drawdowns.
Psychological Bias:
Behavioral finance research suggests that the "Averaging Down" strategy may be influenced by loss aversion, a bias where investors prefer to avoid losses rather than achieve gains (Kahneman & Tversky, 1979). This can lead to poor decision-making, as investors continue to add to losing positions in the hope of a recovery.
Empirical Studies:
Gencay (1998): The study "The Predictability of Security Returns with Simple Technical Trading Rules" found that technical indicators like RSI can provide predictive value in certain markets, particularly in volatile environments. However, they are less reliable in markets that lack clear trends.
Barberis & Huang (2001): Their research on behavioral biases, including loss aversion, explains why investors are often tempted to average down despite the risks, as they attempt to avoid realizing losses.
Statman (2004): In "The Diversification Puzzle," Statman discusses how strategies like averaging down can increase risk exposure without necessarily improving long-term returns, especially if the underlying asset continues to perform poorly.
Conclusion:
The "Averaging Down Strategy with RSI" combines elements of technical analysis with a psychologically-driven averaging down approach. While the strategy may offer opportunities in trending or oversold markets, it carries significant risks, particularly in volatile or declining markets. Traders should be cautious when using this strategy, ensuring they manage risk effectively and avoid overexposure to a losing position.
Candles In Row (Expo)โ Overview
The Candles In Row (Expo) indicator is a powerful tool designed to track and visualize sequences of consecutive candlesticks in a price chart. Whether you're looking to gauge momentum or determine the prevailing trend, this indicator offers versatile functionality tailored to the needs of active traders. The Candles In Row indicator can be an integral part of a multi-timeframe trading strategy, allowing traders to understand market momentum, and set trading bias. By recognizing the patterns and likelihood of future price movements, traders can make more informed decisions and align their trades with the overall market direction.
โ How to use
The indicator enhances traders' understanding of the consecutive candle patterns, helping them to uncover trends and momentum. Consecutive candles in the same direction may indicate a strong trend. The Candles In Row indicator can be an essential tool for traders employing a multiple timeframes strategy.
Analyzing a Higher Timeframe:
Understanding Momentum: By analyzing consecutive green or red candles in a higher timeframe, traders can identify the prevailing momentum in the market. A series of green candles would suggest an upward trend, while a series of red candles would indicate a downward trend.
Predicting Next Candle: The indicator's predictive feature calculates the likelihood of the next candle being green or red based on historical patterns. This probability helps traders gauge the potential continuation of the trend.
Setting the Trading Bias: If the likelihood of the next candle being green is high, the trader may decide to focus on long (buy) opportunities. Conversely, if the likelihood of the next candle being red is high, the trader may look for short (sell) opportunities.
In this example, we are using the Heikin Ashi candles.
Moving to a Lower Timeframe:
Finding Entry Points: Once the trading bias is set based on the higher timeframe analysis, traders can switch to a lower timeframe to look for entry points in the direction of the bias. For example, if the higher timeframe suggests a high likelihood of a green candle, traders may look for buy opportunities in the lower timeframe.
Combining Timeframes for a Comprehensive Strategy:
Confirmation and Alignment: By analyzing the higher timeframe and confirming the direction in the lower timeframe, traders can ensure that they are trading in alignment with the broader trend.
Avoiding False Signals: By using a higher timeframe to set the trading bias and a lower timeframe to find entries, traders can avoid false signals and whipsaws that might be present in a single timeframe analysis.
โ Settings
Price Input Selection: Choose between regular open and close prices or Heikin Ashi candles as the basis for calculation.
Data Window Control: Decide between displaying the full data window or only the active data. You can also enable a counter that keeps track of the number of candles.
Alert Configuration: Set the desired number and color of consecutive candles that must occur in a row to trigger an alert.
Table Display Customization: Customize the location and size of the display table according to your preferences.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Smart Money Decoded [GOLD]Title: Smart Money Decoded
Description:
Introduction
Smart Money Decoded is a comprehensive, institutional-grade visualization suite designed to simplify the complex world of Smart Money Concepts (SMC). While many indicators flood the chart with noise, this tool focuses on clarity, precision, and high-probability structure.
This script is built for traders who follow the "Inner Circle Trader" (ICT) methodologies but struggle to identify valid Zones, Displacement, and Liquidity Sweeps in real-time.
๐ Key Features & Logic
1. Refined Market Structure (BOS & CHoCH)
Instead of marking every minor pivot, this script uses a filtered Swing High/Low detection system.
HH/LL/LH/HL Labels: Only significant structure points are mapped.
BOS (Break of Structure): Marks trend continuations in the direction of the bias.
CHoCH (Change of Character): Marks potential trend reversals.
2. Advanced Order Blocks (with "Strict Mode")
Not all down-candles before an up-move are Order Blocks. This script separates the weak from the strong.
Standard OBs: Visualized with standard transparency.
โก SWEEP OBs (High Probability): Order Blocks that explicitly swept liquidity (Stop Hunt) before the reversal are highlighted with a thicker border, brighter color, and a โก symbol. These are your high-probability "Turtle Soup" entries.
Strict Mode Toggle: In the settings, you can choose to hide all weak OBs and only see the ones that swept liquidity.
3. Dynamic Breaker Blocks
A true ICT Breaker is a failed Order Block that trapped liquidity.
This script automatically detects when a valid OB is mitigated (broken through) and projects it forward as a Breaker Block.
This ensures you are trading off valid flipped zones (Support becomes Resistance, Resistance becomes Support).
4. Fair Value Gaps (FVG)
Automatically detects Imbalances (Imbalance/Inefficiency).
Includes an ATR Filter to ignore tiny, insignificant gaps, keeping your chart clean.
Option to show the Consequent Encroachment (50% CE) level for precision entries.
5. Liquidity Zones (BSL / SSL)
Automatically plots Buy Side Liquidity (BSL) and Sell Side Liquidity (SSL) at key swing points.
Once price sweeps these levels, the zone is removed or marked as "Swept," helping you identify when the draw on liquidity has been met.
6. Institutional Data Panel
A dashboard in the top right corner displays:
Market Bias: Bullish/Bearish/Neutral based on structure.
Premium/Discount: Tells you if price is in the expensive (Premium) or cheap (Discount) part of the current dealing range.
Active Zones: Counts of current open arrays.
โ๏ธ How To Use This Indicator
Identify Bias: Look at the Structure Labels (HH/LL) and the Panel. Are we making Higher Highs?
Wait for the Trap: Look for a Liquidity Sweep (BSL/SSL taken) or a โก Sweep OB.
Entry Confirmation: Watch for a return to a Fair Value Gap (FVG) or a retest of a Breaker Block (BRK).
Manage Risk: Use the visuals to place stops above/below invalidation points.
Customization:
Go to the settings to toggle "Strict Mode" for Order Blocks, change colors to match your theme, or adjust the lookback periods to fit your specific asset (Forex, Crypto, or Indices).
๐ Credits & Acknowledgments
This script is an educational tool based on the public teachings of Michael J. Huddleston (The Inner Circle Trader - ICT).
Concepts used: Order Blocks, Breakers, FVGs, Market Structure, Liquidity Pools.
Credit is fully given to ICT for originating these concepts and sharing them with the world.
โ ๏ธ Disclaimer
This script is NOT affiliated with, endorsed by, or connected to Michael J. Huddleston (ICT) in any way. It is an independent coding project intended for educational purposes and visual assistance.
Trading involves substantial risk. This indicator does not guarantee profits. Always use proper risk management. Trust your analysis first, and use indicators as confluence.
#Smart Money Concepts, #SMC, #ICT,#Liquidity, #Market Structure, #Trend, #Price Action.
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite
This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion .
Core Architecture
Why These Components Are Combined:
The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention.
The Four Trading Agents
1. Spoofing Detector Agent ๐ญ
Detects iceberg orders through persistent volume at similar price levels over 5 bars
Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8ร average)
Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model)
Signal Logic: Contrarianโfades false breakouts caused by institutional manipulation
Best Markets: Consolidations, institutional trading windows, low-liquidity hours
2. Exhaustion Detector Agent โก
Calculates RSI divergence between price movement and momentum indicator over 5-bar window
Detects VWAP exhaustion (price at 2ฯ bands with declining volume)
Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure
Signal Logic: Counter-trendโenters when momentum extreme shows weakness
Best Markets: Trending markets reaching climax points, over-extended moves
3. Liquidity Void Detector Agent ๐ง
Measures Bollinger Band squeeze (width <60% of 50-period average)
Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike
Detects hidden liquidity absorption (volume >2ร average with range <0.3ร ATR)
Signal Logic: Breakout anticipationโenters after liquidity grab but before main move
Best Markets: Range-bound pre-breakout, volatility compression zones
4. Mean Reversion Agent ๐
Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ยฑ2ฯ)
Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model)
Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability)
Signal Logic: Statistical reversionโenters when price deviates significantly from statistical equilibrium
Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments
Adaptive Selection: Multi-Armed Bandit System
The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance:
Thompson Sampling (Default - Recommended):
Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent)
Balances exploration (trying underused agents) vs. exploitation (using proven winners)
Each agent's win/loss history informs its selection probability
Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation
UCB1 (Upper Confidence Bound):
Calculates confidence intervals using: average_reward + sqrt(2 ร ln(total_pulls) / agent_pulls)
Deterministic algorithm favoring agents with high uncertainty (potential upside)
More conservative than Thompson Sampling
Epsilon-Greedy:
Exploits best-performing agent (1-ฮต)% of the time
Explores randomly ฮต% of the time (default 10%, configurable 1-50%)
Simple, transparent, easily tuned via epsilon parameter
Gradient Bandit:
Uses softmax probability distribution over agent preference weights
Updates weights via gradient ascent based on rewards
Best for Blend mode where all agents contribute
Selection Modes:
Switch Mode: Uses only the selected agent's signal (clean, decisive)
Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified)
Lock Agent Feature:
Optional manual override to force one specific agent
Useful after identifying which agent dominates your specific instrument
Only applies in Switch mode
Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion
Memory System
Dual-Layer Architecture:
Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50)
Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars)
Memory Boost Mechanism: Recent performance modulates agent scores by up to ยฑ20%
Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage
Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds)
How Memory Works:
Agent generates signal โ outcome tracked after 8 bars (performance horizon)
Result stored in short-term memory (win = 1.0, loss = 0.0)
Short-term average influences agent's future scores (positive feedback loop)
After threshold met (default 10 results), episode averaged into long-term storage
Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost
Market Microstructure Analysis
These advanced metrics quantify institutional order flow dynamics:
Order Flow Toxicity (Simplified VPIN):
Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol)
Detects informed trading activity (institutional players with non-public information)
Values >0.4 indicate "toxic flow" (informed traders active)
Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification
Price Impact Analysis (Simplified Kyle's Lambda):
Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10)
Low values = large orders with minimal price impact ( stealth accumulation )
High values = retail-dominated moves with high slippage
Lite Approximation: Uses simplified denominator instead of regression-based signed order flow
Market Randomness (Entropy Analysis):
Counts unique price changes over 20 bars / 20
Measures market predictability
High entropy (>0.6) = human-driven, chaotic price action
Low entropy (<0.25) = algorithmic trading dominance (predictable patterns)
Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -ฮฃ p(x)ยทlogโ(p(x))
Order Clustering (Simplified Hawkes Process):
Tracks self-exciting event intensity (coordinated order activity)
Decays at 0.9ร per bar, spikes +1.0 when volume >1.5ร average
High intensity (>0.7) indicates clustering (potential spoofing/accumulation)
Lite Approximation: Simple exponential decay instead of full ฮป(t) = ฮผ + ฮฃ ฮฑยทexp(-ฮฒ(t-tแตข)) with MLE
Signal Generation Process
Multi-Stage Validation:
Stage 1: Agent Scoring
Each agent calculates internal score based on its detection criteria
Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier)
Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0)
Stage 2: Memory Boost
Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance)
Successful agents get amplified, failing agents get dampened
Stage 3: Bandit Selection/Blending
If Adaptive Mode ON:
Switch: Bandit selects single best agent, uses only its signal
Blend: All agents combined using softmax-weighted confidence scores
If Adaptive Mode OFF:
Traditional consensus voting with confidence-squared weighting
Signal fires when consensus exceeds threshold (default 70%)
Stage 4: Confirmation Filter
Raw signal must repeat for consecutive bars (default 3, configurable 2-4)
Minimum confidence threshold: 0.25 (25%) enforced regardless of mode
Trend alignment check: Long signals require trend_score โฅ -2, Short signals require trend_score โค 2
Stage 5: Cooldown Enforcement
Minimum bars between signals (default 10, configurable 5-15)
Prevents over-trading during choppy conditions
Stage 6: Performance Tracking
After 8 bars (performance horizon), signal outcome evaluated
Win = price moved in signal direction, Loss = price moved against
Results fed back into memory and bandit statistics
Trading Modes (Presets)
Pre-configured parameter sets:
Conservative: 85% consensus, 4 confirmations, 15-bar cooldown
Expected: 60-70% win rate, 3-8 signals/week
Best for: Swing trading, capital preservation, beginners
Balanced: 70% consensus, 3 confirmations, 10-bar cooldown
Expected: 55-65% win rate, 8-15 signals/week
Best for: Day trading, most traders, general use
Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown
Expected: 50-58% win rate, 15-30 signals/week
Best for: Scalping, high-frequency trading, active management
Elite: 75% consensus, 3 confirmations, 12-bar cooldown
Expected: 58-68% win rate, 5-12 signals/week
Best for: Selective trading, high-conviction setups
Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown
Expected: Varies based on learning
Best for: Experienced users leveraging bandit system
How to Use
1. Initial Setup (5 Minutes):
Select Trading Mode matching your style (start with Balanced)
Enable Adaptive Learning (recommended for automatic agent selection)
Choose Thompson Sampling algorithm (best all-around performance)
Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume)
2. Agent Tuning (Optional):
Adjust Agent Sensitivity multipliers (0.5-2.0):
<0.8 = Highly selective (fewer signals, higher quality)
0.9-1.2 = Balanced (recommended starting point)
1.3 = Aggressive (more signals, lower individual quality)
Monitor dashboard for 20-30 signals to identify dominant agent
If one agent consistently outperforms, consider using Lock Agent feature
3. Bandit Configuration (Advanced):
Blend Temperature (0.1-2.0):
0.3 = Sharp decisions (best agent dominates)
0.5 = Balanced (default)
1.0+ = Smooth (equal weighting, democratic)
Memory Decay (0.8-0.99):
0.90 = Fast adaptation (volatile markets)
0.95 = Balanced (most instruments)
0.97+ = Long memory (stable trends)
4. Signal Interpretation:
Green triangle (โฒ): Long signal confirmed
Red triangle (โผ): Short signal confirmed
Dashboard shows:
Active agent (highlighted row with โบ marker)
Win rate per agent (green >60%, yellow 40-60%, red <40%)
Confidence bars (โโโโโ = maximum confidence)
Memory size (short-term buffer count)
Colored zones display:
Entry level (current close)
Stop-loss (1.5ร ATR)
Take-profit 1 (2.0ร ATR)
Take-profit 2 (3.5ร ATR)
5. Risk Management:
Never risk >1-2% per signal (use ATR-based stops)
Signals are entry triggers, not complete strategies
Combine with your own market context analysis
Consider fundamental catalysts and news events
Use "Confirming" status to prepare entries (not to enter early)
6. Memory Persistence (Optional):
After 50-100 trades, check Memory Export Panel
Record displayed alpha/beta/weight values for each agent
Record VPIN and Kyle threshold values
Enable "Restore From Memory" and input saved values to continue learning
Useful when switching timeframes or restarting indicator
Visual Components
On-Chart Elements:
Spectral Layers: EMA8 ยฑ 0.5 ATR bands (dynamic support/resistance, colored by trend)
Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers)
Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence ร ATR)
Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal)
Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets
Signal Markers: Triangle up/down at validated entry points
Dashboard (Configurable Position & Size):
Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear)
Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus)
Agent Performance Table: Real-time win%, confidence, and memory stats
Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled)
Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress
Memory Panel (Configurable Position & Size):
Live Parameter Export: Alpha, beta, and weight values per agent
Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold
Save Reminder: Visual indicator if parameters should be recorded
What Makes This Original
This script's originality lies in three key innovations:
1. Genuine Meta-Learning Framework:
Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimizationโit's real-time learning.
2. Episodic Memory Architecture with Transfer Learning:
The dual-layer memory system mimics human learning patterns:
Short-term memory captures recent performance (recency bias)
Long-term memory preserves historical patterns (experience)
Automatic transfer mechanism consolidates knowledge
Memory boost creates positive feedback loops (successful strategies become stronger)
This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates.
3. Institutional Microstructure Integration:
Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis.
Mashup Justification:
The four agents are combined specifically for risk diversification across failure modes:
Spoofing Detector: Prevents false breakout losses from manipulation
Exhaustion Detector: Prevents chasing extended trends into reversals
Liquidity Void: Exploits volatility compression (different regime than trending)
Mean Reversion: Provides mathematical anchoring when patterns fail
The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals.
Why "ML-lite"? Simplifications and Approximations
This is the "lite" version due to necessary simplifications for Pine Script execution:
1. Simplified VPIN Calculation:
Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags
This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume)
Impact: May misclassify volume during ranging/choppy markets; works best in directional moves
2. Pseudo-Random Sampling:
Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods
This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close ร 100 - floor(close ร 100)) + (volume % 100) / 100
Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection
3. Hawkes Process Approximation:
Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: ฮป(t) = ฮผ + ฮฃ ฮฑยทexp(-ฮฒ(t-tแตข)) fitted via iterative optimization
This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event)
Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments
4. Kyle's Lambda Simplification:
Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: ฮp = ฮป ร ฮv + ฮต
This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression
Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals
5. Entropy Calculation:
Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -ฮฃ p(x)ยทlogโ(p(x)) where p(x) is probability of each price change magnitude
This Implementation: Simple ratio of unique price changes to total observations (variety measure)
Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape
6. Memory System Constraints:
Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces
This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores
Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking
7. Limited Feature Engineering:
Advanced Implementation: Dozens of engineered features, polynomial interactions (xยฒ, xยณ), dimensionality reduction (PCA, autoencoders), feature selection algorithms
This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation
Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations
8. Single-Instrument Data:
Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes
This Implementation: Only OHLCV data from displayed instrument
Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets
9. Fixed Performance Horizon:
Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement
This Implementation: Fixed 8-bar evaluation window
Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach
Performance Impact Summary:
These simplifications make the script:
โ
Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations
โ
More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers
โ
More Transparent: All calculations visible in Pine Script (no black-box compiled models)
โ
Lower Resource Usage: <500 bars lookback, minimal memory footprint
โ ๏ธ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations
โ ๏ธ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows
โ ๏ธ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized
When to Upgrade to Full Implementation:
Consider professional Python/C++ versions with institutional data feeds if:
Trading with >$100K capital where precision differences materially impact returns
Operating in microsecond-competitive environments (HFT, market making)
Requiring regulatory-grade audit trails and reproducibility
Backtesting with tick-level precision for strategy validation
Need true real-time adaptation with neural network-based learning
For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logicโmulti-agent detection with adaptive selectionโremains intact.
Technical Notes
All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap )
VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above)
Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling
No repainting: All calculations use confirmed bar data (no forward-looking)
Maximum lookback: 500 bars (set via max_bars_back parameter)
Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed)
Confidence threshold: Minimum 0.25 (25%) enforced on all signals
Memory arrays: Dynamic sizing with FIFO queue management
Limitations and Disclaimers
Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty.
Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context.
Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms.
Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts.
Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets.
No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss.
Forward-Looking Bias: Performance evaluation uses 8-bar forward windowโthis creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics.
Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes.
Recommended Settings
Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning)
Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices)
Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable)
Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts
Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss
Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens)
Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0)
After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent
Alert Configuration
The script includes built-in alert conditions:
Long Signal: Fires when validated long entry confirmed
Short Signal: Fires when validated short entry confirmed
Alerts fire once per bar (after confirmation requirements met)
Set alert to "Once Per Bar Close" for reliability
Taking you to school. โ Dskyz, Trade with insight. Trade with anticipation.
DYNAMIC TRADING DASHBOARDStudy Material for the "Dynamic Trading Dashboard"
This Dynamic Trading Dashboard is designed as an educational tool within the TradingView environment. It compiles commonly used market indicators and analytical methods into one visual interface so that traders and learners can see relationships between indicators and price action. Understanding these indicators, step by step, can help traders develop discipline, improve technical analysis skills, and build strategies. Below is a detailed explanation of each module.
________________________________________
1. Price and Daily Reference Points
The dashboard displays the current price, along with percentage change compared to the dayโs opening price. It also highlights whether the price is moving upward or downward using directional symbols. Alongside, it tracks daily high, low, open, and daily range.
For traders, daily levels provide valuable reference points. The daily high and low are considered intraday support and resistance, while the median price of the day often acts as a pivot level for mean reversion traders. Monitoring these helps learners see how price oscillates within daily ranges.
________________________________________
2. VWAP (Volume Weighted Average Price)
VWAP is calculated as a cumulative average price weighted by volume. The dashboard compares the current price with VWAP, showing whether the market is trading above or below it.
For traders, VWAP is often a guide for institutional order flow. Price trading above VWAP suggests bullish sentiment, while trading below VWAP indicates bearish sentiment. Learners can use VWAP as a training tool to recognize trend-following vs. mean reversion setups.
________________________________________
3. Volume Analysis
The system distinguishes between buy volume (when the closing price is higher than the open) and sell volume (when the closing price is lower than the open). A progress bar highlights the ratio of buying vs. selling activity in percentage.
This is useful because volume confirms price action. For instance, if prices rise but sell volume dominates, it can signal weakness. New traders learning with this tool should focus on how volume often precedes price reversals and trends.
________________________________________
4. RSI (Relative Strength Index)
RSI is a momentum oscillator that measures price strength on a scale from 0 to 100. The dashboard classifies RSI readings into overbought (>70), oversold (<30), or neutral zones and adds visual progress bars.
RSI helps learners understand momentum shifts. During training, one should notice how trending markets can keep RSI extended for longer periods (not immediate reversal signals), while range-bound markets react more sharply to RSI extremes. It is an excellent tool for practicing trend vs. range identification.
________________________________________
5. MACD (Moving Average Convergence Divergence)
The MACD indicator involves a fast EMA, slow EMA, and signal line, with focus on crossovers. The dashboard shows whether a โbullish crossโ (MACD above signal line) or โbearish crossโ (MACD below signal line) has occurred.
MACD teaches traders to identify trend momentum shifts and divergence. During practice, traders can explore how MACD signals align with VWAP trends or RSI levels, which helps in building a structured multi-indicator analysis.
________________________________________
6. Stochastic Oscillator
This indicator compares the current close relative to a range of highs and lows over a period. Displayed values oscillate between 0 and 100, marking zones of overbought (>80) and oversold (<20).
Stochastics are useful for students of trading to recognize short-term momentum changes. Unlike RSI, it reacts faster to price volatility, so false signals are common. Part of the training exercise can be to observe how stochastic โflipsโ can align with volume surges or daily range endpoints.
________________________________________
7. Trend & Momentum Classification
The dashboard adds simple labels for trend (uptrend, downtrend, neutral) based on RSI thresholds. Additionally, it provides quick momentum classification (โbullish holdโ, โbearish holdโ, or neutral).
This is beneficial for beginners as it introduces structured thinking: differentiating long-term market bias (trend) from short-term directional momentum. By combining both, traders can practice filtering signals instead of trading randomly.
________________________________________
8. Accumulation / Distribution Bias
Based on RSI levels, the script generates simplified tags such as โAccumulate Longโ, โAccumulate Shortโ, or โWaitโ.
This is purely an interpretive guide, helping learners think in terms of accumulation phases (when markets are low) and distribution phases (when markets are high). It reinforces the concept that trading is not only directional but also involves timing.
________________________________________
9. Overall Market Status and Score
Finally, the dashboard compiles multiple indicators (VWAP position, RSI, MACD, Stochastics, and price vs. median levels) into a Market Score expressed as a percentage. It also labels the market as Overbought, Oversold, or Normal.
This scoring system isnโt a recommendation but a learning framework. Students can analyze how combining different indicators improves decision-making. The key training focus here is confluence: not depending on one indicator but observing when several conditions align.
Extended Study Material with Formulas
________________________________________
1. Daily Reference Levels (High, Low, Open, Median, Range)
โข Day High (H): Maximum price of the session.
DayHigh=maxโก(Hightoday)DayHigh=max(Hightoday)
โข Day Low (L): Minimum price of the session.
DayLow=minโก(Lowtoday)DayLow=min(Lowtoday)
โข Day Open (O): Opening price of the session.
DayOpen=OpentodayDayOpen=Opentoday
โข Day Range:
Range=DayHighโDayLowRange=DayHighโDayLow
โข Median: Mid-point between high and low.
Median=DayHigh+DayLow2Median=2DayHigh+DayLow
These act as intraday guideposts for seeing how far the price has stretched from its key reference levels.
________________________________________
2. VWAP (Volume Weighted Average Price)
VWAP considers both price and volume for a weighted average:
VWAPt=โi=1t(PriceiรVolumei)โi=1tVolumeiVWAPt=โi=1tVolumeiโi=1t(PriceiรVolumei)
Here, Price_i can be the average price (High + Low + Close) รท 3, also known as hlc3.
โข Interpretation: Price above VWAP = bullish bias; Price below = bearish bias.
________________________________________
3. Volume Buy/Sell Analysis
The dashboard splits total volume into buy volume and sell volume based on candle type.
โข Buy Volume:
BuyVol=Volumeif Close > Open, else 0BuyVol=Volumeif Close > Open, else 0
โข Sell Volume:
SellVol=Volumeif Close < Open, else 0SellVol=Volumeif Close < Open, else 0
โข Buy Ratio (%):
VolumeRatio=BuyVolBuyVol+SellVolร100VolumeRatio=BuyVol+SellVolBuyVolร100
This helps traders gauge who is in control during a sessionโbuyers or sellers.
________________________________________
4. RSI (Relative Strength Index)
RSI measures strength of momentum by comparing gains vs. losses.
Step 1: Compute average gains (AG) and losses (AL).
AG=Average of Upward Closes over N periodsAG=Average of Upward Closes over N periodsAL=Average of Downward Closes over N periodsAL=Average of Downward Closes over N periods
Step 2: Calculate relative strength (RS).
RS=AGALRS=ALAG
Step 3: RSI formula.
RSI=100โ1001+RSRSI=100โ1+RS100
โข Used to detect overbought (>70), oversold (<30), or neutral momentum zones.
________________________________________
5. MACD (Moving Average Convergence Divergence)
โข Fast EMA:
EMAfast=EMA(Close,length=fast)EMAfast=EMA(Close,length=fast)
โข Slow EMA:
EMAslow=EMA(Close,length=slow)EMAslow=EMA(Close,length=slow)
โข MACD Line:
MACD=EMAfastโEMAslowMACD=EMAfastโEMAslow
โข Signal Line:
Signal=EMA(MACD,length=signal)Signal=EMA(MACD,length=signal)
โข Histogram:
Histogram=MACDโSignalHistogram=MACDโSignal
Crossovers between MACD and Signal are used in studying bullish/bearish phases.
________________________________________
6. Stochastic Oscillator
Stochastic compares the current close against a range of highs and lows.
%K=CloseโLowestLowHighestHighโLowestLowร100%K=HighestHighโLowestLowCloseโLowestLowร100
Where LowestLow and HighestHigh are the lowest and highest values over N periods.
The %D line is a smooth version of %K (using a moving average).
%D=SMA(%K,smooth)%D=SMA(%K,smooth)
โข Values above 80 = overbought; below 20 = oversold.
________________________________________
7. Trend and Momentum Classification
This dashboard generates simplified trend/momentum logic using RSI.
โข Trend:
โข RSI < 40 โ Downtrend
โข RSI > 60 โ Uptrend
โข In Between โ Neutral
โข Momentum Bias:
โข RSI > 70 โ Bullish Hold
โข RSI < 30 โ Bearish Hold
โข Otherwise Neutral
This is not predictive, only a classification framework for educational use.
________________________________________
8. Accumulation/Distribution Bias
Based on extreme RSI values:
โข RSI < 25 โ Accumulate Long Bias
โข RSI > 80 โ Accumulate Short Bias
โข Else โ Wait/No Action
This helps learners understand the idea of accumulation at lows (strength building) and distribution at highs (profit booking).
________________________________________
9. Overall Market Status and Score
The tool adds up 5 bullish conditions:
1. Price above VWAP
2. RSI > 50
3. MACD > Signal
4. Stochastic > 50
5. Price above Daily Median
BullishScore=ConditionsMet5ร100BullishScore=5ConditionsMetร100
Then it categorizes the market:
โข RSI > 70 or Stoch > 80 โ Overbought
โข RSI < 30 or Stoch < 20 โ Oversold
โข Else โ Normal
This encourages learners to think in terms of probabilistic conditions instead of single-indicator signals.
________________________________________
โ ๏ธ Warning:
โข Trading financial markets involves substantial risk.
โข You can lose more money than you invest.
โข Past performance of indicators does not guarantee future results.
โข This script must not be copied, resold, or republished without authorization from aiTrendview.
By using this material or the code, you agree to take full responsibility for your trading decisions and acknowledge that this is not financial advice.
________________________________________
โ ๏ธ Disclaimer and Warning (From aiTrendview)
This Dynamic Trading Dashboard is created strictly for educational and research purposes on the TradingView platform. It does not provide financial advice, buy/sell recommendations, or guaranteed returns. Any use of this tool in live trading is completely at the userโs own risk. Markets are inherently risky; losses can exceed initial investment.
The intellectual property of this script and its methodology belongs to aiTrendview. Unauthorized reproduction, modification, or redistribution of this code is strictly prohibited. By using this study material or the script, you acknowledge personal responsibility for any trading outcomes. Always consult professional financial advisors before making investment decisions.
Rounded Grid Levels๐ฉ Rounded Grid Levels is a visual tool that helps traders quickly identify key psychological price levels on any chart. By dynamically adapting to the user's visible screen area, it provides consistent, easy-to-read round number grids that align with price action. The indicator offers a traditional visualization of horizontal round level grids, along with enhanced options such as tilted grids that align with market sentiment, and fan-shaped grids for alternative price interaction views. It serves purely as a visual aid, providing an adaptable way to observe rounded price levels without making predictions or generating trading signals.
โก OVERVIEW โก
The Rounded Grid Levels indicator is a visual tool designed to help traders identify and track price levels that may hold psychological significance, such as round numbers or significant milestones. These levels often serve as potential areas for price reactions, including support, resistance, or points of market interest. The indicator's gridlines are determined by user-defined settings and adjust dynamically based on the visible chart area, meaning they are influenced by the user's current zoom level and perspective. This behavior is similar to TradingView's built-in grid lines found in the chart settings canvas, which also adjust in real-time based on the visible screen, ensuring the most relevant price levels are displayed. By default, the indicator provides consistent gridlines to represent traditional round number levels, offering a straightforward view of key psychological areas. Additionally, users have access to experimental and novel configurations, such as fan-shaped layouts, which expand from a central point and adapt directionally based on user settings. This configuration can provide an alternate perspective for traders, especially useful in analyzing broader market moves and visualizing expansion relative to the current price.
Users can display the gridlines in a variety of configurations, including horizontal, neutral, auto, or fan-shaped layouts, depending on their preferred method of analysis. This flexibility allows traders to focus on different types of price action without overcrowding the visual representation of price movements.
This indicator is intended purely as a visual aid for understanding how price interacts with rounded levels over time. It does not generate predictive trading signals or recommendations but rather provides traders with a customizable framework to enhance their market analysis.
โญ ROUND NUMBERS IN MARKET PSYCHOLOGY โญ
Round numbers hold a significant place in financial markets, largely due to the psychological tendencies of traders and investors. These levels often represent areas of interest where human behavior, market biases, and trading strategies converge. Whether it's prices ending in 000, 500, or other recognizable values, these levels naturally attract more attention and influence decision-making.
Round numbers can act as key support or resistance levels and often become focal points in market activity. They are frequently highlighted by financial media, embedded in products like options, and serve as foundations for various trading theories. Their impact extends across different market participants and strategies, making them important focal points in both short-term and long-term market analysis.
Round numbers play an important role in guiding trader behavior and market activity. To better understand why these levels are so impactful, there are several key factors that highlight their significance in trading and price dynamics:
Psychological Impact : Humans naturally gravitate toward round numbers, such as prices ending in 000, 500, or 00. These levels tend to draw attention as traders perceive them as psychologically significant. This behavior is rooted in the cognitive bias known as "left-digit bias," where people assign greater importance to rounded, more recognizable numbers. In trading, this means that prices at these levels are more memorable and thus more likely to attract attention, creating an area where traders focus their buying or selling decisions.
Order Clustering : Traders often place buy and sell orders around these rounded levels, either manually or automatically through stop and limit orders. This clustering leads to the formation of visible support or resistance zones, as the concentrated orders tend to influence price behavior around these key levels. Market participants tend to converge their orders around these price points because of their perceived psychological importance, creating a liquidity pocket. As a result, these areas often act as barriers that the price either struggles to cross or uses as springboards for further movement.
External Influences : Financial media frequently highlights round-number milestones, amplifying market sentiment and drawing traders' attention to these levels. Additionally, algorithmic trading systems often react to round-number thresholds, which can further reinforce price movements, creating self-reinforcing reactions at these levels. As media and analysts emphasize these milestones, more traders pay attention to them, leading to increased volume and often heightened volatility at those points. This self-reinforcing cycle makes round numbers an area where price movement can either accelerate due to a breakout or stall because of clustering interest.
Option Strike Prices : Options contracts typically have strike prices set at round numbers, and as expiration approaches, these levels can influence the price of the underlying asset due to concentrated trading activity. The behavior around these levels, often called "pinning," happens because traders adjust their positions to avoid unfavorable scenarios at these key strikes. This activity tends to concentrate price movement toward these levels as traders hedge their positions, leading to increased liquidity and the potential for abrupt price reactions near option expiration dates.
Whole Number Theory : This theory suggests that whole numbers act as natural psychological barriers, where traders tend to make decisions, place orders, or expect price reactions, making these levels crucial for analysis. Whole numbers are simple to remember and are often used as informal targets for profit-taking or stop placement. This behavior leads to a natural ebb and flow around these levels, where the market finds equilibrium temporarily before deciding on a future direction. Whole numbers tend to work like magnets, drawing price to them and often creating reactions that are visible across different timeframes.
Quarters Theory : Commonly used in Forex markets, this theory focuses on quarter-point increments (e.g., 1.0000, 1.2500, 1.5000) as key levels where price often pauses or reverses. These quarter levels are treated as important psychological barriers, with price frequently interacting at these intervals. Traders use these points to gauge market strength or weakness because quarter levels divide larger round-number ranges into more manageable and meaningful segments. For example, in highly traded forex pairs like EUR/USD, traders might treat 1.2500 as a significant barrier because it represents a halfway point between 1.0000 and 1.5000, offering a balanced reference point for decision-making.
Big Round Numbers : Major round numbers, such as 100, 500, or 1000, often attract significant attention and serve as psychological thresholds. Traders anticipate strong reactions when prices approach or cross these levels. This is often because large round numbers symbolize major milestones, and price behavior around them tends to signal important market sentiment shifts. When price crosses a major level, such as a stock moving above $100 or Bitcoin crossing $50,000, it often creates a surge in trading activity as it is viewed as a validation or invalidation of market trends, drawing in momentum traders and triggering both retail and institutional responses.
By visualizing these round levels on the chart, the Rounded Grid Levels indicator helps traders identify areas where price may pause, reverse, or gain momentum. While round numbers provide useful insights, they should be used in conjunction with other technical analysis tools for a comprehensive trading strategy.
๐ ๏ธ CONFIGURATION AND SETTINGS ๐ ๏ธ
The Rounded Grid Levels indicator offers a variety of configurable settings to tailor the visualization according to individual trader preferences. Below are the key settings available for customization:
Custom Settings
Rounding Step : The Rounding Step parameter sets the minimum interval between gridlines. This value determines how closely spaced the rounded levels are on the chart. For example, if the Rounding Step is set to 100, gridlines will be displayed at every 100 points (e.g., $100, $200, $300) relative to the current price level. The Rounding Step is scaled to the chart's visible area, meaning users should adjust it appropriately for different assets to ensure effective visualization. Lower values provide a more granular view, while larger values give a broader, higher-level perspective.
Major Grids : Defines the interval at which major gridlines will appear compared to minor ones. For example, if the Rounding Step is 100 and Major Grids is set to 10, major gridlines will be displayed every $1,000, while minor gridlines will be at every $100. This distinction allows traders to better visualize key psychological levels by emphasizing significant price intervals.
Direction : Users can select the gridline direction, choosing between options such as 'Up', 'Down', 'Auto', or 'Neutral'. This setting controls how the gridlines extend relative to the current price level, which can help in analyzing directional trends.
Neutral Direction : This option provides balanced gridlines both above and below the current price, allowing traders to visualize support and resistance levels symmetrically. This is useful for analyzing sideways or ranging markets without directional bias.
Up Direction : The gridlines are tilted upwards, starting from visible lows and extending toward the rounded level at the current price. By choosing Up , traders emphasize an upward sentiment, visualizing price action that aligns with rising trends. This option helps illustrate potential areas where pullbacks may occur, as well as how price might expand upwards in the current market context.
Down Direction : The gridlines are tilted downwards, starting from visible highs and extending toward the rounded level at the current price. Selecting Down allows traders to emphasize a downward sentiment, visualizing how price may expand downwards, which is particularly useful when analyzing downtrends or potential correction levels. The gridlines provide an illustrative view of how price interacts with lower levels during market declines.
Auto Direction : The gridlines automatically adjust their direction based on recent market trends. This adaptive option allows traders to visualize gridlines that dynamically change according to price action, making it suitable for evolving market conditions where the direction is uncertain. Itโs useful for traders looking for an indicator that moves in sync with market shifts and doesnโt require manual adjustment.
Grid Type : Allows users to choose between 'Linear' or 'Fan' grid types. The Linear type creates evenly spaced gridlines that can be either horizontal or tilted, depending on the chosen direction setting, providing a straightforward view of price levels. The Fan type radiates lines from a central point, offering a more dynamic perspective for analyzing price expansions relative to the current price. These grid types introduce experimental visualizations influenced by chart properties, including visible highs, lows, and the current price. Regardless of the configuration, the gridlines will always end at the current bar, which represents a rounded price level, ensuring consistency in how key price areas are displayed.
Extend : This setting allows gridlines to be projected into the future, helping traders see potential levels beyond the current bar. When enabled, the behavior of the extended lines varies based on the selected grid type and direction. For Neutral and Horizontal Linear settings, the extended gridlines maintain their round-number alignment indefinitely. However, for Up , Down , or Auto directions, the angle of the extended gridlines can change dynamically based on the chartโs visible high and low or the latest price action. As a result, extended lines may not continue to align with round-number levels beyond the current bar, reflecting instead the current trend and sentiment of the market. Regardless of direction, extended gridlines remain consistently spaced and either parallel or evenly distributed, ensuring a structured visual representation.
Color Settings : Users can customize the colors for resistance, support, and minor gridlines at the current price. This helps in visually distinguishing between different grid types and their significance on the chart.
Color Options
These configuration options make the Rounded Grid Levels indicator a versatile tool for traders looking to customize their charts based on their personal trading strategies and analytical preferences.
๐ผ๏ธ CHART EXAMPLES ๐ผ๏ธ
The following chart examples illustrate different configurations available in the Rounded Grid Levels indicator. These examples show how variations in grid type, direction, and rounding step settings impact the visualization of price levels. Traders may find that smaller rounding steps are more effective on lower time frames, where precision is key, whereas larger rounding steps help to reduce clutter and highlight key levels on higher time frames. Each image includes a caption to explain the specific configuration used, helping users better understand how to apply these settings in different market conditions.
Smaller Rounding Step (100) : With a smaller rounding step, the gridlines are spaced closely together. This setting is particularly useful for lower time frames where price action is more granular and finer details are needed. It allows traders to track price interactions at narrower levels, but on higher time frames, it may lead to clutter and exceed Pine Script's 500-line limit.
Larger Rounding Step (1000) : With a larger rounding step, the gridlines are spaced farther apart. This visualization is better suited for higher time frames or broader market overviews, allowing users to focus on major psychological levels without overloading the chart. On lower time frames, this may result in fewer actionable levels, but it helps in maintaining clarity and staying within Pine Script's line limit.
Linear Grid Type, Neutral Direction (Traditional Rounded Price Levels) : The Linear gridlines are displayed in a neutral fashion, representing traditional round-number levels with consistent spacing above and below the current price. This layout helps visualize key psychological price levels over time in a straightforward manner.
Linear Grid Type, Down Direction : The Linear gridlines are tilted downwards, remaining parallel and ending at the rounded level at the current price. This setup emphasizes downward market sentiment, allowing traders to visualize price expansion towards lower levels, which is useful when analyzing downtrends or potential correction levels.
Linear Grid Type, Down Direction : The Linear gridlines are tilted downwards, extending from the current price to lower levels. Useful for observing downtrending price movements and visualizing pullback areas during uptrends.
Linear Grid Type, Auto Direction : The Linear gridlines adjust dynamically, tilting either upwards or downwards to align with recent price trends, remaining parallel and ending at the rounded level at the current price. This configuration reflects the current market sentiment and offers traders a flexible way to observe price dynamics as they develop in real time.
Fan Grid Type, Neutral Direction : The fan-shaped gridlines radiate symmetrically from a central point, ending at the rounded level at the current price. This configuration provides an unbiased view of price action, giving traders a balanced visualization of rounded levels without directional influence.
Fan Grid Type, Up Direction : The fan-shaped gridlines originate from lower visible price points and radiate upwards, ending at the rounded level at the current price. This layout helps visualize potential price expansion to higher levels, offering insights into upward momentum while maintaining a dynamic and evolving perspective on market conditions.
Fan Grid Type, Down Direction : The fan-shaped gridlines originate from higher visible price points and radiate downwards, ending at the rounded level at the current price. This setup is particularly useful for observing potential price expansion towards lower levels, illustrating areas where the price might extend during a downtrend.
Fan Grid Type, Auto Direction : The fan-shaped gridlines dynamically adjust, originating from visible chart points based on the current market trend, and radiate outward, ending at the rounded level at the current price. This adaptive visualization offers a continuously evolving representation that aligns with changing market sentiment, helping traders assess price expansion dynamically.
๐ SUMMARY ๐
The Rounded Grid Levels indicator helps traders highlight important round-number price levels on their charts, providing a dynamic way to visualize these psychological areas. With customizable gridline optionsโincluding traditional, tilted, and fan-shaped stylesโusers can adapt the indicator to suit their analysis needs. The gridlines adjust with chart zoom or scale, offering a flexible tool for observing price action, without providing specific trading signals or predictions.
โ๏ธ COMPATIBILITY AND LIMITATIONS โ๏ธ
Asset Compatibility :
The Rounded Grid Levels indicator is compatible with all asset classes, including cryptocurrencies, forex, stocks, and commodities. Users should adjust both the Rounding Step and the Major Grid settings to ensure the correct scale is used for the specific asset. This adjustment ensures that the most relevant round price levels are displayed effectively regardless of the instrument being analyzed. For instance, when analyzing BTCUSD, a higher Rounding Step may be needed compared to forex pairs like EURUSD, and the Major Grid value should also be adjusted to appropriately emphasize significant levels.
Line Limitations in Pine Script :
The Rounded Grid Levels indicator is subject to Pine Script's 500-line limit. This means that it cannot draw more than 500 gridlines on the chart at any given time. The number of gridlines depends directly on the chosen Rounding Step . If the steps are too small, the gridlines will be spaced too closely, causing the indicator to quickly reach the line limit. For example, if Ethereum is trading around $2,500, a Rounding Step of 100 might be appropriate, but a step of 1.00 would create too many gridlines, exceeding Pine Script's limit. Users should consider appropriate settings to avoid running into this constraint.
Runtime Error Considerations
When using the Rounded Grid Levels indicator, users might encounter a runtime error in specific scenarios. This typically happens if the Rounding Step is set too small, causing the indicator to exceed Pine Script's line limit or take too long to process. This can often occur when switching between charts that have significantly different price ranges. Since the Rounding Step requires flexibility to work with a wide variety of assetsโranging from decimals to thousandsโit is not practically limited within the script itself. If a runtime error occurs, the recommended solution is to increase the Rounding Step to a larger value that better matches the current asset's price range.
Runtime Error: If the Rounding Step is too small for the current asset or chart, the indicator may generate a runtime error. Users should increase the Rounding Step to ensure proper visualization.
โ ๏ธ DISCLAIMER โ ๏ธ
The Rounded Grid Levels indicator is not designed as a predictive tool. While it extends gridlines into the future, this extension is purely for visual continuity and does not imply any forecast of future price movements. The primary function of this indicator is to help users visualize significant round number price levels.
The gridlines adjust dynamically based on the visible chart range, ensuring that the most relevant round price levels are displayed. This behavior allows the indicator to adapt to your current view of the market, but it should not be used to predict price movements. The indicator is intended as a visual aid and should be used alongside other tools in a comprehensive market analysis approach.
While gridlines may align with significant price levels in hindsight, they should not be interpreted as indicators of future price movements. Traders are encouraged to adjust settings based on their strategy and market conditions.
๐ง BEYOND THE CODE ๐ง
The Rounded Grid Levels indicator, like other xxattaxx indicators , is designed with education and community collaboration in mind. Its open-source nature encourages exploration, experimentation, and the development of new grid calculation indicators, drawings, and strategies. We hope this indicator serves as a framework and a starting point for future innovations in grid trading.
Your comments, suggestions, and discussions are invaluable in shaping the future of this project. We actively encourage your feedback and contributions, which will directly help us refine and improve the Rounded Grid Levels indicator. We look forward to seeing the creative ways in which you use and enhance this tool.
Crypto Leverage Index(OI Norm. + FR)Crypto Leverage Index (OI Z-Score + Funding Rate Signals)
(A tool for detecting speculative extremes and leverage load in crypto derivatives markets.)
Hello, fellow traders around the globe!
In today's crypto futures market, often perceived as a 'playground for large players' (whales/smart money), catching extreme leverage behavior is crucial for survival. I wanted to come up with an indicator to quickly identify such market extremes by focusing on the two most potent indicators of leveraged action: Open Interest (OI) and Funding Rate (FR). The goal is to ride on the shoulders of the market movers by anticipating their next liquidity-driven actions. hope this helps.
โ IMPORTANT NOTE: This indicator works exclusively on Perpetual Futures or Swap Charts that provide Open Interest (OI) data.
โชย Overview
This indicator provides a standardized view of speculative activity by calculating the Open Interest (OI) Z-Score . This score reveals when the current level of open leverage is abnormally high (premium) or low (discount) relative to its historical mean and volatility. The index is also augmented with Extreme Funding Rate Signals , which plot simple White Dots on the chart when derivative positioning (long or short bias) reaches an unsustainable, overheated level. The combination of OI volume and positioning bias offers a good method to identify potential market reversal zones driven by leverage liquidation risks (short/long squeezes).
โชย Score Components
Open Interest Z-Score (Leverage Load)
The primary component standardizes the Open Interest value over a defined lookback `Period` (default 50). This calculation reveals the statistical deviation of current leverage from the norm.
OI Z-Score = (OI - Mean(OI)) / StDev(OI)
Funding Rate (Positioning Bias)
Calculates the approximate funding rate using a TWAP (Time-Weighted Average Price) of the Perpetual Futures Premium, combined with the standard 0.01% Interest Rate.
โชย Extreme Condition Detection
OI Z-Score Extremes
* Premium Zone (Red Fill) : OI Z-Score is above the user-defined `Threshold` (default 2.0). Indicates high/overstretched leverage.
* Discount Zone (Green Fill) : OI Z-Score is below the user-defined negative threshold (default -2.0). Indicates low/unwinded leverage.
Funding Rate Extreme Signals (White Dots)
These appear as small White Dots ( ยท ) plotted at fixed levels within the indicator pane. The position indicates the bias:
* Top Dot (Excessive Longs) : Triggered when Funding Rate is greater than Abnormal Funding Rate Threshold (e.g. 0.03%). Indicates excessive Long positioning/greed and potential for a short-term reversal (Long Squeeze risk). The dot is plotted at the positive `FR Signal Plot Level`.
* Bottom Dot (Excessive Shorts) : Triggered when Funding Rate is lower than -Abnormal Funding Rate Threshold(e.g. -0.03%). Indicates excessive Short positioning/fear and potential for a short-term reversal (Short Squeeze risk). The dot is plotted at the negative `FR Signal Plot Level`.
โชย Leverage Case Scenarios (Price, OI Dynamics & Context)
The OI Z-Score reflects the premium/discount state of *leverage* (Open Interest) , not the price. The price may not be in a premium or discount area simply because the OI is. OI only indicates the volume of outstanding futures positions. You must observe price action and candlestick patterns alongside the OI movements to determine the true contextual hint. Understanding the relationship between price and Open Interest (OI) change is key to interpreting market movements. The cases listed below represent the most common and thinkable patterns, but do not exhaust all possible market behaviors.
1. Long Build-Up (Price โฒ, OI โฒ): New long positions enter, confirming the rising trend.
2. Short Build-Up (Price โผ, OI โฒ): New short positions enter, confirming the falling trend. Due to the inherently long-biased nature of the crypto market, this scenario is less frequently observed than Long Build-Up.
3. Long Covering/liquidation (Price โผ, OI โผ): Existing longs are closed/liquidated. This activity usually results from Panic Selling or forced long liquidation.
4. Short Covering (Price โฒ, OI โผ): Existing shorts are forced to close (Short Squeeze).
5. Long Trap (Price โฒ, OI โฒ or โผ): Price rises, but OI suggests new positioning that might be trapping longs. Bearish candle pattern can be often shown with the sweep.
6. Short Trap (Price โผ, OI โฒ or โผ): Warning Sign - Price falls, but OI suggests new positioning that might be trapping shorts.
โชย Key Input Parameters
OI Z-Score
* Period (Default: 50)
Determines how many recent bars are used to calculate the rolling mean and volatility (standard deviation) of the Open Interest data.
* Z-Score Threshold (Default: 2.0)
The critical level that the OI Z-Score must cross to be considered 'extreme' (overstretched leverage).
Funding Rate
* Abnormal FR Threshold (Default: 0.03)
The absolute percentage value (e.g., 0.03%) that the Funding Rate must exceed or fall below to trigger an extreme signal dot.
* FR Signal Plot Level (Default: 4.0)
Sets the fixed vertical position (Y-level) on the Z-Score chart where the Funding Rate signal dots will appear. (e.g., 4.0 plots the dot at the Z-Score +-4.0 level).
Disclaimer
This script is for educational and informational purposes only and does not constitute financial advice or investment recommendations. Trading cryptocurrencies involves significant risk and you are solely responsible for your own investment decisions, based on your financial situation, objectives, and risk tolerance. The author assumes no liability for losses arising from the use of this indicator.
Double Median SD Bands | MisinkoMasterThe Double Median SD Bands (DMSDB) is a trend-following tool designed to capture market direction in a way that balances responsiveness and smoothness, filtering out excessive noise without introducing heavy lag.
Think of it like a house:
A jail (too restrictive) makes you miss opportunities.
No house at all (too unsafe) leaves you exposed to false signals.
DMSDB acts like a comfortable house with windowsโprotecting you from the noise while still letting you see whatโs happening in the market.
๐ Methodology
The script works in the following steps:
Standard Deviation (SD) Calculation
Computes the standard deviation of the selected price source (ohlc4 by default).
The user can choose whether to use biased (sample) or unbiased (population) standard deviation.
Raw Bands Construction
Upper Band = source + (SD ร multiplier)
Lower Band = source - (SD ร multiplier)
The multiplier can be adjusted for tighter or looser bands.
First Median Smoothing
Applies a median filter over half of the length (len/2) to both bands.
This reduces noise without creating excessive lag.
Second Median Smoothing
Applies another median filter over โlen to the already smoothed bands.
This produces a balance:
Cutting the length โ maintains responsiveness.
Median smoothing โ reduces whipsaws.
The combination creates a fast yet clean band system ideal for trend detection.
๐ Trend Logic
The trend is detected based on price crossing the smoothed bands:
Long / Bullish (Purple) โ when price crosses above the upper band.
Short / Bearish (Gold) โ when price crosses below the lower band.
Neutral โ when price remains between the bands.
๐จ Visualization
Upper and lower bands are plotted as colored lines.
The area between the bands is filled with a transparent zone that reflects the current bias:
Purple shading = Bullish zone.
Golden shading = Bearish zone.
This creates a visual tunnel for trend confirmation, helping traders quickly identify whether price action is trending or consolidating.
โก Features
Adjustable Length parameter (len) for dynamic control.
Adjustable Band Multiplier for volatility adaptation.
Choice between biased vs. unbiased standard deviation.
Double median smoothing for clarity + responsiveness.
Works well on cryptocurrencies (e.g., BTCUSD) but is flexible enough for stocks, forex, and indices.
โ
Use Cases
Trend Following โ Ride trends by staying on the correct side of the bands.
Entry Timing โ Use crossovers above/below bands for entry triggers.
Filter for Other Strategies โ Can serve as a directional filter to avoid trading against the trend.
โ ๏ธ Limitations & Notes
This is a trend-following tool, so it will perform best in trending conditions.
In sideways or choppy markets, whipsaws may still occur (although smoothing reduces them significantly).
The indicator is not a standalone buy/sell system. For best results, combine with volume, momentum, or higher-timeframe confluence.
All of this makes for a really unique & original tool, as it removes noise but keeps good responsitivity, using methods from many different principles which make for a smooth a very useful tool
Vin's Playzone Strategy How it works
Playzone is a very simple system, utilizing just two exponential moving
averages. The 'Zones' in which different 'actions' should be taken is
highlighted with different colors on the chart. Calculations for the zones
are based on the relative position of price to the two EMA lines and the
relationship between the two EMAs
How to use
The basic method for using Playzone is to follow the green/red color.
Buy when bar closes in green.
Sell when bar closes in red.
Using it this way is safe but slow and is expected to have around 35-40%
accuracy, while yielding around 2-3 profit factors. The system works best
on larger time frames.
The more advanced method uses the zones to switch between different
trading system and biases, or in conjunction with other indicators.
example 1:
Buy when Yellow-Green and Bullish Divergence between price and RSI is visible,
if not Buy on Green and vise-versa
example 2:
Set up a long-biased grid and trade long only when actionzone is in green
change the bias to short when actionzone turns to te bearish side(red)
(Look at colors on a larger time frame)
"We let the market tell us what to do, Not to outguess what the market gonna do."
CDC ActionZone V3 2020## CDC ActionZone V3 2020 ##
This is an update to my earlier script, CDC ActionZone V2
The two scripts works slightly differently with V3 reacting slightly faster.
The main update is focused around conforming the standard to Pine Script V4.
## How it works ##
ActionZone is a very simple system, utilizing just two exponential moving
averages. The 'Zones' in which different 'actions' should be taken is
highlighted with different colors on the chart. Calculations for the zones
are based on the relative position of price to the two EMA lines and the
relationship between the two EMAs
CDCActionZone is your barebones basic, tried and true, trend following system
that is very simple to follow and has also proven to be relatively safe.
## How to use ##
The basic method for using ActionZone is to follow the green/red color.
Buy when bar closes in green.
Sell when bar closes in red.
There is a small label to help with reading the buy and sell signal.
Using it this way is safe but slow and is expected to have around 35-40%
accuracy, while yielding around 2-3 profit factors. The system works best
on larger time frames.
The more advanced method uses the zones to switch between different
trading system and biases, or in conjunction with other indicators.
example 1:
Buy when blue and Bullish Divergence between price and RSI is visible,
if not Buy on Green and vise-versa
example 2:
Set up a long-biased grid and trade long only when actionzone is in
green, yellow or orange.
change the bias to short when actionzone turns to te bearish side
(red, blue, aqua)
(Look at colors on a larger time frame)
## Note ##
The price field is set to close by default. change to either HL2 or OHLC4
when using the system in intraday timeframes or on market that does not close
(ie. Cryptocurrencies)
## Note2 ##
The fixed timeframe mode is for looking at the current signal on a larger time frame
ie. When looking at charts on 1h you can turn on fixed time frame on 1D to see the
current 'zone' on the daily chart plotted on to the hourly chart.
This is useful if you wanted to use the system's 'Zones' in conjunction with other
types of signals like Stochastic RSI, for example.
Major exchages total Open interest & Long/Short OI trends๐ Indicator: Major Exchanges Total OI & Long/Short Trends
This Pine Scriptโข indicator is designed to provide a comprehensive analysis of Open Interest (OI) and Long/Short position trends across major cryptocurrency exchanges (Binance, Bybit, OKX, Bitget, HTX, Deribit). It serves as a powerful tool for traders seeking to understand market liquidity, participant positioning, and overall market sentiment.
๐ Key Features and Functionalities
Aggregated Multi-Exchange Open Interest (OI):
Consolidates real-time Open Interest data from user-selected major cryptocurrency exchanges.
Provides a unified view of the total OI, offering insights into the collective market liquidity and the aggregate size of participants' open positions.
Visualized Combined OI Candles:
Presents the aggregated total OI data in a candlestick chart format.
Displays the Open, High, Low, and Close of the combined OI, with color variations indicating increases or decreases from the previous period. This enables intuitive visualization of OI trend shifts.
Estimated Long/Short OI and Visualization:
Calculates and visualizes estimated Long and Short position Open Interest based on the total aggregated OI data.
Estimation Logic:
Employs a sophisticated logic that considers both price changes and OI fluctuations to infer the balance between Long and Short positions. For instance, an increase in both price and OI may suggest an accumulation of Long positions, while a price decrease coupled with an OI increase might indicate growing Short positions.
Initial 50:50 Ratio:
The estimation for Long/Short OI begins with an assumption of a 50:50 ratio at the initial data point available for the selected timeframe. This establishes a neutral baseline, from which subsequent price and OI changes drive the divergence and evolution of the estimated Long/Short balance.
Flexible Visualization Options:
Allows users to display Long/Short OI data in either line or candlestick styles, with customizable color schemes. This flexibility aids in clearly discerning bullish or bearish positioning trends.
๐ก Development Background
The development of this indicator stems from the critical importance of Open Interest data in the cryptocurrency derivatives market. Recognizing the limitations of analyzing individual exchange OI in isolation, the primary objective was to integrate data from leading exchanges to offer a holistic perspective on market sentiment and overall positioning dynamics.
The inclusion of the Long/Short position estimation feature is crucial for deciphering the specific directional biases of market participants, which is often not evident from raw OI data alone. This enables a deeper understanding of how positions are being accumulated or liquidated, moving beyond simple OI change analysis.
Furthermore, a key design consideration was to leverage the characteristic where the indicator's data start point dynamically adjusts with the chart's timeframe selection. This allows for the analysis of short-term Long/Short trends on shorter timeframes and long-term trends on longer timeframes. This inherent flexibility empowers traders to conduct analyses across various time scales, aligning with their diverse trading strategies.
๐ Trading Applications
Leveraging Combined Open Interest (OI):
Trend Confirmation: A sustained increase in total OI signifies growing market interest and capital inflow, potentially confirming the strength of an existing trend. Conversely, decreasing OI may suggest diminishing participant interest or widespread position liquidation.
Validation of Price Extremes: If price forms a new high but OI fails to increase or declines, it could signal a potential trend reversal (divergence). Conversely, a sharp increase in OI during a price decline might indicate a surge in short positions or renewed selling pressure.
Identifying Volatility Triggers: Monitoring rapid shifts in OI during significant news events or market catalysts can help assess immediate market reactions and liquidity changes.
๐Utilizing Long/Short OI Trends
Assessing Market Bias: A sustained dominance or rapid increase in Long OI suggests a prevalent bullish sentiment, which could inform decisions to enter or maintain long positions. The inverse scenario indicates bearish sentiment and potential short entry opportunities.
Anticipating Squeezes: The indicator can help identify scenarios conducive to short or long squeezes. Excessive short positioning followed by a price uptick can trigger a short squeeze, leading to rapid price appreciation. Conversely, an oversupply of long positions preceding a price drop can result in a long squeeze and sharp declines.
Divergence Analysis: Divergences between price action and Long/Short OI estimates can signal potential trend reversals. For example, if price is rising but the increase in Long OI slows down or Short OI begins to grow, it may suggest weakening buying pressure.
๐Timeframe-Specific Trend Analysis:
Shorter Timeframes (e.g., 1m, 5m, 15m): Ideal for identifying short-term shifts in participant positioning, beneficial for day trading and scalping strategies. Provides insights into immediate market reactions to price movements.
Longer Timeframes (e.g., 1h, 4h, Daily): Valuable for evaluating broader positioning trends and the sustainability or potential reversal of medium-to-long-term trends. Offers a macro perspective on Long/Short dynamics, suitable for swing trading or long-term investment strategies.
This indicator integrates complex market data, provides nuanced Long/Short position estimations, and offers multi-timeframe analytical capabilities, empowering traders to make more informed and strategic decisions.
VWAP Trend
**Overview**
The VWAP Trend indicator is a volume-weighted price analysis tool that visualizes the relationship between price and the anchored Volume Weighted Average Price (VWAP) over different timeframes. This script is designed to reveal when the market is trending above or below its volume-weighted equilibrium point, providing a clear framework for identifying directional bias, trend strength, and potential reversals.
By combining an anchored VWAP with exponential smoothing and a secondary trend EMA, the indicator helps traders distinguish between short-term price fluctuations and genuine volume-supported directional moves.
**Core Concept**
VWAP (Volume Weighted Average Price) represents the average price of an asset weighted by traded volume. It reflects where the majority of trading activity has taken place within a chosen period, serving as a critical reference level for institutions and professional traders.
This indicator extends the traditional VWAP concept by:
1. Allowing users to **anchor VWAP to different timeframes** (Daily, Weekly, or Monthly).
2. Applying **smoothing** to create a stable reference curve less prone to noise.
3. Overlaying a **trend EMA** to identify whether current price momentum aligns with or diverges from VWAP equilibrium.
The combination of these elements produces a visual representation of priceโs relationship to its fair value across time, helping to identify accumulation and distribution phases.
**Calculation Methodology**
1. **Anchored VWAP Calculation:**
The script resets cumulative volume and cumulative volumeโprice data at the start of each new VWAP session (based on the selected anchor timeframe). It continuously accumulates the product of price and volume, dividing this by total volume to compute the current VWAP value.
2. **Smoothing Process:**
The raw VWAP line is smoothed using an Exponential Moving Average (EMA) of user-defined length, producing a cleaner, more stable trend curve that minimizes intraperiod noise.
3. **Trend Determination:**
An additional EMA is calculated on the closing price. By comparing the position of this EMA to the smoothed VWAP, the indicator determines the prevailing market bias:
* When the trend EMA is above the smoothed VWAP, the market is considered to be in an **uptrend**.
* When the trend EMA is below the smoothed VWAP, the market is classified as a **downtrend**.
**Visual Structure**
The indicator uses color dynamics and chart overlays to make interpretation intuitive:
* **Smoothed VWAP Line:** The main trend reference, colored blue during bullish conditions and orange during bearish conditions.
* **Price Fill Region:** The area between the smoothed VWAP and price is filled with a translucent color matching the current trend, visually representing whether price is trading above or below equilibrium.
* **Trend EMA (implicit):** Although not separately plotted, it drives the color state of the VWAP, ensuring seamless visual transitions between bullish and bearish conditions.
**Inputs and Parameters**
* **VWAP Timeframe:** Choose between Daily, Weekly, or Monthly anchoring. This determines the reset frequency for cumulative volume and price data.
* **VWAP Smoothing Length:** Defines how many periods are used to smooth the VWAP line. Shorter values produce a more reactive line; longer values create smoother, steadier signals.
* **Trend EMA Length:** Sets the period for the trend detection EMA applied to price. Adjust this to calibrate how quickly the indicator reacts to directional changes.
**Interpretation and Use Cases**
* **Trend Confirmation:** When price and the trend EMA both remain above the smoothed VWAP, the market is showing strong bullish control. Conversely, consistent price action below the VWAP suggests sustained bearish sentiment.
* **Fair Value Assessment:** VWAP serves as a dynamic equilibrium level. Price repeatedly reverting to this line indicates consolidation or fair value zones, while strong directional moves away from VWAP highlight momentum phases.
* **Institutional Benchmarking:** Because large market participants often benchmark entries and exits relative to VWAP, this indicator helps align retail analysis with institutional logic.
* **Reversal Detection:** Sudden crossovers of the trend EMA relative to the VWAP can signal potential reversals or shifts in momentum strength.
**Trading Applications**
* **Trend Following:** Use VWAPโs direction and color state to determine trade bias. Long entries are favored when the VWAP turns blue, while short entries align with orange phases.
* **Mean Reversion:** In ranging conditions, traders may look for price deviations far above or below VWAP as potential reversion opportunities.
* **Multi-Timeframe Confluence:** Combine the Daily VWAP Trend with higher anchor periods (e.g., Weekly or Monthly) to confirm larger trend structure.
* **Support and Resistance Mapping:** VWAP often acts as a strong intraday or session-level support/resistance zone. The smoothed version refines this behavior into a cleaner, more reliable reference.
**Originality and Innovation**
The VWAP Trend indicator stands apart from conventional VWAP scripts through several original features:
1. **Anchor Flexibility:** Most VWAP indicators fix the anchor to a specific session (like daily). This version allows switching between Daily, Weekly, and Monthly anchors dynamically, adapting to various trading styles and time horizons.
2. **Volume-Weighted Smoothing:** The use of an EMA smoothing layer over the raw VWAP provides enhanced stability without compromising responsiveness, delivering a more analytically consistent signal.
3. **EMA-Based Trend Comparison:** By introducing a second trend EMA, the indicator creates a comparative framework that merges volume-weighted price analysis with classical momentum tracking โ a rare and powerful combination.
4. **Adaptive Visual System:** The color-shifting and shaded fill between VWAP and price are integrated into a single, lightweight structure, giving traders immediate insight into market bias without the clutter of multiple overlapping indicators.
**Advantages**
* Adaptable to any market, timeframe, or trading style.
* Provides both equilibrium (VWAP) and momentum (EMA) perspectives.
* Smooths out noise while retaining the integrity of volume-based price dynamics.
* Enhances situational awareness through intuitive color-coded visualization.
* Ideal for professional, swing, and intraday traders seeking context-driven market direction.
**Summary**
The VWAP Trend indicator is a modern enhancement of the classical VWAP methodology. By merging anchored volume-weighted analysis with smoothed trend detection and visual state feedback, it provides a comprehensive perspective on market equilibrium and directional strength. It is built for traders who seek more than static price references โ offering an adaptive, volume-aware framework for identifying market trends, reversals, and fair-value zones with precision and clarity.
Opening Range Breakout with Multi-Timeframe Liquidity]โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
OPENING RANGE BREAKOUT WITH MULTI-TIMEFRAME LIQUIDITY
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
A professional Opening Range Breakout (ORB) indicator enhanced with multi-timeframe liquidity detection, trading session visualization, volume analysis, and trend confirmation tools. Designed for intraday trading with comprehensive alert system.
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
WHAT THIS INDICATOR DOES
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
This indicator combines multiple trading concepts:
- Opening Range Breakout (ORB) - Customizable time period detection with automatic high/low identification
- Multi-Timeframe Liquidity - HTF (Higher Timeframe) and LTF (Lower Timeframe) key level detection
- Trading Sessions - Tokyo, London, New York, and Sydney session visualization
- Volume Analysis - Volume spike detection and strength measurement
- Multi-Timeframe Confirmation - Trend bias from higher timeframes
- EMA Integration - Trend filter and dynamic support/resistance
- Smart Alerts - Quality-filtered breakout notifications
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
HOW IT WORKS
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
OPENING RANGE BREAKOUT (ORB):
Concept:
The Opening Range is a period at the start of a trading session where price establishes an initial high and low. Breakouts beyond this range often indicate the direction of the day's trend.
Detection Method:
- Default: 15-minute opening range (configurable)
- Custom Range: Set specific session times with timezone support
- Automatically identifies ORH (Opening Range High) and ORL (Opening Range Low)
- Tracks ORB mid-point for reference
Range Establishment:
1. Session starts (or custom time begins)
2. Tracks highest high and lowest low during the period
3. Range confirmed at end of opening period
4. Levels extend throughout the session
Breakout Detection:
- Bullish Breakout: Close above ORH
- Bearish Breakout: Close below ORL
- Mid-point acts as bias indicator
Visual Display:
- Shaded box during range formation
- Horizontal lines for ORH, ORL, and mid-point
- Labels showing level values
- Color-coded fills based on selected method
Fill Color Methods:
1. Session Comparison:
- Green: Current OR mid > Previous OR mid
- Red: Current OR mid < Previous OR mid
- Gray: Equal or first session
- Shows day-over-day momentum
2. Breakout Direction (Recommended):
- Green: Price currently above ORH (bullish breakout)
- Red: Price currently below ORL (bearish breakout)
- Gray: Price inside range (no breakout)
- Real-time breakout status
MULTI-TIMEFRAME LIQUIDITY:
Two-Tier System for comprehensive level identification:
HTF (Higher Timeframe) Key Liquidity:
- Default: 4H timeframe (configurable to Daily, Weekly)
- Identifies major institutional levels
- Uses pivot detection with adjustable parameters
- Suitable for swing highs/lows where large orders rest
LTF (Lower Timeframe) Key Liquidity:
- Default: 1H timeframe (configurable)
- Provides precision entry/exit levels
- Finer granularity for intraday trading
- Captures minor swing points
Calculation Method:
- Pivot high/low detection algorithm
- Configurable left bars (lookback) and right bars (confirmation)
- Timeframe multiplier for accurate multi-timeframe detection
- Automatic level extension
Mitigation System:
- Tracks when levels are swept (broken)
- Configurable mitigation type: Wick or Close-based
- Option to remove or show mitigated levels
- Display limit prevents chart clutter
Asset-Specific Optimization:
The indicator includes quick reference settings for different assets:
- Major Forex (EUR/USD, GBP/USD): Default settings optimal
- Crypto (BTC/ETH): Left=12, Right=4, Display=7
- Gold: HTF=1D, Left=20
TRADING SESSIONS:
Four Major Sessions with Full Customization:
Tokyo Session:
- Default: 04:00-13:00 UTC+4
- Asian trading hours
- Often sets daily range
London Session:
- Default: 11:00-20:00 UTC+4
- Highest liquidity period
- Major institutional activity
New York Session:
- Default: 16:00-01:00 UTC+4
- US market hours
- High-impact news events
Sydney Session:
- Default: 01:00-10:00 UTC+4
- Earliest Asian activity
- Lower volatility
Session Features:
- Shaded background boxes
- Session name labels
- Optional open/close lines
- Session high/low tracking with colored lines
- Each session has independent color settings
- Fully customizable times and timezones
VOLUME ANALYSIS:
Volume-Based Trade Confirmation:
Volume MA:
- Configurable period (default: 20)
- Establishes average volume baseline
- Used for spike detection
Volume Spike Detection:
- Identifies when volume exceeds MA * multiplier
- Default: 1.5x average volume
- Confirms breakout strength
Volume Strength Measurement:
- Calculates current volume as percentage of average
- Shows relative volume intensity
- Used in alert quality filtering
High Volume Bars:
- Identifies bars above 50th percentile
- Additional confirmation layer
- Indicates institutional participation
MULTI-TIMEFRAME CONFIRMATION:
Trend Bias from Higher Timeframes:
HTF 1 (Trend):
- Default: 1H timeframe
- Uses EMA to determine intermediate trend
- Compares current timeframe EMA to HTF EMA
HTF 2 (Bias):
- Default: 4H timeframe
- Uses 50 EMA for longer-term bias
- Confirms overall market direction
Bias Classifications:
- Bullish Bias: HTF close > HTF 50 EMA AND Current EMA > HTF1 EMA
- Bearish Bias: HTF close < HTF 50 EMA AND Current EMA < HTF1 EMA
- Neutral Bias: Mixed signals between timeframes
EMA Stack Analysis:
- Compares EMA alignment across timeframes
- +1: Bullish stack (lower TF EMA > higher TF EMA)
- -1: Bearish stack (lower TF EMA < higher TF EMA)
- 0: Neutral/crossed
Usage:
- Filters false breakouts
- Confirms trend direction
- Improves trade quality
EMA INTEGRATION:
Dynamic EMA for Trend Reference:
Features:
- Configurable period (default: 20)
- Customizable color and width
- Acts as dynamic support/resistance
- Trend filter for ORB trades
Application:
- Above EMA: Favor long breakouts
- Below EMA: Favor short breakouts
- EMA cross: Potential trend change
- Distance from EMA: Momentum gauge
SMART ALERT SYSTEM:
Quality-Filtered Breakout Notifications:
Alert Types:
1. Standard ORB Breakout
2. High Quality ORB Breakout
Quality Criteria:
- Volume Confirmation: Volume > 1.2x average
- MTF Confirmation: Bias aligned with breakout direction
Standard Alert:
- Basic breakout detection
- Price crosses ORH or ORL
- Icon: ๐ (bullish) or ๐ป (bearish)
High Quality Alert:
- Both volume AND MTF confirmed
- Stronger probability setup
- Icon: ๐โญ (bullish) or ๐ปโญ (bearish)
Alert Information Includes:
- Alert quality rating
- Breakout level and current price
- Volume strength percentage (if enabled)
- MTF bias status (if enabled)
- Recommended action
One Alert Per Bar:
- Prevents alert spam
- Uses flag system to track sent alerts
- Resets on new ORB session
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
HOW TO USE
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
OPENING RANGE SETUP:
Basic Configuration:
1. Select time period for opening range (default: 15 minutes)
2. Choose fill color method (Breakout Direction recommended)
3. Enable historical data display if needed
Custom Range (Advanced):
1. Enable Custom Range toggle
2. Set specific session time (e.g., 0930-0945)
3. Select appropriate timezone
4. Useful for specific market opens (NYSE, LSE, etc.)
LIQUIDITY LEVELS SETUP:
Quick Configuration by Asset:
- Forex: Use default settings (Left=15, Right=5)
- Crypto: Set Left=12, Right=4, Display=7
- Gold: Set HTF=1D, Left=20
HTF Liquidity:
- Purpose: Major support/resistance levels
- Recommended: 4H for day trading, 1D for swing trading
- Use as profit targets or reversal zones
LTF Liquidity:
- Purpose: Entry/exit refinement
- Recommended: 1H for day trading, 4H for swing trading
- Use for position management
Mitigation Settings:
- Wick-based: More sensitive (default)
- Close-based: More conservative
- Remove or Show mitigated levels based on preference
TRADING SESSIONS SETUP:
Enable/Disable Sessions:
- Master toggle for all sessions
- Individual session controls
- Show/hide session names
Session High/Low Lines:
- Enable to see session extremes
- Each session has custom colors
- Useful for range trading
Customization:
- Adjust session times for your broker
- Set timezone to match your location
- Customize colors for visibility
VOLUME ANALYSIS SETUP:
Enable Volume Analysis:
1. Toggle on Volume Analysis
2. Set MA length (20 recommended)
3. Adjust spike multiplier (1.5 typical)
Usage:
- Confirm breakouts with volume
- Identify climactic moves
- Filter false signals
MULTI-TIMEFRAME SETUP:
HTF Selection:
- HTF 1 (Trend): 1H for day trading, 4H for swing
- HTF 2 (Bias): 4H for day trading, 1D for swing
Interpretation:
- Trade only with bias alignment
- Neutral bias: Be cautious
- Bias changes: Potential reversals
EMA SETUP:
Configuration:
- Period: 20 for responsive, 50 for smoother
- Color: Choose contrasting color
- Width: 1-2 for visibility
Usage:
- Filter trades: Long above, Short below
- Dynamic support/resistance reference
- Trend confirmation
ALERT SETUP:
TradingView Alert Creation:
1. Enable alerts in indicator settings
2. Enable ORB Breakout Alerts
3. Right-click chart โ Add Alert
4. Select this indicator
5. Choose "Any alert() function call"
6. Configure delivery method (mobile, email, webhook)
Alert Filtering:
- All alerts include quality rating
- High Quality alerts = Volume + MTF confirmed
- Standard alerts = Basic breakout only
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
TRADING STRATEGIES
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
CLASSIC ORB STRATEGY:
Setup:
1. Wait for opening range to complete
2. Price breaks and closes above ORH or below ORL
3. Volume > average (if enabled)
4. MTF bias aligned (if enabled)
Entry:
- Bullish: Buy on break above ORH
- Bearish: Sell on break below ORL
- Consider retest entries for better risk/reward
Stop Loss:
- Bullish: Below ORL or range mid-point
- Bearish: Above ORH or range mid-point
- Adjust based on volatility
Targets:
- Initial: Range width extension (ORH + range width)
- Secondary: HTF liquidity levels
- Final: Session high/low or major support/resistance
ORB + LIQUIDITY CONFLUENCE:
Enhanced Setup:
1. Opening range established
2. HTF liquidity level near or beyond ORH/ORL
3. Breakout occurs with volume
4. Price targets the liquidity level
Entry:
- Enter on ORB breakout
- Target the HTF liquidity level
- Use LTF liquidity for position management
Management:
- Partial profits at ORB + range width
- Move stop to breakeven at LTF liquidity
- Final exit at HTF liquidity sweep
ORB REJECTION STRATEGY (Counter-Trend):
Setup:
1. Price breaks above ORH or below ORL
2. Weak volume (below average)
3. MTF bias opposite to breakout
4. Price closes back inside range
Entry:
- Failed bullish break: Short below ORH
- Failed bearish break: Long above ORL
Stop Loss:
- Beyond the failed breakout level
- Or beyond session extreme
Target:
- Opposite end of opening range
- Range mid-point for partial profit
SESSION-BASED ORB TRADING:
Tokyo Session:
- Typically narrower ranges
- Good for range trading
- Wait for London open breakout
London Session:
- Highest volume and volatility
- Strong ORB setups
- Major liquidity sweeps common
New York Session:
- Strong trending moves
- News-driven volatility
- Good for momentum trades
Sydney Session:
- Quieter conditions
- Suitable for range strategies
- Sets up Tokyo session
EMA-FILTERED ORB:
Rules:
- Only take bullish breaks if price > EMA
- Only take bearish breaks if price < EMA
- Ignore counter-trend breaks
Benefits:
- Reduces false signals
- Aligns with larger trend
- Improves win rate
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
CONFIGURATION GUIDE
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
OPENING RANGE SETTINGS:
Time Period:
- 15 min: Standard for most markets
- 30 min: Wider range, fewer breakouts
- 60 min: For slower markets or swing trades
Custom Range:
- Use for specific market opens
- NYSE: 0930-1000 EST
- LSE: 0800-0830 GMT
- Set timezone to match exchange
Historical Display:
- Enable: See all previous session data
- Disable: Cleaner chart, current session only
LIQUIDITY SETTINGS:
Left Bars (5-30):
- Lower: More frequent, sensitive levels
- Higher: Fewer, more significant levels
- Recommended: 15 for most markets
Right Bars (1-25):
- Confirmation period
- Higher: More reliable, less frequent
- Recommended: 5 for balance
Display Limit (1-20):
- Number of active levels shown
- Higher: More context, busier chart
- Recommended: 7 for clarity
Extension Options:
- Short: Levels visible near formation
- Current: Extended to current bar (recommended)
- Max: Extended indefinitely
VOLUME SETTINGS:
MA Length (5-50):
- Shorter: More responsive to spikes
- Longer: Smoother baseline
- Recommended: 20 for balance
Spike Multiplier (1.0-3.0):
- Lower: More sensitive spike detection
- Higher: Only extreme spikes
- Recommended: 1.5 for day trading
MULTI-TIMEFRAME SETTINGS:
HTF 1 (Trend):
- 5m chart: Use 15m or 1H
- 15m chart: Use 1H or 4H
- 1H chart: Use 4H or 1D
HTF 2 (Bias):
- One level higher than HTF 1
- Provides longer-term context
- Don't use same as HTF 1
EMA SETTINGS:
Length:
- 20: Responsive, more signals
- 50: Smoother, stronger filter
- 200: Long-term trend only
Style:
- Choose contrasting color
- Width 1-2 for visibility
- Match your trading style
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
BEST PRACTICES
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Chart Timeframe Selection:
- ORB Trading: Use 5m or 15m charts
- Session Review: Use 1H or 4H charts
- Swing Trading: Use 1H or 4H charts
Quality Over Quantity:
- Wait for high-quality alerts (volume + MTF)
- Avoid trading every breakout
- Focus on confluence setups
Risk Management:
- Position size based on range width
- Wider ranges = smaller positions
- Use stop losses always
- Take partial profits at targets
Market Conditions:
- Best results in trending markets
- Reduce position size in choppy conditions
- Consider session overlaps for volatility
- Avoid trading near major news if inexperienced
Continuous Improvement:
- Track win rate by session
- Note which confluence factors work best
- Adjust settings based on market volatility
- Review performance weekly
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
PERFORMANCE OPTIMIZATION
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
This indicator is optimized with:
- max_bars_back declarations for efficient processing
- Conditional calculations based on enabled features
- Proper memory management for drawing objects
- Minimal recalculation on each bar
Best Practices:
- Disable unused features (sessions, MTF, volume)
- Limit historical display to reduce rendering
- Use appropriate timeframe for your strategy
- Clear old drawing objects periodically
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
EDUCATIONAL DISCLAIMER
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
This indicator combines established trading concepts:
- Opening Range Breakout theory (price action)
- Liquidity level detection (pivot analysis)
- Session-based trading (time-of-day patterns)
- Volume analysis (confirmation technique)
- Multi-timeframe analysis (trend alignment)
All calculations use standard technical analysis methods:
- Pivot high/low detection algorithms
- Moving averages for trend and volume
- Session time filtering
- Timeframe security functions
The indicator identifies potential trading setups but does not predict future price movements. Success requires proper application within a complete trading strategy including risk management, position sizing, and market context.
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
USAGE DISCLAIMER
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
This tool is for educational and analytical purposes. Opening Range Breakout trading involves substantial risk. The alert system and quality filters are designed to identify potential setups but do not guarantee profitability. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results. Trading intraday breakouts requires experience and discipline.
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
CREDITS & ATTRIBUTION
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
ORIGINAL SOURCE:
This indicator builds upon concepts from LuxAlgo's-ORB
F & W SMC Alerthis script is a custom TradingView indicator designed to combine elements of a trendโfollowing VWAP approach (inspired by the โFabioโ strategy) with a smartโmoneyโconcepts framework (inspired by Waqar Asim). Hereโs what it does:
* **Directional bias:** It calculates a 15โminute VWAP and compares the current 15โminute close to it. When price is above the 15โminute VWAP, the script assumes a long bias; when below, a short bias. This reflects the trendโfollowing aspect of the Fabio strategy.
* **Liquidity sweeps:** Using recent pivot highs and lows on the current timeframe, it identifies when price takes out a recent high (for potential longs) or low (for potential shorts). This represents a โliquidity sweepโ โ a fake breakout that collects stops and signals a possible reversal or continuation.
* **Break of structure (BOS):** After a sweep, the script confirms that price is breaking away from the swept level (i.e., higher than recent highs for longs or lower than recent lows for shorts). This BOS confirmation helps avoid false signals.
* **Entry filters:** For a long setup, the bias must be long, there must be a liquidity sweep followed by a BOS, and price must reclaim the currentโtimeframe VWAP. For a short setup, the opposite conditions apply (short bias, sweep + BOS to the downside, and price rejecting the VWAP).
* **Alerts and plot:** It provides two alert conditions (โFabioโWaqar Long Setupโ and โFabioโWaqar Short Setupโ) that you can attach to notifications. It also plots the intraday VWAP on your chart for visual reference.
In short, this script watches for a confluence of trend direction, liquidity sweeps, structural shifts, and VWAP reclaim/rejection, and then notifies you when those conditions align. You can use it as an alerting tool to identify highโprobability setups based on these combined strategies.
Fabio + Waqar SMC AlertThis script is a custom TradingView indicator designed to combine elements of a trendโfollowing VWAP approach (inspired by the โFabioโ strategy) with a smartโmoneyโconcepts framework (inspired by Waqar Asim). Hereโs what it does:
* **Directional bias:** It calculates a 15โminute VWAP and compares the current 15โminute close to it. When price is above the 15โminute VWAP, the script assumes a long bias; when below, a short bias. This reflects the trendโfollowing aspect of the Fabio strategy.
* **Liquidity sweeps:** Using recent pivot highs and lows on the current timeframe, it identifies when price takes out a recent high (for potential longs) or low (for potential shorts). This represents a โliquidity sweepโ โ a fake breakout that collects stops and signals a possible reversal or continuation.
* **Break of structure (BOS):** After a sweep, the script confirms that price is breaking away from the swept level (i.e., higher than recent highs for longs or lower than recent lows for shorts). This BOS confirmation helps avoid false signals.
* **Entry filters:** For a long setup, the bias must be long, there must be a liquidity sweep followed by a BOS, and price must reclaim the currentโtimeframe VWAP. For a short setup, the opposite conditions apply (short bias, sweep + BOS to the downside, and price rejecting the VWAP).
* **Alerts and plot:** It provides two alert conditions (โFabioโWaqar Long Setupโ and โFabioโWaqar Short Setupโ) that you can attach to notifications. It also plots the intraday VWAP on your chart for visual reference.
In short, this script watches for a confluence of trend direction, liquidity sweeps, structural shifts, and VWAP reclaim/rejection, and then notifies you when those conditions align. You can use it as an alerting tool to identify highโprobability setups based on these combined strategies.
