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.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ 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.
⚖️ 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 dimensions—Momentum, Volatility, and Trend Structure—into 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:
• 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.
• 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.
• 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" — specifically, the divergence between short-term and long-term volatility baselines—prior 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.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• 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.
🔍 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.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ 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
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• 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.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ 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
• 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.
• 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.
• 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
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• 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
🚦 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.
• 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).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ 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.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ 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.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ 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.
◦ 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:
• 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.
• 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.
• 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.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ 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.
◦ 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.
◦ 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.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• 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.
• Visuals: Labeled signals appear above/below specific candles.
• 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.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• 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.
• Visuals: Triangle or circle glows near the price bars.
• 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.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ 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)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• 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 (5.0–7.0 / 3.0–5.0): 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)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• 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
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• 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
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• 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
• 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.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• 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)
• 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.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ 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.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ 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.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ 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.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ 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.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ 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.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ 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.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ 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.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ 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.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ 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.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 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:
🚀 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.
🎯 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.
🛡️ 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.
💡 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.
⚠️ 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 — Volatility, Momentum, and Structure — 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
◦ 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.
◦ 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.
◦ 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.
◦ 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.
Signals
Structure Breakout - Buy Sell IndicatorStructure Breakout - Buy Sell Indicator
📈 OVERVIEW:
A minimalist indicator that identifies market structure breakouts using swing point analysis.
Displays clear blue buy arrows and red sell arrows when price breaks key swing levels.
🔧 HOW IT WORKS:
1. Identifies swing highs and lows using configurable lookback period
2. Triggers BUY signal (blue arrow) when price closes above previous swing high
3. Triggers SELL signal (red arrow) when price closes below previous swing low
4. Uses clean visual arrows without cluttering the chart
⚙️ KEY FEATURES:
• Clean, uncluttered visual signals
• Customizable sensitivity period
• Blue arrows for buy signals (below bars)
• Red arrows for sell signals (above bars)
• No lagging repainting
• Works on all timeframes
🎯 TRADING APPLICATIONS:
• Swing trading entries
• Breakout confirmation
• Trend continuation signals
• Support/resistance breaks
⚡ SETTINGS:
• Structure Detection Period (default: 20) - Adjust sensitivity of swing detection
⚠️ RISK DISCLAIMER:
This is an educational tool. Always use proper risk management.
Past performance does not guarantee future results.
Strategy: HMA 50 + Supertrend SniperHMA 50 + Supertrend Confluence Strategy (Trend Following with Noise Filtering)
Description:
Introduction and Concept This strategy is designed to solve a common problem in trend-following trading: Lag vs. False Signals. Standard Moving Averages often lag too much, while price action indicators can generate false signals during choppy markets. This script combines the speed of the Hull Moving Average (HMA) with the volatility-based filtering of the Supertrend indicator to create a robust "Confluence System."
The primary goal of this script is not just to overlay two indicators, but to enforce a strict rule where a trade is only taken when Momentum (HMA) and Volatility Direction (Supertrend) are in perfect agreement.
Why this combination? (The Logic Behind the Mashup)
Hull Moving Average (HMA 50): We use the HMA because it significantly reduces lag compared to SMA or EMA by using weighted calculations. It acts as our primary Trend Direction detector. However, HMA can be too sensitive and "whipsaw" during sideways markets.
Supertrend (ATR-based): We use the Supertrend (Factor 3.0, Period 10) as our Volatility Filter. It uses Average True Range (ATR) to determine the significant trend boundary.
How it Works (Methodology) The strategy uses a boolean logic system to filter out low-quality trades:
Bullish Confluence: The HMA must be rising (Slope > 0) AND the Close Price must be above the Supertrend line (Uptrend).
Bearish Confluence: The HMA must be falling (Slope < 0) AND the Close Price must be below the Supertrend line (Downtrend).
The "Choppy Zone" (Noise Filter): This is a unique feature of this script. If the HMA indicates one direction (e.g., Rising) but the Supertrend indicates the opposite (e.g., Downtrend), the market is considered "Choppy" or indecisive. In this state, the script paints the candles or HMA line Gray and exits all positions (optional setting) to preserve capital.
Visual Guide & Signals To make the script easy to interpret for traders who do not read Pine Script, I have implemented specific visual cues:
Green Cross (+): Indicates a LONG entry signal. Both HMA and Supertrend align bullishly.
Red Cross (X): Indicates a SHORT entry signal. Both HMA and Supertrend align bearishly.
Thick Line (HMA): The main line changes color based on the trend.
Green: Bullish Confluence.
Red: Bearish Confluence.
Gray: Divergence/Choppy (No Trade Zone).
Thin Step Line: This is the Supertrend line, serving as your dynamic Trailing Stop Loss.
Strategy Settings
HMA Length: Default is 50 (Mid-term trend).
ATR Factor/Period: Default is 3.0/10 (Standard for trend catching).
Exit on Choppy: A toggle switch allowing users to decide whether to hold through noise or exit immediately when indicators disagree.
Risk Warning This strategy performs best in trending markets (Forex, Crypto, Indices). Like all trend-following systems, it may experience drawdown during prolonged accumulation/distribution phases. Please backtest with your specific asset before using it with real capital.
Trend Follow Line Point📌 Trend Follow Line Point
The Trend Follow Line Point indicator removes the confusing, repainting-based swing connections commonly found in traditional swing tools.
It maintains consistent swing-point calculation, keeps structural swing lines intact even when trend lines are broken, and integrates market structure + trend + volatility + volume into one intuitive, visual indicator.
This tool is designed for:
Trend Following
Swing Structure Analysis
Volatility-Based Entry & Exit
Market Strength Evaluation
📊 Component Explanation
🔹 1. Swing High / Swing Low Detection
Based on the user-defined sensitivity (swgLen):
A Swing High forms when the current high exceeds the previous swgLen highs.
A Swing Low forms when the current low falls below the previous swgLen lows.
🔹 2. Swing-Based Structure Lines
Connect Swing Highs → Structural visualization
Connect Swing Lows → Structural visualization
These lines reveal the underlying market structure without repainting or disappearing unexpectedly.
🔹 3. Dynamic ATR + Volume Weighting
ATR values combined with the volume ratio (vol / volMA) create a dynamic volatility channel that reflects real-time market pressure.
🔹 4. Enhanced SuperTrend Calculation
Uses ATR-based stability to produce more realistic and smoother trend lines, reducing noise and improving signal clarity.
🔹 5. Trend Color Mapping
Up Trend → User-selected color
Down Trend → User-selected color
Visual trend direction and strength can be identified immediately.
🧭 How to Use
When Swing Highs/Lows are detected, structure lines are automatically drawn between previous swings.
Use these lines to evaluate support/resistance breaks and overall structural direction.
Manage risk with volatility guidance:
Higher ATR (volume-weighted) → wider trend spacing → increased risk
Lower ATR → tighter spacing → reduced risk
This helps with position sizing, entry timing, and exit decisions.
+
Viprasol Elite Advanced Pattern Scanner# 🚀 Viprasol Elite Advanced Pattern Scanner
## Overview
The **Viprasol Elite Advanced Pattern Scanner** is a sophisticated technical analysis tool designed to identify high-probability double bottom (DISCOUNT) and double top (PREMIUM) patterns with unprecedented accuracy. Unlike basic pattern detectors, this elite scanner employs an AI-powered quality scoring system to filter out false signals and highlight only the most reliable trading opportunities.
## 🎯 Key Features
### Advanced Pattern Detection
- **DISCOUNT Patterns** (Double Bottoms): Identifies bullish reversal zones where price may bounce
- **PREMIUM Patterns** (Double Tops): Detects bearish reversal zones where price may decline
- Multi-point validation system (5-point structure)
- Symmetry analysis with customizable tolerance
### 🤖 AI Quality Scoring System
Each pattern receives a quality score (0-100) based on:
- **Symmetry Analysis** (32% weight): How closely the two bottoms/tops match
- **Trend Context** (22% weight): Strength of the preceding trend using ADX
- **Volume Profile** (22% weight): Volume confirmation at key points
- **Pattern Depth** (16% weight): Significance of the pattern's price range
- **Structure Quality** (16% weight): Overall pattern formation quality
Quality Grades:
- ⭐ **ELITE** (88-100): Highest probability setups
- ✨ **VERY STRONG** (77-87): Strong trade opportunities
- ✓ **STRONG** (67-76): Valid patterns with good potential
- ○ **VALID** (65-66): Acceptable patterns meeting minimum criteria
### 🎯 Intelligent Target System
Three target modes per pattern direction:
- **Conservative**: 0.618 Fibonacci extension (safer, closer targets)
- **Balanced**: 1.0 extension (moderate risk/reward)
- **Aggressive**: 1.618 extension (higher risk/reward)
Targets automatically adjust based on pattern quality score.
### 🔧 Advanced Filtering Options
- **Volatility Filter (ATR)**: Excludes patterns during extreme volatility
- **Momentum Filter (ADX)**: Ensures sufficient trend strength
- **Liquidity Filter (Volume)**: Confirms adequate trading volume
### 📊 Pattern Lifecycle Management
- Real-time neckline tracking with extension multiplier
- Pattern invalidation after extended wait period
- Breakout/breakdown confirmation
- Reversal detection (pattern failure scenarios)
- Target achievement tracking
### 🌈 Premium Visual System
- Color-coded quality levels
- Cyber-themed color scheme (Neon Green/Hot Pink/Purple/Cyan)
- Transparent fills for pattern zones
- Dynamic labels with pattern information
- Elite dashboard showing live pattern stats
## 📈 How To Use
### Basic Setup
1. Add indicator to your chart
2. Enable desired patterns (DISCOUNT and/or PREMIUM)
3. Adjust quality threshold (default: 65) - higher = fewer but better signals
4. Set your preferred target mode
### Trading DISCOUNT Patterns (Bullish)
1. Wait for pattern detection (labeled points 1-4)
2. Check quality score on dashboard
3. Entry on breakout above neckline (point 5)
4. Stop loss below the lowest bottom
5. Target shown automatically based on your mode
6. ⚠️ Watch for pattern failure (break below bottoms = SHORT signal)
### Trading PREMIUM Patterns (Bearish)
1. Wait for pattern detection (labeled points 1-4)
2. Check quality score on dashboard
3. Entry on breakdown below neckline (point 5)
4. Stop loss above the highest top
5. Target shown automatically based on your mode
6. ⚠️ Watch for pattern failure (break above tops = LONG signal)
## ⚙️ Input Settings Guide
### 🔍 Detection Engine
- **Left/Right Pivots**: Higher = fewer but cleaner patterns (default: 6/4)
- **Min Pattern Width**: Minimum bars between bottoms/tops (default: 12)
- **Symmetry Tolerance**: Max % difference allowed between levels (default: 1.8%)
- **Extension Multiplier**: How long to wait for breakout (default: 2.2x pattern width)
### ⭐ Quality AI
- **Min Quality Score**: Only show patterns above this score (default: 65)
- **Weight Distribution**: Customize what matters most (symmetry/trend/volume/depth/structure)
### 🔧 Filters
- **Volatility Filter**: Avoid choppy markets (recommended: ON)
- **Momentum Filter**: Ensure trend strength (recommended: ON)
- **Liquidity Filter**: Volume confirmation (recommended: ON)
### 💎 Target System
- Choose target aggression for each pattern type and direction
- Higher quality patterns get adjusted targets automatically
## 🎨 Visual Customization
- Adjust colors for DISCOUNT/PREMIUM patterns
- Set quality-based color coding
- Customize label sizes
- Toggle dashboard visibility and position
- Show/hide historical patterns
## 🚨 Alert System
Set up TradingView alerts for:
- 🚀 **LONG Signals**: DISCOUNT breakout, PREMIUM failure
- 📉 **SHORT Signals**: PREMIUM breakdown, DISCOUNT failure
- ✅ **Target Achievement**: When price hits your target
## 💡 Pro Tips
1. **Higher Timeframes = Better Signals**: Patterns on 4H, Daily, Weekly are more reliable
2. **Quality Over Quantity**: Focus on ELITE and VERY STRONG grades
3. **Combine with Trend**: DISCOUNT in uptrend, PREMIUM in downtrend = best results
4. **Watch Pattern Failures**: Failed patterns often provide strong counter-trend signals
5. **Adjust for Your Style**: Intraday traders use Conservative, swing traders use Aggressive
## 🔒 Pattern Invalidation
Patterns become invalid if:
- No breakout/breakdown within extension period
- Support/resistance levels are broken prematurely
- Pattern shown in faded colors = no longer active
## ⚠️ Risk Disclaimer
This indicator is a tool for technical analysis and does not guarantee profitable trades. Always:
- Use proper risk management
- Combine with other analysis methods
- Never risk more than you can afford to lose
- Past performance does not indicate future results
DeepClean Linear indicator 1. Indicator Name
DeepClean Linear indicator
2. One-Line Introduction
A trend-recognition indicator that overlays a “transparent wave” on price, removing noise and revealing directional bias and trend intensity in a highly intuitive visual form.
3. Overall Summary
The DeepClean Linear indicator calculates trend direction using changes in linear regression slope and determines trend strength by comparing how consistently the regression line moves over a defined lookback window.
Rather than merely identifying trend direction, the indicator applies a triple-layer noise-filtering process (EMA → SMA → RMA) to produce a clean, wave-shaped data line that filters out unnecessary market noise.
This transparent wave sits directly on top of price, allowing traders to visually compare price movement and trend strength at the same time.
A stronger trend results in a taller, thicker wave, while weakening momentum causes the wave to thin, making it easier to spot trend continuation, exhaustion, or upcoming reversal.
Color automatically shifts based on trend:
Bright cyan/teal during bullish conditions
Reddish tones during bearish conditions
Transparency dynamically adjusts depending on strength
The indicator excels at identifying the true underlying trend by ignoring minor fluctuations and is well suited for scalping, swing trading, and position trading.
It also significantly reduces false signals in ranging markets, making it ideal for trend-following strategies.
4. Advantages
① Ultra-Clean Noise-Reduced Wave
Utilizes a 3-stage smoothing filter (EMA → SMA → RMA) to produce a much cleaner wave than standard moving averages, highlighting only core trend movement.
② Trend Direction & Strength at a Glance
Based on comparative linear regression behavior, the indicator quantifies both direction and strength, making convergence/divergence highly visible.
③ Intuitive Price Overlay Visualization
The semi-transparent wave sits directly on price action, allowing traders to instantly see divergence from price, trend weakening, or early turning points.
④ Dynamic Transparency Coloring
Strong trends appear bold and intense, while weaker trends fade visually—making signal interpretation effortless.
⑤ Excellent Range Filtering
During low-direction phases (state = 0), the wave turns neutral, preventing forced or premature entries.
⑥ Multi-Timeframe Compatibility
The wave remains stable from 1-minute to weekly charts, making it suitable for trend analysis, execution, and risk control across all timeframes.
📌 Core Concept Overview
The indicator evaluates the relative comparison of linear regression values over the last n periods.
A positive trend value indicates bullish bias
A negative trend value indicates bearish bias
Intensity represents strength and controls wave height
waveTop / waveBot define the visual wave area relative to price
State Values
1 = Bullish Trend
-1 = Bearish Trend
0 = Neutral / Weak Direction
⚙️ Settings Overview
Option Description
Trend Lookback (n) Comparison window for regression slope. Higher = bigger trend focus.
Range Tolerance (%) Strength threshold to classify bullish/bearish movement. Higher = more conservative.
Source Price source for regression calculations.
Linear Reg Length Length of the linear regression.
Noise Filter Strength (smoothK) Controls the smoothing intensity. Higher = smoother wave.
Wave Amplitude (amp) Adjusts the height/thickness of the wave.
Bull/Bear Color Colors for bullish/bearish waves.
Base Transparency Base opacity level; modified dynamically by trend strength.
📈 Bullish Timing Recognition Examples
Wave begins turning brighter teal and more opaque, indicating strengthening upward pressure.
waveTop expands above price, signaling early trend expansion.
State flips to 1, often marking a trend restart or early reversal phase.
A steadily rising wave height suggests sustained bullish momentum.
📉 Bearish Timing Recognition Examples
Wave shifts into red tones, showing bearish dominance.
waveBot expands below price, indicating rising downside volatility.
State stays at -1 while intensity increases, signaling entry into strong downtrend conditions.
A shift from weak → strong bearish intensity can provide short-entry timing cues.
🧪 Recommended Usage
Use as a core component in trend-following systems
Adjust position size based on wave thickness (trend strength)
Combine with RSI/MACD to reduce false signals during overbought/oversold zones
Sudden wave expansion during volatility increases helps detect trend acceleration
In sideways markets, frequent state = 0 readings help avoid low-probability trades
🔒 Important Notes
As a trend-based indicator, it may misread choppy/ranging markets
Because of smoothing, signals may appear slightly delayed
Extreme news volatility can temporarily distort trend clarity
Buy/Sell Signals [WynTrader]Hello dear Friend
Here is a new version ( B-S_251121_wt ) of my Buy/Sell Signals indicator.
Some calculation updates and useful enhancements have been applied.
Concepts
This Buy/Sell Signals indicator generates Buy/Sell signals as accurately as possible, identifying trend changes. Compared to other tools that detect trend shifts, this one is simple, easy to use, and demonstrates its efficiency on its own.
- Its features are carefully designed to minimize false signals while ensuring optimal signal placement.
- The Table results allow you to quickly evaluate signal performance, both on their own and compared to a Buy & Hold strategy.
- The Table calculations are fully synchronized with the visible chart (WYSIWYG – What You See Is What You Get). You can also scroll the chart across different date ranges to see how a stock or product performs under various market conditions.
- Seeing Buy/Sell signals on a chart is appealing, but assessing their performance in a Table makes it even more convincing. And without running a full backtest, you can get a clear overview of overall performance immediately.
Features
This indicator generates Buy/Sell signals using:
- Fast and Slow Moving Averages (adjustable).
- Bollinger Bands (adjustable).
- Filters (optional, adjustable) to refine signals, including : Bollinger Bands Lookback Trend Filter; High-Low vs Candle Range Threshold %; Distance from Fast and Slow MAs Threshold %.
- Results are displayed in a Table on the chart, based on the currently visible start and end dates.
Functionality
- The indicator aims to confirm trend changes through timely Buy/Sell signals.
- It uses two Moving Averages and Bollinger Bands, combined with filters such as BB Lookback, -- The variable settings have been tested with a mix of manual and AI testing to find the optimal configuration. You can adjust the variables to suit your goals.
- The design is simple, with clear parameters and instant readability of Buy/Sell Signals on the chart and in the Table results, without complex interpretation needed.
- It works effectively by requiring both trend confirmation and volatility control management.
- Signals are timed to be as accurate as possible, avoiding futile weak or false ones.
- A Table shows the effectiveness of the signals on the current visible chart, providing immediate, realistic feedback. The Buy & Hold strategy results are also included for comparison with the Buy/Sell swing strategy. The Buy & Hold results start from the first Buy signal to ensure a fair comparison.
- Changing the parameters instantly updates the Table, giving a quick, at-a-glance performance check.
Caution
- No technical tool is perfect; it cannot predict disasters, wars, or the actions of large fund managers or short sellers.
- After testing thousands of TradingView indicators over 24 years, I’ve found none to be 100% accurate all the time.
- This Buy/Sell Signals indicator may outperform some others but is still not perfect.
So, just be aware, and don’t be fooled by this tool.
Smart RSI MTF [DotGain]Summary
Are you tired of constantly switching between timeframes to check the RSI, only to miss the bigger picture?
The Smart RSI MTF (Multi-Timeframe) is designed to solve this exact problem. It is a streamlined chart overlay that monitors RSI conditions across up to 10 different timeframes simultaneously —from the 1-minute chart all the way up to the Monthly view.
This indicator removes the need for multiple open tabs and declutters your analysis by plotting signals directly on your main chart using a smart "visual hierarchy" system based on transparency.
⚙️ Core Components and Logic
The Smart RSI MTF relies on a sophisticated 3-layer logic to deliver clear, actionable context:
Multi-Timeframe Engine: The script runs 10 independent RSI calculations in the background. It checks standard intervals (5m, 15m, 1h, 4h, Daily, Weekly, Monthly) to ensure you never miss a momentum extreme on any scale.
Classic RSI Thresholds:
Overbought (> 70): Indicates price may be extended to the upside.
Oversold (< 30): Indicates price may be extended to the downside.
Smart Visibility System (The "Secret Sauce"): Not all signals are equal. A 5-minute Overbought signal is "noise" compared to a Weekly Overbought signal. This indicator automatically applies Transparency to differentiate importance:
Minutes = High Transparency (Faint).
Hours = Medium Transparency.
Days/Weeks/Months = No Transparency (Solid/Bold).
🚦 How to Read the Indicator
The indicator plots shapes (Labels by default) directly above or below the candles. The appearance tells you the direction and the timeframe significance:
🟥 RED SIGNALS (Overbought Condition)
Trigger: RSI is above 70 on a specific timeframe.
Location: Placed above the candle bar.
Meaning: Potential bearish reversal or pullback.
🟩 GREEN SIGNALS (Oversold Condition)
Trigger: RSI is below 30 on a specific timeframe.
Location: Placed below the candle bar.
Meaning: Potential bullish reversal or bounce.
👻 TRANSPARENCY (Signal Strength)
Faint/Ghostly: The signal comes from a lower timeframe (e.g., 5m, 15m). Use for scalping or entry timing.
Solid/Bright: The signal comes from a major timeframe (e.g., Daily, Weekly). Use for swing trading and identifying major market turns.
Visual Elements
Symbol Shapes: Fully customizable (Label, Diamond, Circle, Triangle, etc.) via settings.
Stacking: If multiple timeframes trigger at once, symbols will overlay, creating a visually denser and darker color, indicating Confluence .
Key Benefit
The goal of the Smart RSI MTF is to help traders instantly spot Confluence . When you see a faint short-term signal align with a solid long-term signal, you have identified a high-probability reversal zone without leaving your chart.
Have fun :)
Disclaimer
This "Smart RSI MTF" indicator is provided for informational and educational purposes only. It does not, and should not be construed as, financial, investment, or trading advice.
The signals generated by this tool (both "Buy" and "Sell" indications) are the result of a specific set of algorithmic conditions. They are not a direct recommendation to buy or sell any asset. All trading and investing in financial markets involves substantial risk of loss. You can lose all of your invested capital.
Past performance is not indicative of future results. The signals generated may produce false or losing trades. The creator (© DotGain) assumes no liability for any financial losses or damages you may incur as a result of using this indicator.
You are solely responsible for your own trading and investment decisions. Always conduct your own research (DYOR) and consider your personal risk tolerance before making any trades.
Filter Ribbon1. Indicator Name
Filter Ribbon
2. One-line Introduction
A trend visualization ribbon that uses linear regression and directional scoring to highlight bullish and bearish strength with intuitive color gradients.
3. General Overview
Filter Ribbon is a minimalistic yet powerful trend visualization tool that leverages linear regression slope ordering to determine directional momentum. It analyzes the ordering of regression values over a defined lookback period and quantifies how consistently the price has been trending upward or downward.
Using a pairwise comparison system, it calculates a trend "score" and compares this to a configurable threshold to determine if a bullish, bearish, or neutral condition exists.
The result is a color-coded ribbon that sits over the chart, changing hue and opacity based on both the direction and strength of the trend. The stronger the directional alignment, the more opaque the ribbon becomes, offering traders a fast, intuitive way to assess market sentiment at a glance.
It also includes an optional linear regression line to further help visualize the central trend.
This indicator is best used in trend-following systems or as a dynamic background layer when combined with signal-based strategies.
Thanks to its efficient design and protected logic, Filter Ribbon offers high-performance visualization without compromising strategy integrity.
4. Key Advantages
🌈 Visual Trend Heatmap
Dynamic color ribbon gives real-time visual feedback on both trend direction and strength.
🔢 Quantified Trend Scoring
Calculates a mathematically sound trend score using pairwise linear regression comparisons.
⚖️ Adjustable Sensitivity
Users can tune lookback and threshold parameters to fit different asset classes and timeframes.
📉 Smooth Ribbon Effect
Plots upper/lower bands around regression line with smooth filling for a professional chart look.
🎯 Precise Trend Confirmation
Acts as a confidence layer for other entry/exit signals by confirming broader trend bias.
🔒 Secure and Minimal Codebase
Core logic is embedded securely with minimal exposure, reducing risk of replication or misuse.
📘 Indicator User Guide
📌 Basic Concept
Filter Ribbon determines trend direction and intensity by comparing the order of linear regression values over time.
It forms a ribbon on the chart that changes color based on trend direction and opacity based on trend strength.
This makes it ideal for identifying clear trending periods vs. uncertain consolidations.
⚙️ Settings Explained
Lookback Period: Number of bars for scoring the trend direction (higher = smoother trend)
Range Tolerance (%): Determines how aggressive the trend classification is (lower = stricter)
Regression Length: Period for calculating the base linear regression line
Ribbon Colors: Customize colors for bullish and bearish conditions
📈 Bullish Timing Example
Ribbon color is green and becomes increasingly opaque
Regression line slopes upward and price remains above it
Can be used as trend confirmation for long trades
📉 Bearish Timing Example
Ribbon color is red with higher opacity
Price consistently below the regression line
Useful for confirming short trade setups or avoiding long entries
🧪 Recommended Use Cases
Combine with breakout indicators to validate if the breakout aligns with broader trend
Use in swing or trend-following strategies as a background filter
Helps filter out trades during unclear, sideways market conditions
🔒 Precautions
Not a signal generator on its own — meant for trend context only
Ribbon may lag slightly during sudden trend reversals; best used with reactive entry tools
Always test ribbon parameters on your specific market/timeframe before applying live
Avoid using solely in low-volatility or flat markets — sensitivity may require tuning
+++
Hash Momentum IndicatorHash Momentum Indicator
Overview
The Hash Momentum Indicator provides real-time momentum-based trading signals with visual entry/exit markers and automatic risk management levels. This is the indicator version of the popular Hash Momentum Strategy, designed for traders who want signal alerts without backtesting functionality.
Perfect for: Live trading, automation via alerts, multi-indicator setups, and clean chart visualization.
What Makes This Indicator Special
1. Pure Momentum-Based Signals
Captures price acceleration in real-time - not lagging moving average crossovers. Enters when momentum exceeds a dynamic ATR-based threshold, catching moves as they begin accelerating.
2. Automatic Risk Management Visualization
Every signal automatically displays:
Entry level (white dashed line)
Stop loss level (red line)
Take profit target (green line)
Partial TP levels (dotted green lines)
3. Smart Trade Management
Trade Cooldown: Prevents overtrading by enforcing waiting period between signals
EMA Trend Filter: Only trades with the trend (optional)
Session Filters: Trade only during Tokyo/London/New York sessions (optional)
Weekend Toggle: Avoid low-liquidity weekend periods (optional)
4. Clean Visual Design
🟢 Tiny green dot = Long entry signal
🔴 Tiny red dot = Short entry signal
🔵 Blue X = Long exit
🟠 Orange X = Short exit
No cluttered labels or dashboard - just clean signals
5. Professional Alerts Ready
Set up TradingView alerts for:
Long signals
Short signals
Long exits
Short exits
How It Works
Step 1: Calculate Momentum
Momentum = Current Price - Price
Normalized by standard deviation for consistency
Must exceed ATR × Threshold to trigger
Step 2: Confirm Acceleration
Momentum must be increasing (positive momentum change)
Price must be moving in signal direction
Step 3: Apply Filters
EMA Filter: Long only above EMA, short only below EMA (if enabled)
Session Filter: Check if in allowed trading session (if enabled)
Weekend Filter: Block signals on Sat/Sun (if enabled)
Cooldown: Ensure minimum bars passed since last signal
Step 4: Generate Signal
All conditions met = Entry signal fires
Lines automatically drawn for entry, stop, and targets
Step 5: Exit Detection
Opposite momentum detected = Exit signal
Stop loss or take profit hit = Exit signal
Lines removed from chart
⚙️ Settings Guide
Core Strategy
Momentum Length (Default: 13)
Number of bars for momentum calculation. Higher values = stronger signals but fewer trades.
Aggressive: 10
Balanced: 13
Conservative: 18-24
Momentum Threshold (Default: 2.25)
ATR multiplier for signal generation. Higher values = only trade the biggest momentum moves.
Aggressive: 2.0
Balanced: 2.25
Conservative: 2.5-3.0
Risk:Reward Ratio (Default: 2.5)
Your target profit as a multiple of your risk. With 2.2% stop and 2.5 R:R, your target is 5.5% profit.
Conservative: 3.0+ (need 25% win rate to profit)
Balanced: 2.5 (need 29% win rate to profit)
Aggressive: 2.0 (need 33% win rate to profit)
Reduced-Lag Chande Momentum Oscillator [BOSWaves]Reduced-Lag Chande Momentum Oscillator – Adaptive Momentum Geometry with Reduced-Latency Reversion Logic
Overview
The Reduced-Lag Chande Momentum Oscillator represents a sophisticated extension of the classical Chande Momentum Oscillator, preserving the foundational measurement of net directional pressure while addressing inherent limitations in lag, noise, and signal clarity. The traditional CMO provides reliable snapshots of upward versus downward force but reacts slowly to rapid market accelerations and can obscure meaningful momentum inflections with delayed readings. This iteration integrates a dual-stage reduced-lag filter, optional advanced smoothing, and acceleration-based analytics, producing a real-time, multi-dimensional representation of market momentum.
The design reframes classical momentum using a layered curvature and gradient structure - main, midline, and shadow - to show trajectory, velocity, and intensity in one view. Instead of the usual ±70/30 extremes, it uses ±50 as a statistically grounded threshold where one side of the market begins exerting true dominance. This captures structural imbalance more reliably, exposing exhaustion and actionable inflection without amplifying noise.
This visualization gives traders a continuous, responsive read on market structure, revealing not just direction but rate of change, acceleration alignment, and curvature behavior. The oscillator becomes a momentum map, expressing both probability and intensity behind directional shifts.
Where conventional oscillators mislabel short-lived swings as signals, the Reduced-Lag CMO separates baseline shifts from high-conviction transitions, enabling cleaner, more decisive signal interpretation.
Theoretical Foundation
The classical Chande Momentum Oscillator, created by Tushar Chande, calculates the normalized net difference between consecutive upward and downward price changes over a defined window, generating readings from –100 to +100. While effective for capturing basic directional pressure, the unmodified CMO suffers from signal latency and sensitivity to abrupt market swings, which can obscure actionable inflection points.
The Reduced-Lag CMO augments this foundation with three key mechanisms:
Reduced-Lag Filtering : A dual-EMA structure eliminates inertial lag, aligning the oscillator curve closely with real-time market momentum without producing overshoot artifacts.
Smoothing Architecture : Optional SMA, EMA, or WMA smoothing is applied post-filter, balancing noise reduction with trajectory fidelity. A multi-layer line system (shadow → midline → main) communicates depth, curvature, and gradient dynamics.
Acceleration Integration : First and second derivatives of the smoothed curve quantify velocity and acceleration, allowing the indicator to identify not only momentum flips but the force behind each shift, forming the basis for the strong-signal overlay.
The combination of these mechanisms produces an oscillator that respects the original CMO framework while delivering real-time, context-sensitive intelligence. The ±50 boundaries are selected as the statistically validated pressure zones where directional dominance exceeds neutral oscillation. Crosses and rejections at these boundaries are not arbitrary overbought/oversold events, but measurable imbalances with actionable significance.
How It Works
The Reduced-Lag CMO is constructed through a multi-stage process:
Momentum Estimation Core : Raw CMO values are calculated and then passed through a reduced-lag filter to remove delay, creating a curve that closely tracks instantaneous directional pressure.
Smoothing & Layered Representation : The filtered curve can be smoothed and split into three layers - shadow, midline, and main - giving visual depth, trajectory clarity, and curvature instead of a single-line oscillator.
Gradient-Based Pressure Mapping : Color gradients encode momentum strength and polarity. Green-yellow transitions highlight increasing upward dominance, while red-yellow transitions indicate weakening downward force.
Pressure-Zone Anchoring (±50) : The system defines statistically significant pressure zones at ±50. Moves beyond these levels reflect dominant directional control, and rejections inside the zone signal potential exhaustion.
Signal Generation : Momentum events are evaluated through velocity and acceleration. Standard signals appear as triangle markers indicating validated momentum flips. Strong signals appear as triangles with diamonds when acceleration confirms a high-conviction transition.
A cooldown rule spaces signals apart to reduce clutter and emphasize structurally meaningful events.
Interpretation
The Reduced-Lag CMO reframes momentum as a dynamic equilibrium between directional force and structural pressure:
Positive Momentum Phases : Curves above zero with green-yellow gradients indicate sustained upward pressure. Shallow retracements or midline tests denote controlled pullbacks.
Negative Momentum Phases : Curves below zero with red-yellow gradients show downward dominance. Rejections from –50 highlight potential exhaustion and reversal readiness.
Pressure-Zone Dynamics (±50) : Crosses beyond ±50 confirm dominant directional force. Meanwhile, rejections and rotations inside the zone signal structural fatigue.
Velocity & Acceleration Analysis : Rising momentum with decelerating velocity suggests fading force; acceleration alignment amplifies signal strength and forms the basis of strong signals.
Signal Architecture
The Reduced-Lag CMO produces a single event type with two intensities: a validated momentum inflection.
Standard Signals - Triangles:
Triggered by momentum flips confirmed by velocity.
Represent moderate-intensity directional changes.
Appear at zero-line crosses or ±50 rejections with aligned velocity.
Strong Signals Triangles + Diamonds:
Triggered when acceleration confirms the directional change.
Represent high-intensity, high-conviction shifts.
Rare by design; indicate robust momentum inflections.
Cooldown mechanics prevent repeated signals in short succession, emphasizing structural reliability over noise.
Strategy Integration
Trend Confirmation : Align zero-line flips with higher-timeframe directional bias.
Reversal Detection : Strong signals from ±50 zones highlight potential inflection points.
Volatility Assessment : Gradient transitions reveal strengthening or weakening momentum.
Pullback Timing : Multi-layer curvature identifies controlled retracements vs trend exhaustion.
Confluence Mapping : Pair with structure-based indicators to filter signals in context.
Technical Implementation Details
Core Engine : Classical CMO with Ehlers reduced-lag extension
Lag Reduction : Dual EMA filtering
Smoothing : Optional SMA/EMA/WMA post-filter
Multi-Layer Curve : Shadow, midline, main
Signal System : Two-tier momentum-acceleration framework
Pressure Zones : ±50 statistically validated thresholds
Cooldown Logic : Bar-indexed suppression
Gradient Mapping : Encodes magnitude and direction
Alerts : Standard and strong signals
Optimal Application Parameters
Timeframes:
1 - 5 min : Intraday momentum tracking
15 - 60 min : Trend rotations & volatility transitions
4H - Daily : Macro momentum exhaustion & re-accumulation mapping
Suggested Ranges:
CMO Length : 7 - 12
Reduced-Lag Length : 5 - 15
Smoothing : 10 - 20
Cooldown Bars : 5 - 15
Performance Characteristics
High Effectiveness:
Markets with directional pulses & clean pressure transitions
Trending phases with measurable pullbacks
Instruments with stable volatility cycles
Reduced Edge:
Choppy consolidations
Ultra-low volatility environments
Disclaimer
The Reduced-Lag Chande Momentum Oscillator is a professional-grade analytical tool. It is not predictive and carries no guaranteed profitability. Effectiveness depends on asset class, volatility regime, parameter selection, and disciplined execution. Any suggested application timeframes or recommended ranges are guidance only - they are not universally optimal and will not deliver consistent accuracy on every asset or market condition. BOSWaves recommends using it in conjunction with structure, liquidity, and momentum context.
Bollinger Bands Regression Forecast [BigBeluga]🔵 OVERVIEW
The Bollinger Bands Regression Forecast combines volatility envelopes from Bollinger Bands with a linear regression-based projection model .
It visualizes both current and future price zones by extrapolating the Bollinger channel forward in time, giving traders a statistical forecast of probable support and resistance behavior.
🔵 CONCEPTS
Classic Bollinger Bands use a moving average (basis) and standard deviation (deviation) to form dynamic envelopes around price.
This indicator enhances them with linear regression slope detection , allowing it to forecast how the band may expand or contract in the future.
Regression is applied to both the band’s basis and deviation components to predict their trajectory for a user-defined number of Forecast Bars .
The resulting forecast creates a smoothed, funnel-shaped projection that dynamically adapts to volatility.
▲ and ▼ markers highlight potential mean reversion points when price crosses the outer bounds of the bands.
🔵 FEATURES
Forecast Engine : Uses linear regression to project Bollinger Band movement into the future.
Dynamic Channel Width : Adapts standard deviation and slope for realistic volatility modeling.
Auto-Labeled Levels : Displays live upper and lower forecast values for quick reference.
Cross Signals : Marks potential overbought and oversold zones with ▲/▼ signals when price exits the band.
Trend-Adaptive Basis Color : Basis line automatically switches color to represent short-term trend direction.
Customizable Colors and Widths for complete visual control.
🔵 HOW TO USE
Apply the indicator to visualize both current Bollinger structure and its forward projection.
Use ▲/▼ breakout markers to identify short-term reversals or volatility shifts.
When price consistently rides the upper band forecast, the trend is strong and likely continuing.
When regression shows narrowing bands ahead, expect a volatility contraction or consolidation period.
For range traders, outer projected bands can be used as potential mean reversion entry points .
Combine with volume or momentum filters to confirm whether breakouts are genuine or fading.
🔵 CONCLUSION
Bollinger Bands Regression Forecast transforms classic Bollinger analysis into a predictive forecasting model .
By merging volatility dynamics with regression-based extrapolation, it provides traders with a forward-looking visualization of likely price boundaries — revealing not only where volatility is but also where it’s heading next.
McMillan Volatility Bands (MVB) – with Entry Logic// McMillan Volatility Bands (MVB) with signal + entry logic
// Author: ChatGPT for OneRyanAlexander
// Notes:
// - Bands are computed using percentage volatility (log returns), per the Black‑Scholes framing.
// - Inner band (default 3σ) and outer band (default 4σ) are configurable.
// - A setup occurs when price closes outside the outer band, then closes back within the inner band.
// The bar that re‑enters is the "signal bar." We then require price to trade beyond the signal bar's
// extreme by a user‑defined cushion (default 0.34 * signal bar range) to confirm entry.
// - Includes alertconditions for both setups and confirmed entries.
Island Reversal [LuxAlgo]The Island Reversal tool allows traders to identify reversal patterns directly on the chart. These patterns signal a potential change in trend, either from bullish to bearish or vice versa.
The tool enables traders to filter these patterns by trend, volume, and range, making it easy to display pure or less constrained island reversals.
🔶 USAGE
An island reversal pattern may indicate a change in trend. It occurs when prices change direction from an uptrend to a downtrend, or vice versa.
This pattern is a great tool for timing the market. Traders should be aware of when these patterns develop and watch how prices behave after the pattern forms.
Now, let's take a closer look at one of these island reversal patterns to highlight its different components.
The different parts are depicted in the image above.
1. A trend prior to the pattern
2. A gap starts the pattern.
3. A range of prices
4. A final gap, opposite to the first one, closes the pattern.
5. In this case, the pattern leads to a bearish trend, which is opposite to the trend in the first step.
🔹 Trend, Volume and Range Filters
Enabling the trend filter causes the tool to only detect top island reversals during a bullish trend and bottom island reversals during a bearish trend.
Traders can adjust the size of the detected trend in the settings panel. The larger the trend size, the more relevant the reversal patterns can be.
The volume filter only detects reversal patterns if there is more volume within the range of the pattern than in the preceding trend.
The idea is that more people tend to participate at the top and bottom of a trend as it changes direction.
The tool has two range filters that discriminate the range within the island reversal pattern:
Horizontality Filter (R2): Based on the R-squared statistic from linear regression, it detects whether the price is moving sideways within the range.
Volatility Filter: Based on long-term volatility, it detects the size of the range within the pattern.
The smaller the value in the Horizontality Filter, the more horizontal the prices will be within the range. A larger value will detect more reversal patterns.
The larger the value in the Volatility Filter, the larger the ranges will be. A smaller value will detect fewer reversal patterns.
🔶 SETTINGS
🔹 Trend Filter
Trend Filter: Enable or disable the trend filter.
Trend Length: Select the size of the detected trend.
🔹 Volume Filter
Volume Filter: Enable or disable the volume filter.
🔹 Range Filter
Horizontality Filter (R2): Enable or disable the Horizontality filter and select a threshold value.
Volatility Filter: Enable or disable the Volatility filter and select the multiplier value.
🔹 Style
Bullish: Select a color for bullish sessions.
Bearish: Select a color for bearish sessions.
Transparency: Select a transparency level from 100 to 0.
Ornstein-Uhlenbeck Trend Channel [BOSWaves]Ornstein-Uhlenbeck Trend Channel - Adaptive Mean Reversion with Dynamic Equilibrium Geometry
Overview
The Ornstein-Uhlenbeck Trend Channel introduces an advanced equilibrium-mapping framework that blends statistical mean reversion with adaptive trend geometry. Traditional channels and regression bands react linearly to volatility, often failing to capture the natural rhythm of price equilibrium. This model evolves that concept through a dynamic reversion engine, where equilibrium adapts continuously to volatility, trend slope, and structural bias - forming a living channel that bends, expands, and contracts in real time.
The result is a smooth, equilibrium-driven representation of market balance - not just trend direction. Instead of static bands or abrupt slope shifts, traders see fluid, volatility-aware motion that mirrors the natural pull-and-release dynamic of market behavior. Each channel visualizes the probabilistic boundaries of fair value, showing where price tends to revert and where it accelerates away from its statistical mean.
Unlike conventional envelopes or Bollinger-type constructs, the Ornstein-Uhlenbeck framework is volatility-reactive and equilibrium-sensitive, providing traders with a contextual map of where price is likely to stabilize, extend, or exhaust.
Theoretical Foundation
The Ornstein-Uhlenbeck Trend Channel is inspired by stochastic mean-reversion processes - mathematical models used to describe systems that oscillate around a drifting equilibrium. While linear regression channels assume constant variance, financial markets operate under variable volatility and shifting equilibrium points. The OU process accounts for this by treating price as a mean-seeking motion governed by volatility and trend persistence.
At its core are three interacting components:
Equilibrium Mean (μ) : Represents the evolving balance point of price, adjusting to directional bias and volatility.
Reversion Rate (θ) : Defines how strongly price is pulled back toward equilibrium after deviation, capturing the self-correcting nature of market structure.
Volatility Coefficient (σ) : Controls how far and how quickly price can diverge from equilibrium before mean reversion pressure increases.
By embedding this stochastic model inside a volatility-adjusted framework, the system accurately scales across different markets and conditions - maintaining meaningful equilibrium geometry across crypto, forex, indices, or commodities. This design gives traders a mathematically grounded yet visually intuitive interpretation of dynamic balance in live market motion.
How It Works
The Ornstein-Uhlenbeck Trend Channel is constructed through a structured multi-stage process that merges stochastic logic with volatility mechanics:
Equilibrium Estimation Core : The indicator begins by identifying the evolving mean using adaptive smoothing influenced by trend direction and volatility. This becomes the live centerline - the statistical anchor around which price naturally oscillates.
Volatility Normalization Layer : ATR or rolling deviation is used to calculate volatility intensity. The output scales the channel width dynamically, ensuring that boundaries reflect current variance rather than static thresholds.
Directional Bias Engine : EMA slope and trend confirmation logic determine whether equilibrium should tilt upward or downward. This creates asymmetrical channel motion that bends with the prevailing trend rather than staying horizontal.
Channel Boundary Construction : Upper and lower bands are plotted at volatility-proportional distances from the mean. These envelopes form the “statistical pressure zones” that indicate where mean reversion or acceleration may occur.
Signal and Lifecycle Control : Channel breaches, mean crossovers, and slope flips mark statistically significant events - exhaustion, continuation, or rebalancing. Older equilibrium zones gradually fade, ensuring a clear, context-aware visual field.
Through these layers, the channel forms a continuously updating equilibrium corridor that adapts in real time - breathing with the market’s volatility and rhythm.
Interpretation
The Ornstein-Uhlenbeck Trend Channel reframes how traders interpret balance and momentum. Instead of viewing price as directional movement alone, it visualizes the constant tension between trending force and equilibrium pull.
Uptrend Phases : The equilibrium mean tilts upward, with price oscillating around or slightly above the midline. Upper band touches signal momentum extension; lower touches reflect healthy reversion.
Downtrend Phases : The mean slopes downward, with upper-band interactions marking resistance zones and lower bands acting as reversion boundaries.
Equilibrium Transitions : Flat mean sections indicate balance or distribution phases. Breaks from these neutral zones often precede directional expansion.
Overextension Events : When price closes beyond an outer boundary, it marks statistically significant disequilibrium - an early warning of exhaustion or volatility reset.
Visually, the OU channel translates volatility and equilibrium into structured geometry, giving traders a statistical lens on trend quality, reversion probability, and volatility stress points.
Strategy Integration
The Ornstein-Uhlenbeck Trend Channel integrates seamlessly into both mean-reversion and trend-continuation systems:
Trend Alignment : Use mean slope direction to confirm higher-timeframe bias before entering continuation setups.
Reversion Entries : Target rejections from outer bands when supported by volume or divergence, capturing snapbacks toward equilibrium.
Volatility Breakout Mapping : Monitor boundary expansions to identify transition from compression to expansion phases.
Liquidity Zone Confirmation : Combine with BOS or order-block indicators to validate structural zones against equilibrium positioning.
Momentum Filtering : Align with oscillators or volume profiles to isolate equilibrium-based pullbacks with statistical context.
Technical Implementation Details
Core Engine : Stochastic Ornstein-Uhlenbeck process for continuous mean recalibration.
Volatility Framework : ATR- and deviation-based scaling for dynamic channel expansion.
Directional Logic : EMA-slope driven bias for adaptive mean tilt.
Channel Composition : Independent upper and lower envelopes with smoothing and transparency control.
Signal Structure : Alerts for mean crossovers and boundary breaches.
Performance Profile : Lightweight, multi-timeframe compatible implementation optimized for real-time responsiveness.
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Reactive equilibrium tracking for short-term scalping and microstructure analysis.
15 - 60 min : Medium-range setups for volatility-phase transitions and intraday structure.
4H - Daily : Macro equilibrium mapping for identifying exhaustion, distribution, or reaccumulation zones.
Suggested Configuration:
Mean Length : 20 - 50
Volatility Multiplier : 1.5× - 2.5×
Reversion Sensitivity : 0.4 - 0.8
Smoothing : 2 - 5
Parameter tuning should reflect asset liquidity, volatility, and desired reversion frequency.
Performance Characteristics
High Effectiveness:
Trending environments with cyclical pullbacks and volatility oscillation.
Markets exhibiting consistent equilibrium-return behavior (indices, majors, high-cap crypto).
Reduced Effectiveness:
Low-volatility consolidations with minimal variance.
Random walk markets lacking definable equilibrium anchors.
Integration Guidelines
Confluence Framework : Pair with BOSWaves structural tools or momentum oscillators for context validation.
Directional Control : Follow mean slope alignment for directional conviction before acting on channel extremes.
Risk Calibration : Use outer band violations for controlled contrarian entries or trailing stop management.
Multi-Timeframe Synergy : Derive macro equilibrium zones on higher timeframes and refine entries on lower levels.
Disclaimer
The Ornstein-Uhlenbeck Trend Channel is a professional-grade equilibrium and volatility framework. It is not predictive or profit-assured; performance depends on parameter calibration, volatility regime, and disciplined execution. BOSWaves recommends using it as part of a comprehensive analytical stack combining structure, liquidity, and momentum context.
Dynamic Fractal Flow [Alpha Extract]An advanced momentum oscillator that combines fractal market structure analysis with adaptive volatility weighting and multi-derivative calculus to identify high-probability trend reversals and continuation patterns. Utilizing sophisticated noise filtering through choppiness indexing and efficiency ratio analysis, this indicator delivers entries that adapt to changing market regimes while reducing false signals during consolidation via multi-layer confirmation centered on acceleration analysis, statistical band context, and dynamic omega weighting—without any divergence detection.
🔶 Fractal-Based Market Structure Detection
Employs Williams Fractal methodology to identify pivotal market highs and lows, calculating normalized price position within the established fractal range to generate oscillator signals based on structural positioning. The system tracks fractal points dynamically and computes relative positioning with ATR fallback protection, ensuring continuous signal generation even during extended trending periods without fractal formation.
🔶 Dynamic Omega Weighting System
Implements an adaptive weighting algorithm that adjusts signal emphasis based on real-time volatility conditions and volume strength, calculating dynamic omega coefficients ranging from 0.3 to 0.9. The system applies heavier weighting to recent price action during high-conviction moves while reducing sensitivity during low-volume environments, mitigating lag inherent in fixed-period calculations through volatility normalization and volume-strength integration.
🔶 Cascading Robustness Filtering
Features up to five stages of progressive EMA smoothing with user-adjustable robustness steps, each layer systematically filtering microstructure noise while preserving essential trend information. Smoothing periods scale with the chosen fractal length and robustness steps using a fixed smoothing multiplier for consistent, predictable behavior.
🔶 Adaptive Noise Suppression Engine
Integrates dual-component noise filtering combining Choppiness Index calculation with Kaufman’s Efficiency Ratio to detect ranging versus trending market conditions. The system applies dynamic damping that maintains full signal strength during trending environments while suppressing signals during choppy consolidation, aligning output with the prevailing regime.
🔶 Acceleration and Jerk Analysis Framework
Calculates second-derivative acceleration and third-derivative jerk to identify explosive momentum shifts before they fully materialize on traditional indicators. Detects bullish acceleration when both acceleration and jerk turn positive in negative oscillator territory, and bearish acceleration when both turn negative in positive territory, providing early entry signals for high-velocity trend initiation phases.
🔶 Multi-Layer Signal Generation Architecture
Combines three primary signal types with hierarchical validation: acceleration signals, band crossover entries, and threshold momentum signals. Each signal category includes momentum confirmation, trend-state validation, and statistical band context; signals are further conditioned by band squeeze detection to avoid low-probability entries during compression phases. Divergence is intentionally excluded for a purely structure- and momentum-driven approach.
🔶 Dynamic Statistical Band System
Utilizes Bollinger-style standard deviation bands with configurable multiplier and length to create adaptive threshold zones that expand during volatile periods and contract during consolidation. Includes band squeeze detection to identify compression phases that typically precede expansion, with signal suppression during squeezes to prevent premature entries.
🔶 Gradient Color Visualization System
Features color gradient mapping that dynamically adjusts line intensity based on signal strength, transitioning from neutral gray to progressively intense bullish or bearish colors as conviction increases. Includes gradient fills between the signal line and zero with transparency scaling based on oscillator intensity for immediate visual confirmation of trend strength and directional bias.
All analysis provided by Alpha Extract is for educational and informational purposes only. The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations.
CCI [Hash Adaptive]Adaptive CCI Pro: Professional Technical Analysis Indicator
The Commodity Channel Index is a momentum oscillator developed by Donald Lambert in 1980. CCI measures the relationship between an asset's price and its statistical average, identifying cyclical turns and overbought/oversold conditions. The indicator oscillates around zero, with values above +100 indicating overbought conditions and values below -100 suggesting oversold conditions.
Standard CCI Formula: (Typical Price - Moving Average) / (0.015 × Mean Deviation)
This indicator transforms the traditional CCI into a sophisticated visual analysis tool through several key enhancements:
Implements dual exponential moving average smoothing to eliminate market noise
Preserves signal integrity while reducing false signals
Adaptive smoothing responds to market volatility conditions
Dynamic Color Visualization System
Continuous gradient transitions from red (bearish momentum) to green (bullish momentum)
Real-time color intensity reflects momentum strength
Eliminates discrete color jumps for fluid visual interpretation
Adaptive Intelligence Features
Dynamic overbought/oversold thresholds adapt to market conditions
Reduces false signals during high volatility periods
Maintains sensitivity during low volatility environments
Momentum Vector Analysis
Incorporates velocity calculations for early trend identification
Crossover detection with momentum confirmation
Advanced signal filtering reduces market noise
Extreme Level Analysis
Values above +100: Strong overbought conditions, potential reversal zones
Values below -100: Strong oversold conditions, potential buying opportunities
Zero-line crossovers: Momentum shift confirmation
Optimization Parameters
CCI Period (Default: 14)
Shorter periods (10-12): Increased sensitivity, more signals
Standard periods (14-20): Balanced responsiveness and reliability
Longer periods (21-30): Reduced noise, stronger signal confirmation
Smoothing Factor (Default: 5)
Lower values (1-3): Maximum responsiveness, suitable for scalping
Medium values (4-6): Balanced approach for swing trading
Higher values (7-10): Institutional-grade smoothness for position trading
Signal Sensitivity (Default: 6)
Conservative (7-10): High-probability signals, reduced frequency
Balanced (5-6): Optimal risk-reward ratio
Aggressive (1-4): Maximum signal generation, requires additional confirmation
Strategic Implementation
Oversold reversals in red zones with momentum confirmation
Zero-line breaks with sustained color transitions
Extreme readings followed by momentum divergence
Risk Management
Use extreme levels (+100/-100) for position sizing decisions
Monitor color intensity for momentum strength assessment
Combine with price action analysis for comprehensive market view
Market Context Application
Trending markets: Focus on momentum direction and extreme readings
Range-bound markets: Utilize overbought/oversold levels for mean reversion
Volatile markets: Increase smoothing parameters and signal sensitivity
Professional Advantages
Instantaneous momentum assessment through color visualization
Reduced cognitive load compared to traditional oscillators
Professional presentation suitable for client reporting
Adaptive Technology
Self-adjusting parameters reduce manual optimization requirements
Consistent performance across varying market conditions
Advanced mathematics eliminate common CCI limitations
The Adaptive CCI Pro represents the evolution of momentum analysis, combining Lambert's foundational CCI concept with modern computational techniques to deliver institutional-grade market intelligence through an intuitive visual interface.
PDB - RSI Based Buy/Sell signals with 4 MARSI Based Buy/Sell Signals on Price chart + 4 MA System
This indicator plots RSI-based Buy & Sell signals directly on the price chart , combined with a 4-Moving-Average trend filter (20/50/100/200) for higher accuracy and cleaner trade timing.
The signal triggers when RSI reaches user-defined overbought/oversold levels, but unlike a standard RSI, this version plots the signals **on the chart**, not in the RSI window — making entries and exits easier to see in real time.
RSI Levels Are Fully Customizable
The default RSI thresholds are 30 (oversold) and 70 (overbought).
However, you can adjust these to fit your trading style. For example:
> When day trading on the 5–15 min timeframe, I personally use 35 (oversold) and 75 (overbought) to catch moves earlier.
> The example shown in the preview image uses 10-minute timeframe settings.
You can change the RSI levels to trigger signals from **any value you choose**, allowing you to tailor the indicator to scalping, day trading, or swing trading.
4 Moving Averages Included:
20, 50, 100, 200 MAs act as dynamic trend filters so you can:
✔ trade signals only in the direction of trend
✔ avoid false reversals
✔ identify momentum shifts more clearly
Works on all markets and timeframes — crypto, stocks, FX, indices.
Zero Lag Trend Signals (MTF) [Quant Trading] V7Overview
The Zero Lag Trend Signals (MTF) V7 is a comprehensive trend-following strategy that combines Zero Lag Exponential Moving Average (ZLEMA) with volatility-based bands to identify high-probability trade entries and exits. This strategy is designed to reduce lag inherent in traditional moving averages while incorporating dynamic risk management through ATR-based stops and multiple exit mechanisms.
This is a longer term horizon strategy that takes limited trades. It is not a high frequency trading and therefore will also have limited data and not > 100 trades.
How It Works
Core Signal Generation:
The strategy uses a Zero Lag EMA (ZLEMA) calculated by applying an EMA to price data that has been adjusted for lag:
Calculate lag period: floor((length - 1) / 2)
Apply lag correction: src + (src - src )
Calculate ZLEMA: EMA of lag-corrected price
Volatility bands are created using the highest ATR over a lookback period multiplied by a band multiplier. These bands are added to and subtracted from the ZLEMA line to create upper and lower boundaries.
Trend Detection:
The strategy maintains a trend variable that switches between bullish (1) and bearish (-1):
Long Signal: Triggers when price crosses above ZLEMA + volatility band
Short Signal: Triggers when price crosses below ZLEMA - volatility band
Optional ZLEMA Trend Confirmation:
When enabled, this filter requires ZLEMA to show directional momentum before entry:
Bullish Confirmation: ZLEMA must increase for 4 consecutive bars
Bearish Confirmation: ZLEMA must decrease for 4 consecutive bars
This additional filter helps avoid false signals in choppy or ranging markets.
Risk Management Features:
The strategy includes multiple stop-loss and take-profit mechanisms:
Volatility-Based Stops: Default stop-loss is placed at ZLEMA ± volatility band
ATR-Based Stops: Dynamic stop-loss calculated as entry price ± (ATR × multiplier)
ATR Trailing Stop: Ratcheting stop-loss that follows price but never moves against position
Risk-Reward Profit Target: Take-profit level set as a multiple of stop distance
Break-Even Stop: Moves stop to entry price after reaching specified R:R ratio
Trend-Based Exit: Closes position when price crosses EMA in opposite direction
Performance Tracking:
The strategy includes optional features for monitoring and analyzing trades:
Floating Statistics Table: Displays key metrics including win rate, GOA (Gain on Account), net P&L, and max drawdown
Trade Log Labels: Shows entry/exit prices, P&L, bars held, and exit reason for each closed trade
CSV Export Fields: Outputs trade data for external analysis
Default Strategy Settings
Commission & Slippage:
Commission: 0.1% per trade
Slippage: 3 ticks
Initial Capital: $1,000
Position Size: 100% of equity per trade
Main Calculation Parameters:
Length: 70 (range: 70-7000) - Controls ZLEMA calculation period
Band Multiplier: 1.2 - Adjusts width of volatility bands
Entry Conditions (All Disabled by Default):
Use ZLEMA Trend Confirmation: OFF - Requires ZLEMA directional momentum
Re-Enter on Long Trend: OFF - Allows multiple entries during sustained trends
Short Trades:
Allow Short Trades: OFF - Strategy is long-only by default
Performance Settings (All Disabled by Default):
Use Profit Target: OFF
Profit Target Risk-Reward Ratio: 2.0 (when enabled)
Dynamic TP/SL (All Disabled by Default):
Use ATR-Based Stop-Loss & Take-Profit: OFF
ATR Length: 14
Stop-Loss ATR Multiplier: 1.5
Profit Target ATR Multiplier: 2.5
Use ATR Trailing Stop: OFF
Trailing Stop ATR Multiplier: 1.5
Use Break-Even Stop-Loss: OFF
Move SL to Break-Even After RR: 1.5
Use Trend-Based Take Profit: OFF
EMA Exit Length: 9
Trade Data Display (All Disabled by Default):
Show Floating Stats Table: OFF
Show Trade Log Labels: OFF
Enable CSV Export: OFF
Trade Label Vertical Offset: 0.5
Backtesting Date Range:
Start Date: January 1, 2018
End Date: December 31, 2069
Important Usage Notes
Default Configuration: The strategy operates in its most basic form with default settings - using only ZLEMA crossovers with volatility bands and volatility-based stop-losses. All advanced features must be manually enabled.
Stop-Loss Priority: If multiple stop-loss methods are enabled simultaneously, the strategy will use whichever condition is hit first. ATR-based stops override volatility-based stops when enabled.
Long-Only by Default: Short trading is disabled by default. Enable "Allow Short Trades" to trade both directions.
Performance Monitoring: Enable the floating stats table and trade log labels to visualize strategy performance during backtesting.
Exit Mechanisms: The strategy can exit trades through multiple methods: stop-loss hit, take-profit reached, trend reversal, or trailing stop activation. The trade log identifies which exit method was used.
Re-Entry Logic: When "Re-Enter on Long Trend" is enabled with ZLEMA trend confirmation, the strategy can take multiple long positions during extended uptrends as long as all entry conditions remain valid.
Capital Efficiency: Default setting uses 100% of equity per trade. Adjust "default_qty_value" to manage position sizing based on risk tolerance.
Realistic Backtesting: Strategy includes commission (0.1%) and slippage (3 ticks) to provide realistic performance expectations. These values should be adjusted based on your broker and market conditions.
Recommended Use Cases
Trending Markets: Best suited for markets with clear directional moves where trend-following strategies excel
Medium to Long-Term Trading: The default length of 70 makes this strategy more appropriate for swing trading rather than scalping
Risk-Conscious Traders: Multiple stop-loss options allow traders to customize risk management to their comfort level
Backtesting & Optimization: Comprehensive performance tracking features make this strategy ideal for testing different parameter combinations
Limitations & Considerations
Like all trend-following strategies, performance may suffer in choppy or ranging markets
Default 100% position sizing means full capital exposure per trade - consider reducing for conservative risk management
Higher length values (70+) reduce signal frequency but may improve signal quality
Multiple simultaneous risk management features may create conflicting exit signals
Past performance shown in backtests does not guarantee future results
Customization Tips
For more aggressive trading:
Reduce length parameter (minimum 70)
Decrease band multiplier for tighter bands
Enable short trades
Use lower profit target R:R ratios
For more conservative trading:
Increase length parameter
Enable ZLEMA trend confirmation
Use wider ATR stop-loss multipliers
Enable break-even stop-loss
Reduce position size from 100% default
For optimal choppy market performance:
Enable ZLEMA trend confirmation
Increase band multiplier
Use tighter profit targets
Avoid re-entry on trend continuation
Visual Elements
The strategy plots several elements on the chart:
ZLEMA line (color-coded by trend direction)
Upper and lower volatility bands
Long entry markers (green triangles)
Short entry markers (red triangles, when enabled)
Stop-loss levels (when positions are open)
Take-profit levels (when enabled and positions are open)
Trailing stop lines (when enabled and positions are open)
Optional ZLEMA trend markers (triangles at highs/lows)
Optional trade log labels showing complete trade information
Exit Reason Codes (for CSV Export)
When CSV export is enabled, exit reasons are coded as:
0 = Manual/Other
1 = Trailing Stop-Loss
2 = Profit Target
3 = ATR Stop-Loss
4 = Trend Change
Conclusion
Zero Lag Trend Signals V7 provides a robust framework for trend-following with extensive customization options. The strategy balances simplicity in its core logic with sophisticated risk management features, making it suitable for both beginner and advanced traders. By reducing moving average lag while incorporating volatility-based signals, it aims to capture trends earlier while managing risk through multiple configurable exit mechanisms.
The modular design allows traders to start with basic trend-following and progressively add complexity through ZLEMA confirmation, multiple stop-loss methods, and advanced exit strategies. Comprehensive performance tracking and export capabilities make this strategy an excellent tool for systematic testing and optimization.
Note: This strategy is provided for educational and backtesting purposes. All trading involves risk. Past performance does not guarantee future results. Always test thoroughly with paper trading before risking real capital, and adjust position sizing and risk parameters according to your risk tolerance and account size.
================================================================================
TAGS:
================================================================================
trend following, ZLEMA, zero lag, volatility bands, ATR stops, risk management, swing trading, momentum, trend confirmation, backtesting
================================================================================
CATEGORY:
================================================================================
Strategies
================================================================================
CHART SETUP RECOMMENDATIONS:
================================================================================
For optimal visualization when publishing:
Use a clean chart with no other indicators overlaid
Select a timeframe that shows multiple trade signals (4H or Daily recommended)
Choose a trending asset (crypto, forex major pairs, or trending stocks work well)
Show at least 6-12 months of data to demonstrate strategy across different market conditions
Enable the floating stats table to display key performance metrics
Ensure all indicator lines (ZLEMA, bands, stops) are clearly visible
Use the default chart type (candlesticks) - avoid Heikin Ashi, Renko, etc.
Make sure symbol information and timeframe are clearly visible
================================================================================
COMPLIANCE NOTES:
================================================================================
✅ Open-source publication with complete code visibility
✅ English-only title and description
✅ Detailed explanation of methodology and calculations
✅ Realistic commission (0.1%) and slippage (3 ticks) included
✅ All default parameters clearly documented
✅ Performance limitations and risks disclosed
✅ No unrealistic claims about performance
✅ No guaranteed results promised
✅ Appropriate for public library (original trend-following implementation with ZLEMA)
✅ Educational disclaimers included
✅ All features explained in detail
================================================================================
Luxy Adaptive MA Cloud - Trend Strength & Signal Tracker V2Luxy Adaptive MA Cloud - Professional Trend Strength & Signal Tracker
Next-generation moving average cloud indicator combining ultra-smooth gradient visualization with intelligent momentum detection. Built for traders who demand clarity, precision, and actionable insights.
═══════════════════════════════════════════════
WHAT MAKES THIS INDICATOR SPECIAL?
═══════════════════════════════════════════════
Unlike traditional MA indicators that show static lines, Luxy Adaptive MA Cloud creates a living, breathing visualization of market momentum. Here's what sets it apart:
Exponential Gradient Technology
This isn't just a simple fill between two lines. It's a professionally engineered gradient system with 26 precision layers using exponential density distribution. The result? An organic, cloud-like appearance where the center is dramatically darker (15% transparency - where crossovers and price action occur), while edges fade gracefully (75% transparency). Think of it as a visual "heat map" of trend strength.
Dynamic Momentum Intelligence
Most MA clouds only show structure (which MA is on top). This indicator shows momentum strength in real-time through four intelligent states:
- 🟢 Bright Green = Explosive bullish momentum (both MAs rising strongly)
- 🔵 Blue = Weakening bullish (structure intact, but momentum fading)
- 🟠 Orange = Caution zone (bearish structure forming, weak momentum)
- 🔴 Deep Red = Strong bearish momentum (both MAs falling)
The cloud literally tells you when trends are accelerating or losing steam.
Conditional Performance Architecture
Every calculation is optimized for speed. Disable a feature? It stops calculating entirely—not just hidden, but not computed . The 26-layer gradient only renders when enabled. Toggle signals off? Those crossover checks don't run. This makes it one of the most efficient cloud indicators available, even with its advanced visual system.
Zero Repaint Guarantee
All signals and momentum states are based on confirmed bar data only . What you see in historical data is exactly what you would have seen trading live. No lookahead bias. No repainting tricks. No signals that "magically" appear perfect in hindsight. If a signal shows in history, it would have triggered in real-time at that exact moment.
Educational by Design
Every single input includes comprehensive tooltips with:
- Clear explanations of what each parameter does
- Practical examples of when to use different settings
- Recommended configurations for scalping, day trading, and swing trading
- Real-world trading impact ("This affects entry timing" vs "This is visual only")
You're not just getting an indicator—you're learning how to use it effectively .
═══════════════════════════════════════════════
THE GRADIENT CLOUD - TECHNICAL DETAILS
═══════════════════════════════════════════════
Architecture:
26 precision layers for silk-smooth transitions
Exponential density curve - layers packed tightly near center (where crossovers happen), spread wider at edges
75%-15% transparency range - center is highly opaque (15%), edges fade gracefully (75%)
V-Gradient design - emphasizes the action zone between Fast and Medium MAs
The Four Momentum States:
🟢 GREEN - Strong Bullish
Fast MA above Medium MA
Both MAs rising with momentum > 0.02%
Action: Enter/hold LONG positions, strong uptrend confirmed
🔵 BLUE - Weak Bullish
Fast MA above Medium MA
Weak or flat momentum
Action: Caution - bullish structure but losing strength, consider trailing stops
🟠 ORANGE - Weak Bearish
Medium MA above Fast MA
Weak or flat momentum
Action: Warning - bearish structure developing, consider exits
🔴 RED - Strong Bearish
Medium MA above Fast MA
Both MAs falling with momentum < -0.02%
Action: Enter/hold SHORT positions, strong downtrend confirmed
Smooth Transitions: The momentum score is smoothed using an 8-bar EMA to eliminate noise and prevent whipsaws. You see the true trend , not every minor fluctuation.
═══════════════════════════════════════════════
FLEXIBLE MOVING AVERAGE SYSTEM
═══════════════════════════════════════════════
Three Customizable MAs:
Fast MA (default: EMA 10) - Reacts quickly to price changes, defines short-term momentum
Medium MA (default: EMA 20) - Balances responsiveness with stability, core trend reference
Slow MA (default: SMA 200, optional) - Long-term trend filter, major support/resistance
Six MA Types Available:
EMA - Exponential; faster response, ideal for momentum and day trading
SMA - Simple; smooth and stable, best for swing trading and trend following
WMA - Weighted; middle ground between EMA and SMA
VWMA - Volume-weighted; reflects market participation, useful for liquid markets
RMA - Wilder's smoothing; used in RSI/ADX, excellent for trend filters
HMA - Hull; extremely responsive with minimal lag, aggressive option
Recommended Settings by Trading Style:
Scalping (1m-5m):
Fast: EMA(5-8)
Medium: EMA(10-15)
Slow: Not needed or EMA(50)
Day Trading (5m-1h):
Fast: EMA(10-12)
Medium: EMA(20-21)
Slow: SMA(200) for bias
Swing Trading (4h-1D):
Fast: EMA(10-20)
Medium: EMA(34-50)
Slow: SMA(200)
Pro Tip: Start with Fast < Medium < Slow lengths. The gradient works best when there's clear separation between Fast and Medium MAs.
═══════════════════════════════════════════════
CROSSOVER SIGNALS - CLEAN & RELIABLE
═══════════════════════════════════════════════
Golden Cross ⬆ LONG Signal
Fast MA crosses above Medium MA
Classic bullish reversal or trend continuation signal
Most reliable when accompanied by GREEN cloud (strong momentum)
Death Cross ⬇ SHORT Signal
Fast MA crosses below Medium MA
Classic bearish reversal or trend continuation signal
Most reliable when accompanied by RED cloud (strong momentum)
Signal Intelligence:
Anti-spam filter - Minimum 5 bars between signals prevents noise
Clean labels - Placed precisely at crossover points
Alert-ready - Built-in ALERTS for automated trading systems
No repainting - Signals based on confirmed bars only
Signal Quality Assessment:
High-Quality Entry:
Golden Cross + GREEN cloud + Price above both MAs
= Strong bullish setup ✓
Low-Quality Entry (skip or wait):
Golden Cross + ORANGE cloud + Choppy price action
= Weak bullish setup, likely whipsaw ✗
═══════════════════════════════════════════════
REAL-TIME INFO PANEL
═══════════════════════════════════════════════
An at-a-glance dashboard showing:
Trend Strength Indicator:
Visual display of current momentum state
Color-coded header matching cloud color
Instant recognition of market bias
MA Distance Table:
Shows percentage distance of price from each enabled MA:
Green rows : Price ABOVE MA (bullish)
Red rows : Price BELOW MA (bearish)
Gray rows : Price AT MA (rare, decision point)
Distance Interpretation:
+2% to +5%: Healthy uptrend
+5% to +10%: Getting extended, caution
+10%+: Overextended, expect pullback
-2% to -5%: Testing support
-5% to -10%: Oversold zone
-10%+: Deep correction or downtrend
Customization:
4 corner positions
5 font sizes (Tiny to Huge)
Toggle visibility on/off
═══════════════════════════════════════════════
HOW TO USE - PRACTICAL TRADING GUIDE
═══════════════════════════════════════════════
STRATEGY 1: Trend Following
Identify trend : Wait for GREEN (bullish) or RED (bearish) cloud
Enter on signal : Golden Cross in GREEN cloud = LONG, Death Cross in RED cloud = SHORT
Hold position : While cloud maintains color
Exit signals :
• Cloud turns ORANGE/BLUE = momentum weakening, tighten stops
• Opposite crossover = close position
• Cloud turns opposite color = full reversal
STRATEGY 2: Pullback Entries
Confirm trend : GREEN cloud established (bullish bias)
Wait for pullback : Price touches or crosses below Fast MA
Enter when : Price rebounds back above Fast MA with cloud still GREEN
Stop loss : Below Medium MA or recent swing low
Target : Previous high or when cloud weakens
STRATEGY 3: Momentum Confirmation
Your setup triggers : (e.g., chart pattern, support/resistance)
Check cloud color :
• GREEN = proceed with LONG
• RED = proceed with SHORT
• BLUE/ORANGE = skip or reduce size
Use gradient as confluence : Not as primary signal, but as momentum filter
Risk Management Tips:
Never enter against the cloud color (don't LONG in RED cloud)
Reduce position size during BLUE/ORANGE (transition periods)
Place stops beyond Medium MA for swing trades
Use Slow MA (200) as final trend filter - don't SHORT above it in uptrends
═══════════════════════════════════════════════
PERFORMANCE & OPTIMIZATION
═══════════════════════════════════════════════
Tested On:
Crypto: BTC, ETH, major altcoins
Stocks: SPY, AAPL, TSLA, QQQ
Forex: EUR/USD, GBP/USD, USD/JPY
Indices: S&P 500, NASDAQ, DJI
═══════════════════════════════════════════════
TRANSPARENCY & RELIABILITY
═══════════════════════════════════════════════
Educational Focus:
Detailed tooltips on every input
Clear documentation of methodology
Practical examples in descriptions
Teaches you why , not just what
Open Logic:
Momentum calculation: (Fast slope + Medium slope) / 2
Smoothing: 8-bar EMA to reduce noise
Thresholds: ±0.02% for strong momentum classification
Everything is transparent and explainable
═══════════════════════════════════════════════
COMPLETE FEATURE LIST
═══════════════════════════════════════════════
Visual Components:
26-layer exponential gradient cloud
3 customizable moving average lines
Golden Cross / Death Cross labels
Real-time info panel with trend strength
MA distance table
Calculation Features:
6 MA types (EMA, SMA, WMA, VWMA, RMA, HMA)
Momentum-based cloud coloring
Smoothed trend strength scoring
Conditional performance optimization
Customization Options:
All MA lengths adjustable
All colors customizable (when gradient disabled)
Panel position (4 corners)
Font sizes (5 options)
Toggle any feature on/off
Signal Features:
Anti-spam filter (configurable gap)
Clean, non-overlapping labels
Built-in alert conditions
No repainting guarantee
═══════════════════════════════════════════════
IMPORTANT DISCLAIMERS
═══════════════════════════════════════════════
This indicator is for educational and informational purposes only
Not financial advice - always do your own research
Past performance does not guarantee future results
Use proper risk management - never risk more than you can afford to lose
Test on paper/demo accounts before using with real money
Combine with other analysis methods - no single indicator is perfect
Works best in trending markets; less effective in choppy/sideways conditions
Signals may perform differently in different timeframes and market conditions
The indicator uses historical data for MA calculations - allow sufficient lookback period
═══════════════════════════════════════════════
CREDITS & TECHNICAL INFO
═══════════════════════════════════════════════
Version: 2.0
Release: October 2025
Special Thanks:
TradingView community for feedback and testing
Pine Script documentation for technical reference
═══════════════════════════════════════════════
SUPPORT & UPDATES
═══════════════════════════════════════════════
Found a bug? Comment below with:
Ticker symbol
Timeframe
Screenshot if possible
Steps to reproduce
Feature requests? I'm always looking to improve! Share your ideas in the comments.
Questions? Check the tooltips first (hover over any input) - most answers are there. If still stuck, ask in comments.
═══════════════════════════════════════════════
Happy Trading!
Remember: The best indicator is the one you understand and use consistently. Take time to learn how the cloud behaves in different market conditions. Practice on paper before going live. Trade smart, manage risk, and may the trends be with you! 🚀
VWAP Entry Assistant (v1.0)Description:
Anchored VWAP with a lightweight assistant for VWAP reversion trades.
It shows the distance to VWAP, an estimated hit probability for the current bar, the expected number of bars to reach VWAP, and a recommended entry price.
If the chance of touching VWAP is low, the script suggests an adjusted limit using a fraction of ATR.
The VWAP line is white by default, and a compact summary table appears at the bottom-left.
Educational tool. Not financial advice. Not affiliated with TradingView or any exchange. Always backtest before use.
Buy/Sell Signals [WynTrader]My name is WynTrader. I cumulate 24 years of experience.
This Indicator produces Buy/Sell Signals using these features:
- Fast and Slow Moving averages (modifiable) optimized at EMA-8 and SMA-35
- Bollinger Bands (modifiable) optimized at Basis-18 and Multiplier-1
Also, the Buy/Sell Signals are conditioned by three Filters (optionable, modifiable) :
. Bollinger-Bands Lookback
. High-Low vs Candle Range %
. Distance from Fast and Slow Moving averages %
The Results Calculation presented in a Table are based :
- on the Current Chart Visible Range (optionable)
or
- on the specified TIme Frame Start and End Dates (modifiable)
The Table shows Calculation Results of the Buy and Sell Signals that are activated on the chart, with the Number of Trades (Signals), the Winning Points and the Win Rate %. The Buy&Hold starts calculation at the first Buy encountered.
So be surprised by my Buy/Sell Indicator. But always remember that the world is not perfect. The Graal Indicator, even with AI, doesn't already exist, maybe one day (all of us richier...), but not now. , depending on the chart product (stocks...), volatility, probabilities, unpredictable behaviour. , the moves, etc.
Enjoy
WynTrader
P. s. :
My name is WynTrader. I cumulate 24 years of experience. In 2001, I took an intensive technical analysis course taught by an exceptional friend, Cyril, who taught me everything I know. The foundation I gained through his teaching remains solid and relevant to this day, never failing me.
Before i made this Indicator, I have used many Trading View Buy/Sell Indicators using alone or combined RSI, SMI, OBV, MACD ATR, ADX, Neural, Fractal, Geometry, etc., that are already available for the Trading View community. A great thanks to those who give their time that help me build this tool.
Note that I'm not a programmer, so... ;-)
Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
