Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]

Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]


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.

// [Code Snippet] 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 [ApexLegion]" 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.