Praetor Sentinel V11.2 NOLOOSE BETA📈 Praetor Sentinel V11.2 – "NOLOOSE BETA"
Algorithmic Trading Strategy for Trend Markets with Adaptive Risk Management
Praetor Sentinel V11.2 is an advanced algorithmic trading strategy for TradingView, specifically designed to operate in strong trend conditions. It combines multiple technical systems—including dynamic trend filters, multi-layer EMA structures, ADX-based volatility control, and adaptive trailing stops—into a powerful and automated trading framework.
🔧 Core Features
Multi-EMA Trend Detection: Two EMA pairs (short/long) to identify and confirm directional trends.
XO-EMA Breakout Logic: Fast EMA crossover to detect breakout opportunities.
ADX Trend Filter: Trades only during strong market trends (above custom ADX threshold).
HTF Filter: Optional higher timeframe trend confirmation (e.g. Daily 50 EMA).
VWAP Validation: Ensures entries aren't taken against the volumetric average.
RSI Filter: Adds a momentum filter (e.g. RSI > 50 for long trades).
🎯 Entry Signals
The strategy uses two entry types:
Breakout Entries: Based on XO-EMA cross and multi-EMA trend alignment.
Pullback Entries: Configurable via various methods such as EMA21 reentry, RSI reversal, engulfing candles, or VWAP reclaim.
All entries can be delayed via confirmation candle logic, requiring a bullish or bearish follow-up bar.
🛡️ Risk Management & Exit Logic
Dynamic ATR Trailing Stop: Adjusts stop distance according to market volatility with optional swing high/low protection.
Break-Even Logic: Locks in trades at breakeven once a defined profit is reached.
Hard Stop-Loss: Caps potential loss per trade with a fixed % (e.g. 1%).
Safe Mode ("NOLOOSE"): Exits early if price moves too far against the position — ideal for automated bots that must avoid drawdowns.
🤖 Automation & Alerts
This strategy is fully automatable with services like 3Commas using built-in alert messages for entries and exits.
All parameters are fully configurable to adapt to different assets, timeframes, and trading styles.
⚙️ Additional Features
Configurable leverage & position sizing
Time-based trading window
Built-in Anchored VWAP
Modular design for easy extension
📌 Summary
Praetor Sentinel V11.2 is a professional-grade tool for trend traders who want rule-based entry/exit logic, adaptive stop systems, and robust protection features. When paired with automation tools, it offers a reliable, low-maintenance setup that emphasizes safety, structure, and scalability.
🛠 How to Use Praetor Sentinel V11.2 – NOLOOSE BETA
🔍 1. Basic Configuration (Required)
Setting Description
Enable Long Trades Enables long (buy) positions.
Enable Short Trades Enables short (sell) positions.
Leverage Used for position sizing calculations.
Position Size % Defines % of capital to be used per trade.
⏰ 2. Time Filter (Optional)
Restricts trading to a defined time range.
Setting Description
Start Date Start date for strategy to be active.
End Date End date for strategy to stop.
Time Zone Time zone for above settings.
📊 3. Trend Setup (Essential for Entry Signals)
Setting Description
MA Type Type of moving average: EMA or SMA.
EMA1/2 Short & Long Two EMA-based systems to determine trend.
Fast/Slow EMA (XO) Used for crossover breakout detection.
HTF Filter Uses higher timeframe trend for additional confirmation.
RSI Filter Confirms entries only if momentum (RSI) supports it.
ADX Threshold Ensures trades only occur during strong trends.
🎯 4. Entry Logic
Setting Description
Pullback Entry Type Enables optional entry setups:
"Off"
"EMA21"
"RSI"
"Engulfing"
"VWAP"
| Use Confirmation Candle | Entry is delayed until a confirmation bar appears. |
| VWAP Confirmation | Trade only if price is above/below the VWAP (based on direction). |
Note: You can combine breakout + pullback signals. Only one has to trigger.
🧯 5. Risk Control & Exit Settings
Setting Description
Trailing Stop Mode
"Standard": Classic trailing stop
"Dynamic ATR": Adjusts to current volatility
"Dynamic ATR + Swing": Adds swing high/low buffer
| Enable Break-Even | Moves SL to breakeven once a target % gain is reached. |
| Enable Hard Stop-Loss | Fixed stop-loss (e.g. 1%) to cap trade risk. |
| Enable Safe Mode | Exits trade early if price moves against it beyond defined % (e.g. 0.3%). |
🔔 6. Alerts & Bot Automation
Setting Description
Entry Long/Short Msg Text message sent via alert when a position opens.
Exit Long/Short Msg Alert message for stop-loss/exit logic.
How to automate with 3Commas:
Load the strategy on your chart.
Manually create alerts using "Create Alert" in TradingView.
Use the built-in alert_message values for bot integration.
✅ Recommended Settings (Example for BTC/ETH on 1H)
Long & Short: ✅ Enabled
Leverage: 2.0
Timeframe: 1H
Pullback Entry: "EMA21"
MA Type: EMA
HTF Filter: Enabled (Daily EMA50)
RSI Filter: Enabled
VWAP Filter: Enabled
Break-Even: On at 0.5%
Hard SL: 1.0%
Safe Mode: On at -0.3%
Trailing Stop: "Dynamic ATR + Swing"
📘 Pro Tips for Testing & Customization
Use the Strategy Tester in TradingView to analyze performance over different assets.
Experiment with timeframes and entry modes.
Ideal for trending assets like BTC, ETH, SOL, etc.
You can expand it with take-profit logic, fixed TPs, indicator exits, etc.
指標和策略
[blackcat] L2 Trend Guard OscillatorOVERVIEW
📊 The L2 Trend Guard Oscillator is a comprehensive technical analysis framework designed specifically to identify market trend reversals using adaptive filtering algorithms that combine price action dynamics with statistical measures of volatility and momentum.
Key Purpose:
Generate reliable early warning signals before major trend changes occur
Provide clear directional bias indicators aligned with institutional investor behavior patterns
Offer risk-managed entry/exit opportunities suitable for various timeframes
TECHNICAL FOUNDATION EXPLAINED
🎓 Core Mechanism Breakdown:
→ Advanced smoothing technique emphasizing recent data points more heavily than older ones
↓ Reduces lag while maintaining signal integrity compared to traditional MA approaches
• Short-term Momentum Assessment:
🔶 Relative strength between closing prices vs lower bounds
• Long-term Directional Bias Analysis:
📈 Extended timeframe comparison generating structural context
• Defense Level Generation:
➜ Protective boundary calculation incorporating EMAs for stability enhancement
PARAMETER CONFIGURATION GUIDE
🔧 Adjustable Settings Explained In Detail:
Timeframe Selection:**
↔ Controls lookback period sensitivity affecting responsiveness
↕ Adjusts reaction speed vs accuracy trade-off dynamically
Weight Factor Specification:**
⚡ Influences emphasis on newer versus historical observations
🎯 Defines key decision-making thresholds clearly
ALGORITHM EXECUTION FLOW
💻 Processing Sequence Overview:
:
→ Gather raw pricing inputs across required periods
↓ Normalize values preparing them for subsequent processing stages
:
✔ Calculate relative strength positions against established ranges
❌ Filter outliers maintaining signal integrity consistently
⟶ Apply dual-pass filtering reducing false signals effectively
➡ Generate actionable trading opportunities systematically
VISUALIZATION ARCHITECTURE
🎨 Display Elements Designated Purpose:
🔵 Primary Indicator Traces:
→ Aqua Trace: Buy/Sell Signal Progression
↑ Red Line: Opposing Force Boundary
🟥 Gray Dashed: Zero Reference Point
🏷️ Label System For Critical Events:
✅ BUY: Bullish Opportunity Markers
❌ SELL: Bearish Setup Validations
STRATEGIC IMPLEMENTATION FRAMEWORK
📋 Practical Deployment Steps:
Initial Integration Protocol:
• Select appropriate timeframe matching strategy objectives
• Configure input parameters aligning with target asset behavior traits
• Conduct thorough backtesting under simulated environments initially
Active Monitoring Procedures:
→ Regular observation of labeled event placements versus actual movements
↓ Track confirmation patterns leading up to signaled opportunities carefully
↑ Evaluate overall framework reliability across different regime types regularly
Execution Guidelines Formulation:
✔ Enter positions only after achieving minimum number of confirming inputs
❌ Avoid isolated occurrences lacking adequate supporting evidence always
➞ Look for convergent factors strengthening conviction before acting decisively
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Continuous Improvement Strategies:
Parameter Calibration Approach:
✓ Start testing default suggested configurations thoroughly
↕ Gradually adjust individual components observing outcome changes methodically
✨ Document findings building personalized version profile incrementally
Context Adaptability Methods:
🔄 Add supplementary indicators enhancing overall reliability when needed
🔧 Remove unnecessary complexity layers avoiding confusion/distracted decisions
💫 Incorporate custom rules adapting specific security behaviors effectively
Efficiency Improvement Tactics:
⚙️ Streamline redundant computational routines wherever possible efficiently
♻️ Leverage shared data streams minimizing resource utilization significantly
⏳ Optimize refresh frequencies balancing update speed vs overhead properly
MarketCap_FreeFloatGive you market cap and free float instantly..
Considers TOTAL_SHARES_OUTSTANDING & FLOAT_SHARES_OUTSTANDING
Multiplies by
// Calculate metrics in crores
MarketCap = Outstanding * close
FreeFloat = free_float * close
Values are in INR (Crores)
Breakout Swing High LowThis open-source indicator identifies swing high and swing low breakouts, providing clear visual signals for potential trend entries. It is designed for traders who use price action to spot breakout opportunities in trending markets.
How It Works
Swing Detection: The indicator uses a user-defined lookback period (default: 4 candles) to identify swing highs (peaks) and swing lows (troughs). A swing high is confirmed when a candle's high is higher than the surrounding candles, and a swing low is confirmed when a candle's low is lower.
Breakout Signals: A green triangle below the candle signals a breakout above the most recent swing high, indicating a potential buy opportunity. A red triangle above the candle signals a breakout below the most recent swing low, indicating a potential sell opportunity. Each swing level triggers only one breakout signal to avoid clutter.
Visualization: Swing high levels are drawn as green dashed lines, and swing low levels as red dashed lines, extending 15 candles for clarity. Breakout signals are marked with small triangles.
How to Use
Apply the Indicator: Add the indicator to your TradingView chart.
Adjust Lookback: Set the "Lookback Candles" input (default: 4) to control the sensitivity of swing detection. Smaller values detect shorter-term swings, while larger values identify more significant levels.
Interpret Signals:
Green triangle (below candle): Consider a buy opportunity when price breaks above a swing high.
Red triangle (above candle): Consider a sell opportunity when price breaks below a swing low.
Combine with Other Tools: Use in conjunction with trend indicators (e.g., 50-period EMA) or support/resistance levels to filter signals in trending markets.
Timeframes: Works best on higher timeframes (e.g., 1H, 4H) in trending markets to avoid false breakouts in sideways conditions.
Uptrend Filter: Price > 50 & 200 MA + Upward SlopeThis indicator is designed to help traders instantly identify strong uptrend conditions based on two simple yet powerful criteria:
Price is above both the 50-day and 200-day moving averages
Both moving averages are sloping upward (positive momentum)
When both conditions are met, the indicator plots a green “UP” label below the candle, signaling a valid uptrend setup. This filter is ideal for asset selection in strategy-building, portfolio rotation, or trend-following systems.
🧠 Why it works:
The 50-day MA reflects medium-term momentum.
The 200-day MA represents the long-term trend.
When both are aligned and sloping upward, it confirms strong market structure and trend health.
🧰 Best used for:
Token screening (e.g., filtering altcoins)
Momentum-based entries
Trend confirmation
Risk filtering in strategy backtesting
[blackcat] L3 Smart Money FlowCOMPREHENSIVE ANALYSIS OF THE L3 SMART MONEY FLOW INDICATOR
🌐 OVERVIEW:
The L3 Smart Money Flow indicator represents a sophisticated multi-dimensional analytics tool combining traditional momentum measurements with advanced institutional investor tracking capabilities. It's particularly effective at identifying large-scale capital movement dynamics that often precede significant price shifts.
Core Objectives:
• Detect subtle but meaningful price action anomalies indicating major player involvement
• Provide clear entry/exit markers based on multiple validated criteria
• Offer risk-managed positioning strategies suitable for various account sizes
• Maintain operational efficiency even during high volatility regimes
THEORETICAL BACKDROP AND METHODOLOGY
🎓 Conceptual Foundation Principles:
Utilizes Time-Varying Moving Averages (TVMA) responding adaptively to changing market states
Implements Extended Smoothing Algorithm (XSA) providing enhanced filtration characteristics
Employs asymmetric weight distribution favoring recent price observations over historical ones
→ Analyzes price-weighted closing prices incorporating volume influence indirectly
← Applies Asymmetric Local Maximum (ALMA) filters generating institution-specific trends
⟸ Combines multiple temporal perspectives producing robust directional assessments
✓ Calculates normalized momentum ratios comparing current state against extended range extremes
✗ Filters out insignificant fluctuations via double-stage verification process
⤾ Generates actionable alerts upon exceeding predefined significance boundaries
CONFIGURABLE PARAMETERS IN DEPTH
⚙️ Input Customization Options Detailed Explanation:
Temporal Resolution Control:
→ TVMA Length Setting:
Minimum value constraint ensuring mathematical validity
Higher numbers increase smoothing effect reducing reaction velocity
Lower intervals enhance responsiveness potentially increasing noise exposure
Validation Threshold Definition:
↓ Bull-Bear Boundary Level:
Establishes fundamental acceptance/rejection zones
Typically set near extreme values reflecting rare occurrence probability
Can be adjusted per instrument liquidity profiles if necessary
ADVANCED ALGORITHMIC PROCEDURES BREAKDOWN
💻 Internal Operation Architecture:
Base Calculations Infrastructure:
☑ Raw Data Preparation and Normalization
☐ High/Low/Closing Aggregation Processes
☒ Range Estimation Algorithms
Intermediate Transform Engine:
📈 Momentum Ratio Computation Workflow
↔ First Pass XSA Application Details
➖ Second Stage Refinement Mechanics
Final Output Synthesis Framework:
➢ Composite Reading Compilation Logic
➣ Validation Status Determination Process
➤ Alert Trigger Decision Making Structure
INTERACTIVE VISUAL INTERFACE COMPONENTS
🎨 User Experience Interface Elements:
🔵 Plotting Series Hierarchy:
→ Primary FundFlow Signal: White trace marking core oscillator progression
↑ Secondary Confirmation Overlay: Orange/Yellow highlighting validation status
🟥 Risk/Reward Boundaries: Aqua line delineating strategic areas requiring attention
🏷️ Interactive Marker System:
✔ "BUY": Green upward-pointing labels denoting confirmed long entries
❌ "SELL": Red downward-facing badges signaling short setups
PRACTICAL APPLICATION STRATEGY GUIDE
📋 Operational Deployment Instructions:
Strategic Planning Initiatives:
• Define precise profit targets considering realistic reward/risk scenarios
→ Set maximum acceptable loss thresholds protecting available resources adequately
↓ Develop contingency plans addressing unexpected adverse developments promptly
Live Trading Engagement Protocols:
→ Maintaining vigilant monitoring of label placement activities continuously
↓ Tracking order fill success rates across implemented grids regularly
↑ Evaluating system effectiveness compared alternative methodologies periodically
Performance Optimization Techniques:
✔ Implement incremental improvements iteratively throughout lifecycle
❌ Eliminate ineffective component variations systematically
⟹ Ensure proportional growth capability matching user needs appropriately
EFFICIENCY ENHANCEMENT APPROACHES
🚀 Ongoing Development Strategy:
Resource Management Focus Areas:
→ Minimizing redundant computation cycles through intelligent caching mechanisms
↓ Leveraging parallel processing capabilities where feasible efficiently
↑ Optimizing storage access patterns improving response times substantially
Scalability Consideration Factors:
✔ Adapting to varying account sizes/market capitalizations seamlessly
❌ Preventing bottlenecks limiting concurrent operation capacity
⟹ Ensuring balanced growth capability matching evolving requirements accurately
Maintenance Routine Establishment:
✓ Regular codebase updates incorporation keeping functionality current
↓ Periodic performance audits conducting verifying continued effectiveness
↑ Documentation refinement updating explaining any material modifications made
SYSTEMATIC RISK CONTROL MECHANISMS
🛡️ Comprehensive Protection Systems:
Position Sizing Governance:
∅ Never exceed predetermined exposure limitations strictly observed
± Scale entries proportionally according to available resources carefully
× Include slippage allowances within planning stages realistically
Emergency Response Procedures:
↩ Well-defined exit strategies including trailing stops activation logic
🌀 Contingency plan formulation covering worst-case scenario contingencies
⇄ Recovery procedure documentation outlining restoration steps methodically
EMA Cloud with Custom MAs and RSI [deepakks444]This all-in-one technical analysis tool merges an EMA Cloud, customizable dual moving averages (MA1 & MA2), and an advanced RSI oscillator with divergence detection, smoothing, and alerts.
Designed for traders who rely on trend direction, momentum, and reversal confluence, this indicator helps filter high-probability setups and reduces the need to juggle multiple indicators on the chart.
🔍 Components and Features
🔸 1. EMA Cloud (Trend Filter)
A lightweight 3-period EMA manually calculated using exponential smoothing.
Two EMAs: One tracking highs and one tracking lows.
Creates a "cloud" between them to visually represent short-term trend direction.
Cloud color logic:
🟢 Green: Price is bullish, staying above the EMA cloud.
🔴 Red: Price is bearish, below the EMA cloud.
🟡 Yellow: Price is indecisive or in consolidation.
Why it's useful:
The EMA Cloud helps identify the immediate short-term bias of the market. It quickly reacts to price and gives a clear visual guide for trend-following or pullback trades.
🔸 2. Custom Moving Averages (MA1 & MA2)
Both MA1 and MA2 are user-configurable in type, length, and price source.
Supported types include:
SMA, EMA, WMA, HMA, RMA, VWMA.
Color logic:
🟩 Green: MA1 is below MA2 (bullish alignment).
🟥 Red: MA1 is above MA2 (bearish alignment).
Why include this?
MA crossovers are a classic way to determine medium/long-term trend shifts or confirm trend continuation. The flexibility allows users to tailor them to suit any strategy—from mean reversion to trend-following.
🔸 3. RSI Oscillator with Enhancements
This is more than a basic RSI—it's been expanded to become a momentum engine and divergence detector, complete with alerting and smoothing options.
Main features:
✅ Customizable RSI Source & Length
✅ Colored RSI Zones:
RSI > 60 → Overbought strength zone (green background).
RSI < 40 → Oversold weakness zone (red background).
Neutral background in between.
✅ Smoothing Options:
Apply additional MA smoothing to RSI: SMA, EMA, WMA, RMA, VWMA, or even SMA + Bollinger Bands.
Visualizes volatility around RSI for breakout/reversal analysis.
✅ RSI Alerts:
Alert when RSI crosses above 60 → potential bullish momentum.
Alert when RSI crosses below 40 → potential bearish momentum.
✅ Divergence Detection (Optional):
Bullish Divergence: Price makes lower low while RSI makes higher low → Possible reversal up.
Bearish Divergence: Price makes higher high while RSI makes lower high → Possible reversal down.
Marks divergence using “Bull” and “Bear” labels directly on the RSI pane.
Why enhance RSI?
The RSI is a cornerstone of momentum trading. By adding zone shading, volatility overlays, and divergence detection, traders can better assess:
Whether a trend is strong or weakening.
Whether to enter on continuation or wait for reversal.
Spot early signs of price turning points using divergence patterns.
🤝 Why Merge These Three Systems?
Combining EMA Cloud + MAs + RSI in a single tool allows traders to:
Avoid conflicting signals by seeing multiple confirmations in one view.
Reduce chart clutter by replacing multiple indicators with one efficient visual system.
Get trend, momentum, and reversal analysis all-in-one:
EMA Cloud = short-term trend.
MA1/MA2 = medium-term trend & crossover confirmation.
RSI = momentum extremes, breakout confirmation, or divergence reversal zones.
🔔 Built-in Alerts
RSI crosses above 60 → Potential buy signal.
RSI crosses below 40 → Potential sell signal.
These alerts can be used to automate notifications, integrate with webhook systems, or trigger manual reviews.
⚠️ Disclaimer
This script is provided for educational and informational purposes only. It is not financial advice, and past performance is not indicative of future results. Always use proper risk management and verify signals with your own analysis before trading.
FA Dashboard: Valuation, Profitability & SolvencyFundamental Analysis Dashboard: A Multi-Dimensional View of Company Quality
This script presents a structured and customizable dashboard for evaluating a company’s fundamentals across three key dimensions: Valuation, Profitability, and Solvency & Liquidity.
Unlike basic fundamental overlays, this dashboard consolidates multiple financial indicators into visual tables that update dynamically and are grouped by category. Each ratio is compared against configurable thresholds, helping traders quickly assess whether a company meets certain value investing criteria. The tables use color-coded checkmarks and fail marks (✔️ / ❌) to visually signal pass/fail evaluations.
▶️ Key Features
Valuation Ratios:
Earnings Yield: EBIT / EV
EV / EBIT and EV / FCF: Enterprise value metrics for profitability
Price-to-Book, Free Cash Flow Yield, PEG Ratio
Profitability Ratios:
Return on Invested Capital (ROIC), ROE, Operating, Net & Gross Margins, Revenue Growth
Solvency & Liquidity Ratios:
Debt to Equity, Debt to EBITDA, Current Ratio, Quick Ratio, Altman Z-Score
Each of these metrics is calculated using request.financial() and can be viewed using either annual (FY) or quarterly (FQ) data, depending on user preference.
🧠 How to Use
Add the script to any stock chart.
Select your preferred data period (FY or FQ).
Adjust thresholds if desired to match your personal investing strategy.
Review the visual dashboard to see which metrics the company passes or fails.
💡 Why It’s Useful
This tool is ideal for traders or long-term investors looking to filter stocks using fundamental criteria. It draws inspiration from principles used by Benjamin Graham, Warren Buffett, and Joel Greenblatt, offering a fast and informative way to screen quality businesses.
This is not a repackaged built-in or autogenerated script. It’s a custom-built, interactive tool tailored for fundamental analysis using official financial data provided via Pine Script’s request.financial().
[NIC] Volatility Anomaly Indicator (Inspired by Jeff Augen)Volatility Anomaly Indicator (Inspired by Jeff Augen)
The Volatility Anomaly Indicator, inspired by Jeff Augen’s The Volatility Edge in Options Trading, helps traders spot price distortions by analyzing volatility imbalances. It compares short-term (10-day) and long-term (30-day) historical volatility (HV), plotting the ratio in a subgraph with clusters of dots to highlight anomalies—red for volatility spikes (potential sells) and green for calm periods (potential buys).
Originality: This indicator uniquely adapts Augen’s volatility concepts into a visual tool, focusing on relative volatility distortions rather than absolute levels, making it ideal for volatile assets like $TQQQ.
Features:
Calculates the ratio of short-term to long-term volatility.
Detects spikes (ratio > 1.5) and calm periods (ratio < 0.67) with customizable thresholds.
Plots volatility ratio as a blue line, with red/green dots for anomalies.
Includes optional buy/sell signals on the main chart (if overlay is enabled).
How It Works
The indicator computes historical volatility using log returns, then calculates the short-term to long-term volatility ratio. Spikes and calm periods are marked with dots in the subgraph, and threshold lines (1.5 and 0.67) provide context. Buy signals (green triangles) trigger during calm periods, and sell signals (red triangles) during spikes.
How to Use
Apply to any chart (e.g., NASDAQ:TQQQ daily).
Adjust inputs: Short Volatility Period (10), Long Volatility Period (30), Volatility Spike Threshold (1.5).
Watch for red dot clusters (spikes, potential sells) and green dot clusters (calm, potential buys).
Combine with price action or RSI for confirmation.
Why Use This Indicator?
Focuses on volatility-driven price inefficiencies.
Clear visualization with dot clusters.
Customizable for different assets and timeframes.
Limitations
Not a standalone system; requires confirmation.
May give false signals in choppy markets.
Money Flow based probabilityMoney Flow based probability
This indicator provides a comprehensive correlation and momentum analysis between your main asset and up to three selected correlated assets. It combines correlation, trend, momentum, and overbought/oversold signals into a single, easy-to-read table directly on your chart.
Correlated Asset Selection :
You can select up to three correlated assets (e.g., indices, currencies, bonds) to compare with your main chart symbol. Each asset can be toggled on or off.
Correlation Calculation :
The indicator uses the native Pine Script ta.correlation function to measure the statistical relationship between the closing prices of your asset and each selected pair over a user-defined period.
Technical Analysis Integration :
For each asset (including the main one), the indicator calculates:
Trend direction using EMA (Exponential Moving Average) – optional
Momentum using MACD – optional
Overbought/oversold status using RSI – optional
Probability Scoring :
A weighted scoring system combines correlation, trend, MACD, RSI, and trend exhaustion signals to produce buy and sell probabilities for the main asset.
Visual Table Output :
A customizable table is displayed on the chart, showing:
Asset name
Correlation (as a percentage, -100% to +100%)
Trend (Bullish/Bearish)
MACD status (Bullish/Bearish)
RSI value and status
Buy/Sell probability (with fixed-width formatting for stability)
User Customization :
You can adjust:
Table size, color, and position
Correlation period
EMA, MACD, and RSI parameters
Which assets to display
This indicator is ideal for traders who want to quickly assess the influence of major correlated markets and technical signals on their trading instrument, all in a single glance.
---
Example: Correlation Calculation
corrCurrentAsset1 = ta.correlation(close, asset1Data, correlationPeriod)
Example: Table Output (Buy/Sell %)
buyStr = f_formatPercent(buyProbability) + "%"
sellStr = f_formatPercent(sellProbability) + "%"
cellStr = buyStr + " / " + sellStr
Intraday Trading IndicatorIndicator Overview
Moving Averages: Uses a fast EMA (9-period) and a slow EMA (21-period) to determine the trend direction.
Market Profile Approximation: Utilizes VWAP (Volume Weighted Average Price) as a simplified proxy for value area, acting as a dynamic support/resistance level.
SMC: Incorporates the concept of trend confirmation and price interaction with key levels, focusing on pullbacks to the fast EMA within a trending market.
Signals: Generates buy and sell signals when price crosses the fast EMA, filtered by the trend (fast EMA vs. slow EMA) and VWAP position, aiming for high-probability setups.
This design ensures responsiveness on short timeframes while filtering out noise, aligning with the goal of accurate signals for intraday trading.
FRP Options Risk CalculatorThe Options Risk Calculator V1.0 is a fast, visual tool designed to help options traders evaluate position sizing, risk exposure, and profit targets in real-time.
🔹 Features:
- Contract-based entry price
- User-defined quantity, stop loss %, and take profit %
- Per-contract and total value breakdown
- Dynamic, color-coded table display
- Adjustable colors to match your theme
📘 How to Use:
1. Set your contract price (e.g. 2.50 = $250)
2. Enter how many contracts you’re buying
3. Set your Stop Loss % (e.g. 21%) and Target % (e.g. 30%)
4. View the on-screen table
→ It updates live with dollar values per contract and total risk/reward
⚠️ Note: This tool is for planning and visualization purposes only. It does not execute or suggest trades.
Source code is protected.
MACD + SMA 200 Indicator v6🔹 Overview
This advanced indicator combines MACD components with a 200-period SMA to identify high-probability trend directions. It provides:
✅ Multi-timeframe trend analysis (Fast, Slow, and Very Slow MAs)
✅ Visual alerts when the 200 SMA changes direction (bullish/bearish)
✅ Customizable display options (toggle MAs on/off individually)
✅ Clean, professional visuals with color-coded trend confirmation
Perfect for swing traders and investors who want to align with the dominant trend while avoiding false signals.
📊 Key Features
1. Triple Moving Average System
Fast MA (12-period) – Short-term momentum
Slow MA (26-period) – Medium-term trend
Very Slow MA (200-period) – Long-term trend filter (bullish/bearish market)
2. Smart Trend Detection
200 SMA Color Shift: Automatically changes color when trend reverses (green = bullish, red = bearish).
Visual Labels ("BU" / "SD"): Marks where the 200 SMA confirms a new trend direction.
3. Fully Customizable
Toggle each MA on/off (reduce clutter if needed).
Enable/disable colors for cleaner charts.
Adjustable lengths for all moving averages.
4. Built-in Alerts
🔔 "Very Slow MA Turned Green" – Signals potential bullish reversal.
🔔 "Very Slow MA Turned Red" – Signals potential bearish reversal.
🎯 How to Use This Indicator
📈 Bullish Confirmation (Long Setup)
✔ Price above 200 SMA (Very Slow MA turns green)
✔ Fast MA (12) > Slow MA (26) (MACD momentum supports uptrend)
✔ "BU" label appears (confirms trend shift)
📉 Bearish Confirmation (Short Setup)
✔ Price below 200 SMA (Very Slow MA turns red)
✔ Fast MA (12) < Slow MA (26) (MACD momentum supports downtrend)
✔ "SD" label appears (confirms trend shift)
⚙️ Settings & Customization
MA Visibility: Turn individual MAs on/off.
Colors: Disable if you prefer a minimal chart.
Alerts: Enable to get notifications when the 200 SMA changes trend.
📌 Why This Indicator?
Avoid false signals by combining MACD with the 200 SMA.
Clear visual cues make trend identification effortless.
Works on all timeframes (best on 1H, 4H, Daily for swing trades).
🔗 Try it now and trade with the trend! 🚀
📥 Get the Indicator
👉 Click "Add to Chart" and customize it to your trading style!
💬 Feedback? Let me know in the comments how it works for you!
The Echo System🔊 The Echo System – Trend + Momentum Trading Strategy
Overview:
The Echo System is a trend-following and momentum-based trading tool designed to identify high-probability buy and sell signals through a combination of market trend analysis, price movement strength, and candlestick validation.
Key Features:
📈 Trend Detection:
Uses a 30 EMA vs. 200 EMA crossover to confirm bullish or bearish trends.
Visual trend strength meter powered by percentile ranking of EMA distance.
🔄 Momentum Check:
Detects significant price moves over the past 6 bars, enhanced by ATR-based scaling to filter weak signals.
🕯️ Candle Confirmation:
Validates recent price action using the previous and current candle body direction.
✅ Smart Conditions Table:
A live dashboard showing all trade condition checks (Trend, Recent Price Move, Candlestick confirmations) in real-time with visual feedback.
📊 Backtesting & Stats:
Auto-calculates average win, average loss, risk-reward ratio (RRR), and win rate across historical signals.
Clean performance dashboard with color-coded metrics for easy reading.
🔔 Alerts:
Set alerts for trade signals or significant price movements to stay updated without monitoring the chart 24/7.
Visuals:
Trend markers and price movement flags plotted directly on the chart.
Dual tables:
📈 Conditions table (top-right): breaks down trade criteria status.
📊 Performance table (bottom-right): shows real-time stats on win/loss and RRR.🔊 The Echo System – Trend + Momentum Trading Strategy
Overview:
The Echo System is a trend-following and momentum-based trading tool designed to identify high-probability buy and sell signals through a combination of market trend analysis, price movement strength, and candlestick validation.
Key Features:
📈 Trend Detection:
Uses a 30 EMA vs. 200 EMA crossover to confirm bullish or bearish trends.
Visual trend strength meter powered by percentile ranking of EMA distance.
🔄 Momentum Check:
Detects significant price moves over the past 6 bars, enhanced by ATR-based scaling to filter weak signals.
🕯️ Candle Confirmation:
Validates recent price action using the previous and current candle body direction.
✅ Smart Conditions Table:
A live dashboard showing all trade condition checks (Trend, Recent Price Move, Candlestick confirmations) in real-time with visual feedback.
📊 Backtesting & Stats:
Auto-calculates average win, average loss, risk-reward ratio (RRR), and win rate across historical signals.
Clean performance dashboard with color-coded metrics for easy reading.
🔔 Alerts:
Set alerts for trade signals or significant price movements to stay updated without monitoring the chart 24/7.
Visuals:
Trend markers and price movement flags plotted directly on the chart.
Dual tables:
📈 Conditions table (top-right): breaks down trade criteria status.
📊 Performance table (bottom-right): shows real-time stats on win/loss and RRR.
6 Moving Averages Difference TableIndicator Summary: 6 Moving Averages Difference Table (6MADIFF)
This TradingView indicator calculates and plots up to six distinct moving averages (MAs) directly on the price chart. Users have extensive control over each MA, allowing selection of:
Type: SMA, EMA, WMA, VWMA, HMA, RMA
Length: Any positive integer
Color: User-defined
Visibility: Can be toggled on/off
A core feature is the on-chart data table, designed to provide a quick overview of the relationships between the MAs and the price. This table displays:
$-MA Column: The absolute difference between the user-selected Input Source (e.g., Close, Open, HLC3) and the current value of each MA.
MA$ Column: The actual calculated price value of each MA for the current bar.
MA vs. MA Matrix: A grid showing the absolute difference between every possible pair of the calculated MAs (e.g., MA1 vs. MA2, MA1 vs. MA3, MA2 vs. MA5, etc.).
Customization Options:
Input Source: Select the price source (Open, High, Low, Close, HL2, HLC3, OHLC4) used for all MA calculations and the price difference column.
Table Settings: Control the table's visibility, position on the chart, text size, decimal precision for displayed values, and the text used for the column headers ("$-MA" and "MA$").
Purpose:
This indicator is useful for traders who utilize multiple moving averages in their analysis. The table provides an immediate, quantitative snapshot of:
How far the current price is from each MA.
The exact value of each MA.
The spread or convergence between different MAs.
This helps in quickly assessing trend strength, potential support/resistance levels based on MA clusters, and the relative positioning of short-term versus long-term averages.
Darvas Box Breakout Signals v6 (Manus)Purpose:
This script is designed for TradingView to automatically identify potential "Darvas Boxes" on your price chart and signal when the price breaks out of these boxes.
How it Works:
Finds Highs: It looks back over a set number of bars (default is 20, but you can change this) to find the highest price point.
Confirms Box Top: It waits until the price stays below that high point for a specific number of bars (default is 3) to confirm the top of the box.
Confirms Box Bottom: After the top is confirmed, it looks for the lowest price reached and waits until the price stays above that low point for the same number of bars (3) to confirm the bottom of the box.
Draws Box (Optional): If enabled in the settings, it draws lines on the chart representing the top and bottom of the confirmed box.
What Signals It Shows:
Breakout Signal: When the price closes above the top line of a confirmed box, it plots a green upward-pointing triangle above that price bar. This suggests the stock might be starting a move higher.
Breakdown Signal: When the price closes below the bottom line of a confirmed box, it plots a red downward-pointing triangle below that price bar. This suggests the stock might be starting a move lower.
Key Features:
Uses the Darvas Box theory logic.
Provides clear visual signals for potential entries based on breakouts or breakdowns.
Allows customization of the lookback period and confirmation bars via the indicator settings.
Written in Pine Script version 6.
Remember, this script just provides signals based on price patterns; it doesn't predict the future or guarantee profits. It should be used as one tool within the larger trading plan we discussed, especially considering risk management.
MLExtensions_CoreLibrary "MLExtensions_Core"
A set of extension methods for a novel implementation of a Approximate Nearest Neighbors (ANN) algorithm in Lorentzian space, focused on computation.
normalizeDeriv(src, quadraticMeanLength)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the first-order derivative for price).
quadraticMeanLength (int) : The length of the quadratic mean (RMS).
Returns: nDeriv The normalized derivative of the input series.
normalize(src, min, max)
Rescales a source value with an unbounded range to a target range.
Parameters:
src (float) : The input series
min (float) : The minimum value of the unbounded range
max (float) : The maximum value of the unbounded range
Returns: The normalized series
rescale(src, oldMin, oldMax, newMin, newMax)
Rescales a source value with a bounded range to anther bounded range
Parameters:
src (float) : The input series
oldMin (float) : The minimum value of the range to rescale from
oldMax (float) : The maximum value of the range to rescale from
newMin (float) : The minimum value of the range to rescale to
newMax (float) : The maximum value of the range to rescale to
Returns: The rescaled series
getColorShades(color)
Creates an array of colors with varying shades of the input color
Parameters:
color (color) : The color to create shades of
Returns: An array of colors with varying shades of the input color
getPredictionColor(prediction, neighborsCount, shadesArr)
Determines the color shade based on prediction percentile
Parameters:
prediction (float) : Value of the prediction
neighborsCount (int) : The number of neighbors used in a nearest neighbors classification
shadesArr (array) : An array of colors with varying shades of the input color
Returns: shade Color shade based on prediction percentile
color_green(prediction)
Assigns varying shades of the color green based on the KNN classification
Parameters:
prediction (float) : Value (int|float) of the prediction
Returns: color
color_red(prediction)
Assigns varying shades of the color red based on the KNN classification
Parameters:
prediction (float) : Value of the prediction
Returns: color
tanh(src)
Returns the the hyperbolic tangent of the input series. The sigmoid-like hyperbolic tangent function is used to compress the input to a value between -1 and 1.
Parameters:
src (float) : The input series (i.e., the normalized derivative).
Returns: tanh The hyperbolic tangent of the input series.
dualPoleFilter(src, lookback)
Returns the smoothed hyperbolic tangent of the input series.
Parameters:
src (float) : The input series (i.e., the hyperbolic tangent).
lookback (int) : The lookback window for the smoothing.
Returns: filter The smoothed hyperbolic tangent of the input series.
tanhTransform(src, smoothingFrequency, quadraticMeanLength)
Returns the tanh transform of the input series.
Parameters:
src (float) : The input series (i.e., the result of the tanh calculation).
smoothingFrequency (int)
quadraticMeanLength (int)
Returns: signal The smoothed hyperbolic tangent transform of the input series.
n_rsi(src, n1, n2)
Returns the normalized RSI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the RSI calculation).
n1 (simple int) : The length of the RSI.
n2 (simple int) : The smoothing length of the RSI.
Returns: signal The normalized RSI.
n_cci(src, n1, n2)
Returns the normalized CCI ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the CCI calculation).
n1 (simple int) : The length of the CCI.
n2 (simple int) : The smoothing length of the CCI.
Returns: signal The normalized CCI.
n_wt(src, n1, n2)
Returns the normalized WaveTrend Classic series ideal for use in ML algorithms.
Parameters:
src (float) : The input series (i.e., the result of the WaveTrend Classic calculation).
n1 (simple int)
n2 (simple int)
Returns: signal The normalized WaveTrend Classic series.
n_adx(highSrc, lowSrc, closeSrc, n1)
Returns the normalized ADX ideal for use in ML algorithms.
Parameters:
highSrc (float) : The input series for the high price.
lowSrc (float) : The input series for the low price.
closeSrc (float) : The input series for the close price.
n1 (simple int) : The length of the ADX.
regime_filter(src, threshold, useRegimeFilter)
Parameters:
src (float)
threshold (float)
useRegimeFilter (bool)
filter_adx(src, length, adxThreshold, useAdxFilter)
filter_adx
Parameters:
src (float) : The source series.
length (simple int) : The length of the ADX.
adxThreshold (int) : The ADX threshold.
useAdxFilter (bool) : Whether to use the ADX filter.
Returns: The ADX.
filter_volatility(minLength, maxLength, sensitivityMultiplier, useVolatilityFilter)
filter_volatility
Parameters:
minLength (simple int) : The minimum length of the ATR.
maxLength (simple int) : The maximum length of the ATR.
sensitivityMultiplier (float) : Multiplier for the historical ATR to control sensitivity.
useVolatilityFilter (bool) : Whether to use the volatility filter.
Returns: Boolean indicating whether or not to let the signal pass through the filter.
ETH to RTH Gap DetectorETH to RTH Gap Detector
What It Does
This indicator identifies and tracks custom-defined gaps that form between Extended Trading Hours (ETH) and Regular Trading Hours (RTH). Unlike traditional gap definitions, this indicator uses a specialized approach - defining up gaps as the space between previous session close high to current session initial balance low, and down gaps as the space from previous session close low to current session initial balance high. Each detected gap is monitored until it's touched by price.
Key Features
Detects custom-defined ETH-RTH gaps based on previous session close and current session initial balance
Automatically identifies both up gaps and down gaps
Visualizes gaps with color-coded boxes that extend until touched
Tracks when gaps are filled (when price touches the gap area)
Offers multiple display options for filled gaps (color change, border only, pattern, or delete)
Provides comprehensive statistics including total gaps, up/down ratio, and touched gap percentage
Includes customizable alert system for real-time gap filling notifications
Features toggle options for dashboard visibility and weekend sessions
Uses time-based box coordinates to avoid common TradingView drawing limitations
How To Use It
Configure Session Times : Set your preferred RTH hours and timezone (default 9:30-16:00 America/New York)
Set Initial Balance Period : Adjust the initial balance period (default 30 minutes) for gap detection sensitivity
Monitor Gap Formation : The indicator automatically detects gaps between the previous session close and current session IB
Watch For Gap Fills : Gaps change appearance or disappear when price touches them, based on your selected style
Check Statistics : View the dashboard to see total gaps, directional distribution, and touched percentage
Set Alerts : Enable alerts to receive notifications when gaps are filled
Settings Guide
RTH Settings : Configure the start/end times and timezone for Regular Trading Hours
Initial Balance Period : Controls how many minutes after market open to calculate the initial balance (1-240 minutes)
Display Settings : Toggle gap boxes, extension behavior, and dashboard visibility
Filled Box Style : Choose how filled gaps appear - Filled (color change), Border Only, Pattern, or Delete
Color Settings : Customize colors for up gaps, down gaps, and filled gaps
Alert Settings : Control when and how alerts are triggered for gap fills
Weekend Session Toggle : Option to include or exclude weekend trading sessions
Technical Details
The indicator uses time-based coordinates (xloc.bar_time) to prevent "bar index too far" errors
Gap boxes are intelligently limited to avoid TradingView's 500-bar drawing limitation
Box creation and fill detection use proper range intersection logic for accuracy
Session detection is handled using TradingView's session string format for reliability
Initial balance detection is precisely calculated based on time difference
Statistics calculations exclude zero-division scenarios for stability
This indicator works best on futures markets with extended and regular trading hours, especially indices (ES, NQ, RTY) and commodities. Performs well on timeframes from 1-minute to 1-hour.
What Makes It Different
Most gap indicators focus on traditional open-to-previous-close gaps, but this tool offers a specialized definition more relevant to ETH/RTH transitions. By using the initial balance period to define gap edges, it captures meaningful price discrepancies that often provide trading opportunities. The indicator combines sophisticated gap detection logic with clean visualization and comprehensive tracking statistics. The customizable fill styles and integrated alert system make it practical for both chart analysis and active trading scenarios.
Adaptive RSI | Lyro RSThe Adaptive RSI | 𝓛𝔂𝓻𝓸 𝓡𝓢 indicator enhances the traditional Relative Strength Index (RSI) by integrating adaptive smoothing techniques and dynamic bands. This design aims to provide traders with a nuanced view of market momentum, highlighting potential trend shifts and overbought or oversold conditions.
Key Features
Adaptive RSI Calculation: Combines fast and slow Exponential Moving Averages (EMAs) of the RSI to capture momentum shifts effectively.
Dynamic Bands: Utilizes a smoothed standard deviation approach to create upper and lower bands around the adaptive RSI, aiding in identifying extreme market conditions.
Signal Line: An additional EMA of the adaptive RSI serves as a signal line, assisting in confirming trend directions.
Customizable Color Schemes: Offers multiple predefined color palettes, including "Classic," "Mystic," "Accented," and "Royal," with an option for users to define custom colors for bullish and bearish signals.
How It Works
Adaptive RSI Computation: Calculates the difference between fast and slow EMAs of the RSI, producing a responsive oscillator that adapts to market momentum.
Band Formation: Applies a smoothing factor to the standard deviation of the adaptive RSI, generating dynamic upper and lower bands that adjust to market volatility.
Signal Line Generation: Computes an EMA of the adaptive RSI to act as a signal line, providing additional confirmation for potential entries or exits.
Visualization: Plots the adaptive RSI as color-coded columns, with colors indicating bullish or bearish momentum. The dynamic bands are filled to visually represent overbought and oversold zones.
How to Use
Identify Momentum Shifts: Observe crossovers between the adaptive RSI and the signal line to detect potential changes in trend direction.
Spot Overbought/Oversold Conditions: Monitor when the adaptive RSI approaches or breaches the dynamic bands, signaling possible market extremes.
Customize Visuals: Select from predefined color palettes or define custom colors to align the indicator's appearance with personal preferences or chart themes.
Customization Options
RSI and EMA Lengths: Adjust the lengths of the RSI, fast EMA, slow EMA, and signal EMA to fine-tune the indicator's sensitivity.
Band Settings: Modify the band length, multiplier, and smoothing factor to control the responsiveness and width of the dynamic bands.
Color Schemes: Choose from predefined color modes or enable custom color settings to personalize the indicator's appearance.
⚠️ DISCLAIMER ⚠️: This indicator alone is not reliable and should be combined with other indicator(s) for a stronger signal.
ADX Forecast [Titans_Invest]ADX Forecast
This isn’t just another ADX indicator — it’s the most powerful and complete ADX tool ever created, and without question the best ADX indicator on TradingView, possibly even the best in the world.
ADX Forecast represents a revolutionary leap in trend strength analysis, blending the timeless principles of the classic ADX with cutting-edge predictive modeling. For the first time on TradingView, you can anticipate future ADX movements using scientifically validated linear regression — a true game-changer for traders looking to stay ahead of trend shifts.
1. Real-Time ADX Forecasting
By applying least squares linear regression, ADX Forecast projects the future trajectory of the ADX with exceptional accuracy. This forecasting power enables traders to anticipate changes in trend strength before they fully unfold — a vital edge in fast-moving markets.
2. Unmatched Customization & Precision
With 26 long entry conditions and 26 short entry conditions, this indicator accounts for every possible ADX scenario. Every parameter is fully customizable, making it adaptable to any trading strategy — from scalping to swing trading to long-term investing.
3. Transparency & Advanced Visualization
Visualize internal ADX dynamics in real time with interactive tags, smart flags, and fully adjustable threshold levels. Every signal is transparent, logic-based, and engineered to fit seamlessly into professional-grade trading systems.
4. Scientific Foundation, Elite Execution
Grounded in statistical precision and machine learning principles, ADX Forecast upgrades the classic ADX from a reactive lagging tool into a forward-looking trend prediction engine. This isn’t just an indicator — it’s a scientific evolution in trend analysis.
⯁ SCIENTIFIC BASIS LINEAR REGRESSION
Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥.
The general formula for a simple linear regression is given by:
y = β₀ + β₁x + ε
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
y = is the predicted variable (e.g. future value of RSI)
x = is the explanatory variable (e.g. time or bar index)
β0 = is the intercept (value of 𝑦 when 𝑥 = 0)
𝛽1 = is the slope of the line (rate of change)
ε = is the random error term
The goal is to estimate the coefficients 𝛽0 and 𝛽1 so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares.
⯁ LEAST SQUARES ESTIMATION
To minimize the error between predicted and observed values, we use the following formulas:
β₁ = /
β₀ = ȳ - β₁x̄
Where:
∑ = sum
x̄ = mean of x
ȳ = mean of y
x_i, y_i = individual values of the variables.
Where:
x_i and y_i are the means of the independent and dependent variables, respectively.
i ranges from 1 to n, the number of observations.
These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity.
⯁ LINEAR REGRESSION IN MACHINE LEARNING
Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies.
By applying this model to the ADX, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis.
⯁ VISUAL INTERPRETATION
Imagine an ADX time series like this:
Time →
ADX →
The regression line will smooth these values and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted ADX, which can be crossed with the actual ADX to generate more intelligent signals.
⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED
Linear Regression Models the relationship between variables using a straight line.
Least Squares Minimizes the sum of squared errors between prediction and reality.
Time Series Forecasting Estimates future values based on historical data.
Supervised Learning Trains models to predict outputs from known inputs.
Statistical Smoothing Reduces noise and reveals underlying trends.
⯁ WHY THIS INDICATOR IS REVOLUTIONARY
Scientifically-based: Based on statistical theory and mathematical inference.
Unprecedented: First public ADX with least squares predictive modeling.
Intelligent: Built with machine learning logic.
Practical: Generates forward-thinking signals.
Customizable: Flexible for any trading strategy.
⯁ CONCLUSION
By combining ADX with linear regression, this indicator allows a trader to predict market momentum, not just follow it.
ADX Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology.
⯁ Example of simple linear regression, which has one independent variable:
⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ).
⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values using Matlab:
⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables.
⯁ The result of fitting a set of data points with a quadratic function:
_______________________________________________________________________
🥇 This is the world’s first ADX indicator with: Linear Regression for Forecasting 🥇_______________________________________________________________________
_________________________________________________
🔮 Linear Regression: PineScript Technical Parameters 🔮
_________________________________________________
Forecast Types:
• Flat: Assumes prices will remain the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
ta.linreg (built-in function)
Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values calculated using the least squares method on the source series.
Syntax:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset: Offset.
• return: Linear regression curve.
This function has been cleverly applied to the RSI, making it capable of projecting future values based on past statistical trends.
______________________________________________________
______________________________________________________
⯁ WHAT IS THE ADX❓
The Average Directional Index (ADX) is a technical analysis indicator developed by J. Welles Wilder. It measures the strength of a trend in a market, regardless of whether the trend is up or down.
The ADX is an integral part of the Directional Movement System, which also includes the Plus Directional Indicator (+DI) and the Minus Directional Indicator (-DI). By combining these components, the ADX provides a comprehensive view of market trend strength.
⯁ HOW TO USE THE ADX❓
The ADX is calculated based on the moving average of the price range expansion over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and has three main zones:
• Strong Trend: When the ADX is above 25, indicating a strong trend.
• Weak Trend: When the ADX is below 20, indicating a weak or non-existent trend.
• Neutral Zone: Between 20 and 25, where the trend strength is unclear.
______________________________________________________
______________________________________________________
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
______________________________________________________
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 +DI > -DI
🔹 +DI < -DI
🔹 +DI > ADX
🔹 +DI < ADX
🔹 -DI > ADX
🔹 -DI < ADX
🔹 ADX > Threshold
🔹 ADX < Threshold
🔹 +DI > Threshold
🔹 +DI < Threshold
🔹 -DI > Threshold
🔹 -DI < Threshold
🔹 +DI (Crossover) -DI
🔹 +DI (Crossunder) -DI
🔹 +DI (Crossover) ADX
🔹 +DI (Crossunder) ADX
🔹 +DI (Crossover) Threshold
🔹 +DI (Crossunder) Threshold
🔹 -DI (Crossover) ADX
🔹 -DI (Crossunder) ADX
🔹 -DI (Crossover) Threshold
🔹 -DI (Crossunder) Threshold
🔮 +DI (Crossover) -DI Forecast
🔮 +DI (Crossunder) -DI Forecast
🔮 ADX (Crossover) +DI Forecast
🔮 ADX (Crossunder) +DI Forecast
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 +DI > -DI
🔸 +DI < -DI
🔸 +DI > ADX
🔸 +DI < ADX
🔸 -DI > ADX
🔸 -DI < ADX
🔸 ADX > Threshold
🔸 ADX < Threshold
🔸 +DI > Threshold
🔸 +DI < Threshold
🔸 -DI > Threshold
🔸 -DI < Threshold
🔸 +DI (Crossover) -DI
🔸 +DI (Crossunder) -DI
🔸 +DI (Crossover) ADX
🔸 +DI (Crossunder) ADX
🔸 +DI (Crossover) Threshold
🔸 +DI (Crossunder) Threshold
🔸 -DI (Crossover) ADX
🔸 -DI (Crossunder) ADX
🔸 -DI (Crossover) Threshold
🔸 -DI (Crossunder) Threshold
🔮 +DI (Crossover) -DI Forecast
🔮 +DI (Crossunder) -DI Forecast
🔮 ADX (Crossover) +DI Forecast
🔮 ADX (Crossunder) +DI Forecast
______________________________________________________
______________________________________________________
🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : ADX Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
True Seasonal Pattern [tradeviZion]True Seasonal Pattern: Uncover Hidden Market Cycles
Markets have rhythms and patterns that repeat with surprising regularity. The True Seasonal Pattern indicator reveals these hidden cycles across different timeframes, helping you anticipate potential market movements based on historical seasonal tendencies.
What This Indicator Does
The True Seasonal Pattern analyzes years of historical price data to identify recurring seasonal trends. It then plots these patterns on your chart, showing you both the historical pattern and future projection based on past seasonal behavior.
Automatic Timeframe Detection: Works with Monthly, Weekly, and Daily charts
Historical Pattern Analysis: Analyzes up to 100 years of data (customizable)
Future Projection: Projects the seasonal pattern ahead on your chart
Smart Smoothing: Applies appropriate smoothing based on your timeframe
How to Use This Indicator
Add the indicator to a Daily, Weekly, or Monthly chart (not designed for intraday timeframes)
The indicator automatically detects your chart's timeframe
The blue line shows the historical seasonal pattern
Watch for potential turning points in the pattern that align with other technical signals
Seasonal patterns work best as a supporting factor in your analysis, not as standalone trading signals. They are particularly effective in markets with well-established seasonal influences.
Best Applications
Futures Markets: Commodities and futures often show strong seasonal tendencies due to production cycles, weather patterns, and economic factors
Stock Indices: Many stock markets demonstrate regular seasonal patterns (like the "Sell in May" phenomenon)
Individual Stocks: Companies with seasonal business cycles often show predictable price patterns
Practical Applications
Identify potential turning points based on historical seasonal patterns
Plan entries and exits around seasonal tendencies
Add seasonal context to your existing technical analysis
Understand why certain months or periods might show consistent behavior
Pro Tip: For best results, use this tool on instruments with at least 5+ years of historical data. Longer timeframes often reveal more reliable seasonal patterns.
Important Notes
This indicator works best on Daily, Weekly, and Monthly timeframes - not intraday charts
Seasonal patterns are tendencies, not guarantees
Always combine seasonal analysis with other technical tools
Past patterns may not repeat exactly in the future
// Sample of the seasonal calculation approach
float yearHigh = array.max(currentYearHighs)
float yearLow = array.min(currentYearLows)
// Calculate seasonality for each period
for i = 0 to array.size(currentYearCloses) - 1
float periodClose = array.get(currentYearCloses, i)
if not na(periodClose) and yearHigh != yearLow
float seasonality = (periodClose - yearLow) / (yearHigh - yearLow) * 100
I developed this indicator to help traders incorporate seasonal analysis into their trading approach without the complexity of traditional seasonal tools. Whether you're analyzing agricultural commodities, energy futures, or stock indices, understanding the seasonal context can provide valuable insights for your trading decisions.
Remember: Markets don't always follow seasonal patterns, but when they do, being aware of these tendencies can give you a meaningful edge in your analysis.
Nyx-AI Market Intelligence DashboardNyx AI Market Intelligence Dashboard is a non-signal-based environmental analysis tool that provides real-time insight into short-term market behavior. It is designed to help traders understand the quality of current price action, volume dynamics, volatility conditions, and structural behavior. It informs the trader whether the current market environment is supportive or hostile to trading and whether any active signal (from other tools) should be trusted, filtered, or avoided altogether.
Nyx is composed of seven intelligent modules. Each module operates independently but is visually unified through a floating dashboard panel on the chart. This panel renders live diagnostics every few bars, maintaining a low visual footprint without drawing overlays or modifying price.
Market Posture Engine
This module reads individual candlesticks using real-time candle anatomy to interpret directional bias and sentiment. It examines body-to-range ratio, wick imbalances, and compares them to prior bars. If the current candle is a large momentum body with minimal wick, it is interpreted as a directional thrust. If it is a small body with equal wicks, it is considered indecision. Engulfing patterns are used to detect potential liquidity tests. The system outputs a plain-text posture signal such as Building Bullish Intent, Bearish Momentum, Indecision Zone, Testing Liquidity (Up or Down), or Neutral.
Flow Reversal Engine
This module monitors short-term structural shifts and volume contraction to detect early signs of reversal or exhaustion. It looks for lower highs or higher lows paired with weakening volume and closing behavior that implies loss of momentum. It also monitors divergence between price and volume, as well as bar-to-bar momentum stalls (where highs and lows stop expanding). When these conditions are met, it outputs one of several states including Top Forming, Bottom Forming, Flow Divergence, Momentum Stall, or Neutral. This is useful for detecting inflection points before they manifest on trend indicators.
Fractal Context Engine
This engine compares the current bar’s range to its surrounding structural context. It uses a dynamic lookback length based on volatility. It determines whether the market is in expansion (strong directional trend), compression (shrinking range), or a transitional phase. A special case called Flip In Progress is triggered when the current high and low exceed the entire recent range, which often precedes sharp reversals or volatility expansion. The result is one of the following: Trend Expansion, Trend Breakdown, Sideways or Coil, Flip In Progress, or Expansion to Coil.
Candle Behavior Analyzer
This module analyzes the last five candles as a set to detect behavioral traits that a single candle may not reveal. It calculates average body and wick size, and counts how many recent candles show thrust (large body dominance), trap behavior (price returns inside wicks), or weakness (small bodies with high wick ratios). The module outputs one of the following behaviors: Aggressive Buying, Aggressive Selling, Trap Pattern, Trap During Coil, Low Participation, Low Energy, or Fakeout Candle. This helps the trader assess sentiment quality and the reliability of price movement.
Volatility Forecast and Compression Memory
This module predicts whether a breakout is likely based on recent compression behavior. It tracks how many of the last 10 bars had significantly reduced range compared to average. If a certain threshold is met without any recent large expansion bar, the system forecasts that a volatility expansion is likely in the near future. It also records how many bars ago the last high volatility impulse occurred and classifies whether current conditions are compressing. The outputs are Expansion Likely, Active Compression, and Last Burst memory, which provide breakout timing and energy insights.
Entry Filter
This module scores the current bar based on four adaptive criteria: body size relative to range, volume strength relative to average, current volatility versus historical volatility, and price position relative to a 20-period moving average. Each factor is scored as either 1 or 2. The total score is adjusted by a behavioral modifier that adds or subtracts a point if recent candles show aggression or trap behavior. Final scores range from 4 to 8 and are classified into Optimal, Mixed, or Avoid categories. This module is not a trade signal. It is a confluence filter that evaluates whether conditions are favorable for entry. It is particularly effective when layered with other indicators to improve precision.
Liquidity Intent Engine
This engine checks for price behavior around recent swing highs and lows. It uses adaptive pivots based on volatility to determine if price has swept above a recent high or below a recent low. This behavior is often associated with institutional liquidity hunts. If a sweep is detected and price has moved away from the sweep level, the engine infers directional intent and compares current distance to the high and low to determine which liquidity pool is more dominant. The output is Magnet Above, Magnet Below, or Conflict Zone. This is useful for anticipating directional bias driven by smart money activity.
Sticky Memory Tracking
To avoid flickering between states on low volatility or noisy price action, Nyx includes a sticky memory system. Each module’s output is preserved until a meaningful change is detected. For example, if Market Posture is Neutral and remains so for several bars, the previous non-neutral value is retained. This makes the dashboard more stable and easier to interpret without misleading noise.
Dashboard Rendering
All module outputs are displayed in a clean two-column panel anchored to any corner of the chart. Text values are color-coded, tooltips are added for context, and the data refreshes every few bars to maintain speed. The dashboard avoids clutter and blends seamlessly with other chart tools.
This tool is intended for informational and educational purposes only. It does not provide financial advice or trading signals. Nyx analyzes price, volume, structure, and volatility to offer context about the current market environment. It is not designed to predict future price movements or guarantee profitable outcomes. Traders should always use independent judgment and risk management. Past performance of any analysis logic does not guarantee future results.
Parsifal.Swing.CompositeThe Parsifal.Swing.Composite indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators such as:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module serves as an indicator facilitating judgment of the current swing state in the underlying market.
________________________________________
Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These oscillations—or swings—within the trend are inherently tradable.
They can be approached:
• One-sidedly, aligning with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions as well.
Note: Mean reversions in strong trends often manifest as sideways consolidations, making one-sided trades more stable.
________________________________________
The Parsifal Swing Suite
The modules aim to provide additional insights into the swing state within a trend and offer various trigger points to assist with entry decisions.
All modules in the suite act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., RSI, which is constrained between 0% and 100%).
________________________________________
The Parsifal.Swing.Composite – Specifics
This module consolidates multiple insights into price swing behavior, synthesizing them into an indicator reflecting the current swing state.
It employs layered bagging and smoothing operations based on standard price inputs (OHLC) and classical technical indicators. The module integrates several slightly different sub-modules.
Process overview:
1. Per candle/bin, sub-modules collect directional signals (up/down), with each signal casting a vote.
2. These votes are aggregated via majority counting (bagging) into a single bin vote.
3. Bin votes are then smoothed, typically with short-term EMAs, to create a sub-module vote.
4. These sub-module votes are aggregated and smoothed again to generate the final module vote.
The final vote is a score indicating the module’s assessment of the current swing state. While it fluctuates in a range, it's not a true oscillator, as most inputs are normalized via Z-scores (value divided by standard deviation over a period).
• Historically high or low values correspond to high or low quantiles, suggesting potential overbought or oversold conditions.
• The chart displays a fast (orange) and slow (white) curve against a solid background state.
• Extreme values followed by curve reversals may signal upcoming mean-reversions.
Background Value:
• Value > 0: shaded green → bullish mode
• Value < 0: shaded red → bearish mode
• The absolute value indicates confidence in the mode.
________________________________________
How to Use the Parsifal.Swing.Composite
Several change points in the indicator serve as potential entry triggers:
• Fast Trigger: change in slope of the fast curve
• Trigger: fast line crossing the slow line or change in the slow curve’s slope
• Slow Trigger: change in sign of the background value
These are illustrated in the introductory chart.
Additionally, market highs and lows aligned with swing values may act as pivot points, support, or resistance levels for evolving price processes.
________________________________________
As always, supplement this indicator with other tools and market information. While it provides valuable insights and potential entry points, it does not predict future prices. It reflects recent tendencies and should be used judiciously.
________________________________________
Extensions
All modules in the Parsifal Swing Suite are simple yet adaptable, whether used individually or in combination.
Customization options:
• Weights in EMAs for smoothing are adjustable
• Bin vote aggregation (currently via sum-of-experts) can be modified
• Alternative weighting schemes can be tested
Advanced options:
• Bagging weights may be historical, informational, or relevance-based
• Selection algorithms (e.g., ID3, C4.5, CAT) could replace the current bagging approach
• EMAs may be generalized into expectations relative to relevance-based probability
• Negative weights (akin to wavelet transforms) can be incorporated
