Stock Relative Strength Rotation Graph🔄 Visualizing Market Rotation & Momentum (Stock RSRG)
This tool visualizes the sector rotation of your watchlist on a single graph. Instead of checking 40 different charts, you can see the entire market cycle in one view. It plots Relative Strength (Trend) vs. Momentum (Velocity) to identify which assets are leading the market and which are lagging.
📜 Credits & Disclaimer
Original Code: Adapted from the open-source " Relative Strength Scatter Plot " by LuxAlgo.
Trademark: This tool is inspired by Relative Rotation Graphs®. Relative Rotation Graphs® is a registered trademark of JOOS Holdings B.V. This script is neither endorsed, nor sponsored, nor affiliated with them.
📊 How It Works (The Math)
The script calculates two metrics for every symbol against a benchmark (Default: SPX):
X-Axis (RS-Ratio): Is the trend stronger than the benchmark? (>100 = Yes)
Y-Axis (RS-Momentum): Is the trend accelerating? (>100 = Yes)
🧩 The 4 Market Quadrants
🟩 Leading (Top-Right): Strong Trend + Accelerating. (Best for holding).
🟦 Improving (Top-Left): Weak Trend + Accelerating. (Best for entries).
⬜ Weakening (Bottom-Right): Strong Trend + Decelerating. (Watch for exits).
🟥 Lagging (Bottom-Left): Weak Trend + Decelerating. (Avoid).
✨ Significant Improvements
This open-source version adds unique features not found in standard rotation scripts:
📝 Quick-Input Engine: Paste up to 40 symbols as a single comma-separated list (e.g., NVDA, AMD, TSLA). No more individual input boxes.
🎯 Quadrant Filtering: You can now hide specific quadrants (like "Lagging") to clear the noise and focus only on actionable setups.
🐛 Trajectory Trails: Visualizes the historical path of the rotation so you can see the direction of momentum.
🛠️ How to Use
Paste Watchlist: Go to settings and paste your symbols (e.g., US Sectors: XLK, XLF, XLE...).
Find Entries: Look for tails moving from Improving ➔ Leading.
Find Exits: Be cautious when tails move from Leading ➔ Weakening.
Zoom: Use the "Scatter Plot Resolution" setting to zoom in or out if dots are bunched up.
Forecasting
Risk Management Console Pro by ShogunRisk Management Console Pro - Professional Trading Analytics
⚠️ CRITICAL LIQUIDATION DISCLAIMER ⚠️
The liquidation price calculated by this indicator is an approximation based on MEXC perpetual futures methodology and serves as a guide only. This level represents a catastrophic threshold and should never be approached in live trading. Actual liquidation prices vary by exchange, position size, market conditions, and fee structures. It is the trader's sole responsibility to diligently monitor risk exposure, maintain adequate margin buffers, and manage positions appropriately. This tool does not replace proper risk management protocols or real-time exchange data.
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Overview
The Risk Management Console Pro is institutional-grade risk architecture I've built for futures traders who need precision capital deployment and surgical risk management. After a decade working across institutional finance and fintech, I developed this tool to bridge the gap between professional trading desks and retail execution.
Core Functionality
When you load the indicator, it prompts you to set three critical price anchors using a simple drag-and-drop interface: Entry Price, Stop Loss, and Take Profit. The system calculates an approximate liquidation threshold using MEXC perpetual futures methodology, so you can visualize your catastrophic risk boundary. All levels appear as horizontal reference lines with visual labels - a much cleaner approach than standard long/short tools.
The console automatically detects whether you're going long or short based on where your entry sits relative to your take profit. No manual configuration needed. The liquidation calculations adapt correctly for both directions.
Capital Allocation Framework
You configure two key parameters:
- Maintenance Margin (default $1,000 USD) - the collateral required to open and maintain your leveraged position
- Leverage (default 50x) - your position multiplier that determines capital efficiency and risk exposure
These inputs drive all the real-time calculations, letting you model position sizing with institutional precision before you commit capital.
Dashboard Analytics
The on-chart console displays comprehensive trade metrics in a clean, modern interface built for quick decision-making:
- Position Architecture: Margin, Leverage, Position Size, Quantity
- Risk/Reward Ratio: Real-time R:R calculation showing your trade asymmetry
- Price Levels: Entry, Stop Loss, Take Profit, Liquidation (color-coded as blue/red/green/orange)
- Live Performance: Unrealized P/L updating tick-by-tick with percentage of margin exposure (green for profit, red for loss)
- Projected Outcomes: Maximum loss and profit potential with margin-relative percentages
Display Customization
You have full control over visual elements through Display Settings:
- Toggle horizontal price lines
- Show/hide price level labels
- Toggle dashboard visibility
- Adjust table position (6 locations available)
- Modify color scheme (title, data, text, accent colors)
Professional Design
I went with an institutional dark theme using a slate/charcoal palette. The interface delivers Wall Street-caliber aesthetics with functional clarity. Every element is built for traders operating in high-stakes environments where milliseconds and basis points matter. The dashboard footer carries the Kaizen Systems signature, representing our commitment to continuous improvement in trading methodology.
Key Features Summary
- Automatic long/short detection
- MEXC-based liquidation calculation
- Real-time unrealized P/L tracking
- Draggable price level inputs
- Color-coded risk visualization
- Institutional-grade interface
- Fully customizable display options
- Position size optimization
- R:R ratio analysis
Risk Management Philosophy
This tool embodies a principle I've learned over the years: professional traders quantify risk before entering positions. By visualizing entry, exit, and catastrophic thresholds simultaneously, the Risk Management Console Pro enforces disciplined capital allocation and eliminates emotional decision-making during live market conditions.
Intended Use
I designed this for futures traders using leverage on perpetual contracts, particularly those trading on MEXC or similar platforms. It's ideal for intraday scalpers, swing traders, and position traders who need precise risk calculations across varying timeframes. The console transforms abstract concepts like "position sizing" and "risk/reward" into tangible, actionable data.
About Me
I'm Shogun, and I've spent the last decade deep in quantitative analysis, algorithmic strategy development, and institutional trading operations. As Founding Director of Kaizen Systems - a fintech platform I built to democratize institutional-grade tools for retail traders - I've created multiple proprietary indicators including the Katana strategy series. My focus is translating complex quantitative frameworks into accessible, actionable tools that empower traders at every level to execute with professional discipline.
The Risk Management Console Pro represents my commitment to elevating retail trading standards by providing the same caliber of risk analytics used by professional trading desks. Through continuous refinement and trader feedback, Kaizen Systems delivers tools that merge technical sophistication with practical usability.
Technical Notes
- Compatible with all timeframes and instruments
- Lightweight execution with minimal CPU overhead
- Updates in real-time on every tick
- No repainting or future data leakage
- Pure Pine Script v5 implementation
Support and Updates
For questions, feature requests, or trading strategy consultation, connect with me through TradingView messaging or visit Kaizen Systems for comprehensive trading resources and community support.
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© 2025 Shogun for Kaizen Systems | All Rights Reserved
Trade responsibly. Past performance does not guarantee future results. Leverage amplifies both gains and losses.
NeuralFlow Forecast Engine™ | SPY Weekly NeuralFlow Forecast Engine™ | SPY Weekly
AI-adaptive market equilibrium & expansion mapping. NeuralFlow doesn’t forecast by direction — it forecasts by where markets prefer to stabilize.
NeuralFlow Forecast Engine™ is a proprietary Artificial Intelligence framework trained to identify where price is statistically inclined to rebalance and where expansion zones historically exhaust rather than extend.
What the Bands Represent
Band Layer Meaning
AI Equilibrium (white core) Primary weekly balance zone where price is most likely to mean-revert
Predictive Rails (aqua / purple) High-confidence corridor of institutional flow containment
Outer Zones (green / red) Expansion limits where continuation historically decays
Extreme Zones (top/bottom) Rare deviation envelope where auction completion is statistically favored
NeuralFlow operates on proprietary, institution-grade Artificial Intelligence models trained specifically to map statistical rebalancing behavior, not trader predictions or sentiment. No discretionary drawing. No correlations. No lagging overlays.
This engine updates only when underlying structure changes — not when candles fluctuate intraday.
⚠ Risk & Use Notice
NeuralFlow Forecast Engine™ provides AI-derived structural zones, not trade signals or financial advice.
Markets can behave outside modeled distributions, especially during macro catalysts, thin liquidity, or surprise volatility events.
By loading or using this indicator, the user acknowledges full responsibility for any trades or outcomes based on its interpretation.
Educational & analytical use only. Not financial advice.
Range Deviations PRO | Trade SymmetryRange Deviations PRO — Extended Session Levels
An enhanced version of the original Range Deviations by @joshuuu, retaining the full core logic while adding a key upgrade:
🔹 All session ranges, midlines, and deviation levels now extend into the next trading session, giving seamless multi-session context.
Supports Asia, CBDR, Flout, ONS, and Custom Sessions — with options for half/full standard deviations, equilibrium, and range boxes exactly as in the original.
Extending these levels helps identify:
• Liquidity sweeps
• Trap moves / false breaks
• Daily high/low projections
• Premium–discount behavior across sessions
Ideal for traders using ICT concepts who want clearer continuation of session structure into the next day.
Credit: Original logic by @joshuuu — enhancements by TradeSymmetry.
Disclaimer: Educational use only. Not financial advice.
Alinin Sihirli Lambası v4.0 [AliBaba]This is not investment advice.
It works with 80% success in a 15-minute period and provides buy and sell signals.
It has been tested on SKL OP XTZ ALT VTHQ 100 CHEMS ZEC LUNC.
When the green vertical bar appears, if it is at least 2% below the upper pink line and institutional buying exceeds institutional selling (upper right window).
If you are a TradingView premium member, and the upper target is closer than the lower target, the best buy point is indicated.
The default profit and risk ratio is 2 to 1.5. You can try changing it.
A signal is generated by reprocessing the best indicators and considering general institutional buying and selling pressures.
NQ H1 Stats+NQ H1 Stats - Detailed Prob & Excursion Indicator
Overview
NQ H1 Stats - Detailed Prob & Excursion is a specialized statistical overlay indicator for TradingView, tailored for the Nasdaq futures (NQ) on a 1-hour timeframe. It provides real-time insights into the probability of price returning to the hourly open after sweeping the previous hour's high (PHH) or low (PHL), based on historical data segmented by hour and 20-minute intervals. The indicator visualizes these sweeps with lines, labels, circles, background fills, and "excursion zones" (also called "Magic Boxes") that highlight median/mean extensions post-sweep, along with percentile lines (75th, 90th, 95th) for gauging potential "pain" or extreme moves. This tool is designed for intraday traders focusing on liquidity sweeps, or mean-reversion setups, helping to quantify edge based on empirical probabilities and volatility excursions.
The data is hardcoded from extensive historical analysis of NQ behavior (e.g., probabilities range from ~7% to ~91%, with sample sizes up to 2000+ per segment), making it a backtested reference rather than dynamic learning. It emphasizes visual clarity during active hours, with options to filter for Regular Trading Hours (RTH: 09:00–15:59 ET) or high-probability (>70%) events only. Note: This is an educational tool for analyzing market structure; it does not predict future performance or provide trading signals/advice. Past data does not guarantee future results, and users should backtest on current conditions (as of December 2025 data availability) and use at their own risk, in compliance with TradingView's house rules.
Key Features
• Sweep Detection & Probability Labels: Identifies when price breaks PHH (upside) or PHL (downside), displaying a centered label with probability of returning to the hourly open, sample size (N), time of sweep, and a checkmark (✅) if the open is retested post-sweep.
• Visual Lines & Markers: Draws hourly open (h.o.), PHH, and PHL lines with customizable styles/colors; adds small circles on sweep bars for quick spotting.
• Breakout→Open Background Fill: Shaded zone from sweep bar until price returns to open, visualizing extension duration and retracement.
• Excursion (Pain) Zone - "Magic Box": Post-sweep box showing median/mean extension percentages, colored dynamically by probability (green high, orange mid, red low); includes dashed lines for 75th/90th/95th percentiles to mark statistical extremes.
• Time-Segmented Data: Probabilities and excursions vary by hour (0-23) and 20-min segments (0-19 min: _0, 20-39: _1, 40-59: _2), capturing intraday nuances (e.g., higher probs in early/late hours).
• Filters for Focus: RTH-only mode hides non-session elements; high-prob-only shows >70% events to reduce noise.
• Alerts: Triggers on PHH/PHL sweeps with messages for chart checks.
How It Works
• Data Foundation: Uses pre-computed maps for probabilities (prob_high_taken/prob_low_taken), sample sizes, and excursions (mean, median, p75/p90/p95 as percentages of open). Data is initialized on the first bar via f_init_high_data() and f_init_low_data(), covering 24 hours with 3 segments each (e.g., key "9_1" for 09:20-09:39). Probabilities represent historical likelihood of price returning to open after sweep; excursions quantify average/rare extensions (e.g., 0.156% mean = 0.156% of open price).
• Period Detection: On new 1H bars (new_period_bar), resets visuals, draws lines for open/PHH/PHL extending 1 hour forward, and labels if enabled. Uses request.security on standard ticker for real OHLC, bypassing chart transformations (e.g., Heikin Ashi).
• Sweep Logic: On each bar, checks if real high > PHH or real low < PHL. If so, fetches segment-specific data (hour + floor(minute/20)), displays probability label centered mid-hour. Skips if filtered (RTH-only or <70% prob).
• Excursion Visualization: If enabled, draws "Magic Box" from 1-min to 58-min into the hour, bounded by mean/median levels (top/bottom adjusted for high/low sweep). Adds percentile lines with labels (e.g., "75%") at right end. Box color reflects prob strength for quick bias assessment.
• Retest Check: Monitors for open retest post-sweep (high/low cross open, or gap scenarios from prev bar). Adds ✅ to label if hit on subsequent bars (skips sweep bar to avoid false positives). Stops background fill on retest or at 58-min mark.
• Background Fill: Activates on sweep, shades until retest, using user color.
• Cleanup & Performance: Manages labels in arrays, clears on new periods; no excess drawing beyond max counts (500 lines/labels/boxes).
This setup "meshes" statistical backtesting with real-time visualization: Hardcoded data provides empirical probabilities/excursions (reducing subjectivity in breakouts), while dynamic elements (lines, fills, boxes) overlay structure on the chart. It helps traders assess if a sweep is "high-edge" (e.g., >70% prob of revert) or likely to run (low prob, high excursion), blending historical context with current price action for informed decisions.
Settings and Customization
Inputs are grouped for ease:
1. Settings:
o Show RTH Only (9:00-15:59): Restricts to main session (default: false; tooltip: for RTH-focused stats).
o Show High Prob Only (>70%): Filters low-prob sweeps visually (default: false; tooltip: highlights confidence).
2. Visuals:
o Show Line Labels: Toggle "h.o."/ "phh"/ "phl" (default: true).
o Period Open Line Color: Gray 50% (default).
o Previous High/Low Line Colors: Gray 100% (default).
o Open Line Style/Width: Dotted/1 (default; options: Solid/Dotted/Dashed).
3. Breakout→Open Background:
o Show Breakout→Open Background: Toggle fill (default: true).
o Fill Color: Teal 85% (default).
4. Breakout Circles:
o Show Breakout Circles: Toggle (default: true).
o PHH/PHL Break Circle Colors: White 20% (default).
5. Info Label Style:
o Text Size: Small (default; options: Auto/Tiny/Normal/Large/Huge).
o Label Text Color: White (default).
o Low/Mid/High Probability Colors: Red 20%/Orange 20%/Green 20% (default).
6. Excursion (Pain) Zone:
o Show Excursion Zone: Toggle Magic Box (default: true).
o Excursion Box Color: Gray 75% (default; dynamic overrides).
o 75th/90th/95th Percentile Lines: Orange 30%/Red 30%/Dark Red 100% (default).
No additional tables/plots; all elements are lines/labels/boxes for overlay focus.
Usage Tips
• Breakout Trading: Watch for sweeps with high prob (>70%, green label) as potential fades back to open; low prob (red) may signal runs—use excursion box for targets (e.g., exit at 90th percentile for extremes).
• Time Awareness: Probabilities peak in open hours (e.g., 09:00 ~90%+ for initial sweeps) and drop in off-hours; segments capture momentum shifts (e.g., _2 often lower prob).
• RTH Focus: Enable for cleaner stats during high-liquidity sessions; disable for 24/7 view.
• Visual Filtering: Use high-prob-only in volatile conditions to avoid noise; combine with volume or other indicators for confirmation.
• Alerts Integration: Set TradingView alerts on sweeps; check label for prob/N before acting.
• Chart Setup: Best on 1H or lower NQ charts; adjust text size for readability on mobiles.
• Backtesting: Manually review historical sweeps against data maps to validate; update hardcoded values if new data emerges (as of 2025).
Limitations
• Fixed Data: Hardcoded stats may not reflect recent market changes (e.g., post-2025 volatility shifts); not adaptive.
• Reactive Only: Detects sweeps after they occur; no predictive signals.
• Timeframe Specific: Locked to 1H logic; may not translate to other assets/TFs without recoding data.
• Visual Clutter: On busy charts, labels/boxes may overlap—toggle off selectively.
• No Live Stats: Sample sizes are historical; real-time N/prob not updated.
• Gaps & Extremes: Handles gaps in retest logic, but rare events (e.g., news) may exceed 95th percentile.
Disclaimer
This indicator is for informational and educational purposes only. Trading involves significant risk of loss and is not suitable for all investors. The hardcoded data represents past NQ performance and does not guarantee future outcomes. No claims of profitability are made—results depend on market conditions, user strategy, and risk management. Consult a financial advisor before trading, and backtest extensively. Abiding by TradingView rules, this tool provides no investment recommendations.
Eagle Eye Pro Dashboard 🔴 IMPORTANT NOTICE
This indicator is an advanced trading support tool. It helps you spot opportunities and improve your analysis, but it DOES NOT guarantee results nor replace your personal judgment.
• 🔴 Every trade remains your sole responsibility.
• 🔴 Risk is always present: the indicator does not eliminate it, only helps manage it.
• 🔴 The indicator is restricted: it ONLY generates signals during the London and New York sessions.
• 🔴 It does not generate signals outside those sessions or during weekends, to ensure better accuracy and performance.
• 🔴 It is not recommended to trade other assets or use timeframes different from those specified.
EAGLE EYE PRO V71.2 RENTAL
This indicator is built to deliver clear signals and a professional dashboard, specially optimized for BTC.
🔑 Key highlights:
• 🔴 Exclusively optimized for BTC.
• 🔴 Recommended timeframe: 15 minutes, providing cleaner and more reliable signals.
• 🔴 Adventurous mode: 1 minute, but with higher risk due to extreme volatility.
• 🔴 Restricted hours: the indicator works only during the London and New York sessions.
• 🔴 It does not operate during weekends
TMT Sessions - Hitesh NimjeTMT Sessions - Hitesh Nimje Indicator
Overview
The TMT Sessions indicator is a comprehensive trading tool designed to visualize and analyze the four major global trading sessions. It provides session-based technical analysis including ranges, trends, averages, and statistical metrics for each trading session.
Key Features
Four Global Trading Sessions
1. Session A - New York (13:00-22:00 UTC)
Color: Blue (#0000FF)
Default timeframe: US/Eastern market hours
2. Session B - London (07:00-16:00 UTC)
Color: Black (#000000)
Default timeframe: European market hours
3. Session C - Tokyo (00:00-09:00 UTC)
Color: Red (#FF0000)
Default timeframe: Asian market hours
4. Session D - Sydney (21:00-06:00 UTC)
Color: Orange (#FFA500)
Default timeframe: Australian market hours
Technical Analysis Tools
Range Analysis:
* Visual range boxes showing session high/low boundaries
* Transparent background areas with configurable transparency
* Range outline borders
* Session labels with customizable text display
Trend Analysis:
* Linear regression trendlines for each session
* Statistical metrics including:
R-squared values for trend strength
Standard deviation calculations
Correlation measurements
Statistical Indicators:
* Session Averages: Simple Moving Averages (SMA) calculated within each session
* VWAP: Volume Weighted Average Price for session-based intraday analysis
* Max/Min Lines: Highest and lowest prices recorded during each session
Visual Elements
Session Dividers:
* Visual markers showing session start/end points
* Session identification symbols (NYE, LDN, TYO, SYD)
* Configurable divider display options
Dashboard Features:
* Basic Dashboard: Session status (Active/Inactive) with color-coded indicators
* Advanced Dashboard: Additional metrics including:
Session trend strength (R-squared values)
Volume data
Standard deviation statistics
* Multiple dashboard positions (Top Right, Bottom Right, Bottom Left)
* Configurable text sizes (Tiny, Small, Normal)
Customization Options
Timezone Management:
* UTC offset adjustment (+/- hours)
* Exchange timezone option for automatic adjustment
* Session time customization
Display Settings:
* Individual session enable/disable
* Color customization for each session
* Range area transparency control
* Line description display toggle
* Session text label configuration
Use Cases
1. Session-Based Trading: Identify optimal trading times for each global session
2. Range Trading: Use session ranges as support/resistance levels
3. Trend Analysis: Track session-specific trends and momentum
4. Statistical Analysis: Monitor session volatility and trend strength
5. Market Structure: Understand how price moves across different trading sessions
Technical Specifications
* Pine Script Version: 6
* Overlays: True (displays on price chart)
* Performance: Optimized for up to 500 bars back
* Multi-element Support: Handles up to 500 lines, boxes, and labels
* Data Source: Compatible with all trading instruments and timeframes
Benefits for Traders
1. Global Market Awareness: Visual representation of all major trading sessions
2. Session Analysis: Automated calculation of key session statistics
3. Trading Strategy Development: Session-based entry and exit signals
4. Risk Management: Session ranges for stop-loss and take-profit levels
5. Market Timing: Optimal trading session identification
This indicator is particularly valuable for forex traders, day traders, and anyone who needs to understand price behavior across different global market sessions. It combines multiple technical analysis concepts into a unified, session-focused trading tool.
TRADING DISCLAIMER
RISK WARNING
Trading involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. You should carefully consider whether trading is suitable for you in light of your circumstances, knowledge, and financial resources.
NO FINANCIAL ADVICE
This indicator is provided for educational and informational purposes only. It does not constitute:
* Financial advice or investment recommendations
* Buy/sell signals or trading signals
* Professional investment advice
* Legal, tax, or accounting guidance
LIMITATIONS AND DISCLAIMERS
Technical Analysis Limitations
* Pivot points are mathematical calculations based on historical price data
* No guarantee of accuracy of price levels or calculations
* Markets can and do behave irrationally for extended periods
* Past performance does not guarantee future results
* Technical analysis should be used in conjunction with fundamental analysis
Data and Calculation Disclaimers
* Calculations are based on available price data at the time of calculation
* Data quality and availability may affect accuracy
* Pivot levels may differ when calculated on different timeframes
* Gaps and irregular market conditions may cause level failures
* Extended hours trading may affect intraday pivot calculations
Market Risks
* Extreme market volatility can invalidate all technical levels
* News events, economic announcements, and market manipulation can cause gaps
* Liquidity issues may prevent execution at calculated levels
* Currency fluctuations, inflation, and interest rate changes affect all levels
* Black swan events and market crashes cannot be predicted by technical analysis
USER RESPONSIBILITIES
Due Diligence
* You are solely responsible for your trading decisions
* Conduct your own research before using this indicator
* Verify calculations with multiple sources before trading
* Consider multiple timeframes and confirm levels with other technical tools
* Never rely solely on one indicator for trading decisions
Risk Management
* Always use proper risk management and position sizing
* Set appropriate stop-losses for all positions
* Never risk more than you can afford to lose
* Consider the inherent risks of leverage and margin trading
* Diversify your portfolio and trading strategies
Professional Consultation
* Consult with qualified financial advisors before trading
* Consider your tax obligations and legal requirements
* Understand the regulations in your jurisdiction
* Seek professional advice for complex trading strategies
LIMITATION OF LIABILITY
Indemnification
The creator and distributor of this indicator shall not be liable for:
* Any trading losses, whether direct or indirect
* Inaccurate or delayed price data
* System failures or technical malfunctions
* Loss of data or profits
* Interruption of service or connectivity issues
No Warranty
This indicator is provided "as is" without warranties of any kind:
* No guarantee of accuracy or completeness
* No warranty of uninterrupted or error-free operation
* No warranty of merchantability or fitness for a particular purpose
* The software may contain bugs or errors
Maximum Liability
In no event shall the liability exceed the purchase price (if any) paid for this indicator. This limitation applies regardless of the theory of liability, whether contract, tort, negligence, or otherwise.
REGULATORY COMPLIANCE
Jurisdiction-Specific Risks
* Regulations vary by country and region
* Some jurisdictions prohibit or restrict certain trading strategies
* Tax implications differ based on your location and trading frequency
* Commodity futures and options trading may have additional requirements
* Currency trading may be regulated differently than stock trading
Professional Trading
* If you are a professional trader, ensure compliance with all applicable regulations
* Adhere to fiduciary duties and best execution requirements
* Maintain required records and reporting
* Follow market abuse regulations and insider trading laws
TECHNICAL SPECIFICATIONS
Data Sources
* Calculations based on TradingView data feeds
* Data accuracy depends on broker and exchange reporting
* Historical data may be subject to adjustments and corrections
* Real-time data may have delays depending on data providers
Software Limitations
* Internet connectivity required for proper operation
* Software updates may change calculations or functionality
* TradingView platform dependencies may affect performance
* Third-party integrations may introduce additional risks
MONEY MANAGEMENT RECOMMENDATIONS
Conservative Approach
* Risk only 1-2% of capital per trade
* Use position sizing based on volatility
* Maintain adequate cash reserves
* Avoid over-leveraging accounts
Portfolio Management
* Diversify across multiple strategies
* Don't put all capital into one approach
* Regularly review and adjust trading strategies
* Maintain detailed trading records
FINAL LEGAL NOTICES
Acceptance of Terms
* By using this indicator, you acknowledge that you have read and understood this disclaimer
* You agree to assume all risks associated with trading
* You confirm that you are legally permitted to trade in your jurisdiction
Updates and Changes
* This disclaimer may be updated without notice
* Continued use constitutes acceptance of any changes
* It is your responsibility to stay informed of updates
Governing Law
* This disclaimer shall be governed by the laws of the jurisdiction where the indicator was created
* Any disputes shall be resolved in the appropriate courts
* Severability clause: If any part of this disclaimer is invalid, the remainder remains enforceable
REMEMBER: THERE ARE NO GUARANTEES IN TRADING. THE MAJORITY OF RETAIL TRADERS LOSE MONEY. TRADE AT YOUR OWN RISK.
Contact Information:
* Creator: Hitesh_Nimje
* Phone: Contact@8087192915
* Source: Thought Magic Trading
© HiteshNimje - All Rights Reserved
This disclaimer should be prominently displayed whenever the indicator is shared, sold, or distributed to ensure users are fully aware of the risks and limitations involved in trading.
Return IchimoGiu Reversal FXReturn IchimoGiu Reversal FX — Extreme RSI/CCI Reversal System
Return IchimoGiu Reversal FX is a precision tool designed to detect high-quality reversal points based on extreme momentum exhaustion followed by controlled re-entry into equilibrium.
The system is built around a custom interpretation of the CCI, using:
extreme break levels
validated return thresholds
candle-level confirmation logic
optional signal rejection mechanics
This creates reversal signals that occur only when a genuine over-extension is followed by a structurally clean return into momentum.
🔍 How It Works
1️⃣ Extreme Break Detection
Price must drive the CCI beyond calibrated thresholds:
+266 for bullish exhaustion
−171 for bearish exhaustion
This filters out normal retracements and isolates only high-volatility extensions.
2️⃣ Controlled Return Signal
A signal appears when CCI re-enters moderated levels:
222 for sell setups
−114 for buy setups
The signal is printed directly on the candle that performs this return, ensuring timing precision.
3️⃣ Reset Protection
If the CCI breaks the extreme level again before confirmation → signal is cancelled.
This eliminates the majority of fake reversals.
⭐ What Makes This Indicator Original
Return Reversal FX is not a standard CCI signal.
It uses:
dual-threshold dynamic structure
candle-level validation
a proprietary state machine managing break → return → confirmation
tailored levels optimized through empirical research
This creates a unique reversal system unavailable through classic indicators.
📈 Best Usage
Works on indices, forex majors, metals and crypto
Recommended timeframe: M15 → H1
Ideal for counter-trend scalping and swing reversals
🔒 Access
This is an invite-only script.
To request access, please contact me on TradingView or Telegram.
IchimoGiu FX Pro IchimoGiu FX Pro — Advanced Trend & Structure Confirmation System
IchimoGiu FX Pro is an invite-only indicator designed to identify high-probability trend continuation setups using a dual-stage logic that combines market structure breaks with a custom Ichimoku-based confirmation engine.
Unlike standard Ichimoku or classic breakout indicators, IchimoGiu creates a unique interaction between structure shifts and equilibrium zones, allowing early detection of valid momentum phases while filtering out weak or false breakouts.
🔍 Core Functionalities
1️⃣ Pre-Breakout Detection (Structure Engine)
The indicator tracks relevant swing highs and lows and identifies when price approaches a potential BOS (Break of Structure).
This creates a Pre-Signal label, allowing traders to anticipate momentum shifts and prepare zones.
2️⃣ Confirmation Signal (IchimoGiu Filter)
Once structure is actually broken, the system applies a custom Ichimoku logic:
Tenkan/Kijun dynamic alignment
Cloud directional bias
Price location vs. equilibrium
Optional Chikou confirmation layer
Reset conditions to avoid false trends
Only when all internal conditions align is a confirmed BUY or SELL signal generated.
This makes IchimoGiu a precision tool for continuation trades, not a simple trend-following mashup.
⭐ What Makes IchimoGiu Original
IchimoGiu is not a merge of existing indicators.
It uses:
a proprietary pivot engine designed specifically for BOS/CHOCH,
re-engineered Ichimoku components optimized for confirmation speed,
an original pre-signal → confirmation structure logic,
unique reset and filtering conditions.
These concepts cannot be reproduced through classic Ichimoku or standard TradingView indicators.
📈 Best Practices
Recommended markets: XAUUSD, Nasdaq, US30, GBPUSD, EURUSD
Recommended timeframes: M15 → H1
Use the Pre-Signal to define interest zones
Enter only on confirmed labels for maximum reliability
🔒 Access
This is an invite-only script.
To request access, please send me a private TradingView message or contact me on Telegram.
Ichimoku Traffic Lights Go--no go flags for Ichimoku Cloud. For quick scanning thru your watchlist, and good for scanning through timeframes.
SYNTARU ULTRA (Indicator) — Non-Repaint PROSYNTARU ULTRA (Non-Repaint PRO)
A professional-grade, non-repainting trading indicator designed to identify high-probability entries using multi-layer analysis. Combines core trend EMA (G1), ATR-based volatility bands (G2), momentum (RSI + EMA slope, G3), and optional higher timeframe confirmation (G4) to generate LONG and SHORT signals. Features include ATR spike filters for news/noise avoidance, cool-off bars to reduce false alerts, confidence scoring (0–100%), and full webhook-ready alerts for automation. On-chart panel displays signal, confidence, trend angle, RSI, ATR spike status, and cool-off activity for real-time monitoring.
RSI/VIX Reversal Signal (StevenCharts) [BETA]The RSI/VIX Reversal Signal (StevenCharts) is a specialized mean-reversion indicator that combines technical momentum (RSI) with market sentiment data (VIX).
While standard RSI strategies often fail by catching "falling knives" during strong trends, this indicator filters setups by requiring a specific volatility environment. It identifies moments of extreme fear (High VIX + Oversold RSI) or extreme complacency (Low VIX + Overbought RSI) to pinpoint high-probability reversal zones.
How It Works
This script operates on a two-step confirmation logic to prevent premature entries:
The Trigger (Blue Dot): The indicator first identifies an extreme condition.
Potential Buy: Price is Oversold while Volatility is elevated. This indicates panic selling.
Potential Sell: Price is Overbought while Volatility is suppressed. This indicates market complacency.
The Signal (Triangle Label): Once a trigger is detected, the script waits for Price Action Confirmation.
It will not print a Green Buy Label until a green candle actually closes.
It will not print a Red Sell Label until a red candle actually closes.
Key Features
Dual-Factor Analysis: Filters out weak RSI signals by demanding VIX confirmation.
Stateful Logic: Remembers if a trigger condition was met and patiently waits for the reversal candle before signaling.
Timeframe Noise Filter: Includes a built-in setting to automatically hide signals on lower timeframes to focus on macro reversals.
Data Table: An optional dashboard that displays real-time VIX values, RSI values, and Overbought/Oversold status directly on your chart.
How to Use
Buying the Fear: Look for the Green Triangle. This signals that panic selling has likely exhausted itself and buyers are stepping back in.
Selling the Greed: Look for the Red Triangle. This signals that the market is overextended and volatility is too low to sustain the move.
Blue Dots: Treat these as "Warning Shots." They tell you a setup is building, but the reversal hasn't confirmed yet.
CapitalFlowsResearch: PEMA ThresholdCapitalFlowsResearch: PEMA Threshold — Forward Regime Projection
CapitalFlowsResearch: PEMA Threshold extends the logic of the standard PEMA framework by not only identifying when price is in an extended regime, but also calculating the exact price levels where the next regime flip would occur. Instead of waiting for a signal to trigger, the tool projects the thresholds forward in real time, showing traders the points at which the current regime would shift from positive to negative extension (or vice versa).
Conceptually, the script takes the behaviour of price around its moving equilibrium and determines how far price would need to travel for the underlying extension score to breach its upper or lower band. These projected “flip prices” can be displayed as guide lines or labelled directly on the chart, providing a live map of where key behavioural shifts would take place.
This transforms PEMA from a reactive overlay into an anticipatory one—helping traders plan entries, stops, and scenario paths with a clear understanding of where the market’s statistical pressure points sit, without exposing the underlying calculations.
Historical SimilaritiesHappy trading! This tool provides short-term trend estimations. It is a further evolution of my earlier ANN Trend Prediction indicator, but it uses a completely new feature-vector composition and a different type of neural network.
1. Concept
The underlying idea is that history tends to repeat—not exactly, but with recognizable similarities. When recent market conditions resemble past situations, it is reasonable to assume that price may behave similarly again. That is the foundation of this indicator.
In the image below, you can see the general setup. The most recent bar (the “now” point) separates the past from the future. A sequence of recent bars is interpreted as a pattern and fed into a pre-trained LSTM network, which then produces the prediction for the current bar.
The focus of this tool is to deliver predictions as early as possible—ideally just before a trend reversal—to support short-term trades lasting approximately 5 to 20 bars. While perfect early detection is not reached here, this indicator often identifies reversals within one bar after they occur, which is usually early enough to capture meaningful moves.
There are other indicators capable of signaling trend reversals within a single bar—such as Shooting Star or Hammer candle patterns, or certain indicator setups. They were effective when they were new, but widespread use has reduced their reliability, and sometimes those patterns simply do not appear or appear without trend reversal.
This tool, by contrast, is new and it successfully identifies many trend reversals, as demonstrated in the image below:
2. Experimental Part
Furthermore, because this approach offers multiple settings that influence its behavior, you can configure it to focus on larger trends and ignore smaller fluctuations. The following images show several examples:
The default settings
with only-Body Smoothing enabled
with Generalized Trends enabled
with both Smoothing enabled
However, as you may notice, when targeting larger trends, a number of false-negative predictions may also appear. These still need to be filtered out. Please keep in mind that this version is experimental, requiring further investigation and research, and I would appreciate any feedback or suggestions.
3. Results
The prediction output is shown through a label and background colors as shown in the following image. It provides probabilities for three market directions:
Up - green
Sideways - blue
Down - red
When the model cannot confidently classify the current market conditions, it deliberately withholds a prediction and leaves the background uncolored. In most cases, however, it displays a label with all three probabilities whenever a new dominant prediction emerges, and it remains visible until the next dominant signal appears.
4. Conclusion
In its default settings, this indicator is quite capable when short-term trends last at least five or more bars. A support-and-resistance indicator can be helpful for setting take-profit and stop-loss levels.
5. Settings Menu
The script is delivered with its default settings, all turned off. However, several configuration options are available:
Input Preparation
Smoothing – Using Heikin Ashi or using only Bar Body are two methods that help remove outliers from the incoming bars.
Generalize Trends – Merges nearby trends together and removes smaller, insignificant trends.
Generalize Patterns – Checks the incoming pattern for artifacts and reduces it when possible. This is a trade-off between removing noise and keeping meaningful features.
Shifting – Examines the incoming pattern for consistency and adjusts it when reasonable.
Speed – Determines how quickly a prediction is calculated. A longer calculation time can improve accuracy, but may also risk the script timing out.
Filters
Intrabar – Off by default, allowing new dominant predictions only at bar close. When enabled, predictions may also be updated intrabar, but this introduces repainting on the current open bar.
Start of Classification – Sets the date from which classifications may begin.
Minimum Gains After Pattern – Defines how much price must rise or fall for a pattern to be considered an up, down, or sideways pattern.
Minimum Classification Probability – If the highest probability is below this threshold, no prediction is selected and the background stays translucent. If one probability exceeds the threshold, the largest one is chosen as the prediction.
Minimum Pattern Strength – Removes patterns whose strength is below this threshold.
6. Alert Signals Available
Trend Signal
2 = possible High
1 = Uptrend
0 = Ranging
-1 = Downtrend
-2 = possible Low
na = no prediction
Signal Age - counts the number of bars since last change
7. Declaration for TradingView House Rules on Script Publishing
The unique feature of the Historical Similarities Indicator is it's nearby real-time detection capability for up trends, down trends and side way price action in most cases.
This script is closed-source and invite-only, to support and compensate for years of development work.
8. Disclaimer
Trading involves risk, and losses can and do occur. This script is intended for informational and educational purposes only. All examples are hypothetical and not financial advice.
Decisions to buy, sell, hold, or trade securities, commodities, or other assets should be based on the advice of qualified financial professionals. Past performance does not guarantee future results.
Use this script at your own risk. It may contain bugs, and I cannot be held responsible for any financial losses resulting from its use.
Cheers!
ABK – Alpha Bundle Killer 2025 (FINAL VERSION)Script creado con un arte que no se puede aguantar. Version corregida
Moving Average Ribbon by AbrarIndicator Description — Moving Average Ribbon (Multi-TF Enhanced)
The Moving Average Ribbon (Enhanced) is a powerful trend-analysis tool that displays up to 7 customizable moving averages along with a Weekly SMA 150 for higher-timeframe confluence. Each MA can be individually configured with length, source, type (SMA/EMA/WMA/SMMA/VWMA), and color.
The script also features automatic labels on the latest bar, allowing traders to instantly identify each moving average on the chart without confusion.
This indicator is designed to help traders:
Visualize trend strength and direction
Spot dynamic support/resistance zones
Identify momentum shifts
Incorporate higher-timeframe confirmation through the Weekly SMA 150
Whether you trade intraday or swing, this ribbon provides a clean and flexible layout to understand market structure at a glance.
Hierarchical Hidden Markov Model - Probability Cone
The Hierarchical Hidden Markov Model - Probability Cone Indicator employs Hierarchical Hidden Markov Models for forecasting future price movements in financial markets. HHMMs are statistical tools that predict transitions between hidden states, such as different market regimes, based on observed data. This makes them valuable for understanding market behaviours and projecting future price trajectories. As discussed in the Hierarchical Hidden Markov Model indicator, HHMMs predict future states and their associated outputs based on the current state and model parameters. This tool is fundamentally very similar to the traditional HMM . The application of the HHMM for generating a probability cone forecast is therefore also fundamentally the same between HMM and HHMM. Despite their significant similarity I will go through the same fundamental examples of how probability cone is generated for the HHMM as I did for the HMM probability cone .
As you might know by now the probability cone indicator uses the knowledge about the current identified "state" or "regime" and with the help of transition probabilities, emission probabilities and initial probabilities generate a probabilistic forecast of the expected future price movements. To better understand the behind the Probability Cone we encourage you to use and learn about our free version of the Probability Cone as well as for even deeper understanding the Probability Cone Pro.
WHAT ARE REGIME DEPENDENT FORECASTS
We established that the indicator creates probabilistic forecasts of future price movements dependent on the current identified "state" or market "regime" via the Hidden Markov Model. In the image below we can see an example.
In this example we can see 4 different probability cones forecasting a 70% and 90% probability range (15% and 5% quantiles respectively). What you may notice is that the 4 probability cones look vastly different, despite using the same probability ranges as well as being generated from the same model trained on virtually the same data. What allows for this difference in the forecast, is conditioning the forecast on the current most likely identified state by the HHMM.
The first most cone is generating a forecast taking into account that the model identified the current market condition to be a extremely low in volatility this is a characteristic of the state identified by the light green coloured posterior probability. The second cone is significantly wider as well as has a negative drift, this is the case because that state identified by the red posterior probability is characterised by the most extreme volatility along with significant negative returns. The cone after that remains quite wide however is again associated with positive returns, this is characteristic of the state that the model identified via a high yelow coloured posterior probability. The last probability cone is again generated from a state that is characterised by quite low volatility albeit not the lowest. We can also see the state associated with that behaviour is identified by the high dark green posterior probability which is the highest at that time.
NOTE! Those are within sample forecasts, you can find more information on the difference between within sample model fit and out of sample prediction in the HHMM indicator description
This indicator also allows you to specify whether you wish to display probability based labels at the edges of the cone or whether you would prefer to display percent change based labels. With percent change labels you get the exact percentage value of the probabilistic increase or decrease of the price. See the example below
BARS BACK OFFSET vs DATE BASED OFFSET
The cones position can be offset by specifying the number of bars we wish to move it back similarly as with the rest of probability cone indicators. This indicator has however an additional, date based offset implemented. A user can therefore specify the position of the cone by specifying a date in the settings. The advantage of using the date based offset is that once it is turned on the user can also slide the cone up and down the chart with their mouse without having to manually adjust the date in the settings.
DIFFICULTIES WITH GENERATING FORECASTS (advanced):
The estimation of the probability cone, gets more difficult the more complex the model gets. A simple normal distribution probability cone can scale the distribution over time by simply multiplying the drift by the number of time steps and the volatility by the square root of time steps we wish to forecast for. More complex distributions often have to rely on mode advanced methods like convolutions, monte carlo or other kinds of approximations.
To estimate the probability cone forecast for the Hierarchial Hidden Markov Model, the indicator integrates two primary methodologies: Gaussian approximation and importance sampling. The Gaussian approximation is utilised for estimating the central 90% of future prices. This method provides a quick and efficient estimation within this central range, capturing the most likely price movements. The gaussian approximation will result in a forecast with an equal mean and variance as the true forecast, it will however not accurately reflect higher moments like skewness and kurtosis. For that reason the tail quantiles, which represent extreme price movements beyond the central range (90%), are estimated via importance sampling. This approach ensures a more accurate estimation of the skewness and kurtosis associated with extreme scenarios. While importance sampling leverages the flexibility of Monte Carlo as well as attempts to increase its efficiency by sampling from more precise areas of the distribution, the importance sampling may still underestimate most extreme quantiles associated with the lowest probabilities which is an inherent limitation of the indicator.
Example of gaussian approximation cone for probabilities above 5% (90% range):
Example of importance sampling cone for tail probabilities lower than 5% (beyond 90% range):
WARNING!
As per usual understand that the probabilities are estimations and best guesses based on the historical data and the patterns identified by the model and do not represent the true probability which is unknown in reality.
Settings:
- Source: Data source used for the model
- Forecast Period: Number of bars ahead for generating forecasts.
- Simulation Number: Number of Monte Carlo simulations to run in the case of importance sampling
-Body Probability: Specifies the inner range of the probability cone. The probability specifies the ammount of observations that are expected to fall outside of this range
- Tail Probability: Specifies the outter range of the probability cone. When this probability is under 5%, importance sampling will turn on
- Lock Cone: When ticked on, the cone will be locked at its current position.
- Offset Cone Based on Date: When ticked on, the position of the cone will be determined by the selected date.
- Offset: When "Offset Cone Based on Date" is turned off, you can use offset setting to specify the position of the cone projection.
- Date: When "Offset Cone Based on Date" is turned on, you can use the date setting to specify the date from which the forecast starts.
- Reestimate Model Every N Bars: This is especially useful if you wish to use the indicator on lower timeframes where model estimation might take longer than for the new datapoint to arrive. In that case you can specify after how many bars the model should be reestimated.
- Training Period: Length of historical data used to train the HMM.
- Expectation Maximization Iterations: Number of iterations for the EM algorithm.
- Cone Colors: Customizable colors for the probability cone, when approximation is on and when importance sampling is on
Hidden Markov Model - Probability Cone
The Hidden Markov Model - Probability Cone Indicator employs Hidden Markov Models (HMMs) for forecasting future price movements in financial markets. HMMs are statistical tools that predict transitions between hidden states, such as different market regimes, based on observed data. This makes them valuable for understanding market behaviours and projecting future price trajectories. As discussed in the Hidden Markov Model indicator, HMMs predict future states and their associated outputs based on the current state and model parameters.
The probability cone indicator therefore uses the knowledge about the current identified "state" or "regime" and with the help of transition probabilities, emission probabilities and initial probabilities generate a probabilistic forecast of the expected future price movements. To better understand the behind the Probability Cone we encourage you to use and learn about our free version of the Probability Cone as well as for even deeper understanding the Probability Cone Pro.
WHAT ARE REGIME DEPENDENT FORECASTS
As mentioned above the indicator creates probabilistic forecasts of future price movements dependent on the current identified "state" or market "regime" via the Hidden Markov Model. In the image below we can see an example.
In this example we can see 3 different probability cones forecasting a 70% and 90% probability range (15% and 5% quantiles respectively). What you may notice is that the 3 probability cones look vastly different, despite using the same probability ranges as well as being generated from the same model trained on virtually the same data. What allows for this difference in the forecast is conditioning the forecast on the current most likely identified state by the HMM.
The first most wide cone is generating a forecast taking into account that the model identified the current market condition to be a very volatile which is a characteristic of the state identified by the orange coloured posterior probability. The second cone is significantly more narrow as that state identified by the purple posterior probability is characterised by lower volatility. Nevertheless, the last probability cone is generated from the state that is characterised by the lowest volatility, we can also see the light blue posterior probability to be the highest at that time.
The indicator also allows you to specify whether you wish to display probability based labels at the edges of the cone or whether you would prefer to display percent change based labels. With percent change labels you get the exact percentage value of the probabilistic increase or decrease of the price. See the example below
BARS BACK OFFSET vs DATE BASED OFFSET
The cones position can be offset by specifying the number of bars we wish to move it back similarly as with the rest of probability cone indicators. This indicator has however an additional, date based offset implemented. A user can therefore specify the position of the cone by specifying a date in the settings. The advantage of using the date based offset is that once it is turned on the user can also slide the cone up and down the chart with their mouse without having to manually adjust the date in the settings.
DIFFICULTIES WITH GENERATING FORECASTS (advanced):
The estimation of the probability cone, gets more difficult the more complex the model gets. A simple normal distribution probability cone can scale the distribution over time by simply multiplying the drift by the number of time steps and the volatility by the square root of time steps we wish to forecast for. More complex distributions often have to rely on mode advanced methods like convolutions, monte carlo or other kinds of approximations.
To estimate the probability cone forecast for the Hidden Markov Model, the indicator integrates two primary methodologies: Gaussian approximation and importance sampling. The Gaussian approximation is utilized for estimating the central 90% of future prices. This method provides a quick and efficient estimation within this central range, capturing the most likely price movements. The gaussian approximation will result in a forecast with an equal mean and variance as the true forecast, it will however not accurately reflect higher moments like skewness and kurtosis. For that reason the tail quantiles, which represent extreme price movements beyond the central range (90%), are estimated via importance sampling. This approach ensures a more accurate estimation of the skewness and kurtosis associated with extreme scenarios. While impoortance sampling leverages the flexibility of monte carlo as well as attempts to increase its efficiency by sampling from more precise areas of the distribution, the importance sampling may still underestimate most extreme quantiles associated with the lowest probabilties which is an inherent limitation of the indicator.
Example of gaussian approximation cone for probabilities above 5% (90% range):
Example of importance sampling cone for tail probabilities lower than 5% (beyond 90% range):
WARNING!
As per usual understand that the probabilities are estimations and best guesses based on the historical data and the patterns identified by the model and do not represent the true probability which is unknown in reality.
Settings:
- Source: Data source used for the model
- Forecast Period: Number of bars ahead for generating forecasts.
- Simulation Number: Number of Monte Carlo simulations to run in the case of importance sampling
-Body Probability: Specifies the inner range of the probability cone. The probability specifies the ammount of observations that are expected to fall outside of this range
- Tail Probability: Specifies the outter range of the probability cone. When this probability is under 5%, importance sampling will turn on
- Lock Cone: When ticked on, the cone will be locked at its current position.
- Offset Cone Based on Date: When ticked on, the position of the cone will be determined by the selected date.
- Offset: When "Offset Cone Based on Date" is turned off, you can use offset setting to specify the position of the cone projection.
- Date: When "Offset Cone Based on Date" is turned on, you can use the date setting to specify the date from which the forecast starts.
- Reestimate Model Every N Bars: This is especially useful if you wish to use the indicator on lower timeframes where model estimation might take longer than for the new datapoint to arrive. In that case you can specify after how many bars the model should be reestimated.
- Training Period: Length of historical data used to train the HMM.
- Expectation Maximization Iterations: Number of iterations for the EM algorithm.
- Cone Colors: Customizable colors for the probability cone, when approximation is on and when importance sampling is on
Ultimate RSI [captainua]Ultimate RSI
Overview
This indicator combines multiple RSI calculations with volume analysis, divergence detection, and trend filtering to provide a comprehensive RSI-based trading system. The script calculates RSI using three different periods (6, 14, 24) and applies various smoothing methods to reduce noise while maintaining responsiveness. The combination of these features creates a multi-layered confirmation system that reduces false signals by requiring alignment across multiple indicators and timeframes.
The script includes optimized configuration presets for instant setup: Scalping, Day Trading, Swing Trading, and Position Trading. Simply select a preset to instantly configure all settings for your trading style, or use Custom mode for full manual control. All settings include automatic input validation to prevent configuration errors and ensure optimal performance.
Configuration Presets
The script includes preset configurations optimized for different trading styles, allowing you to instantly configure the indicator for your preferred trading approach. Simply select a preset from the "Configuration Preset" dropdown menu:
- Scalping: Optimized for fast-paced trading with shorter RSI periods (4, 7, 9) and minimal smoothing. Noise reduction is automatically disabled, and momentum confirmation is disabled to allow faster signal generation. Designed for quick entries and exits in volatile markets.
- Day Trading: Balanced configuration for intraday trading with moderate RSI periods (6, 9, 14) and light smoothing. Momentum confirmation is enabled for better signal quality. Ideal for day trading strategies requiring timely but accurate signals.
- Swing Trading: Configured for medium-term positions with standard RSI periods (14, 14, 21) and moderate smoothing. Provides smoother signals suitable for swing trading timeframes. All noise reduction features remain active.
- Position Trading: Optimized for longer-term trades with extended RSI periods (24, 21, 28) and heavier smoothing. Filters are configured for highest-quality signals. Best for position traders holding trades over multiple days or weeks.
- Custom: Full manual control over all settings. All input parameters are available for complete customization. This is the default mode and maintains full backward compatibility with previous versions.
When a preset is selected, it automatically adjusts RSI periods, smoothing lengths, and filter settings to match the trading style. The preset configurations ensure optimal settings are applied instantly, eliminating the need for manual configuration. All settings can still be manually overridden if needed, providing flexibility while maintaining ease of use.
Input Validation and Error Prevention
The script includes comprehensive input validation to prevent configuration errors:
- Cross-Input Validation: Smoothing lengths are automatically validated to ensure they are always less than their corresponding RSI period length. If you set a smoothing length greater than or equal to the RSI length, the script automatically adjusts it to (RSI Length - 1). This prevents logical errors and ensures valid configurations.
- Input Range Validation: All numeric inputs have minimum and maximum value constraints enforced by TradingView's input system, preventing invalid parameter values.
- Smart Defaults: Preset configurations use validated default values that are tested and optimized for each trading style. When switching between presets, all related settings are automatically updated to maintain consistency.
Core Calculations
Multi-Period RSI:
The script calculates RSI using the standard Wilder's RSI formula: RSI = 100 - (100 / (1 + RS)), where RS = Average Gain / Average Loss over the specified period. Three separate RSI calculations run simultaneously:
- RSI(6): Uses 6-period lookback for high sensitivity to recent price changes, useful for scalping and early signal detection
- RSI(14): Standard 14-period RSI for balanced analysis, the most commonly used RSI period
- RSI(24): Longer 24-period RSI for trend confirmation, provides smoother signals with less noise
Each RSI can be smoothed using EMA, SMA, RMA (Wilder's smoothing), WMA, or Zero-Lag smoothing. Zero-Lag smoothing uses the formula: ZL-RSI = RSI + (RSI - RSI ) to reduce lag while maintaining signal quality. You can apply individual smoothing lengths to each RSI period, or use global smoothing where all three RSIs share the same smoothing length.
Dynamic Overbought/Oversold Thresholds:
Static thresholds (default 70/30) are adjusted based on market volatility using ATR. The formula: Dynamic OB = Base OB + (ATR × Volatility Multiplier × Base Percentage / 100), Dynamic OS = Base OS - (ATR × Volatility Multiplier × Base Percentage / 100). This adapts to volatile markets where traditional 70/30 levels may be too restrictive. During high volatility, the dynamic thresholds widen, and during low volatility, they narrow. The thresholds are clamped between 0-100 to remain within RSI bounds. The ATR is cached for performance optimization, updating on confirmed bars and real-time bars.
Adaptive RSI Calculation:
An adaptive RSI adjusts the standard RSI(14) based on current volatility relative to average volatility. The calculation: Adaptive Factor = (Current ATR / SMA of ATR over 20 periods) × Volatility Multiplier. If SMA of ATR is zero (edge case), the adaptive factor defaults to 0. The adaptive RSI = Base RSI × (1 + Adaptive Factor), clamped to 0-100. This makes the indicator more responsive during high volatility periods when traditional RSI may lag. The adaptive RSI is used for signal generation (buy/sell signals) but is not plotted on the chart.
Overbought/Oversold Fill Zones:
The script provides visual fill zones between the RSI line and the threshold lines when RSI is in overbought or oversold territory. The fill logic uses inclusive conditions: fills are shown when RSI is currently in the zone OR was in the zone on the previous bar. This ensures complete coverage of entry and exit boundaries. A minimum gap of 0.1 RSI points is maintained between the RSI plot and threshold line to ensure reliable polygon rendering in TradingView. The fill uses invisible plots at the threshold levels and the RSI value, with the fill color applied between them. You can select which RSI (6, 14, or 24) to use for the fill zones.
Divergence Detection
Regular Divergence:
Bullish divergence: Price makes a lower low (current low < lowest low from previous lookback period) while RSI makes a higher low (current RSI > lowest RSI from previous lookback period). Bearish divergence: Price makes a higher high (current high > highest high from previous lookback period) while RSI makes a lower high (current RSI < highest RSI from previous lookback period). The script compares current price/RSI values to the lowest/highest values from the previous lookback period using ta.lowest() and ta.highest() functions with index to reference the previous period's extreme.
Pivot-Based Divergence:
An enhanced divergence detection method that uses actual pivot points instead of simple lowest/highest comparisons. This provides more accurate divergence detection by identifying significant pivot lows/highs in both price and RSI. The pivot-based method uses a tolerance-based approach with configurable constants: 1% tolerance for price comparisons (priceTolerancePercent = 0.01) and 1.0 RSI point absolute tolerance for RSI comparisons (pivotTolerance = 1.0). Minimum divergence threshold is 1.0 RSI point (minDivergenceThreshold = 1.0). It looks for two recent pivot points and compares them: for bullish divergence, price makes a lower low (at least 1% lower) while RSI makes a higher low (at least 1.0 point higher). This method reduces false divergences by requiring actual pivot points rather than just any low/high within a period. When enabled, pivot-based divergence replaces the traditional method for more accurate signal generation.
Strong Divergence:
Regular divergence is confirmed by an engulfing candle pattern. Bullish engulfing requires: (1) Previous candle is bearish (close < open ), (2) Current candle is bullish (close > open), (3) Current close > previous open, (4) Current open < previous close. Bearish engulfing is the inverse: previous bullish, current bearish, current close < previous open, current open > previous close. Strong divergence signals are marked with visual indicators (🐂 for bullish, 🐻 for bearish) and have separate alert conditions.
Hidden Divergence:
Continuation patterns that signal trend continuation rather than reversal. Bullish hidden divergence: Price makes a higher low (current low > lowest low from previous period) but RSI makes a lower low (current RSI < lowest RSI from previous period). Bearish hidden divergence: Price makes a lower high (current high < highest high from previous period) but RSI makes a higher high (current RSI > highest RSI from previous period). These patterns indicate the trend is likely to continue in the current direction.
Volume Confirmation System
Volume threshold filtering requires current volume to exceed the volume SMA multiplied by the threshold factor. The formula: Volume Confirmed = Volume > (Volume SMA × Threshold). If the threshold is set to 0.1 or lower, volume confirmation is effectively disabled (always returns true). This allows you to use the indicator without volume filtering if desired.
Volume Climax is detected when volume exceeds: Volume SMA + (Volume StdDev × Multiplier). This indicates potential capitulation moments where extreme volume accompanies price movements. Volume Dry-Up is detected when volume falls below: Volume SMA - (Volume StdDev × Multiplier), indicating low participation periods that may produce unreliable signals. The volume SMA is cached for performance, updating on confirmed and real-time bars.
Multi-RSI Synergy
The script generates signals when multiple RSI periods align in overbought or oversold zones. This creates a confirmation system that reduces false signals. In "ALL" mode, all three RSIs (6, 14, 24) must be simultaneously above the overbought threshold OR all three must be below the oversold threshold. In "2-of-3" mode, any two of the three RSIs must align in the same direction. The script counts how many RSIs are in each zone: twoOfThreeOB = ((rsi6OB ? 1 : 0) + (rsi14OB ? 1 : 0) + (rsi24OB ? 1 : 0)) >= 2.
Synergy signals require: (1) Multi-RSI alignment (ALL or 2-of-3), (2) Volume confirmation, (3) Reset condition satisfied (enough bars since last synergy signal), (4) Additional filters passed (RSI50, Trend, ADX, Volume Dry-Up avoidance). Separate reset conditions track buy and sell signals independently. The reset condition uses ta.barssince() to count bars since the last trigger, returning true if the condition never occurred (allowing first signal) or if enough bars have passed.
Regression Forecasting
The script uses historical RSI values to forecast future RSI direction using four methods. The forecast horizon is configurable (1-50 bars ahead). Historical data is collected into an array, and regression coefficients are calculated based on the selected method.
Linear Regression: Calculates the least-squares fit line (y = mx + b) through the last N RSI values. The calculation: meanX = sumX / horizon, meanY = sumY / horizon, denominator = sumX² - horizon × meanX², m = (sumXY - horizon × meanX × meanY) / denominator, b = meanY - m × meanX. The forecast projects this line forward: forecast = b + m × i for i = 1 to horizon.
Polynomial Regression: Fits a quadratic curve (y = ax² + bx + c) to capture non-linear trends. The system of equations is solved using Cramer's rule with a 3×3 determinant. If the determinant is too small (< 0.0001), the system falls back to linear regression. Coefficients are calculated by solving: n×c + sumX×b + sumX²×a = sumY, sumX×c + sumX²×b + sumX³×a = sumXY, sumX²×c + sumX³×b + sumX⁴×a = sumX²Y. Note: Due to the O(n³) computational complexity of polynomial regression, the forecast horizon is automatically limited to a maximum of 20 bars when using polynomial regression to maintain optimal performance. If you set a horizon greater than 20 bars with polynomial regression, it will be automatically capped at 20 bars.
Exponential Smoothing: Applies exponential smoothing with adaptive alpha = 2/(horizon+1). The smoothing iterates from oldest to newest value: smoothed = alpha × series + (1 - alpha) × smoothed. Trend is calculated by comparing current smoothed value to an earlier smoothed value (at 60% of horizon): trend = (smoothed - earlierSmoothed) / (horizon - earlierIdx). Forecast: forecast = base + trend × i.
Moving Average: Uses the difference between short MA (horizon/2) and long MA (horizon) to estimate trend direction. Trend = (maShort - maLong) / (longLen - shortLen). Forecast: forecast = maShort + trend × i.
Confidence bands are calculated using RMSE (Root Mean Squared Error) of historical forecast accuracy. The error calculation compares historical values with forecast values: RMSE = sqrt(sumSquaredError / count). If insufficient data exists, it falls back to calculating standard deviation of recent RSI values. Confidence bands = forecast ± (RMSE × confidenceLevel). All forecast values and confidence bands are clamped to 0-100 to remain within RSI bounds. The regression functions include comprehensive safety checks: horizon validation (must not exceed array size), empty array handling, edge case handling for horizon=1 scenarios, division-by-zero protection, and bounds checking for all array access operations to prevent runtime errors.
Strong Top/Bottom Detection
Strong buy signals require three conditions: (1) RSI is at its lowest point within the bottom period: rsiVal <= ta.lowest(rsiVal, bottomPeriod), (2) RSI is below the oversold threshold minus a buffer: rsiVal < (oversoldThreshold - rsiTopBottomBuffer), where rsiTopBottomBuffer = 2.0 RSI points, (3) The absolute difference between current RSI and the lowest RSI exceeds the threshold value: abs(rsiVal - ta.lowest(rsiVal, bottomPeriod)) > threshold. This indicates a bounce from extreme levels with sufficient distance from the absolute low.
Strong sell signals use the inverse logic: RSI at highest point, above overbought threshold + rsiTopBottomBuffer (2.0 RSI points), and difference from highest exceeds threshold. Both signals also require: volume confirmation, reset condition satisfied (separate reset for buy vs sell), and all additional filters passed (RSI50, Trend, ADX, Volume Dry-Up avoidance).
The reset condition uses separate logic for buy and sell: resetCondBuy checks bars since isRSIAtBottom, resetCondSell checks bars since isRSIAtTop. This ensures buy signals reset based on bottom conditions and sell signals reset based on top conditions, preventing incorrect signal blocking.
Filtering System
RSI(50) Filter: Only allows buy signals when RSI(14) > 50 (bullish momentum) and sell signals when RSI(14) < 50 (bearish momentum). This filter ensures you're buying in uptrends and selling in downtrends from a momentum perspective. The filter is optional and can be disabled. Recommended to enable for noise reduction.
Trend Filter: Uses a long-term EMA (default 200) to determine trend direction. Buy signals require price above EMA, sell signals require price below EMA. The EMA slope is calculated as: emaSlope = ema - ema . Optional EMA slope filter additionally requires the EMA to be rising (slope > 0) for buy signals or falling (slope < 0) for sell signals. This provides stronger trend confirmation by requiring both price position and EMA direction.
ADX Filter: Uses the Directional Movement Index (calculated via ta.dmi()) to measure trend strength. Signals only fire when ADX exceeds the threshold (default 20), indicating a strong trend rather than choppy markets. The ADX calculation uses separate length and smoothing parameters. This filter helps avoid signals during sideways/consolidation periods.
Volume Dry-Up Avoidance: Prevents signals during periods of extremely low volume relative to average. If volume dry-up is detected and the filter is enabled, signals are blocked. This helps avoid unreliable signals that occur during low participation periods.
RSI Momentum Confirmation: Requires RSI to be accelerating in the signal direction before confirming signals. For buy signals, RSI must be consistently rising (recovering from oversold) over the lookback period. For sell signals, RSI must be consistently falling (declining from overbought) over the lookback period. The momentum check verifies that all consecutive changes are in the correct direction AND the cumulative change is significant. This filter ensures signals only fire when RSI momentum aligns with the signal direction, reducing false signals from weak momentum.
Multi-Timeframe Confirmation: Requires higher timeframe RSI to align with the signal direction. For buy signals, current RSI must be below the higher timeframe RSI by at least the confirmation threshold. For sell signals, current RSI must be above the higher timeframe RSI by at least the confirmation threshold. This ensures signals align with the larger trend context, reducing counter-trend trades. The higher timeframe RSI is fetched using request.security() from the selected timeframe.
All filters use the pattern: filterResult = not filterEnabled OR conditionMet. This means if a filter is disabled, it always passes (returns true). Filters can be combined, and all must pass for a signal to fire.
RSI Centerline and Period Crossovers
RSI(50) Centerline Crossovers: Detects when the selected RSI source crosses above or below the 50 centerline. Bullish crossover: ta.crossover(rsiSource, 50), bearish crossover: ta.crossunder(rsiSource, 50). You can select which RSI (6, 14, or 24) to use for these crossovers. These signals indicate momentum shifts from bearish to bullish (above 50) or bullish to bearish (below 50).
RSI Period Crossovers: Detects when different RSI periods cross each other. Available pairs: RSI(6) × RSI(14), RSI(14) × RSI(24), or RSI(6) × RSI(24). Bullish crossover: fast RSI crosses above slow RSI (ta.crossover(rsiFast, rsiSlow)), indicating momentum acceleration. Bearish crossover: fast RSI crosses below slow RSI (ta.crossunder(rsiFast, rsiSlow)), indicating momentum deceleration. These crossovers can signal shifts in momentum before price moves.
StochRSI Calculation
Stochastic RSI applies the Stochastic oscillator formula to RSI values instead of price. The calculation: %K = ((RSI - Lowest RSI) / (Highest RSI - Lowest RSI)) × 100, where the lookback is the StochRSI length. If the range is zero, %K defaults to 50.0. %K is then smoothed using SMA with the %K smoothing length. %D is calculated as SMA of smoothed %K with the %D smoothing length. All values are clamped to 0-100. You can select which RSI (6, 14, or 24) to use as the source for StochRSI calculation.
RSI Bollinger Bands
Bollinger Bands are applied to RSI(14) instead of price. The calculation: Basis = SMA(RSI(14), BB Period), StdDev = stdev(RSI(14), BB Period), Upper = Basis + (StdDev × Deviation Multiplier), Lower = Basis - (StdDev × Deviation Multiplier). This creates dynamic zones around RSI that adapt to RSI volatility. When RSI touches or exceeds the bands, it indicates extreme conditions relative to recent RSI behavior.
Noise Reduction System
The script includes a comprehensive noise reduction system to filter false signals and improve accuracy. When enabled, signals must pass multiple quality checks:
Signal Strength Requirement: RSI must be at least X points away from the centerline (50). For buy signals, RSI must be at least X points below 50. For sell signals, RSI must be at least X points above 50. This ensures signals only trigger when RSI is significantly in oversold/overbought territory, not just near neutral.
Extreme Zone Requirement: RSI must be deep in the OB/OS zone. For buy signals, RSI must be at least X points below the oversold threshold. For sell signals, RSI must be at least X points above the overbought threshold. This ensures signals only fire in extreme conditions where reversals are more likely.
Consecutive Bar Confirmation: The signal condition must persist for N consecutive bars before triggering. This reduces false signals from single-bar spikes or noise. The confirmation checks that the signal condition was true for all bars in the lookback period.
Zone Persistence (Optional): Requires RSI to remain in the OB/OS zone for N consecutive bars, not just touch it. This ensures RSI is truly in an extreme state rather than just briefly touching the threshold. When enabled, this provides stricter filtering for higher-quality signals.
RSI Slope Confirmation (Optional): Requires RSI to be moving in the expected signal direction. For buy signals, RSI should be rising (recovering from oversold). For sell signals, RSI should be falling (declining from overbought). This ensures momentum is aligned with the signal direction. The slope is calculated by comparing current RSI to RSI N bars ago.
All noise reduction filters can be enabled/disabled independently, allowing you to customize the balance between signal frequency and accuracy. The default settings provide a good balance, but you can adjust them based on your trading style and market conditions.
Alert System
The script includes separate alert conditions for each signal type: buy/sell (adaptive RSI crossovers), divergence (regular, strong, hidden), crossovers (RSI50 centerline, RSI period crossovers), synergy signals, and trend breaks. Each alert type has its own alertcondition() declaration with a unique title and message.
An optional cooldown system prevents alert spam by requiring a minimum number of bars between alerts of the same type. The cooldown check: canAlert = na(lastAlertBar) OR (bar_index - lastAlertBar >= cooldownBars). If the last alert bar is na (first alert), it always allows the alert. Each alert type maintains its own lastAlertBar variable, so cooldowns are independent per signal type. The default cooldown is 10 bars, which is recommended for noise reduction.
Higher Timeframe RSI
The script can display RSI from a higher timeframe using request.security(). This allows you to see the RSI context from a larger timeframe (e.g., daily RSI on an hourly chart). The higher timeframe RSI uses RSI(14) calculation from the selected timeframe. This provides context for the current timeframe's RSI position relative to the larger trend.
RSI Pivot Trendlines
The script can draw trendlines connecting pivot highs and lows on RSI(6). This feature helps visualize RSI trends and identify potential trend breaks.
Pivot Detection: Pivots are detected using a configurable period. The script can require pivots to have minimum strength (RSI points difference from surrounding bars) to filter out weak pivots. Lower minPivotStrength values detect more pivots (more trendlines), while higher values detect only stronger pivots (fewer but more significant trendlines). Pivot confirmation is optional: when enabled, the script waits N bars to confirm the pivot remains the extreme, reducing repainting. Pivot confirmation functions (f_confirmPivotLow and f_confirmPivotHigh) are always called on every bar for consistency, as recommended by TradingView. When pivot bars are not available (na), safe default values are used, and the results are then used conditionally based on confirmation settings. This ensures consistent calculations and prevents calculation inconsistencies.
Trendline Drawing: Uptrend lines connect confirmed pivot lows (green), and downtrend lines connect confirmed pivot highs (red). By default, only the most recent trendline is shown (old trendlines are deleted when new pivots are confirmed). This keeps the chart clean and uncluttered. If "Keep Historical Trendlines" is enabled, the script preserves up to N historical trendlines (configurable via "Max Trendlines to Keep", default 5). When historical trendlines are enabled, old trendlines are saved to arrays instead of being deleted, allowing you to see multiple trendlines simultaneously for better trend analysis. The arrays are automatically limited to prevent memory accumulation.
Trend Break Detection: Signals are generated when RSI breaks above or below trendlines. Uptrend breaks (RSI crosses below uptrend line) generate buy signals. Downtrend breaks (RSI crosses above downtrend line) generate sell signals. Optional trend break confirmation requires the break to persist for N bars and optionally include volume confirmation. Trendline angle filtering can exclude flat/weak trendlines from generating signals (minTrendlineAngle > 0 filters out weak/flat trendlines).
How Components Work Together
The combination of multiple RSI periods provides confirmation across different timeframes, reducing false signals. RSI(6) catches early moves, RSI(14) provides balanced signals, and RSI(24) confirms longer-term trends. When all three align (synergy), it indicates strong consensus across timeframes.
Volume confirmation ensures signals occur with sufficient market participation, filtering out low-volume false breakouts. Volume climax detection identifies potential reversal points, while volume dry-up avoidance prevents signals during unreliable low-volume periods.
Trend filters align signals with the overall market direction. The EMA filter ensures you're trading with the trend, and the EMA slope filter adds an additional layer by requiring the trend to be strengthening (rising EMA for buys, falling EMA for sells).
ADX filter ensures signals only fire during strong trends, avoiding choppy/consolidation periods. RSI(50) filter ensures momentum alignment with the trade direction.
Momentum confirmation requires RSI to be accelerating in the signal direction, ensuring signals only fire when momentum is aligned. Multi-timeframe confirmation ensures signals align with higher timeframe trends, reducing counter-trend trades.
Divergence detection identifies potential reversals before they occur, providing early warning signals. Pivot-based divergence provides more accurate detection by using actual pivot points. Hidden divergence identifies continuation patterns, useful for trend-following strategies.
The noise reduction system combines multiple filters (signal strength, extreme zone, consecutive bars, zone persistence, RSI slope) to significantly reduce false signals. These filters work together to ensure only high-quality signals are generated.
The synergy system requires alignment across all RSI periods for highest-quality signals, significantly reducing false positives. Regression forecasting provides forward-looking context, helping anticipate potential RSI direction changes.
Pivot trendlines provide visual trend analysis and can generate signals when RSI breaks trendlines, indicating potential reversals or continuations.
Reset conditions prevent signal spam by requiring a minimum number of bars between signals. Separate reset conditions for buy and sell signals ensure proper signal management.
Usage Instructions
Configuration Presets (Recommended): The script includes optimized preset configurations for instant setup. Simply select your trading style from the "Configuration Preset" dropdown:
- Scalping Preset: RSI(4, 7, 9) with minimal smoothing. Noise reduction disabled, momentum confirmation disabled for fastest signals.
- Day Trading Preset: RSI(6, 9, 14) with light smoothing. Momentum confirmation enabled for better signal quality.
- Swing Trading Preset: RSI(14, 14, 21) with moderate smoothing. Balanced configuration for medium-term trades.
- Position Trading Preset: RSI(24, 21, 28) with heavier smoothing. Optimized for longer-term positions with all filters active.
- Custom Mode: Full manual control over all settings. Default behavior matches previous script versions.
Presets automatically configure RSI periods, smoothing lengths, and filter settings. You can still manually adjust any setting after selecting a preset if needed.
Getting Started: The easiest way to get started is to select a configuration preset matching your trading style (Scalping, Day Trading, Swing Trading, or Position Trading) from the "Configuration Preset" dropdown. This instantly configures all settings for optimal performance. Alternatively, use "Custom" mode for full manual control. The default configuration (Custom mode) shows RSI(6), RSI(14), and RSI(24) with their default smoothing. Overbought/oversold fill zones are enabled by default.
Customizing RSI Periods: Adjust the RSI lengths (6, 14, 24) based on your trading timeframe. Shorter periods (6) for scalping, standard (14) for day trading, longer (24) for swing trading. You can disable any RSI period you don't need.
Smoothing Selection: Choose smoothing method based on your needs. EMA provides balanced smoothing, RMA (Wilder's) is traditional, Zero-Lag reduces lag but may increase noise. Adjust smoothing lengths individually or use global smoothing for consistency. Note: Smoothing lengths are automatically validated to ensure they are always less than the corresponding RSI period length. If you set smoothing >= RSI length, it will be auto-adjusted to prevent invalid configurations.
Dynamic OB/OS: The dynamic thresholds automatically adapt to volatility. Adjust the volatility multiplier and base percentage to fine-tune sensitivity. Higher values create wider thresholds in volatile markets.
Volume Confirmation: Set volume threshold to 1.2 (default) for standard confirmation, higher for stricter filtering, or 0.1 to disable volume filtering entirely.
Multi-RSI Synergy: Use "ALL" mode for highest-quality signals (all 3 RSIs must align), or "2-of-3" mode for more frequent signals. Adjust the reset period to control signal frequency.
Filters: Enable filters gradually to find your preferred balance. Start with volume confirmation, then add trend filter, then ADX for strongest confirmation. RSI(50) filter is useful for momentum-based strategies and is recommended for noise reduction. Momentum confirmation and multi-timeframe confirmation add additional layers of accuracy but may reduce signal frequency.
Noise Reduction: The noise reduction system is enabled by default with balanced settings. Adjust minSignalStrength (default 3.0) to control how far RSI must be from centerline. Increase requireConsecutiveBars (default 1) to require signals to persist longer. Enable requireZonePersistence and requireRsiSlope for stricter filtering (higher quality but fewer signals). Start with defaults and adjust based on your needs.
Divergence: Enable divergence detection and adjust lookback periods. Strong divergence (with engulfing confirmation) provides higher-quality signals. Hidden divergence is useful for trend-following strategies. Enable pivot-based divergence for more accurate detection using actual pivot points instead of simple lowest/highest comparisons. Pivot-based divergence uses tolerance-based matching (1% for price, 1.0 RSI point for RSI) for better accuracy.
Forecasting: Enable regression forecasting to see potential RSI direction. Linear regression is simplest, polynomial captures curves, exponential smoothing adapts to trends. Adjust horizon based on your trading timeframe. Confidence bands show forecast uncertainty - wider bands indicate less reliable forecasts.
Pivot Trendlines: Enable pivot trendlines to visualize RSI trends and identify trend breaks. Adjust pivot detection period (default 5) - higher values detect fewer but stronger pivots. Enable pivot confirmation (default ON) to reduce repainting. Set minPivotStrength (default 1.0) to filter weak pivots - lower values detect more pivots (more trendlines), higher values detect only stronger pivots (fewer trendlines). Enable "Keep Historical Trendlines" to preserve multiple trendlines instead of just the most recent one. Set "Max Trendlines to Keep" (default 5) to control how many historical trendlines are preserved. Enable trend break confirmation for more reliable break signals. Adjust minTrendlineAngle (default 0.0) to filter flat trendlines - set to 0.1-0.5 to exclude weak trendlines.
Alerts: Set up alerts for your preferred signal types. Enable cooldown to prevent alert spam. Each signal type has its own alert condition, so you can be selective about which signals trigger alerts.
Visual Elements and Signal Markers
The script uses various visual markers to indicate signals and conditions:
- "sBottom" label (green): Strong bottom signal - RSI at extreme low with strong buy conditions
- "sTop" label (red): Strong top signal - RSI at extreme high with strong sell conditions
- "SyBuy" label (lime): Multi-RSI synergy buy signal - all RSIs aligned oversold
- "SySell" label (red): Multi-RSI synergy sell signal - all RSIs aligned overbought
- 🐂 emoji (green): Strong bullish divergence detected
- 🐻 emoji (red): Strong bearish divergence detected
- 🔆 emoji: Weak divergence signals (if enabled)
- "H-Bull" label: Hidden bullish divergence
- "H-Bear" label: Hidden bearish divergence
- ⚡ marker (top of pane): Volume climax detected (extreme volume) - positioned at top for visibility
- 💧 marker (top of pane): Volume dry-up detected (very low volume) - positioned at top for visibility
- ↑ triangle (lime): Uptrend break signal - RSI breaks below uptrend line
- ↓ triangle (red): Downtrend break signal - RSI breaks above downtrend line
- Triangle up (lime): RSI(50) bullish crossover
- Triangle down (red): RSI(50) bearish crossover
- Circle markers: RSI period crossovers
All markers are positioned at the RSI value where the signal occurs, using location.absolute for precise placement.
Signal Priority and Interpretation
Signals are generated independently and can occur simultaneously. Higher-priority signals generally indicate stronger setups:
1. Multi-RSI Synergy signals (SyBuy/SySell) - Highest priority: Requires alignment across all RSI periods plus volume and filter confirmation. These are the most reliable signals.
2. Strong Top/Bottom signals (sTop/sBottom) - High priority: Indicates extreme RSI levels with strong bounce conditions. Requires volume confirmation and all filters.
3. Divergence signals - Medium-High priority: Strong divergence (with engulfing) is more reliable than regular divergence. Hidden divergence indicates continuation rather than reversal.
4. Adaptive RSI crossovers - Medium priority: Buy when adaptive RSI crosses below dynamic oversold, sell when it crosses above dynamic overbought. These use volatility-adjusted RSI for more accurate signals.
5. RSI(50) centerline crossovers - Medium priority: Momentum shift signals. Less reliable alone but useful when combined with other confirmations.
6. RSI period crossovers - Lower priority: Early momentum shift indicators. Can provide early warning but may produce false signals in choppy markets.
Best practice: Wait for multiple confirmations. For example, a synergy signal combined with divergence and volume climax provides the strongest setup.
Chart Requirements
For proper script functionality and compliance with TradingView requirements, ensure your chart displays:
- Symbol name: The trading pair or instrument name should be visible
- Timeframe: The chart timeframe should be clearly displayed
- Script name: "Ultimate RSI " should be visible in the indicator title
These elements help traders understand what they're viewing and ensure proper script identification. The script automatically includes this information in the indicator title and chart labels.
Performance Considerations
The script is optimized for performance:
- ATR and Volume SMA are cached using var variables, updating only on confirmed and real-time bars to reduce redundant calculations
- Forecast line arrays are dynamically managed: lines are reused when possible, and unused lines are deleted to prevent memory accumulation
- Calculations use efficient Pine Script functions (ta.rsi, ta.ema, etc.) which are optimized by TradingView
- Array operations are minimized where possible, with direct calculations preferred
- Polynomial regression automatically caps the forecast horizon at 20 bars (POLYNOMIAL_MAX_HORIZON constant) to prevent performance degradation, as polynomial regression has O(n³) complexity. This safeguard ensures optimal performance even with large horizon settings
- Pivot detection includes edge case handling to ensure reliable calculations even on early bars with limited historical data. Regression forecasting functions include comprehensive safety checks: horizon validation (must not exceed array size), empty array handling, edge case handling for horizon=1 scenarios, and division-by-zero protection in all mathematical operations
The script should perform well on all timeframes. On very long historical data, forecast lines may accumulate if the horizon is large; consider reducing the forecast horizon if you experience performance issues. The polynomial regression performance safeguard automatically prevents performance issues for that specific regression type.
Known Limitations and Considerations
- Forecast lines are forward-looking projections and should not be used as definitive predictions. They provide context but are not guaranteed to be accurate.
- Dynamic OB/OS thresholds can exceed 100 or go below 0 in extreme volatility scenarios, but are clamped to 0-100 range. This means in very volatile markets, the dynamic thresholds may not widen as much as the raw calculation suggests.
- Volume confirmation requires sufficient historical volume data. On new instruments or very short timeframes, volume calculations may be less reliable.
- Higher timeframe RSI uses request.security() which may have slight delays on some data feeds.
- Regression forecasting requires at least N bars of history (where N = forecast horizon) before it can generate forecasts. Early bars will not show forecast lines.
- StochRSI calculation requires the selected RSI source to have sufficient history. Very short RSI periods on new charts may produce less reliable StochRSI values initially.
Practical Use Cases
The indicator can be configured for different trading styles and timeframes:
Swing Trading: Select the "Swing Trading" preset for instant optimal configuration. This preset uses RSI periods (14, 14, 21) with moderate smoothing. Alternatively, manually configure: Use RSI(24) with Multi-RSI Synergy in "ALL" mode, combined with trend filter (EMA 200) and ADX filter. This configuration provides high-probability setups with strong confirmation across multiple RSI periods.
Day Trading: Select the "Day Trading" preset for instant optimal configuration. This preset uses RSI periods (6, 9, 14) with light smoothing and momentum confirmation enabled. Alternatively, manually configure: Use RSI(6) with Zero-Lag smoothing for fast signal detection. Enable volume confirmation with threshold 1.2-1.5 for reliable entries. Combine with RSI(50) filter to ensure momentum alignment. Strong top/bottom signals work well for day trading reversals.
Trend Following: Enable trend filter (EMA) and EMA slope filter for strong trend confirmation. Use RSI(14) or RSI(24) with ADX filter to avoid choppy markets. Hidden divergence signals are useful for trend continuation entries.
Reversal Trading: Focus on divergence detection (regular and strong) combined with strong top/bottom signals. Enable volume climax detection to identify capitulation moments. Use RSI(6) for early reversal signals, confirmed by RSI(14) and RSI(24).
Forecasting and Planning: Enable regression forecasting with polynomial or exponential smoothing methods. Use forecast horizon of 10-20 bars for swing trading, 5-10 bars for day trading. Confidence bands help assess forecast reliability.
Multi-Timeframe Analysis: Enable higher timeframe RSI to see context from larger timeframes. For example, use daily RSI on hourly charts to understand the larger trend context. This helps avoid counter-trend trades.
Scalping: Select the "Scalping" preset for instant optimal configuration. This preset uses RSI periods (4, 7, 9) with minimal smoothing, disables noise reduction, and disables momentum confirmation for faster signals. Alternatively, manually configure: Use RSI(6) with minimal smoothing (or Zero-Lag) for ultra-fast signals. Disable most filters except volume confirmation. Use RSI period crossovers (RSI(6) × RSI(14)) for early momentum shifts. Set volume threshold to 1.0-1.2 for less restrictive filtering.
Position Trading: Select the "Position Trading" preset for instant optimal configuration. This preset uses extended RSI periods (24, 21, 28) with heavier smoothing, optimized for longer-term trades. Alternatively, manually configure: Use RSI(24) with all filters enabled (Trend, ADX, RSI(50), Volume Dry-Up avoidance). Multi-RSI Synergy in "ALL" mode provides highest-quality signals.
Practical Tips and Best Practices
Getting Started: The fastest way to get started is to select a configuration preset that matches your trading style. Simply choose "Scalping", "Day Trading", "Swing Trading", or "Position Trading" from the "Configuration Preset" dropdown to instantly configure all settings optimally. For advanced users, use "Custom" mode for full manual control. The default configuration (Custom mode) is balanced and works well across different markets. After observing behavior, customize settings to match your trading style.
Reducing Repainting: All signals are based on confirmed bars, minimizing repainting. The script uses confirmed bar data for all calculations to ensure backtesting accuracy.
Signal Quality: Multi-RSI Synergy signals in "ALL" mode provide the highest-quality signals because they require alignment across all three RSI periods. These signals have lower frequency but higher reliability. For more frequent signals, use "2-of-3" mode. The noise reduction system further improves signal quality by requiring multiple confirmations (signal strength, extreme zone, consecutive bars, optional zone persistence and RSI slope). Adjust noise reduction settings to balance signal frequency vs. accuracy.
Filter Combinations: Start with volume confirmation, then add trend filter for trend alignment, then ADX filter for trend strength. Combining all three filters significantly reduces false signals but also reduces signal frequency. Find your balance based on your risk tolerance.
Volume Filtering: Set volume threshold to 0.1 or lower to effectively disable volume filtering if you trade instruments with unreliable volume data or want to test without volume confirmation. Standard confirmation uses 1.2-1.5 threshold.
RSI Period Selection: RSI(6) is most sensitive and best for scalping or early signal detection. RSI(14) provides balanced signals suitable for day trading. RSI(24) is smoother and better for swing trading and trend confirmation. You can disable any RSI period you don't need to reduce visual clutter.
Smoothing Methods: EMA provides balanced smoothing with moderate lag. RMA (Wilder's smoothing) is traditional and works well for RSI. Zero-Lag reduces lag but may increase noise. WMA gives more weight to recent values. Choose based on your preference for responsiveness vs. smoothness.
Forecasting: Linear regression is simplest and works well for trending markets. Polynomial regression captures curves and works better in ranging markets. Exponential smoothing adapts to trends. Moving average method is most conservative. Use confidence bands to assess forecast reliability.
Divergence: Strong divergence (with engulfing confirmation) is more reliable than regular divergence. Hidden divergence indicates continuation rather than reversal, useful for trend-following strategies. Pivot-based divergence provides more accurate detection by using actual pivot points instead of simple lowest/highest comparisons. Adjust lookback periods based on your timeframe: shorter for day trading, longer for swing trading. Pivot divergence period (default 5) controls the sensitivity of pivot detection.
Dynamic Thresholds: Dynamic OB/OS thresholds automatically adapt to volatility. In volatile markets, thresholds widen; in calm markets, they narrow. Adjust the volatility multiplier and base percentage to fine-tune sensitivity. Higher values create wider thresholds in volatile markets.
Alert Management: Enable alert cooldown (default 10 bars, recommended) to prevent alert spam. Each alert type has its own cooldown, so you can set different cooldowns for different signal types. For example, use shorter cooldown for synergy signals (high quality) and longer cooldown for crossovers (more frequent). The cooldown system works independently for each signal type, preventing spam while allowing different signal types to fire when appropriate.
Technical Specifications
- Pine Script Version: v6
- Indicator Type: Non-overlay (displays in separate panel below price chart)
- Repainting Behavior: Minimal - all signals are based on confirmed bars, ensuring accurate backtesting results
- Performance: Optimized with caching for ATR and volume calculations. Forecast arrays are dynamically managed to prevent memory accumulation.
- Compatibility: Works on all timeframes (1 minute to 1 month) and all instruments (stocks, forex, crypto, futures, etc.)
- Edge Case Handling: All calculations include safety checks for division by zero, NA values, and boundary conditions. Reset conditions and alert cooldowns handle edge cases where conditions never occurred or values are NA.
- Reset Logic: Separate reset conditions for buy signals (based on bottom conditions) and sell signals (based on top conditions) ensure logical correctness.
- Input Parameters: 60+ customizable parameters organized into logical groups for easy configuration. Configuration presets available for instant setup (Scalping, Day Trading, Swing Trading, Position Trading, Custom).
- Noise Reduction: Comprehensive noise reduction system with multiple filters (signal strength, extreme zone, consecutive bars, zone persistence, RSI slope) to reduce false signals.
- Pivot-Based Divergence: Enhanced divergence detection using actual pivot points for improved accuracy.
- Momentum Confirmation: RSI momentum filter ensures signals only fire when RSI is accelerating in the signal direction.
- Multi-Timeframe Confirmation: Optional higher timeframe RSI alignment for trend confirmation.
- Enhanced Pivot Trendlines: Trendline drawing with strength requirements, confirmation, and trend break detection.
Technical Notes
- All RSI values are clamped to 0-100 range to ensure valid oscillator values
- ATR and Volume SMA are cached for performance, updating on confirmed and real-time bars
- Reset conditions handle edge cases: if a condition never occurred, reset returns true (allows first signal)
- Alert cooldown handles na values: if no previous alert, cooldown allows the alert
- Forecast arrays are dynamically sized based on horizon, with unused lines cleaned up
- Fill logic uses a minimum gap (0.1) to ensure reliable polygon rendering in TradingView
- All calculations include safety checks for division by zero and boundary conditions. Regression functions validate that horizon doesn't exceed array size, and all array access operations include bounds checking to prevent out-of-bounds errors
- The script uses separate reset conditions for buy signals (based on bottom conditions) and sell signals (based on top conditions) for logical correctness
- Background coloring uses a fallback system: dynamic color takes priority, then RSI(6) heatmap, then monotone if both are disabled
- Noise reduction filters are applied after accuracy filters, providing multiple layers of signal quality control
- Pivot trendlines use strength requirements to filter weak pivots, reducing noise in trendline drawing. Historical trendlines are stored in arrays and automatically limited to prevent memory accumulation when "Keep Historical Trendlines" is enabled
- Volume climax and dry-up markers are positioned at the top of the pane for better visibility
- All calculations are optimized with conditional execution - features only calculate when enabled (performance optimization)
- Input Validation: Automatic cross-input validation ensures smoothing lengths are always less than RSI period lengths, preventing configuration errors
- Configuration Presets: Four optimized preset configurations (Scalping, Day Trading, Swing Trading, Position Trading) for instant setup, plus Custom mode for full manual control
- Constants Management: Magic numbers extracted to documented constants for improved maintainability and easier tuning (pivot tolerance, divergence thresholds, fill gap, etc.)
- TradingView Function Consistency: All TradingView functions (ta.crossover, ta.crossunder, ta.atr, ta.lowest, ta.highest, ta.lowestbars, ta.highestbars, etc.) and custom functions that depend on historical results (f_consecutiveBarConfirmation, f_rsiSlopeConfirmation, f_rsiZonePersistence, f_applyAllFilters, f_rsiMomentum, f_forecast, f_confirmPivotLow, f_confirmPivotHigh) are called on every bar for consistency, as recommended by TradingView. Results are then used conditionally when needed. This ensures consistent calculations and prevents calculation inconsistencies.
Probability Cone ProProbability Cone Pro is based on the Expected Move Pro . While Expected Move only shows the historical value band on every bar, probability cone extend the period in the future and plot a cone or curve shape of the probable range. It plots the range from bar 1 all the way to any specified number of bars up to 1000.
Probability Cone Pro is an upgraded version of the Probability Cone indicator that uses a Normal Distribution to model the returns. This newer version uses a maximum likelihood estimation for Asymmetric Laplace distribution parameters. Asymmetric Laplace distribution takes into account fatter tails and volatility clustering during low volatility. So it will be thinner in the body (eg: <70% range) and fatter in the tails (>95% range) which fits the stock return better. Despite a better fit users should not blindly follow the probabilities derived from the indicator and should understand that these are very precise estimations of probability based on historical data, not the true probability which is in reality unknown.
When we compare the more peaked asymmetric laplace to the bell curve shaped normal distribution we can see that the asymmetric laplace fits the empirical data (blue histogram) significantly better. The fit is improved in both the body (middle peaked part) as well as in the fatter tails (more of extreme occurrences far from the center)
The area of probability range is based on an inverse cumulative distribution function. The inverse cumulative distribution gives the range of price for given input probability. People can adjust the range by adjusting the input probability in the settings. The entered probability will be shown at the edges of the cone when the “show probability” setting is on.
The indicator allows for specifying the probability for 2 quantiles on each side of the distribution , therefore 4 distinct probability values. The exact probability input is another distinction compared to the Normal Distribution based Probability Cone, in which the probability range is determined by the input of a standard deviation. Additionally now the displayed labels at the edges of the probability cone no longer correspond to the total number of outcomes that are expected to occur within the specific range, instead we chose to display the inverse which is the probability of outcomes outside of the specified range. See comparison below:
Probability cone pro with 68% and 95% ranges also defined by 16% and 2.5% probabilities at the tails on both sides:
Normal Probability cone with 68% and 95% ranges defined by 1st and 2nd standard deviation
SETTINGS:
Bars Back : Number of bars the cone is offset by.
Forecast Bar: Number of bars we forecast the cone for in the future.
Lock Cone : Specify whether we wish t lock the cone to the current bar, so it does not move when new bars arrive.
Show Probability : Specify whether you wish to show the probability labels at the edges of the cone.
Source : Source for computation of log returns whose distribution we forecast
Drift : Whether to take into account the drift in returns or assume 0 mean for the distribution.
Period: The sampling period or lookback for both the drift and the volatility estimation (full distribution estimation).
Up/Down Probabilities: 4 distinct probabilities are specified, 2 for the upper and 2 for the lower side of the distribution.
Expected Move ProExpected Move is the amount that an asset is predicted to increase or decrease from its current price, based on the current levels of volatility.
This Expected Move Pro indicator uses a maximum likelihood estimation for Asymmetric Laplace distribution parameters, and is an upgrade from the regular Expected Move indicator that uses a Normal Distribution. The use of the Asymmetric Laplace distribution ensures a probability range more accurate than the more common expected moves based on a normal distribution assumption for returns. Asymmetric Laplace distribution takes in account fatter tails and volatility clustering during low volatility. So it will be thinner in the body (eg: <70% range) and fatter in the tails (>95% range) which fits the stock return better.
When we compare the more peaked asymmetric laplace to the bell curve shaped normal distribution we can see that the asymmetric laplace fits the empirical data (blue histogram) significantly better. The fit is improved in both the body (middle peaked part) as well as in the fatter tails (more of extreme occurrences far from the center)
EXPECTED MOVE PROBABILITY:
In the expected move settings, the user can specify the range probability they wish to display. In a normal distribution a 1 standard deviation range corresponds to a range within which just under 70% of observations fall. So to specify a 70% probability range one would set 15% probability for both the upper and lower range.
For the more extreme ranges a two tail function is used so the user can only specify one probability. When 5% probability is specified the range will cover 95% and on each side of the range the probability of an occurence that extreme will be 2.5%. In the above Image we can see two tail probabilities specified at 5% and 1%, covering the 95% and 99% ranges respectively.
The indicator also allows for multi timeframe usecases. One can request a daily or perhaps even weekly expected move on an hourly chart, like we see below.
SETTINGS:
Resolution: Specify the timeframe and if you want to use the multi timeframe functionality.
Real Time : Do you wish the expected move to adjust with the current open price or do you wish it to be a forecast based on the yesterdays close. If latter, keep it OFF.
Sample Size : Lookback or the number of bars we sample in the calculation.
Optimization : Keep it on for speed purposes, only slightly higher precision will be achieved without optimization.
Probabilities: One tail - left and right, specify probability for each side of the range, two tail - single probability split in half for each side of the range
Center : Displays the central line which is the central tendency of a distribution / the median
Hide History : Hides expected moves and only the expected move for the current bar remains.
Plot Style Settings : One can adjust the line styles, box styles as well as width and transparency.
Probability Cone█ Overview:
Probability Cone is based on the Expected Move . While Expected Move only shows the historical value band on every bar, probability panel extend the period in the future and plot a cone or curve shape of the probable range. It plots the range from bar 1 all the way to bar 31.
In this model, we assume asset price follows a log-normal distribution and the log return follows a normal distribution.
Note: Normal distribution is just an assumption; it's not the real distribution of return.
The area of probability range is based on an inverse normal cumulative distribution function. The inverse cumulative distribution gives the range of price for given input probability. People can adjust the range by adjusting the standard deviation in the settings. The probability of the entered standard deviation will be shown at the edges of the probability cone.
The shown 68% and 95% probabilities correspond to the full range between the two blue lines of the cone (68%) and the two purple lines of the cone (95%). The probabilities suggest the % of outcomes or data that are expected to lie within this range. It does not suggest the probability of reaching those price levels.
Note: All these probabilities are based on the normal distribution assumption for returns. It's the estimated probability, not the actual probability.
█ Volatility Models :
Sample SD : traditional sample standard deviation, most commonly used, use (n-1) period to adjust the bias
Parkinson : Uses High/ Low to estimate volatility, assumes continuous no gap, zero mean no drift, 5 times more efficient than Close to Close
Garman Klass : Uses OHLC volatility, zero drift, no jumps, about 7 times more efficient
Yangzhang Garman Klass Extension : Added jump calculation in Garman Klass, has the same value as Garman Klass on markets with no gaps.
about 8 x efficient
Rogers : Uses OHLC, Assume non-zero mean volatility, handles drift, does not handle jump 8 x efficient.
EWMA : Exponentially Weighted Volatility. Weight recently volatility more, more reactive volatility better in taking account of volatility autocorrelation and cluster.
YangZhang : Uses OHLC, combines Rogers and Garmand Klass, handles both drift and jump, 14 times efficient, alpha is the constant to weight rogers volatility to minimize variance.
Median absolute deviation : It's a more direct way of measuring volatility. It measures volatility without using Standard deviation. The MAD used here is adjusted to be an unbiased estimator.
You can learn more about each of the volatility models in out Historical Volatility Estimators indicator.
█ How to use
Volatility Period is the sample size for variance estimation. A longer period makes the estimation range more stable less reactive to recent price. Distribution is more significant on larger sample size. A short period makes the range more responsive to recent price. Might be better for high volatility clusters.
People usually assume the mean of returns to be zero. To be more accurate, we can consider the drift in price from calculating the geometric mean of returns. Drift happens in the long run, so short lookback periods are not recommended.
The shape of the cone will be skewed and have a directional bias when the length of mean is short. It might be more adaptive to the current price or trend, but more accurate estimation should use a longer period for the mean.
Using a short look back for mean will make the cone having a directional bias.
When we are estimating the future range for time > 1, we typically assume constant volatility and the returns to be independent and identically distributed. We scale the volatility in term of time to get future range. However, when there's autocorrelation in returns( when returns are not independent), the assumption fails to take account of this effect. Volatility scaled with autocorrelation is required when returns are not iid. We use an AR(1) model to scale the first-order autocorrelation to adjust the effect. Returns typically don't have significant autocorrelation. Adjustment for autocorrelation is not usually needed. A long length is recommended in Autocorrelation calculation.
Note: The significance of autocorrelation can be checked on an ACF indicator.
ACF
Time back settings shift the estimation period back by the input number. It's the origin of when the probability cone start to estimation it's range.
E.g., When time back = 5, the probability cone start its prediction interval estimation from 5 bars ago. So for time back = 5 , it estimates the probability range from 5 bars ago to X number of bars in the future, specified by the Forecast Period (max 1000).
█ Warnings:
People should not blindly trust the probability. They should be aware of the risk evolves by using the normal distribution assumption. The real return has skewness and high kurtosis. While skewness is not very significant, the high kurtosis should be noticed. The Real returns have much fatter tails than the normal distribution, which also makes the peak higher. This property makes the tail ranges such as range more than 2SD highly underestimate the actual range and the body such as 1 SD slightly overestimate the actual range. For ranges more than 2SD, people shouldn't trust them. They should beware of extreme events in the tails.
The uncertainty in future bars makes the range wider. The overestimate effect of the body is partly neutralized when it's extended to future bars. We encourage people who use this indicator to further investigate the Historical Volatility Estimators , Fast Autocorrelation Estimator , Expected Move and especially the Linear Moments Indicator .
The probability is only for the closing price, not wicks. It only estimates the probability of the price closing at this level, not in between.
