Super momentum DBSISuper momentum DBSI: The Ultimate Guide
1. What is this Indicator?
The Super momentum DBSI is a "Consensus Engine." Instead of relying on a single line (like an RSI) to tell you where the market is going, this tool calculates 33 distinct technical indicators simultaneously for every single candle.
It treats the market like a democracy. It asks 33 mathematical "voters" (Momentum, Trend, Volume, Volatility) if they are Bullish or Bearish.
If 30 out of 33 say "Buy," the score is high (Yellow), and the trend is extremely strong.
If only 15 say "Buy," the score is low (Teal), and the trend is weak or choppy.
2. Visual Guide: How to Read the Numbers
The Scores
Top Number (Bears): Represents Selling Pressure.
Bottom Number (Bulls): Represents Buying Pressure.
The Colors (The Traffic Lights)
The colors are your primary signal. They tell you who is currently winning the war.
🟡 YELLOW (Dominance):
This indicates the Winning Side.
If the Bottom Number is Yellow, Bulls are in control.
If the Top Number is Yellow, Bears are in control.
🔴 RED (Weakness):
This appears on the Top. It means Bears are present but losing.
🔵 TEAL (Weakness):
This appears on the Bottom. It means Bulls are present but losing.
3. Trading Strategy
Scenario A: The "Strong Buy" (Long Entry)
The Setup: You are looking for a shift in momentum where Buyers overwhelm Sellers.
Watch the Bottom Number: Wait for it to turn Yellow.
Confirm Strength: Ensure the score is above 15 and rising (e.g., 12 → 18 → 22).
Check the Top: The Top Number should be Red and low (below 10).
Trigger: Enter on the candle close.
Scenario B: The "Strong Sell" (Short Entry)
The Setup: You are looking for Sellers to crush the Buyers.
Watch the Top Number: Wait for it to turn Yellow.
Confirm Strength: Ensure the score is above 15 and rising.
Check the Bottom: The Bottom Number should be Teal and low.
Trigger: Enter on the candle close.
Scenario C: The "No Trade Zone" (Choppy Market)
The Setup: The market is confused.
Visual: Top is Red, Bottom is Teal.
Meaning: NOBODY IS WINNING. There is no Yellow number.
Action: Do not trade. This usually happens during lunch hours, weekends, or right before big news. This filter alone will save you from many false breakouts.
4. What is Inside? (The 33 Indicators)
To give you confidence in the signals, here is exactly what the script is checking:
Group 1: Momentum (Oscillators)
Detects if price is moving fast.
RSI (Relative Strength Index)
CCI (Commodity Channel Index)
Stochastic
Williams %R
Momentum
Rate of Change (ROC)
Ultimate Oscillator
Awesome Oscillator
True Strength Index (TSI)
Stoch RSI
TRIX
Chande Momentum Oscillator
Group 2: Trend Direction
Detects the general path of the market.
13. MACD
14. Parabolic SAR
15. SuperTrend
16. ALMA (Moving Average)
17. Aroon
18. ADX (Directional Movement)
19. Coppock Curve
20. Ichimoku Conversion Line
21. Hull Moving Average
Group 3: Price Action
Detects where price is relative to averages.
22. Price vs EMA 20
23. Price vs EMA 50
24. Price vs EMA 200
Group 4: Volume & Force
Detects if there is money behind the move.
25. Money Flow Index (MFI)
26. On Balance Volume (OBV)
27. Chaikin Money Flow (CMF)
28. VWAP (Intraday)
29. Elder Force Index
30. Ease of Movement
Group 5: Volatility
Detects if price is pushing the outer limits.
31. Bollinger Bands
32. Keltner Channels
33. Donchian Channels
5. Pro Tips for Success
Don't Catch Knives: If the Bear score (Top) is Yellow and 25+, do not try to buy the dip. Wait for the Yellow score to break.
Exit Early: If you are Long and the Yellow Bull score drops from 28 to 15 in one candle, TAKE PROFIT. The momentum has died.
Use Higher Timeframes: This indicator works best on 15m, 1H, and 4H charts. On the 1m chart, it may be too volatile.
ค้นหาในสคริปต์สำหรับ "donchian"
20 Day Range High/Low (Turtle Soup)This indicator identifies the Highest High and Lowest Low of the last 20 periods (customizable) and projects horizontal support/resistance lines to the right.
Unlike standard Donchian Channels or other High/Low indicators that clutter the chart with historical "steps" or extend lines infinitely to the left, this script focuses on chart cleanliness.
Key Features:
Pivot-Point Start: The lines do not span the whole chart. They start exactly at the candle where the High or Low occurred.
Right Extension: Lines extend only to the future, providing a clear visual for potential breakouts or support levels.
No Historical Clutter: It does not draw the past movement of the High/Low, keeping your chart clean for price action analysis.
Dynamic: As new Highs or Lows are made, the lines instantly update to the new positions.
How to Use:
Trend Identification: Use the High line as a resistance/breakout level (similar to Turtle Trading strategies).
Stop Loss Placement: The Low line of the last 20 days often acts as a trailing stop location for long-term trends.
Timeframes: While designed for the classic "20-Day" lookback on the Daily chart, this script works on any timeframe (e.g., finding the 20-hour range on a 1H chart).
Settings:
Length: Default is 20 bars. You can change this in the settings to any lookback period you prefer (e.g., 50, 100).
RSI BREAKOUT SIGNALSThis BB + RSI Breakout indicator is designed to help traders identify potential buy and sell opportunities based on price movements relative to the Donchian channel (or Bollinger-type channel) and momentum conditions. It calculates the highest high and lowest low over a user-defined length to form a dynamic channel, and then it checks whether the current price breaks above the upper band (for a buy signal) or below the lower band (for a sell signal). To avoid repeated signals in a row, the indicator uses a state system: after a buy signal occurs, it will not generate another buy until a sell occurs, and vice versa. When a buy signal is triggered, it automatically calculates a take-profit price a certain percentage above the buy candle and displays this price below the candle as a “TP” label. Sell signals are displayed above the candle, and any previous TP label is cleared. The indicator updates in real time, so the signals move with the chart, giving a clear and lag-free visualization of entry points and potential profit targets.
Trend Pivot Retracements▶ OVERVIEW
Trend Pivot Retracements identifies market trend direction using a Donchian-style channel and dynamically highlights retracement zones during trending conditions. It calculates the percentage pullbacks from recent highs and lows, plots labeled zones with varying intensity, and visually connects key retracement pivots. The indicator also emphasizes price proximity to trend boundaries by dynamically adjusting the thickness of plotted trend bands.
▶ TREND DETECTION & BAND STRUCTURE
The indicator determines the current trend by checking for new 50-bar extremes:
Uptrend: If a new highest high is made, the trend is considered bullish.
Downtrend: If a new lowest low is made, the trend is considered bearish.
Uptrend Band: Plots the 50-bar lowest low as a trailing support level.
Downtrend Band: Plots the 50-bar highest high as a trailing resistance level.
Thickness Variation: The thickness of the band increases the further price moves from it, indicating overextension.
▶ RETRACEMENT LABELING SYSTEM
During a trend, the indicator monitors pivot points in the opposite direction to measure retracements:
Bullish Retracement:
Triggered when a pivot low forms during an uptrend.
Measures % pullback from the most recent swing high (searched up to 20 bars back).
Plots a bold horizontal line at the low and a dashed diagonal from the previous swing high.
Adds a “-%” label above the low; intensity is based on recent 50 pullbacks.
Bearish Retracement:
Triggered when a pivot high forms during a downtrend.
Measures % pullback from the previous swing low (up to 20 bars back).
Plots a bold horizontal line at the high and a dashed diagonal from the prior swing low.
Adds a “%” label below the high with gradient color based on the past 50 extremes.
▶ PIVOT CONNECTION LINES
Each retracement includes a visual connector:
A diagonal dashed line linking the swing extreme (20 bars back) to the retracement point.
This line visually traces the path of price retreat within the trend.
Helps traders understand where the retracement originated and how steep it was.
▶ TREND SWITCH SIGNALS
When trend direction changes:
A diamond marker is plotted on the new pivot confirming the trend shift.
Green diamonds signal new bullish trends at fresh lows.
Magenta diamonds signal new bearish trends at fresh highs.
▶ COLOR INTENSITY & CONTEXTUAL AWARENESS
To help interpret the magnitude of retracements:
The % labels are color-coded using a gradient scale that references the max of the last 50 pullbacks.
Stronger pullbacks result in deeper color intensity, signaling more significant corrections.
Trend bands also use standard deviation normalization to adjust line thickness based on how far price has moved from the band.
This creates a visual cue for potential exhaustion or volatility extremes.
▶ USAGE
Trend Pivot Retracements is a powerful tool for traders who want to:
Identify trend direction and contextual pullbacks within those trends.
Spot key retracement points that may serve as entry opportunities or reversal signals.
Use visual retracement angles to understand market pressure and trend maturity.
Read dynamic band thickness as an alert for price stretch, potential mean reversion, or breakout setups.
▶ CONCLUSION
Trend Pivot Retracements gives traders a clean, visually expressive way to monitor trending markets, while capturing and labeling meaningful retracements. With adaptive color intensity, diagonal connectors, and smart trend switching, it enhances situational awareness and provides immediate clarity on trend health and pullback strength.
Luxy Momentum, Trend, Bias and Breakout Indicators V7
TABLE OF CONTENTS
This is Version 7 (V7) - the latest and most optimized release. If you are using any older versions (V6, V5, V4, V3, etc.), it is highly recommended to replace them with V7.
Why This Indicator is Different
Who Should Use This
Core Components Overview
The UT Bot Trading System
Understanding the Market Bias Table
Candlestick Pattern Recognition
Visual Tools and Features
How to Use the Indicator
Performance and Optimization
FAQ
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### CREDITS & ATTRIBUTION
This indicator implements proven trading concepts using entirely original code developed specifically for this project.
### CONCEPTUAL FOUNDATIONS
• UT Bot ATR Trailing System
- Original concept by @QuantNomad: (search "UT-Bot-Strategy"
- Our version is a complete reimplementation with significant enhancements:
- Volume-weighted momentum adjustment
- Composite stop loss from multiple S/R layers
- Multi-filter confirmation system (swing, %, 2-bar, ZLSMA)
- Full integration with multi-timeframe bias table
- Visual audit trail with freeze-on-touch
- NOTE: No code was copied - this is a complete reimplementation with enhancements.
• Standard Technical Indicators (Public Domain Formulas):
- Supertrend: ATR-based trend calculation with custom gradient fills
- MACD: Gerald Appel's formula with separation filters
- RSI: J. Welles Wilder's formula with pullback zone logic
- ADX/DMI: Custom trend strength formula inspired by Wilder's directional movement concept, reimplemented with volume weighting and efficiency metrics
- ZLSMA: Zero-lag formula enhanced with Hull MA and momentum prediction
### Custom Implementations
- Trend Strength: Inspired by Wilder's ADX concept but using volume-weighted pressure calculation and efficiency metrics (not traditional +DI/-DI smoothing)
- All code implementations are original
### ORIGINAL FEATURES (70%+ of codebase)
- Multi-Timeframe Bias Table with live updates
- Risk Management System (R-multiple TPs, freeze-on-touch)
- Opening Range Breakout tracker with session management
- Composite Stop Loss calculator using 6+ S/R layers
- Performance optimization system (caching, conditional calcs)
- VIX Fear Index integration
- Previous Day High/Low auto-detection
- Candlestick pattern recognition with interactive tooltips
- Smart label and visual management
- All UI/UX design and table architecture
### DEVELOPMENT PROCESS
**AI Assistance:** This indicator was developed over 2+ months with AI assistance (ChatGPT/Claude) used for:
- Writing Pine Script code based on design specifications
- Optimizing performance and fixing bugs
- Ensuring Pine Script v6 compliance
- Generating documentation
**Author's Role:** All trading concepts, system design, feature selection, integration logic, and strategic decisions are original work by the author. The AI was a coding tool, not the system designer.
**Transparency:** We believe in full disclosure - this project demonstrates how AI can be used as a powerful development tool while maintaining creative and strategic ownership.
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1. WHY THIS INDICATOR IS DIFFERENT
Most traders use multiple separate indicators on their charts, leading to cluttered screens, conflicting signals, and analysis paralysis. The Suite solves this by integrating proven technical tools into a single, cohesive system.
Key Advantages:
All-in-One Design: Instead of loading 5-10 separate indicators, you get everything in one optimized script. This reduces chart clutter and improves TradingView performance.
Multi-Timeframe Bias Table: Unlike standard indicators that only show the current timeframe, the Bias Table aggregates trend signals across multiple timeframes simultaneously. See at a glance whether 1m, 5m, 15m, 1h are aligned bullish or bearish - no more switching between charts.
Smart Confirmations: The indicator doesn't just give signals - it shows you WHY. Every entry has multiple layers of confirmation (MA cross, MACD momentum, ADX strength, RSI pullback, volume, etc.) that you can toggle on/off.
Dynamic Stop Loss System: Instead of static ATR stops, the SL is calculated from multiple support/resistance layers: UT trailing line, Supertrend, VWAP, swing structure, and MA levels. This creates more intelligent, price-action-aware stops.
R-Multiple Take Profits: Built-in TP system calculates targets based on your initial risk (1R, 1.5R, 2R, 3R). Lines freeze when touched with visual checkmarks, giving you a clean audit trail of partial exits.
Educational Tooltips Everywhere: Every single input has detailed tooltips explaining what it does, typical values, and how it impacts trading. You're not guessing - you're learning as you configure.
Performance Optimized: Smart caching, conditional calculations, and modular design mean the indicator runs fast despite having 15+ features. Turn off what you don't use for even better performance.
No Repainting: All signals respect bar close. Alerts fire correctly. What you see in history is what you would have gotten in real-time.
What Makes It Unique:
Integrated UT Bot + Bias Table: No other indicator combines UT Bot's ATR trailing system with a live multi-timeframe dashboard. You get precision entries with macro trend context.
Candlestick Pattern Recognition with Interactive Tooltips: Patterns aren't just marked - hover over any emoji for a full explanation of what the pattern means and how to trade it.
Opening Range Breakout Tracker: Built-in ORB system for intraday traders with customizable session times and real-time status updates in the Bias Table.
Previous Day High/Low Auto-Detection: Automatically plots PDH/PDL on intraday charts with theme-aware colors. Updates daily without manual input.
Dynamic Row Labels in Bias Table: The table shows your actual settings (e.g., "EMA 10 > SMA 20") not generic labels. You know exactly what's being evaluated.
Modular Filter System: Instead of forcing a fixed methodology, the indicator lets you build your own strategy. Start with just UT Bot, add filters one at a time, test what works for your style.
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2. WHO WHOULD USE THIS
Designed For:
Intermediate to Advanced Traders: You understand basic technical analysis (MAs, RSI, MACD) and want to combine multiple confirmations efficiently. This isn't a "one-click profit" system - it's a professional toolkit.
Multi-Timeframe Traders: If you trade one asset but check multiple timeframes for confirmation (e.g., enter on 5m after checking 15m and 1h alignment), the Bias Table will save you hours every week.
Trend Followers: The indicator excels at identifying and following trends using UT Bot, Supertrend, and MA systems. If you trade breakouts and pullbacks in trending markets, this is built for you.
Intraday and Swing Traders: Works equally well on 5m-1h charts (day trading) and 4h-D charts (swing trading). Scalpers can use it too with appropriate settings adjustments.
Discretionary Traders: This isn't a black-box system. You see all the components, understand the logic, and make final decisions. Perfect for traders who want tools, not automation.
Works Across All Markets:
Stocks (US, international)
Cryptocurrency (24/7 markets supported)
Forex pairs
Indices (SPY, QQQ, etc.)
Commodities
NOT Ideal For :
Complete Beginners: If you don't know what a moving average or RSI is, start with basics first. This indicator assumes foundational knowledge.
Algo Traders Seeking Black Box: This is discretionary. Signals require context and confirmation. Not suitable for blind automated execution.
Mean-Reversion Only Traders: The indicator is trend-following at its core. While VWAP bands support mean-reversion, the primary methodology is trend continuation.
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3. CORE COMPONENTS OVERVIEW
The indicator combines these proven systems:
Trend Analysis:
Moving Averages: Four customizable MAs (Fast, Medium, Medium-Long, Long) with six types to choose from (EMA, SMA, WMA, VWMA, RMA, HMA). Mix and match for your style.
Supertrend: ATR-based trend indicator with unique gradient fill showing trend strength. One-sided ribbon visualization makes it easier to see momentum building or fading.
ZLSMA : Zero-lag linear-regression smoothed moving average. Reduces lag compared to traditional MAs while maintaining smooth curves.
Momentum & Filters:
MACD: Standard MACD with separation filter to avoid weak crossovers.
RSI: Pullback zone detection - only enter longs when RSI is in your defined "buy zone" and shorts in "sell zone".
ADX/DMI: Trend strength measurement with directional filter. Ensures you only trade when there's actual momentum.
Volume Filter: Relative volume confirmation - require above-average volume for entries.
Donchian Breakout: Optional channel breakout requirement.
Signal Systems:
UT Bot: The primary signal generator. ATR trailing stop that adapts to volatility and gives clear entry/exit points.
Base Signals: MA cross system with all the above filters applied. More conservative than UT Bot alone.
Market Bias Table: Multi-timeframe dashboard showing trend alignment across 7 timeframes plus macro bias (3-day, weekly, monthly, quarterly, VIX).
Candlestick Patterns: Six major reversal patterns auto-detected with interactive tooltips.
ORB Tracker: Opening range high/low with breakout status (intraday only).
PDH/PDL: Previous day levels plotted automatically on intraday charts.
VWAP + Bands : Session-anchored VWAP with up to three standard deviation band pairs.
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4. THE UT BOT TRADING SYSTEM
The UT Bot is the heart of the indicator's signal generation. It's an advanced ATR trailing stop that adapts to market volatility.
Why UT Bot is Superior to Fixed Stops:
Traditional ATR stops use a fixed multiplier (e.g., "stop = entry - 2×ATR"). UT Bot is smarter:
It TRAILS the stop as price moves in your favor
It WIDENS during high volatility to avoid premature stops
It TIGHTENS during consolidation to lock in profits
It FLIPS when price breaks the trailing line, signaling reversals
Visual Elements You'll See:
Orange Trailing Line: The actual UT stop level that adapts bar-by-bar
Buy/Sell Labels: Aqua triangle (long) or orange triangle (short) when the line flips
ENTRY Line: Horizontal line at your entry price (optional, can be turned off)
Suggested Stop Loss: A composite SL calculated from multiple support/resistance layers:
- UT trailing line
- Supertrend level
- VWAP
- Swing structure (recent lows/highs)
- Long-term MA (200)
- ATR-based floor
Take Profit Lines: TP1, TP1.5, TP2, TP3 based on R-multiples. When price touches a TP, it's marked with a checkmark and the line freezes for audit trail purposes.
Status Messages: "SL Touched ❌" or "SL Frozen" when the trade leg completes.
How UT Bot Differs from Other ATR Systems:
Multiple Filters Available: You can require 2-bar confirmation, minimum % price change, swing structure alignment, or ZLSMA directional filter. Most UT implementations have none of these.
Smart SL Calculation: Instead of just using the UT line as your stop, the indicator suggests a better SL based on actual support/resistance. This prevents getting stopped out by wicks while keeping risk controlled.
Visual Audit Trail: All SL/TP lines freeze when touched with clear markers. You can review your trades weeks later and see exactly where entries, stops, and targets were.
Performance Options: "Draw UT visuals only on bar close" lets you reduce rendering load without affecting logic or alerts - critical for slower machines or 1m charts.
Trading Logic:
UT Bot flips direction (Buy or Sell signal appears)
Check Bias Table for multi-timeframe confirmation
Optional: Wait for Base signal or candlestick pattern
Enter at signal bar close or next bar open
Place stop at "Suggested Stop Loss" line
Scale out at TP levels (TP1, TP2, TP3)
Exit remaining position on opposite UT signal or stop hit
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5. UNDERSTANDING THE MARKET BIAS TABLE
This is the indicator's unique multi-timeframe intelligence layer. Instead of looking at one chart at a time, the table aggregates signals across seven timeframes plus macro trend bias.
Why Multi-Timeframe Analysis Matters:
Professional traders check higher and lower timeframes for context:
Is the 1h uptrend aligning with my 5m entry?
Are all short-term timeframes bullish or just one?
Is the daily trend supportive or fighting me?
Doing this manually means opening multiple charts, checking each indicator, and making mental notes. The Bias Table does it automatically in one glance.
Table Structure:
Header Row:
On intraday charts: 1m, 5m, 15m, 30m, 1h, 2h, 4h (toggle which ones you want)
On daily+ charts: D, W, M (automatic)
Green dot next to title = live updating
Headline Rows - Macro Bias:
These show broad market direction over longer periods:
3 Day Bias: Trend over last 3 trading sessions (uses 1h data)
Weekly Bias: Trend over last 5 trading sessions (uses 4h data)
Monthly Bias: Trend over last 30 daily bars
Quarterly Bias: Trend over last 13 weekly bars
VIX Fear Index: Market regime based on VIX level - bullish when low, bearish when high
Opening Range Breakout: Status of price vs. session open range (intraday only)
These rows show text: "BULLISH", "BEARISH", or "NEUTRAL"
Indicator Rows - Technical Signals:
These evaluate your configured indicators across all active timeframes:
Fast MA > Medium MA (shows your actual MA settings, e.g., "EMA 10 > SMA 20")
Price > Long MA (e.g., "Price > SMA 200")
Price > VWAP
MACD > Signal
Supertrend (up/down/neutral)
ZLSMA Rising
RSI In Zone
ADX ≥ Minimum
These rows show emojis: GREEB (bullish), RED (bearish), GRAY/YELLOW (neutral/NA)
AVG Column:
Shows percentage of active timeframes that are bullish for that row. This is the KEY metric:
AVG > 70% = strong multi-timeframe bullish alignment
AVG 40-60% = mixed/choppy, no clear trend
AVG < 30% = strong multi-timeframe bearish alignment
How to Use the Table:
For a long trade:
Check AVG column - want to see > 60% ideally
Check headline bias rows - want to see BULLISH, not BEARISH
Check VIX row - bullish market regime preferred
Check ORB row (intraday) - want ABOVE for longs
Scan indicator rows - more green = better confirmation
For a short trade:
Check AVG column - want to see < 40% ideally
Check headline bias rows - want to see BEARISH, not BULLISH
Check VIX row - bearish market regime preferred
Check ORB row (intraday) - want BELOW for shorts
Scan indicator rows - more red = better confirmation
When AVG is 40-60%:
Market is choppy, mixed signals. Either stay out or reduce position size significantly. These are low-probability environments.
Unique Features:
Dynamic Labels: Row names show your actual settings (e.g., "EMA 10 > SMA 20" not generic "Fast > Slow"). You know exactly what's being evaluated.
Customizable Rows: Turn off rows you don't care about. Only show what matters to your strategy.
Customizable Timeframes: On intraday charts, disable 1m or 4h if you don't trade them. Reduces calculation load by 20-40%.
Automatic HTF Handling: On Daily/Weekly/Monthly charts, the table automatically switches to D/W/M columns. No configuration needed.
Performance Smart: "Hide BIAS table on 1D or above" option completely skips all table calculations on higher timeframes if you only trade intraday.
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6. CANDLESTICK PATTERN RECOGNITION
The indicator automatically detects six major reversal patterns and marks them with emojis at the relevant bars.
Why These Six Patterns:
These are the most statistically significant reversal patterns according to trading literature:
High win rate when appearing at support/resistance
Clear visual structure (not subjective)
Work across all timeframes and assets
Studied extensively by institutions
The Patterns:
Bullish Patterns (appear at bottoms):
Bullish Engulfing: Green candle completely engulfs prior red candle's body. Strong reversal signal.
Hammer: Small body with long lower wick (at least 2× body size). Shows rejection of lower prices by buyers.
Morning Star: Three-candle pattern (large red → small indecision → large green). Very strong bottom reversal.
Bearish Patterns (appear at tops):
Bearish Engulfing: Red candle completely engulfs prior green candle's body. Strong reversal signal.
Shooting Star: Small body with long upper wick (at least 2× body size). Shows rejection of higher prices by sellers.
Evening Star: Three-candle pattern (large green → small indecision → large red). Very strong top reversal.
Interactive Tooltips:
Unlike most pattern indicators that just draw shapes, this one is educational:
Hover your mouse over any pattern emoji
A tooltip appears explaining: what the pattern is, what it means, when it's most reliable, and how to trade it
No need to memorize - learn as you trade
Noise Filter:
"Min candle body % to filter noise" setting prevents false signals:
Patterns require minimum body size relative to price
Filters out tiny candles that don't represent real buying/selling pressure
Adjust based on asset volatility (higher % for crypto, lower for low-volatility stocks)
How to Trade Patterns:
Patterns are NOT standalone entry signals. Use them as:
Confirmation: UT Bot gives signal + pattern appears = stronger entry
Reversal Warning: In a trade, opposite pattern appears = consider tightening stop or taking profit
Support/Resistance Validation: Pattern at key level (PDH, VWAP, MA 200) = level is being respected
Best combined with:
UT Bot or Base signal in same direction
Bias Table alignment (AVG > 60% or < 40%)
Appearance at obvious support/resistance
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7. VISUAL TOOLS AND FEATURES
VWAP (Volume Weighted Average Price):
Session-anchored VWAP with standard deviation bands. Shows institutional "fair value" for the trading session.
Anchor Options: Session, Day, Week, Month, Quarter, Year. Choose based on your trading timeframe.
Bands: Up to three pairs (X1, X2, X3) showing statistical deviation. Price at outer bands often reverses.
Auto-Hide on HTF: VWAP hides on Daily/Weekly/Monthly charts automatically unless you enable anchored mode.
Use VWAP as:
Directional bias (above = bullish, below = bearish)
Mean reversion levels (outer bands)
Support/resistance (the VWAP line itself)
Previous Day High/Low:
Automatically plots yesterday's high and low on intraday charts:
Updates at start of each new trading day
Theme-aware colors (dark text for light charts, light text for dark charts)
Hidden automatically on Daily/Weekly/Monthly charts
These levels are critical for intraday traders - institutions watch them closely as support/resistance.
Opening Range Breakout (ORB):
Tracks the high/low of the first 5, 15, 30, or 60 minutes of the trading session:
Customizable session times (preset for NYSE, LSE, TSE, or custom)
Shows current breakout status in Bias Table row (ABOVE, BELOW, INSIDE, BUILDING)
Intraday only - auto-disabled on Daily+ charts
ORB is a classic day trading strategy - breakout above opening range often leads to continuation.
Extra Labels:
Change from Open %: Shows how far price has moved from session open (intraday) or daily open (HTF). Green if positive, red if negative.
ADX Badge: Small label at bottom of last bar showing current ADX value. Green when above your minimum threshold, red when below.
RSI Badge: Small label at top of last bar showing current RSI value with zone status (buy zone, sell zone, or neutral).
These labels provide quick at-a-glance confirmation without needing separate indicator windows.
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8. HOW TO USE THE INDICATOR
Step 1: Add to Chart
Load the indicator on your chosen asset and timeframe
First time: Everything is enabled by default - the chart will look busy
Don't panic - you'll turn off what you don't need
Step 2: Start Simple
Turn OFF everything except:
UT Bot labels (keep these ON)
Bias Table (keep this ON)
Moving Averages (Fast and Medium only)
Suggested Stop Loss and Take Profits
Hide everything else initially. Get comfortable with the basic UT Bot + Bias Table workflow first.
Step 3: Learn the Core Workflow
UT Bot gives a Buy or Sell signal
Check Bias Table AVG column - do you have multi-timeframe alignment?
If yes, enter the trade
Place stop at Suggested Stop Loss line
Scale out at TP levels
Exit on opposite UT signal
Trade this simple system for a week. Get a feel for signal frequency and win rate with your settings.
Step 4: Add Filters Gradually
If you're getting too many losing signals (whipsaws in choppy markets), add filters one at a time:
Try: "Require 2-Bar Trend Confirmation" - wait for 2 bars to confirm direction
Try: ADX filter with minimum threshold - only trade when trend strength is sufficient
Try: RSI pullback filter - only enter on pullbacks, not chasing
Try: Volume filter - require above-average volume
Add one filter, test for a week, evaluate. Repeat.
Step 5: Enable Advanced Features (Optional)
Once you're profitable with the core system, add:
Supertrend for additional trend confirmation
Candlestick patterns for reversal warnings
VWAP for institutional anchor reference
ORB for intraday breakout context
ZLSMA for low-lag trend following
Step 6: Optimize Settings
Every setting has a detailed tooltip explaining what it does and typical values. Hover over any input to read:
What the parameter controls
How it impacts trading
Suggested ranges for scalping, day trading, and swing trading
Start with defaults, then adjust based on your results and style.
Step 7: Set Up Alerts
Right-click chart → Add Alert → Condition: "Luxy Momentum v6" → Choose:
"UT Bot — Buy" for long entries
"UT Bot — Sell" for short entries
"Base Long/Short" for filtered MA cross signals
Optionally enable "Send real-time alert() on UT flip" in settings for immediate notifications.
Common Workflow Variations:
Conservative Trader:
UT signal + Base signal + Candlestick pattern + Bias AVG > 70%
Enter only at major support/resistance
Wider UT sensitivity, multiple filters
Aggressive Trader:
UT signal + Bias AVG > 60%
Enter immediately, no waiting
Tighter UT sensitivity, minimal filters
Swing Trader:
Focus on Daily/Weekly Bias alignment
Ignore intraday noise
Use ORB and PDH/PDL less (or not at all)
Wider stops, patient approach
---
9. PERFORMANCE AND OPTIMIZATION
The indicator is optimized for speed, but with 15+ features running simultaneously, chart load time can add up. Here's how to keep it fast:
Biggest Performance Gains:
Disable Unused Timeframes: In "Time Frames" settings, turn OFF any timeframe you don't actively trade. Each disabled TF saves 10-15% calculation time. If you only day trade 5m, 15m, 1h, disable 1m, 2h, 4h.
Hide Bias Table on Daily+: If you only trade intraday, enable "Hide BIAS table on 1D or above". This skips ALL table calculations on higher timeframes.
Draw UT Visuals Only on Bar Close: Reduces intrabar rendering of SL/TP/Entry lines. Has ZERO impact on logic or alerts - purely visual optimization.
Additional Optimizations:
Turn off VWAP bands if you don't use them
Disable candlestick patterns if you don't trade them
Turn off Supertrend fill if you find it distracting (keep the line)
Reduce "Limit to 10 bars" for SL/TP lines to minimize line objects
Performance Features Built-In:
Smart Caching: Higher timeframe data (3-day bias, weekly bias, etc.) updates once per day, not every bar
Conditional Calculations: Volume filter only calculates when enabled. Swing filter only runs when enabled. Nothing computes if turned off.
Modular Design: Every component is independent. Turn off what you don't need without breaking other features.
Typical Load Times:
5m chart, all features ON, 7 timeframes: ~2-3 seconds
5m chart, core features only, 3 timeframes: ~1 second
1m chart, all features: ~4-5 seconds (many bars to calculate)
If loading takes longer, you likely have too many indicators on the chart total (not just this one).
---
10. FAQ
Q: How is this different from standard UT Bot indicators?
A: Standard UT Bot (originally by @QuantNomad) is just the ATR trailing line and flip signals. This implementation adds:
- Volume weighting and momentum adjustment to the trailing calculation
- Multiple confirmation filters (swing, %, 2-bar, ZLSMA)
- Smart composite stop loss system from multiple S/R layers
- R-multiple take profit system with freeze-on-touch
- Integration with multi-timeframe Bias Table
- Visual audit trail with checkmarks
Q: Can I use this for automated trading?
A: The indicator is designed for discretionary trading. While it has clear signals and alerts, it's not a mechanical system. Context and judgment are required.
Q: Does it repaint?
A: No. All signals respect bar close. UT Bot logic runs intrabar but signals only trigger on confirmed bars. Alerts fire correctly with no lookahead.
Q: Do I need to use all the features?
A: Absolutely not. The indicator is modular. Many profitable traders use just UT Bot + Bias Table + Moving Averages. Start simple, add complexity only if needed.
Q: How do I know which settings to use?
A: Every single input has a detailed tooltip. Hover over any setting to see:
What it does
How it affects trading
Typical values for scalping, day trading, swing trading
Start with defaults, adjust gradually based on results.
Q: Can I use this on crypto 24/7 markets?
A: Yes. ORB will not work (no defined session), but everything else functions normally. Use "Day" anchor for VWAP instead of "Session".
Q: The Bias Table is blank or not showing.
A: Check:
"Show Table" is ON
Table position isn't overlapping another indicator's table (change position)
At least one row is enabled
"Hide BIAS table on 1D or above" is OFF (if on Daily+ chart)
Q: Why are candlestick patterns not appearing?
A: Patterns are relatively rare by design - they only appear at genuine reversal points. Check:
Pattern toggles are ON
"Min candle body %" isn't too high (try 0.05-0.10)
You're looking at a chart with actual reversals (not strong trending market)
Q: UT Bot is too sensitive/not sensitive enough.
A: Adjust "Sensitivity (Key×ATR)". Lower number = tighter stop, more signals. Higher number = wider stop, fewer signals. Read the tooltip for guidance.
Q: Can I get alerts for the Bias Table?
A: The Bias Table is a dashboard for visual analysis, not a signal generator. Set alerts on UT Bot or Base signals, then manually check Bias Table for confirmation.
Q: Does this work on stocks with low volume?
A: Yes, but turn OFF the volume filter. Low volume stocks will never meet relative volume requirements.
Q: How often should I check the Bias Table?
A: Before every entry. It takes 2 seconds to glance at the AVG column and headline rows. This one check can save you from fighting the trend.
Q: What if UT signal and Base signal disagree?
A: UT Bot is more aggressive (ATR trailing). Base signals are more conservative (MA cross + filters). If they disagree, either:
Wait for both to align (safest)
Take the UT signal but with smaller size (aggressive)
Skip the trade (conservative)
There's no "right" answer - depends on your risk tolerance.
---
FINAL NOTES
The indicator gives you an edge. How you use that edge determines results.
For questions, feedback, or support, comment on the indicator page or message the author.
Happy Trading!
PongExperience PONG! The classic arcade game, now on your charts!
With this indicator, you can finally achieve your lifelong dream of beating the Markets. . . at PONG!
Pong is jam-packed with features! Such as:
2 Paddles
A moving dot
Floating numbers
The idea of a net
This indicator is solely a visualization, it serves simply as an exercise to depict what is capable through PineScript. It can be used to re-skin other indicators or data, but on its own, is not intended as a market indicator.
With that out of the way...
> PONG
The Pong indicator is a recreation of the classic arcade game Pong developed to pit the markets against the cold hard logic of a CPU player.
Given the lack of interaction that is capable, the game is not played in the typical sense, by a player and computer or 2 players.
This version of Pong uses the chart price movements to control the "Market" Paddle, and it is contrasted by a (not AI) "CPU" Paddle, which is controlled by its own set of logic.
> Market Paddle
The Market Paddle is controlled by a data source which can be input by the user.
By default (Auto Mode), the Market Paddle is controlled through a fixed length Donchian channel range, pinning the range high to 100 and range low to 0. As seen below.
This can be altered to use data from different symbols or indicators, and can optionally be smoothed using multiple types of Moving Averages.
In the chart below, you can see how the RSI indicator is imported and smoothed to control the Market Paddle.
Note: The Market Paddle follows the moving average. If not desired, simply set the "Smoothing" input to "NONE".
> CPU Paddle
In simple terms, the CPU Paddle is a handicapped Aimbot.
Its logic is, more or less, "move directly towards the ball's vertical location".
If it were allowed to have full range of the screen, it would be impossible for it to lose a point. Due to this, we must slow it down to "play fair"... as fair as that may be.
The CPU Paddle is allowed to move at a rate specified by a certain Percent of its vertical width. By default, this is set to 2%.
Each update, the CPU Paddle can advance up or down 2% of its vertical width. The directional movement is determined based on the angle of the ball, and it's current position relative to the CPU Paddle's position. Given that it is not a direct follow, it may at times seem more... "human".
When a point is scored, the CPU paddle maintains its position, similar to the original Pong game, the paddles were controlled solely by the raw output of the controllers and did not reset.
> Ball
At the start of each point, the ball begins at the center of the screen and moves in a randomly determined angle at its base speed.
The direction is determined by the player who scored the last point. The loser of the last point "serves" the ball.
Given the circumstances, serving is a gigantic advantage. So the loser serving is just another place where the Market is given an advantage.
The ball's base speed is 1, it will move 1 (horizontal) bar on each update of the script. This speed can "technically" increase to infinity over time, if given the perfect rally. This is due to the hit logic as described below.
Note: The minimum ball speed is also 1.
> Bonk Math
When the ball hits a paddle, essentially 3 outcomes can occur, each resulting in the ball's direction being changed from positive to negative.
Action A: Its angle is doubled, and its speed is doubled.
Action B: Its angle is reversed, and its speed is decreased if it is going faster than base speed.
Action C: Its angle is preserved, and its speed is preserved. "Basic Bounce"
Each paddle is segmented into 3 zones, with the higher and lower tips (20%) of the paddles producing special actions.
The central 60% of each paddle produces a basic bounce. The special actions are determined by the trajectory of the ball and location on the paddle.
> Custom Mode
As stated above, the script loads in "Auto Mode" by default. While this works fine to simply watch the gameplay, the Custom Mode unlocks the ability to visualize countless possibilities of indicators and analyses playing Pong!
In the chart below, we have set up the game to use the NYSE TICK Index as our Market Player. The NYSE TICK Index shows the number of NYSE stocks trading on an uptick minus those on a downtick. Its values fluctuate throughout the day, typically ranging between +1000 and -1000.
Therefore, we have set up Pong to use Ticker USI:TICK and set the Upper Boundary to 1000 and Lower Boundary to -1000. With this method, the paddle is directly controlled by the overall (NYSE) market behaviors.
As seen in a chart earlier, you can also take advantage of the Custom Mode to overlay Pong onto traditional oscillators for use anywhere!
> Styles
This version of Pong comes stocked with 5 colorways to suit your chart vibes!
> Pro Tips & Additional Information
- This game has sound! For the full experience, set alerts for this indicator and a notification sound will play on each hit!*
*Due to server processing, the notification sounds are not precisely played at each hit. :(
- In auto mode, decreasing the length used will give an advantage to the market, as its actions become more sporadic over this window.
- The CPU logic system actually allows the market to have a "technical" edge, since the Market Paddle is not bound to any speed, and is solely controlled by the raw market movements/data input.
- This type of visualization only works on live charts, charts without updates will not see any movement.
- Indicator sources can only be imported from other indicators on the same chart.
- The base screen resolution is 159 bars wide, with the height determined by the boundaries.
- When using a symbol and an outside source, be mindful that the script is attempting to pull the source from the input symbol. Data can appear wonky when not considering the interactions of these inputs.
There are many small interesting details that can't be seen through the description. For example, the mid-line is made from a box. This is because a line object would not appear on top of the box used for the screen. For those keen eye'd coders, feel free to poke around in the source code to make the game truly custom.
Just remember:
The market may never be fair, but now at least it can play Pong!
Enjoy!
LP Sweep / Reclaim & Breakout Grading: Long-onlySignals
1) LP Sweep & Reclaim (mean-reversion entry)
Compute LP bounds from prior-bar window extremes:
lpLL_prev = lowest low of the last N bars (offset 1).
lpHH_prev = highest high of the last N bars (offset 1).
Sweep long trigger: current low dips below lpLL_prev and closes back above it.
Real-time quality grading (A/B/C) for sweep:
Trend filter & slope via EMA(88).
BOS bonus: close > last confirmed swing high.
Body size vs ATR, location above a long EMA, headroom to swing high (penalty if too close), and multi-sweep count bonus.
Sum → score → grade A/B/C; A or B required for sweep entry.
2) Trend Breakout (momentum entry)
Core trigger: close > previous Donchian high (length boLen) + ATR buffer.
Optional filter: close must be above the default EMA.
Breakout grading (A/B/C) in real time combining:
Trend up (price > EMA and EMA rising),
Body/ATR, Gap above breakout level (in ATR),
Volume vs MA,
Upper-wick penalty,
Position-in-Score: headroom to last swing high (penalty if too near) + EMA slope bonus.
Sum → score → A or B required if grading enabled.
Multi-Band Trend LineThis Pine Script creates a versatile technical indicator called "Multi-Band Trend Line" that builds upon the concept of the popular "Follow Line Indicator" by Dreadblitz. While the original Follow Line Indicator uses simple trend detection to place a line at High or Low levels, this enhanced version combines multiple band-based trading strategies with dynamic trend line generation. The indicator supports five different band types and provides more sophisticated buy/sell signals based on price breakouts from various technical analysis bands.
Key Features
Multi-Band Support
The indicator supports five different band types:
- Bollinger Bands: Uses standard deviation to create bands around a moving average
- Keltner Channels: Uses ATR (Average True Range) to create bands around a moving average
- Donchian Channels: Uses the highest high and lowest low over a specified period
- Moving Average Envelopes: Creates bands as a percentage above and below a moving average
- ATR Bands: Uses ATR multiplier to create bands around a moving average
Dynamic Trend Line Generation (Enhanced Follow Line Concept)
- Similar to the Follow Line Indicator, the trend line is placed at High or Low levels based on trend direction
- Key Enhancement: Instead of simple trend detection, this version uses band breakouts to trigger trend changes
- When price breaks above the upper band (bullish signal), the trend line is set to the low (optionally adjusted with ATR) - similar to Follow Line's low placement
- When price breaks below the lower band (bearish signal), the trend line is set to the high (optionally adjusted with ATR) - similar to Follow Line's high placement
- The trend line acts as dynamic support/resistance, following the price action more precisely than the original Follow Line
ATR Filter (Follow Line Enhancement)
- Like the original Follow Line Indicator, an ATR filter can be selected to place the line at a more distance level than the normal mode settled at candles Highs/Lows
- When enabled, it adds/subtracts ATR value to provide more conservative trend line placement
- Helps reduce false signals in volatile markets
- This feature maintains the core philosophy of the Follow Line while adding more precision through band-based triggers
Signal Generation
- Buy Signal: Generated when trend changes from bearish to bullish (trend line starts rising)
- Sell Signal: Generated when trend changes from bullish to bearish (trend line starts falling)
- Signals are displayed as labels on the chart
Visual Elements
- Upper and lower bands are plotted in gray
- Trend line changes color based on direction (green for bullish, red for bearish)
- Background color changes based on trend direction
- Buy/sell signals are marked with labeled shapes
How It Works
Band Calculation: Based on the selected band type, upper and lower boundaries are calculated
Signal Detection: When price closes above the upper band or below the lower band, a breakout signal is generated
Trend Line Update: The trend line is updated based on the breakout direction and previous trend line value
Trend Direction: Determined by comparing current trend line with the previous value
Alert Generation: Buy/sell conditions trigger alerts and visual signals
Use Cases
Enhanced trend following strategies: More precise than basic Follow Line due to band-based triggers
Breakout trading: Multiple band types provide various breakout opportunities
Dynamic support/resistance identification: Combines Follow Line concept with band analysis
Multi-timeframe analysis with different band types: Choose the most suitable band for your timeframe
Reduced false signals: Band confirmation provides better entry/exit points compared to simple trend following
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain?
This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions.
How does a Markov Chain work, and how should I read this spheres-and-arrows diagram?
Think of three weather modes: Sunny, Rainy, Cloudy.
Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow).
The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy).
Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step.
Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny.
Now relabel the spheres to markets: Bull, Bear, Neutral.
Spheres: market regimes (uptrend, downtrend, range).
Self‑loop: tendency for the current regime to continue on the next bar.
Arrows: the most common next regime if a switch happens.
How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear).
What states and transitions are shown?
The three market states visualized are:
Bullish (Bull): Upward or strong-market regime.
Bearish (Bear): Downward or weak-market regime.
Neutral: Sideways or range-bound regime.
Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull).
How does the regime detection system work?
You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.).
Values are statistically normalized (Z-scored) over a configurable lookback period.
The normalized outputs are classified into Bull, Bear, or Neutral zones.
If using three indicators, their regime signals are averaged and smoothed for robustness.
How are transition probabilities calculated?
On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions.
The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear).
Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time.
What is unique about the visualization?
3D animated spheres represent each regime and change visually when active.
Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows.
Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed.
All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format.
Can I use custom indicators for regime classification?
Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement.
What does the “Lookback Period” control?
Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt.
How is this different from a Hidden Markov Model (HMM)?
It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust.
How is this Markov Chain different from a Hidden Markov Model (HMM)?
Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable.
Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training.
A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data.
Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune.
HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data.
How does the indicator avoid “repainting” or look-ahead bias?
All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation.
Are there practical tuning tips?
Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability.
Use custom indicators if your asset has unique regime drivers.
Watch for rapid changes in transition probabilities as early warning of a possible regime shift.
Who is this indicator for?
Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models.
Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting:
The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear).
Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions.
Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies.
It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes.
The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting.
Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis.
What's the mathematical foundation behind this?
The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM).
How to use this indicator programmatically?
The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading.
Step-by-Step Integration with Pine Script (input.source)
Add the Markov Chain indicator to your chart.
This must be done first, since your custom script will "pull" the bias signal from the indicator's plot.
In your strategy, create an input using input.source()
Example:
//@version=5
strategy("MC Bias Strategy Example")
mcBias = input.source(close, "MC Bias Source")
After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot).
Use the bias in your trading logic
Example (long only on Bull, flat otherwise):
if mcBias == 1
strategy.entry("Long", strategy.long)
else
strategy.close("Long")
For more advanced workflows, combine mcBias with additional filters or trailing stops.
How does this work behind-the-scenes?
TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source).
The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.).
This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code.
Integrating 45+ Indicators with Your Markov Chain — How & Why
The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots.
// Enhanced Custom Indicators Export - 45 Technical Indicators
// Comprehensive technical analysis suite for advanced market regime detection
//@version=6
indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500)
// |----- Input Parameters -----| //
momentum_group = "Momentum Indicators"
trend_group = "Trend Indicators"
volume_group = "Volume Indicators"
volatility_group = "Volatility Indicators"
oscillator_group = "Oscillator Indicators"
display_group = "Display Settings"
// Common lengths
length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group)
length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group)
length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group)
// Display options
show_table = input.bool(true, "Show Values Table", group=display_group)
table_size = input.string("Small", "Table Size", options= , group=display_group)
// |----- MOMENTUM INDICATORS (15 indicators) -----| //
// 1. RSI (Relative Strength Index)
rsi_14 = ta.rsi(close, length_14)
rsi_centered = rsi_14 - 50
// 2. Stochastic Oscillator
stoch_k = ta.stoch(close, high, low, length_14)
stoch_d = ta.sma(stoch_k, 3)
stoch_centered = stoch_k - 50
// 3. Williams %R
williams_r = ta.stoch(close, high, low, length_14) - 100
// 4. MACD (Moving Average Convergence Divergence)
= ta.macd(close, 12, 26, 9)
// 5. Momentum (Rate of Change)
momentum = ta.mom(close, length_14)
momentum_pct = (momentum / close ) * 100
// 6. Rate of Change (ROC)
roc = ta.roc(close, length_14)
// 7. Commodity Channel Index (CCI)
cci = ta.cci(close, length_20)
// 8. Money Flow Index (MFI)
mfi = ta.mfi(close, length_14)
mfi_centered = mfi - 50
// 9. Awesome Oscillator (AO)
ao = ta.sma(hl2, 5) - ta.sma(hl2, 34)
// 10. Accelerator Oscillator (AC)
ac = ao - ta.sma(ao, 5)
// 11. Chande Momentum Oscillator (CMO)
cmo = ta.cmo(close, length_14)
// 12. Detrended Price Oscillator (DPO)
dpo = close - ta.sma(close, length_20)
// 13. Price Oscillator (PPO)
ppo = ta.sma(close, 12) - ta.sma(close, 26)
ppo_pct = (ppo / ta.sma(close, 26)) * 100
// 14. TRIX
trix_ema1 = ta.ema(close, length_14)
trix_ema2 = ta.ema(trix_ema1, length_14)
trix_ema3 = ta.ema(trix_ema2, length_14)
trix = ta.roc(trix_ema3, 1) * 10000
// 15. Klinger Oscillator
klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55)
// 16. Fisher Transform
fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25
fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2))
// 17. Stochastic RSI
stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14)
stoch_rsi_centered = stoch_rsi - 50
// 18. Relative Vigor Index (RVI)
rvi_num = ta.swma(close - open)
rvi_den = ta.swma(high - low)
rvi = rvi_den != 0 ? rvi_num / rvi_den : 0
// 19. Balance of Power (BOP)
bop = (close - open) / (high - low)
// |----- TREND INDICATORS (10 indicators) -----| //
// 20. Simple Moving Average Momentum
sma_20 = ta.sma(close, length_20)
sma_momentum = ((close - sma_20) / sma_20) * 100
// 21. Exponential Moving Average Momentum
ema_20 = ta.ema(close, length_20)
ema_momentum = ((close - ema_20) / ema_20) * 100
// 22. Parabolic SAR
sar = ta.sar(0.02, 0.02, 0.2)
sar_trend = close > sar ? 1 : -1
// 23. Linear Regression Slope
lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1)
// 24. Moving Average Convergence (MAC)
mac = ta.sma(close, 10) - ta.sma(close, 30)
// 25. Trend Intensity Index (TII)
tii_sum = 0.0
for i = 1 to length_20
tii_sum += close > close ? 1 : 0
tii = (tii_sum / length_20) * 100
// 26. Ichimoku Cloud Components
ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2
ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2
ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1
// 27. MESA Adaptive Moving Average (MAMA)
mama_alpha = 2.0 / (length_20 + 1)
mama = ta.ema(close, length_20)
mama_momentum = ((close - mama) / mama) * 100
// 28. Zero Lag Exponential Moving Average (ZLEMA)
zlema_lag = math.round((length_20 - 1) / 2)
zlema_data = close + (close - close )
zlema = ta.ema(zlema_data, length_20)
zlema_momentum = ((close - zlema) / zlema) * 100
// |----- VOLUME INDICATORS (6 indicators) -----| //
// 29. On-Balance Volume (OBV)
obv = ta.obv
// 30. Volume Rate of Change (VROC)
vroc = ta.roc(volume, length_14)
// 31. Price Volume Trend (PVT)
pvt = ta.pvt
// 32. Negative Volume Index (NVI)
nvi = 0.0
nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi
// 33. Positive Volume Index (PVI)
pvi = 0.0
pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi
// 34. Volume Oscillator
vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10)
// 35. Ease of Movement (EOM)
eom_distance = high - low
eom_box_height = volume / 1000000
eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0
eom_sma = ta.sma(eom, length_14)
// 36. Force Index
force_index = volume * (close - close )
force_index_sma = ta.sma(force_index, length_14)
// |----- VOLATILITY INDICATORS (10 indicators) -----| //
// 37. Average True Range (ATR)
atr = ta.atr(length_14)
atr_pct = (atr / close) * 100
// 38. Bollinger Bands Position
bb_basis = ta.sma(close, length_20)
bb_dev = 2.0 * ta.stdev(close, length_20)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0
bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0
// 39. Keltner Channels Position
kc_basis = ta.ema(close, length_20)
kc_range = ta.ema(ta.tr, length_20)
kc_upper = kc_basis + (2.0 * kc_range)
kc_lower = kc_basis - (2.0 * kc_range)
kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0
// 40. Donchian Channels Position
dc_upper = ta.highest(high, length_20)
dc_lower = ta.lowest(low, length_20)
dc_basis = (dc_upper + dc_lower) / 2
dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0
// 41. Standard Deviation
std_dev = ta.stdev(close, length_20)
std_dev_pct = (std_dev / close) * 100
// 42. Relative Volatility Index (RVI)
rvi_up = ta.stdev(close > close ? close : 0, length_14)
rvi_down = ta.stdev(close < close ? close : 0, length_14)
rvi_total = rvi_up + rvi_down
rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50
// 43. Historical Volatility
hv_returns = math.log(close / close )
hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100
// 44. Garman-Klass Volatility
gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open)
gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100
// 45. Parkinson Volatility
park_vol = math.log(high/low) * math.log(high/low)
parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100
// 46. Rogers-Satchell Volatility
rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open)
rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100
// |----- OSCILLATOR INDICATORS (5 indicators) -----| //
// 47. Elder Ray Index
elder_bull = high - ta.ema(close, 13)
elder_bear = low - ta.ema(close, 13)
elder_power = elder_bull + elder_bear
// 48. Schaff Trend Cycle (STC)
stc_macd = ta.ema(close, 23) - ta.ema(close, 50)
stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10)
stc_d = ta.ema(stc_k, 3)
stc = ta.stoch(stc_d, stc_d, stc_d, 10)
// 49. Coppock Curve
coppock_roc1 = ta.roc(close, 14)
coppock_roc2 = ta.roc(close, 11)
coppock = ta.wma(coppock_roc1 + coppock_roc2, 10)
// 50. Know Sure Thing (KST)
kst_roc1 = ta.roc(close, 10)
kst_roc2 = ta.roc(close, 15)
kst_roc3 = ta.roc(close, 20)
kst_roc4 = ta.roc(close, 30)
kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15)
// 51. Percentage Price Oscillator (PPO)
ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100
ppo_signal = ta.ema(ppo_line, 9)
ppo_histogram = ppo_line - ppo_signal
// |----- PLOT MAIN INDICATORS -----| //
// Plot key momentum indicators
plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1)
plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1)
plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1)
plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1)
plot(cci, title="05_CCI", color=color.green, linewidth=1)
// Plot trend indicators
plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1)
plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1)
plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1)
plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1)
plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1)
// Plot volatility indicators
plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1)
plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1)
plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1)
plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1)
plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1)
// Plot volume indicators
plot(vroc, title="16_VROC", color=color.blue, linewidth=1)
plot(eom_sma, title="17_EOM", color=color.red, linewidth=1)
plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1)
plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1)
plot(obv, title="20_OBV", color=color.purple, linewidth=1)
// Plot additional oscillators
plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1)
plot(cmo, title="22_CMO", color=color.maroon, linewidth=1)
plot(dpo, title="23_DPO", color=color.teal, linewidth=1)
plot(trix, title="24_TRIX", color=color.lime, linewidth=1)
plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1)
// Plot more momentum indicators
plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1)
plot(ac, title="27_AC", color=color.aqua, linewidth=1)
plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1)
plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1)
plot(klinger, title="30_Klinger", color=color.gray, linewidth=1)
// Plot trend continuation
plot(tii, title="31_TII", color=color.blue, linewidth=1)
plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1)
plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1)
plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1)
plot(bop, title="35_BOP", color=color.purple, linewidth=1)
// Plot volume continuation
plot(nvi, title="36_NVI", color=color.navy, linewidth=1)
plot(pvi, title="37_PVI", color=color.maroon, linewidth=1)
plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1)
plot(roc, title="39_ROC", color=color.lime, linewidth=1)
plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1)
// Plot volatility continuation
plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1)
plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1)
plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1)
plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1)
plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1)
// Plot final oscillators
plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1)
plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1)
plot(stc, title="48_STC", color=color.green, linewidth=1)
plot(coppock, title="49_Coppock", color=color.orange, linewidth=1)
plot(kst, title="50_KST", color=color.purple, linewidth=1)
// Plot final indicators
plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1)
plot(pvt, title="52_PVT", color=color.maroon, linewidth=1)
// |----- Reference Lines -----| //
hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1)
hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
// |----- Enhanced Information Table -----| //
if show_table and barstate.islast
table_position = position.top_right
table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal
var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray)
// Headers
table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
// Key Momentum Indicators
table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size)
table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size)
// Key Trend Indicators
table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90))
table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size)
// Key Volatility Indicators
table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90))
table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size)
// Key Volume Indicators
table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90))
table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size)
// Key Oscillators
table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size)
// Summary Statistics
table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70))
table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size)
regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray
regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL"
table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size)
This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator.
How to use this script with the Markov Chain for research and backtesting:
Add the Enhanced Indicator Export to your chart.
Every calculated indicator is available as an individual data stream.
Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option.
In the Markov Chain indicator’s settings, turn ON the custom indicator mode.
For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name.
This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering.
Backtest regime logic directly.
Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns.
The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration.
Export the regime bias for programmatic use.
As described above, use input.source() in your Pine Script strategy or system and link the bias output.
You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes.
With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you.
Optimize your signal generation by backtesting across a universe of meaningful indicator blends.
Enhance risk management with objective, real-time regime boundaries.
Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes.
Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic.
Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem.
References & Further Reading
Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182.
Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384.
Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg.
Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764.
Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC.
On Quantitative Finance and Markov Models:
Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press.
Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press.
TradingView Pine Script Documentation: www.tradingview.com
TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com
GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org
What makes this indicator original and unique?
- On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm.
- Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script.
- Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time.
- Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window.
- Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior.
Integrate your own signals (using input.source())
- In settings, choose the Source . This is powered by input.source() .
- Feed it price, an indicator you compute inside the script, or a custom composite series.
- The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time.
Credits:
Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community.
Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization.
Disclaimer
This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
Breakout TrendTiltFolio Breakout Trend indicator
The Breakout Trend indicator is designed to help traders clearly visualize trend direction by combining two complementary techniques: moving averages and Donchian-style breakout logic.
Rather than relying on just one type of signal, this indicator merges short-term and long-term moving averages with breakout levels based on recent highs and lows. The moving averages define the broader trend regime, while the breakout logic pinpoints moments when price confirms directional momentum. This layered approach filters out many false signals while still capturing high-conviction moves.
Yes, these are lagging indicators by design — and that’s the point. Instead of predicting every wiggle, the Breakout Trend waits for confirmation, offering higher signal quality and fewer whipsaws. When the price breaks above a recent high and sits above the long-term moving average, the trend is more likely to persist. That’s when this indicator shines.
While it performs best on higher timeframes (daily/weekly), it's also adaptable to shorter timeframes for intraday traders who value clean, systematic trend signals.
For early signal detection, we recommend pairing this with TiltFolio’s Buying/Selling Proxy, which anticipates pressure buildups—albeit with more noise.
It's easy to read and built for real-world trading discipline.
True Range eXpansion🕯️ TRX — True Range eXpansion
Clean Candle Bodies · Volatility Bands · Adaptive Range Envelope System
Not your grandfather’s candles. Not your brokerage’s bands.
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TRX begins with a simple concept: visualize the true range of every candle, without the noise of flickering wicks.
From there, it grows into a fully adaptive price visualization framework.
What started as a candle-only visualizer evolved into a modular, user-controlled price engine.
From wickless candle clarity to dynamic volatility envelopes, TRX adapts to you.
There are plenty of band and channel indicators out there — Bollinger, Keltner, Donchian, Envelope, the whole crew.
But none of them are built on the true candle range, adaptive ATR shaping, and full user control like TRX.
This isn’t just another indicator — it’s a new framework.
Most bands and channels are based on close price and statistical deviation — useful, but limited.
TRX uses the full true range of each candle as its foundation, then applies customizable smoothing and directional ATR scaling to form a dynamic, volatility-reactive envelope.
The result? Bands that breathe with the market — not lag behind it.
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🔧 Core Features:
🕯️ True Range Candles — Each candle is plotted from low to high, body-only, colored by open/close.
📈 Adjustable High/Low Moving Averages — Select your smoothing style: SMA, EMA, WMA, RMA, or HMA.
🌬️ ATR-Based Expansion — Bands dynamically breathe based on market volatility.
🔀 Per-Band Multipliers — Fine-tune expansion individually for the upper and lower bands.
⚖️ Basis Line — Optional centerline between bands for structure tracking and equilibrium zones.
🎛️ Full Visual Control — Width, transparency, color, on/off toggles for each element.
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🧠 Default Use Case:
With the included default settings, TRX behaves like an evolved Bollinger Band system — based on True Range candle structure, not just close price and standard deviation.
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🔄 How to Zero Out the Bands (for Minimalist Use):
Want just candles? A clean MA? Single band? You got it.
➤ Use TRX like a clean moving average:
• Set ATR Multiplier to 0
• Set both Band ATR Adjustments to 0
• Leave the Basis Line ON or OFF — your call
➤ Show only candles (no bands at all):
• Turn off "Show High/Low MAs"
• Turn off Basis Line
➤ Single-line ceiling or floor tracking:
• Set one band’s Transparency to 100
• Use the remaining band as a price envelope or support/resistance guide
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🧬 Notes:
TRX can be made:
• Spiky or silky (via smoothing & ATR)
• Wide or tight (via multipliers)
• Subtle or aggressive (via color/transparency)
• Clean as a compass or dirty as a chaos meter
Built by accident. Tuned with intention.
Released to the world as one of the most adaptable and expressive visual overlays ever made.
Created by Sherlock_MacGyver
My S.T.A.C.K.📊 My S.T.A.C.K. (Simplified TA Combined Kit)
All your favorite technical tools in one clean, customizable overlay.
My S.T.A.C.K. is a power-packed indicator designed to streamline your chart by combining the most commonly used technical analysis tools into a single, space-saving script. Whether you're a trend trader, swing trader, or just looking to declutter your view — this kit gives you everything you need, nothing you don’t.
🔧 Features:
5 Customizable Moving Averages: Choose your type (SMA, EMA, WMA, etc.) and periods to match your strategy.
Bollinger Bands: Visualize volatility and overbought/oversold zones with precision.
Donchian Channels: Spot breakouts and trend reversals based on high/low ranges.
ATR Bands: Adaptive support/resistance zones based on Average True Range.
Clean Visualization: Toggle each element on or off, adjust colors, and focus only on what matters.
✅ Ideal For:
- Traders who want multiple indicators in one place
- Reducing indicator clutter on TradingView
- Quick visual analysis without switching scripts
[blackcat] L3 Ichimoku FusionCOMPREHENSIVE ANALYSIS OF THE L3 ICHIMOKU FUSION INDICATOR
🌐 Overview:
The L3 Ichimoku Fusion is a sophisticated multi-layered technical analysis tool integrating classic Japanese market forecasting techniques with enhanced dynamic elements designed specifically for identifying potential turning points in financial instruments' pricing action.
Key Purpose:
To provide traders with an intuitive yet powerful framework combining established ichimoku principles while incorporating additional validation checkpoints derived from cross-timeframe convergence studies.
THEORETICAL FOUNDATION EXPLAINED
🎓 Conceptual Background:
:
• Conversion & Base Lines tracking intermediate term averages
• Lagging Span providing delayed feedback mechanism
• Lead Spans projecting future equilibrium states
:
• Adaptive parameter scaling options
• Automated labeling system for critical junctures
• Real-time alert infrastructure enabling immediate response capability
PARAMETER CONFIGURATION GUIDE
⚙️ Input Parameters Explained In Detail:
Regional Setting Selection:**
→ Oriental Configuration: Standardized approach emphasizing slower oscillation cycles
→ Occidental Variation: Optimized settings reducing lag characteristics typical of original methodology
Multiplier Adjustment Functionality:**
↔ Allows fine-graining oscillator responsiveness without altering core relationship dynamics
↕ Enables adaptation to various instrument volatility profiles efficiently
Displacement Value Control:**
↓ Controls lead/lag offset positioning relative to current prices
↑ Provides flexibility in adjusting visual representation alignment preferences
DYNAMIC CALCULATION PROCESSES
💻 Algorithmic Foundation:
:
Utilizes highest/lowest extremes over specified lookback windows
Produces more responsive conversions compared to simple MAs
:
→ Confirms directional bias across multiple independent criteria
← Ensures higher probability outcomes reduce random noise influence
:
♾ Creates persistent annotations documenting significant events
🔄 Handles complex state transitions maintaining historical record integrity
VISUALIZATION COMPONENTS OVERVIEW
🎨 Display Architecture Details:
:
→ Solid colored trendlines representing conversion/base relationships
↑ Fill effect overlay differentiating expansion/compression phases
↔ Offset spans positioned according to calculated displacement values
:
→ Green shading indicates positive configuration scenarios
↘ Red filling highlights negative arrangement situations
⟳ Orange transition areas mark transitional periods requiring caution
:
✔️ LE: Long Entry opportunity confirmed
❌ SE: Short Setup validated
☑ XL/XS: Position closure triggers active
✓ RL/RS: Potential re-entry chances emerging
STRATEGIC APPLICATION FRAMEWORK
📋 Practical Deployment Guidelines:
Initial Integration Phase:
Select appropriate timeframe matching trading horizon preference
Configure input parameters aligning with target asset behavior traits
Test thoroughly under simulated conditions prior to live usage
Active Monitoring Procedures:
• Regular observation of cloud formation evolution
• Tracking label placements against actual price movements
• Noting pattern development leading up to signaled entry/exit moments
Decision Making Process Flowchart:
→ Identify clear breakout/crossover events exceeding confirmation thresholds
← Evaluate contextual factors supporting/rejecting indicated direction
↑ Execute trades only after achieving required number of confirming inputs
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Refinement Strategies:
Calibration Optimization Approach:
→ Start testing with default suggested configurations
↓ Gradually adjust individual components observing outcome changes
↑ Document findings systematically building personalized version profile
Context Adaptability Methods:
➕ Add supplementary indicators enhancing overall reliability
➖ Remove unnecessary complexity layers if causing confusion
✨ Incorporate custom rules adapting to specific security behaviors
Efficiency Improvement Tactics:
🔧 Streamline redundant processing routines where possible
♻️ Leverage shared data streams whenever feasible
⚡ Optimize refresh frequencies balancing update speed vs computational load
RISK MITIGATION PROTOCOLS
🛡️ Safety Measures Implementation Guide:
Position Sizing Principles:
∅ Never exceed preset maximum exposure limits defined by risk tolerance
± Scale positions proportionally per account size/market capitalization
× Include slippage allowances within planning stages accounting for liquidity variations
Validation Requirements Hierarchy:
☐ Verify signals meet minimum number of concurrent validations
⛔ Ignore isolated occurrences lacking adequate evidence backing
▶ Look for convergent evidence strengthening conviction level
Emergency Response Planning:
↩ Establish predefined exit strategies including trailing stops mechanisms
🌀 Plan worst-case scenario responses ahead avoiding panic reactions
⇄ Maintain contingency plans addressing unexpected adverse developments
USER EXPERIENCE ENHANCEMENT FEATURES
🌟 Additional Utility Functions:
Alert System Infrastructure:
→ Automatic notifications delivered directly to user devices
↑ Message content customized explaining triggered condition specifics
↔ Timing optimization ensuring minimal missed opportunities due to latency issues
Historical Review Capability:
→ Ability to analyze past performance retrospectively
↓ Assess effectiveness across varying market regimes objectively
↗ Generate statistics measuring success/failure rates quantitatively
Community Collaboration Support:
↪ Share personal optimizations benefiting wider trader community
↔ Exchange experiences improving collective understanding base
✍️ Provide constructive feedback aiding ongoing refinement process
CONCLUSION AND NEXT STEPS
This comprehensive guide serves as your roadmap toward mastering the capabilities offered by the L3 Ichimoku Fusion indicator effectively. Success relies heavily on disciplined application combined with continuous learning and adjustment processes throughout implementation journey.
Wishing you prosperous trading endeavors! 👋💰
Ichimoku Cloud +Ichimoku Cloud Plus - Advanced Technical Analysis Indicator
Ichimoku Cloud Plus is an advanced technical analysis tool that combines the traditional Ichimoku Cloud system with Pearson correlation analysis and multi-timeframe momentum tracking. This innovative approach provides traders with a comprehensive view of market trends, momentum, and potential reversal points across multiple time frames.
Core Components
Enhanced Ichimoku Cloud Analysis
The traditional Ichimoku Cloud components have been preserved and enhanced with customizable visual parameters:
The indicator includes:
- Conversion Line (Tenkan-sen) - Short-term trend identifier
- Base Line (Kijun-sen) - Medium-term trend identifier
- Leading Span A and B (Senkou Span A and B) - Future cloud projections
- Lagging Span (Chikou Span) - Historical price momentum confirmation
The cloud (Kumo) formations provide dynamic support and resistance levels, with color-coding to instantly identify bullish and bearish market conditions.
Pearson Correlation Analysis
A sophisticated Pearson correlation coefficient calculation has been integrated to provide statistical validation of trend strength and direction. This component:
- Calculates correlation between price movement and time
- Provides real-time correlation coefficients
- Identifies trend strength through correlation thresholds
- Generates signals for trend changes and potential reversals
Multi-Timeframe Momentum Tracking
The indicator incorporates a unique multi-timeframe analysis system that:
- Displays momentum calculations across five timeframes (15m, 30m, 1h, 4h, 1d)
- Provides percentage-based momentum values
- Includes volatility adjustment capabilities
- Offers volume-weighted calculations for enhanced accuracy
Advanced Features
Statistical Analysis Panel
A comprehensive statistical panel provides real-time analysis including:
- Current Pearson coefficient value
- Correlation strength classification
- Trend direction identification
- Analysis period information
Dynamic Alert System
The indicator includes sophisticated alert conditions for:
- Bearish trend initiation (positive correlation threshold breach)
- Bullish trend initiation (negative correlation threshold breach)
- Trend direction changes (zero-line crossovers)
Visual Optimization
Advanced visualization features include:
- Customizable color schemes for all components
- Adjustable label sizes and positions
- Transparency controls for better chart visibility
- Warning indicators for potential trend weakening
Technical Implementation
The indicator combines multiple calculation methods:
- Donchian Channel calculations for Ichimoku components
- Pearson correlation coefficient computation with customizable periods
- EMA smoothing for momentum calculations
- Volume-weighted averaging capabilities
- Volatility adjustment mechanisms
Trading Applications
This indicator is particularly effective for:
1. Trend Direction Confirmation
- Multiple timeframe analysis provides comprehensive trend validation
- Pearson correlation adds statistical confidence to trend identification
- Ichimoku cloud formations confirm support and resistance levels
2. Entry and Exit Point Identification
- Cloud breakouts combined with correlation strength indicate potential entry points
- Multi-timeframe momentum alignment helps identify high-probability trades
- Warning indicators assist in timing market exits
3. Risk Management
- Dynamic support and resistance levels from the cloud
- Statistical trend strength measurement
- Multi-timeframe confirmation reduces false signals
Performance Considerations
The indicator uses efficient calculations to maintain good performance while providing comprehensive analysis. The smoothing parameters and analysis periods can be adjusted to balance between responsiveness and reliability.
Future Applications and Research
This combination of indicators opens possibilities for:
- Machine learning integration for pattern recognition
- Additional statistical measures for trend validation
- Enhanced alert systems based on multiple condition combinations
- Further optimization of calculation methods
The innovative combination of traditional Ichimoku analysis with modern statistical methods and multi-timeframe momentum tracking provides traders with a powerful tool for market analysis and decision-making.
*2.2 Aggregated (Raw Z-scores with MA)***To be used with other 2.2 indicator***
Key Indicators Used:
Oscillating Indicators: RSI, TSI, Stochastic, MACD, CCI, Vortex Indicator, Williams %R.
Perpetual Trend Indicators: EMA, ADX, Parabolic SAR, Supertrend, Donchian Channel, Ichimoku Cloud, RVGI.
How to Use the Indicator:
Raw Z-Score (Blue Line): This represents the real-time aggregated Z-score of all the indicators. It shows how far the current market conditions are from their average, helping you identify trends.
Moving Average of Z-Score (Orange Line): A smoothed version of the Z-score that helps confirm trends and eliminate noise.
Shaded Area: The area between the Z-score and its moving average is shaded green if the Z-score is above the moving average (bullish), and red if below the moving average (bearish).
Zero Line (Gray Line): Serves as a reference point. A Z-score crossing above zero could signal a bullish market, while crossing below zero could indicate bearish conditions.
This indicator helps in identifying market extremes and trend reversals by combining various technical indicators into a single aggregate score, ideal for spotting overbought or oversold conditions and possible trend shifts
Oscillator Scatterplot Analysis [Trendoscope®]In this indicator, we demonstrate how to plot oscillator behavior of oversold-overbought against price movements in the form of scatterplots and perform analysis. Scatterplots are drawn on a graph containing x and y-axis, where x represent one measure whereas y represents another. We use the library Graph to collect the data and plot it as scatterplot.
Pictorial explanation of components is defined in the chart below.
🎲 This indicator performs following tasks
Calculate and plot oscillator
Identify oversold and overbought areas based on various methods
Measure the price and bar movement from overbought to oversold and vice versa and plot them on the chart.
In our example,
The x-axis represents price movement. The plots found on the right side of the graph has positive price movements, whereas the plots found on the left side of the graph has negative price movements.
The y-axis represents the number of bars it took for reaching overbought to oversold and/or oversold to overbought. Positive bars mean we are measuring oversold to overbought, whereas negative bars are a measure of overbought to oversold.
🎲 Graph is divided into 4 equal quadrants
Quadrant 1 is the top right portion of the graph. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from oversold to overbought
Quadrant 2 is the top left portion of the graph. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from oversold to overbought.
Quadrant 3 is the bottom left portion of the chart. Plots in this quadrant represent the instances where negative price movement is observed when the oscillator moved from overbought to oversold.
Quadrant 4 is the bottom right portion of the chart. Plots in this quadrant represent the instances where positive price movement is observed when the oscillator moved from overbought to oversold.
🎲 Indicator components in Detail
Let's dive deep into the indicator.
🎯 Oscillator Selection
Select the Oscillator and define the overbought oversold conditions through input settings
Indicator - Oscillator base used for performing analysis
Length - Loopback length on which the oscillator is calculated
OB/OS Method - We use Bollinger Bands, Keltener Channel and Donchian channel to calculate dynamic overbought and oversold levels instead of static 80-10. This is also useful as other type of indicators may not be within 0-100 range.
Length and Multiplier are used for the bands for calculating Overbought/Oversold boundaries.
🎯 Define Graph Properties
Select different graph properties from the input settings that will instruct how to display the scatterplot.
Type - this can be either scatterplot or heatmap. Scatterplot will display plots with specific transparency to indicate the data, whereas heatmap will display background with different transparencies.
Plot Color - this is the color in which the scatterplot or heatmap is drawn
Plot Size - applicable mainly for scatterplot. Since the character we use for scatterplot is very tiny, the large at present looks optimal. But, based on the user's screen size, we may need to select different sizes so that it will render properly.
Rows and Columns - Number of rows and columns allocated per quadrant. This means, the total size of the chart is 2X rows and 2X columns. Data sets are divided into buckets based on the number of available rows and columns. Hence, changing this can change the appearance of the overall chart, even though they are representing the same data. Also, please note that tables can have max 10000 cells. If we increase the rows and columns by too much, we may get runtime errors.
Outliers - this is used to exclude the extreme data. 20% outlier means, the chart will ignore bottom 20% and top 20% when defining the chart boundaries. However, the extreme data is still added to the boundaries.
Moving Average Exponential-DonCHI-SUPERTRENDThe "Moving Average Exponential-DonCHI-SUPERTREND" is a trading strategy or indicator that combines three distinct technical analysis tools:
Moving Average Exponential (EMA): This is a type of moving average that gives more weight to recent prices, making it more responsive to price changes compared to a simple moving average.
Donchian Channels (DonCHI): These are bands that are plotted above and below the recent price highs and lows. They help identify the current price volatility and potential breakout points.
SUPERTREND: This is a trend-following indicator that uses the average true range (ATR) to determine the direction of the trend. It provides signals similar to moving averages but with less lag.
Custom Signal Oscillator StrategyThe CSO is made to help traders easily test their theories by subtracting the difference between two customizable plots(indicators) without having to search for strategies. The general purpose is to provide a tool to users without coding knowledge.
How to use :
Apply the indicator(s) to test
Go to the CSO strategy input settings and select the desired plots from the added indicators. (The back test will enter long or short depending on the fast signal crosses on the slow signal)
Pull up the strategy tester
Adjust the input settings on the selected indicator(s) to back test
For example, the published strategy is using the basis lines from two Donchian channels with varying length. This can be utilized with multiple overlays on the chart and oscillators that are operating on the same scale with each other. Since chart glows aren't extremely common, a glow option is included to stand out on the chart as the chain operator. A long only option for is also included for versatility.
Candle Strength Oscillator by SyntaxGeekThis candle strength oscillator displays a smoothed rolling difference between the body range (close and open) and total candle range (high and low).
When candles have small bodies, such as a doji, it can indicate weakness, when candles have essentially little to no wicks it can indicate strength.
There are two modes of display for the strength trend to show potential exhaustion on either side, bollinger bands and donchian channels. Each has their own pros and cons but as most are familiar with bollinger bands this is the default.
Another feature is the ATR measurement, which can assist in displaying an overall reduction in range volatility when comparing historical price movements to current oscillations.
The zero line can show some importance with regards to the peaks and valleys of the main measurement, when everything is trending and there's a reversal, if the zero line isn't broken it could be considered a trend continuation pullback vs a complete reversal.
Trend arrows and bar coloring are available but should not be considered trade signals for entry and exit, merely just another way of viewing the lower study information.
As the raw data of each candle measurement is quite noisy, the entire dataset is passed through an HMA smoothing process, if more options are requested I'll consider adding them.
Thanks for view my script and happy trading!
Quan Channel - Quan DaoI tried several channels, like the supertrend, ATR, Donchian or Bollingers, but they do not seem to fit my needs.
So I created a new channel to PREDICT the next impulse move of a price.
The current value of the top or bottom of the channel is based on 2 previous candles (not the candle itself), and it takes into account:
- The Direction of the previous candles (red or green) and
- The Width of their bodies
In my channel, the top or bottom lines will cover the price movement most of the time. But in some cases, when the price is on a big move, it will go out of the channel. And this is the time we need to consider a buy/sell (or take some profit) as well (not necessarily 100% of the time, though).
Personally, I like to use another oscillator in combination with this channel to predict whether it will reverse after the breakouts or continue to make another peak. If you are a DCA or long-term investor, I guess it would be safe to buy at the blue signals (out of bottom) and take some profits at the orange signals (out of top).
I also added an alert when the price breaks out of the channel for easier tracking.
Moving Fib Based on Donchain/Pivot/BBThis script's purpose is to provide the user with an indicator that automatically plots Fibonacci levels. The user has three main options for determining the Fibonacci's high and low. This indicator offers an ample number of settings, making it a modular Fibonacci overlay.
The default setting is based on Donchian high and low.
Another option is to base the high and low on TradingView's Pivot indicator.
The last option is to determine Fibonacci levels based on Bollinger Bands.
Add up to 16 Fib levels with customizable settings, plot them on a log scale, and explore various other settings to personalize the Fib overlay.
This indicator can be utilized for trading momentum or mean reversion strategies
[blackcat] L1 NinjaTrader ChannelNinjaTrader is a popular charting software widely used for trading analysis and execution in financial markets such as stocks, futures, and forex. It provides rich features and tools to assist traders in technical analysis, trade strategy development, and trade execution. When I discovered a built-in channel technical indicator in NinjaTrader and became interested in it but didn't understand its principles, I utilized my extensive development experience to simulate a similar version based on its characteristics, naming it "Ninja Channel" for reference only. First, I observed the characteristics and behavior of the built-in channel indicator. Pay attention to how it calculates and plots the channels, as well as its parameter settings and usage methods. This information can help me better understand the principles and functions of this indicator. Then, I attempted to simulate a similar channel indicator using my existing knowledge of technical analysis tools. I used charting tools and indicators to plot and calculate the upper and lower boundaries of the channel according to my needs and preferences. Please remember that this simulated version is for reference only; there is no guarantee that it will be exactly identical to the built-in channel indicator in NinjaTrader. The original built-in indicator may have more complex calculation methods with more precise results. Therefore, before engaging in actual trading activities, it is recommended that you carefully study and understand the principles and usage methods of the original indicator.
The Ninja Channel belongs to a type of technical indicator used for analyzing price range fluctuations and trends. It constructs an upper-lower boundary channel based on high-low points or moving average line fluctuations of prices to assist traders in determining overbought/oversold zones, trend strength/weaknesses,and price reversal points.
The main uses of Ninja Channel include:
1.Trend determination: The Ninja Channel helps traders determine price trends.When prices are located above half partofthechannel,it indicates an uptrend; when prices are located below half partofthechannel,it indicates adowntrend. Traders can formulate corresponding trading strategies based on trend analysis.
2.Overbought/oversold zones: The upper and lower boundaries of the Ninja Channel can be used to determine overbought and oversold zones.When prices touch or exceed the upper boundary of the channel, it may indicate an overbought market condition with a potential price pullback or reversal; when prices touch or fall below the lower boundary of the channel, it may indicate an oversold market condition with a potential price rebound or reversal.Traders can develop counter-trend or reversal trading strategies based on these overbought/oversold zones.
3.Dynamic support and resistance: The upper and lower boundaries of the Ninja Channel can be seen as dynamic support and resistance levels.When prices approach the upper boundary ofthechannel,theupperboundarymay act asresistance, limiting upward price movement; when prices approachthelowerboundaryofthechannel,thelowerboundarymayactassupport,limiting downward price movement.Traderscanmake trading decisions based on these dynamic supportandresistancelevels.
Of course, for this newly created indicator,some aspects are still unfamiliar.However,the learning process can refer to some common channel-type technical indicators including Bollinger Bands,Keltner Channels,and Donchian Channels. Each indicator has its unique calculation method and parameter settings.Traderscan choose suitable indicators according to their own needsandpreferences.
In summary,NinjaChannel is a type of technical indicator used for analyzingprice range fluctuationsandtrends.It helps traders determine trends,overbought/oversoldzones,anddynamic support/resistance levels in order to formulate appropriate trading strategies.However,technicalindicatorsareonly auxiliary tools.Traderstill needsto consider other factorsandsrisk managementstrategiesinorder tomakemore informedtradingdecisions.
Multi Time Frame Composite BandsMulti Time Frame Composite Bands utilizes Fibonacci numbers (5, 8, 13, 21, 34) as period lengths for calculations. The indicator calculates a composite high line (C_high) by averaging the highest prices over Fibonacci periods, incorporating moving averages (SMA) of high prices for added refinement and smoothing. Similarly, a composite low line (C_low) is calculated by averaging the lowest prices with moving averages of low prices. The midline, obtained from the mean of C_high and C_low.
This band can function as volatility bands unlike traditional volatility indicators like Bollinger Bands , ATR bands it does not use traditional measures of volatility such standard deviation , ATR. This hugs closely to the price and during trending markets the some part of the candles stay outside the band and when the entire candle digress outside the band a price correction or reversal can be anticipated. This can be considered as a smoothed Donchian channel.
