J12Matic Builder by galgoomA flexible Renko/tick strategy that lets you choose between two entry engines (Multi-Source 3-way or QBand+Moneyball), with a unified trailing/TP exit engine, NY-time trading windows with auto-flatten, daily profit/loss and trade-count limits (HALT mode), and clean webhook routing using {{strategy.order.alert_message}}.
Highlights
Two entry engines
Multi-Source (3): up to three long/short sources with Single / Dual / Triple logic and optional lookback.
QBand + Moneyball: Gate → Trigger workflow with timing windows, OR/AND trigger modes, per-window caps, optional same-bar fire.
Unified exit engine: Trailing by Bricks or Ticks, plus optional static TP/SL.
Session control (NY time): Evening / Overnight / NY Session windows; auto-flatten at end of any enabled window.
Day controls: Profit/Loss (USD) and Trade-count limits. When hit, strategy HALTS new entries, shows an on-chart label/background.
Alert routing designed for webhooks: Every order sets alert_message= so you can run alerts with:
Condition: this strategy
Notify on: Order fills only
Message: {{strategy.order.alert_message}}
Default JSONs or Custom payloads: If a Custom field is blank, a sensible default JSON is sent. Fill a field to override.
How to set up alerts (the 15-second version)
Create a TradingView alert with this strategy as Condition.
Notify on: Order fills only.
Message: {{strategy.order.alert_message}} (exactly).
If you want your own payloads, paste them into Inputs → 08) Custom Alert Payloads.
Leave blank → the strategy sends a default JSON.
Fill in → your text is sent as-is.
Note: Anything you type into the alert dialog’s Message box is ignored except the {{strategy.order.alert_message}} token, which forwards the payload supplied by the strategy at order time.
Publishing notes / best practices
Renko users: Make sure “Renko Brick Size” in Inputs matches your chart’s brick size exactly.
Ticks vs Bricks: Exit distances switch instantly when you toggle Exit Units.
Same-bar flips: If enabled, a new opposite signal will first close the open trade (with its exit payload), then enter the new side.
HALT mode: When day profit/loss limit or trade-count limit triggers, new entries are blocked for the rest of the session day. You’ll see a label and a soft background tint.
Session end flatten: Auto-closes positions at window ends; these exits use the “End of Session Window Exit” payload.
Bar magnifier: Strategy is configured for on-close execution; you can enable Bar Magnifier in Properties if needed.
Default JSONs (used when a Custom field is empty)
Open: {"event":"open","side":"long|short","symbol":""}
Close: {"event":"close","side":"long|short|flat","reason":"tp|sl|flip|session|limit_profit|limit_loss","symbol":""}
You can paste any text/JSON into the Custom fields; it will be forwarded as-is when that event occurs.
Input sections — user guide
01) Entries & Signals
Entry Logic: Choose Multi-Source (3) or QBand + Moneyball (pick one).
Enable Long/Short Signals: Master on/off switches for entering long/short.
Flip on opposite signal: If enabled, a new opposite signal will close the current position first, then open the other side.
Signal Logic (Multi-Source):
Single: any 1 of the 3 sources > 0
Dual: Source1 AND Source2 > 0
Triple (default): 1 AND 2 AND 3 > 0
Long/Short Signal Sources 1–3: Provide up to three series (often indicators). A positive value (> 0) is treated as a “pulse”.
Use Lookback: Keeps a source “true” for N bars after it pulses (helps catch late triggers).
Long/Short Lookback (bars): How many bars to remember that pulse.
01b) QBands + Moneyball (Gate -> Trigger)
Allow same-bar Gate->Trigger: If ON, a trigger can fire on the same bar as the gate pulse.
Trigger must fire within N bars after Gate: Size of the gate window (in bars).
Max signals per window (0 = unlimited): Cap the number of entries allowed while a gate window is open.
Buy/Sell Source 1 – Gate: Gate pulse sources that open the buy/sell window (often a regime/zone, e.g., QBands bull/bear).
Trigger Pulse Mode (Buy/Sell): How to detect a trigger pulse from the trigger sources (Change / Appear / Rise>0 / Fall<0).
Trigger A/B sources + Extend Bars: Primary/secondary triggers plus optional extension to persist their pulse for N bars.
Trigger Mode: Pick S2 only, S3 only, S2 OR S3, or S2 AND S3. AND mode remembers both pulses inside the window before firing.
02) Exit Units (Trailing/TP)
Exit Units: Choose Bricks (Renko) or Ticks. All distances below switch accordingly.
03) Tick-based Trailing / Stops (active when Exit Units = Ticks)
Initial SL (ticks): Starting stop distance from entry.
Start Trailing After (ticks): Start trailing once price moves this far in your favor.
Trailing Distance (ticks): Offset of the trailing stop from peak/trough once trailing begins.
Take Profit (ticks): Optional static TP distance.
Stop Loss (ticks): Optional static SL distance (overrides trailing if enabled).
04) Brick-based Trailing / Stops (active when Exit Units = Bricks)
Renko Brick Size: Must match your chart’s brick size.
Initial SL / Start Trailing After / Trailing Distance (bricks): Same definitions as tick mode, measured in bricks.
Take Profit / Stop Loss (bricks): Optional static distances.
05) TP / SL Switch
Enable Static Take Profit: If ON, closes the trade at the fixed TP distance.
Enable Static Stop Loss (Overrides Trailing): If ON, trailing is disabled and a fixed SL is used.
06) Trading Windows (NY time)
Use Trading Windows: Master toggle for all windows.
Evening / Overnight / NY Session: Define each session in NY time.
Flatten at End of : Auto-close any open position when a window ends (sends the Session Exit payload).
07) Day Controls & Limits
Enable Profit Limits / Profit Limit (Dollars): When daily net PnL ≥ limit → auto-flatten and HALT.
Enable Loss Limits / Loss Limit (Dollars): When daily net PnL ≤ −limit → auto-flatten and HALT.
Enable Trade Count Limits / Number of Trades Allowed: After N entries, HALT new entries (does not auto-flatten).
On-chart HUD: A label and soft background tint appear when HALTED; a compact status table shows Day PnL, trade count, and mode.
08) Custom Alert Payloads (used as strategy.order.alert_message)
Long/Short Entry: Payload sent on entries (if blank, a default open JSON is sent).
Regular Long/Short Exit: Payload sent on closes from SL/TP/flip (if blank, a default close JSON is sent).
End of Session Window Exit: Payload sent when any enabled window ends and positions are flattened.
Profit/Loss/Trade Limit Close: Payload sent when daily profit/loss limit causes auto-flatten.
Tip: Any tokens you include here are forwarded “as is”. If your downstream expects variables, do the substitution on the receiver side.
Known limitations
No bracket orders from Pine: This strategy doesn’t create OCO/attached brackets on the broker; it simulates exits with strategy logic and forwards your payloads for external automation.
alert_message is per order only: Alerts fire on order events. General status pings aren’t sent unless you wire a separate indicator/alert.
Renko specifics: Backtests on synthetic Renko can differ from live execution. Always forward-test on your instrument and settings.
Quick checklist before you publish
✅ Brick size in Inputs matches your Renko chart
✅ Exit Units set to Bricks or Ticks as you intend
✅ Day limits/Windows toggled as you want
✅ Custom payloads filled (or leave blank to use defaults)
✅ Your alert uses Order fills only + {{strategy.order.alert_message}}
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ForecastForecast (FC), indicator documentation
Type: Study, not a strategy
Primary timeframe: 1D chart, most plots and the on-chart table only render on daily bars
Inspiration: Robert Carver’s “forecast” concept from Advanced Futures Trading Strategies, using normalized, capped signals for comparability across markets
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What the indicator does
FC builds a volatility-normalized momentum forecast for a chosen symbol, optionally versus a benchmark. It combines an EWMAC composite with a channel breakout composite, then caps the result to a common scale. You can run it in three data modes:
• Absolute: Forecast of the selected symbol
• Relative: Forecast of the ratio symbol / benchmark
• Combined: Average of Absolute and Relative
A compact table can summarize the current forecast, short-term direction on the forecast EMAs, correlation versus the benchmark, and ATR-scaled distances to common price EMAs.
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PineScreener, relative-strength screening
This indicator is excellent for screening on relative strength in PineScreener, since the forecast is volatility-normalized and capped on a common scale.
Available PineScreener columns
PineScreener reads the plotted series. You will see at least these columns:
• FC, the capped forecast
• from EMA20, (price − EMA20) / ATR in ATR multiples
• from EMA50, (price − EMA50) / ATR in ATR multiples
• ATR, ATR as a percent of price
• Corr, weekly correlation with the chosen benchmark
Relative mode and Combined mode are recommended for cross-sectional screens. In Relative mode the calculation uses symbol / benchmark, so ensure the ratio ticker exists for your data source.
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How it works, step by step
1. Volatility model
Compute exponentially weighted mean and variance of daily percent returns on D, annualize, optionally blend with a long lookback using 10y %, then convert to a price-scaled sigma.
2. EWMAC momentum, three legs
Daily legs: EMA(8) − EMA(32), EMA(16) − EMA(64), EMA(32) − EMA(128).
Divide by price-scaled sigma, multiply by leg scalars, cap to Cap = 20, average, then apply a small FDM factor.
3. Breakout momentum, three channels
Smoothed position inside 40, 80, and 160 day channels, each scaled, then averaged.
4. Composite forecast
Average the EWMAC composite and the breakout composite, then cap to ±20.
Relative mode runs the same logic on symbol / benchmark.
Combined mode averages Absolute and Relative composites.
5. Weekly correlation
Pearson correlation between weekly closes of the asset and the benchmark over a user-set length.
6. Direction overlay
Two EMAs on the forecast series plus optional green or red background by sign, and optional horizontal level shading around 0, ±5, ±10, ±15, ±20.
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Plots
• FC, capped forecast on the daily chart
• 8-32 Abs, 8-32 Rel, single-leg EWMAC plus breakout view
• 8-32-128 Abs, 8-32-128 Rel, three-leg composite views
• from EMA20, from EMA50, (price − EMA) / ATR
• ATR, ATR as a percent of price
• Corr, weekly correlation with the benchmark
• Forecast EMA1 and EMA2, EMAs of the forecast with an optional fill
• Backgrounds and guide lines, optional sign-based background, optional 0, ±5, ±10, ±15, ±20 guides
Most plots and the table are gated by timeframe.isdaily. Set the chart to 1D to see them.
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Inputs
Symbol selection
• Absolute, Relative, Combined
• Vs. benchmark for Relative mode and correlation, choices: SPY, QQQ, XLE, GLD
• Ticker or Freeform, for Freeform use full TradingView notation, for example NASDAQ:AAPL
Engine selection
• Include:
• 8-32-128, three EWMAC legs plus three breakouts
• 8-32, simplified view based on the 8-32 leg plus a 40-day breakout
EMA, applied to the forecast
• EMA1, EMA2, with line-width controls, plus color and opacity
Volatility
• Span, EW volatility span for daily returns
• 10y %, blend of long-run volatility
• Thresh, Too volatile, placeholders in this version
Background
• Horizontal bg, level shading, enabled by default
• Long BG, Hedge BG, colors and opacities
Show
• Table, Header, Direction, Gain, Extension
• Corr, Length for correlation row
Table settings
• Position, background, opacity, text size, text color
Lines
• 0-lines, 10-lines, 5-lines, level guides
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Reading the outputs
• Forecast > 0, bullish tilt; Forecast < 0, bearish or hedge tilt
• ±10 and ±20 indicate strength on a uniform scale
• EMA1 vs EMA2 on the forecast, EMA1 above EMA2 suggests improving momentum
• Table rows, label colored by sign, current forecast value plus a green or red dot for the forecast EMA cross, optional daily return percent, weekly correlation, and ATR-scaled EMA9, EMA20, EMA50 distances
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Data handling, repainting, and performance
• Daily and weekly series are fetched with request.security().
• Calculations use closed bars, values can update until the bar closes.
• No lookahead, historical values do not repaint.
• Weekly correlation updates during the week, it finalizes on weekly close.
• On intraday charts most visuals are hidden by design.
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Good practice and limitations
• This is a research indicator, not a trading system.
• The fixed Cap = 20 keeps a common scale, extreme moves will be clipped.
• Relative mode depends on the ratio symbol / benchmark, ensure both legs have data for your feed.
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Credits
Concept inspired by Robert Carver’s forecast methodology in Advanced Futures Trading Strategies. Implementation details, parameters, and visuals are specific to this script.
⸻
Changelog
• First version
⸻
Disclaimer
For education and research only, not financial advice. Always test on your market and data feed, consider costs and slippage before using any indicator in live decisions.
Smart Money Precision Structure [BullByte]Smart Money Precision Structure
Advanced Market Structure Analysis Using Institutional Order Flow Concepts
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OVERVIEW
Smart Money Precision Structure (SMPS) is a comprehensive market analysis indicator that combines six analytical frameworks to identify high-probability market structure patterns. The indicator uses multi-dimensional scoring algorithms to evaluate market conditions through institutional order flow concepts, providing traders with professional-grade market analysis.
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PURPOSE AND ORIGINALITY
Why This Indicator Was Developed
• Addresses the gap between retail and institutional analysis methods
• Consolidates multiple analysis techniques that professionals use separately
• Automates complex market structure evaluation into actionable insights
• Eliminates the need for multiple indicators by providing comprehensive analysis
What Makes SMPS Original
• Six-Layer Confluence System - Unique combination of market regime, structure, volume flow, momentum, price action, and adaptive filtering
• Institutional Pattern Recognition - Identifies smart money accumulation and distribution patterns
• Adaptive Intelligence - Parameters automatically adjust based on detected market conditions
• Real-Time Market Scoring - Proprietary algorithm rates market quality from 0-100%
• Structure Break Detection - Advanced pivot analysis identifies trend reversals early
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HOW IT WORKS - TECHNICAL METHODOLOGY
1. Market Regime Analysis Engine
The indicator evaluates five core market dimensions:
• Volatility Score - Measures current volatility against 50-period historical baseline
• Trend Score - Analyzes alignment between 8, 21, and 50-period EMAs
• Momentum Score - Combines RSI divergence with MACD signal alignment
• Structure Score - Evaluates pivot point formation clarity
• Efficiency Score - Calculates directional movement efficiency ratio
These scores combine to classify markets into five regimes:
• TRENDING - Strong directional movement with aligned indicators
• RANGING - Sideways movement with mixed directional signals
• VOLATILE - Elevated volatility with unpredictable price swings
• QUIET - Low volatility consolidation periods
• TRANSITIONAL - Market shifting between different regimes
2. Market Structure Analysis
Advanced pivot point analysis identifies:
• Higher Highs and Higher Lows for bullish structure
• Lower Highs and Lower Lows for bearish structure
• Structure breaks when established patterns fail
• Dynamic support and resistance from recent pivot points
• Key level proximity detection using ATR-based buffers
3. Volume Flow Decoding
Institutional activity detection through:
• Volume surge identification when volume exceeds 2x average
• Buy versus sell pressure analysis using price-volume correlation
• Flow strength measurement through directional volume consistency
• Divergence detection between volume and price movements
• Institutional threshold alerts when unusual volume patterns emerge
4. Multi-Period Momentum Synthesis
Weighted momentum calculation across four timeframes:
• 1-period momentum weighted at 40%
• 3-period momentum weighted at 30%
• 5-period momentum weighted at 20%
• 8-period momentum weighted at 10%
Result smoothed with 6-period EMA for noise reduction.
5. Price Action Quality Assessment
Each bar evaluated for:
• Range quality relative to 20-period average
• Body-to-range ratio for directional conviction
• Wick analysis for rejection pattern identification
• Pattern recognition including engulfing and hammer formations
• Sequential price movement analysis
6. Adaptive Parameter System
Parameters automatically adjust based on detected regime:
• Trending markets reduce sensitivity and confirmation requirements
• Volatile markets increase filtering and require additional confirmations
• Ranging markets maintain neutral settings
• Transitional markets use moderate adjustments
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COMPLETE SETTINGS GUIDE
Section 1: Core Analysis Settings
Analysis Sensitivity (0.3-2.0)
• Default: 1.0
• Lower values require stronger price movements
• Higher values detect more subtle patterns
• Scalpers use 0.8-1.2, swing traders use 1.5-2.0
Noise Reduction Level (2-7)
• Default: 4
• Controls filtering of false patterns
• Higher values reduce pattern frequency
• Increase in volatile markets
Minimum Move % (0.05-0.50)
• Default: 0.15%
• Sets minimum price movement threshold
• Adjust based on instrument volatility
• Forex: 0.05-0.10%, Stocks: 0.15-0.25%, Crypto: 0.20-0.50%
High Confirmation Mode
• Default: True (Enabled)
• Requires all technical conditions to align
• Reduces frequency but increases reliability
• Disable for more aggressive pattern detection
Section 2: Market Regime Detection
Enable Regime Analysis
• Default: True (Enabled)
• Activates market environment evaluation
• Essential for adaptive features
• Keep enabled for best results
Regime Analysis Period (20-100)
• Default: 50 bars
• Determines regime calculation lookback
• Shorter for responsive, longer for stable
• Scalping: 20-30, Swing: 75-100
Minimum Market Clarity (0.2-0.8)
• Default: 0.4
• Quality threshold for pattern generation
• Higher values require clearer conditions
• Lower for more patterns, higher for quality
Adaptive Parameter Adjustment
• Default: True (Enabled)
• Enables automatic parameter optimization
• Adjusts based on market regime
• Highly recommended to keep enabled
Section 3: Market Structure Analysis
Enable Structure Validation
• Default: True (Enabled)
• Validates patterns against support/resistance
• Confirms trend structure alignment
• Essential for reliability
Structure Analysis Period (15-50)
• Default: 30 bars
• Period for structure pattern analysis
• Affects support/resistance calculation
• Match to your trading timeframe
Minimum Structure Alignment (0.3-0.8)
• Default: 0.5
• Required structure score for valid patterns
• Higher values need stronger structure
• Balance with desired frequency
Section 4: Analysis Configuration
Minimum Strength Level (3-5)
• Default: 4
• Minimum confirmations for pattern display
• 5 = Maximum reliability, 3 = More patterns
• Beginners should use 4-5
Required Technical Confirmations (4-6)
• Default: 5
• Number of aligned technical factors
• Higher = fewer but better patterns
• Works with High Confirmation Mode
Pattern Separation (3-20 bars)
• Default: 8 bars
• Minimum bars between patterns
• Prevents clustering and overtrading
• Increase for cleaner charts
Section 5: Technical Filters
Momentum Validation
• Default: True (Enabled)
• Requires momentum alignment
• Filters counter-trend patterns
• Essential for trend following
Volume Confluence Analysis
• Default: True (Enabled)
• Requires volume confirmation
• Identifies institutional participation
• Critical for reliability
Trend Direction Filter
• Default: True (Enabled)
• Only shows patterns with trend
• Reduces counter-trend signals
• Disable for reversal hunting
Section 6: Volume Flow Analysis
Institutional Activity Threshold (1.2-3.5)
• Default: 2.0
• Multiplier for unusual volume detection
• Lower finds more institutional activity
• Stock: 2.0-2.5, Forex: 1.5-2.0, Crypto: 2.5-3.5
Volume Surge Multiplier (1.8-4.5)
• Default: 2.5
• Defines significant volume increases
• Adjust per instrument characteristics
• Higher for stocks, lower for forex
Volume Flow Period (12-35)
• Default: 18 bars
• Smoothing for volume analysis
• Shorter = responsive, longer = smooth
• Match to timeframe used
Section 7: Analysis Frequency Control
Maximum Analysis Points Per Hour (1-5)
• Default: 3
• Limits pattern frequency
• Prevents overtrading
• Scalpers: 4-5, Swing traders: 1-2
Section 8: Target Level Configuration
Target Calculation Method
• Default: Market Adaptive
• Three modes available:
- Fixed: Uses set point distances
- Dynamic: ATR-based calculations
- Market Adaptive: Structure-based levels
Minimum Target/Risk Ratio (1.0-3.0)
• Default: 1.5
• Minimum acceptable reward vs risk
• Higher filters lower probability setups
• Professional standard: 1.5-2.0
Fixed Mode Settings:
• Fixed Target Distance: 50 points default
• Fixed Invalidation Distance: 30 points default
• Use for consistent instruments
Dynamic Mode Settings:
• Dynamic Target Multiplier: 1.8x ATR default
• Dynamic Invalidation Multiplier: 1.0x ATR default
• Adapts to volatility automatically
Market Adaptive Settings:
• Use Structure Levels: True (default)
• Structure Level Buffer: 0.1% default
• Places levels at actual support/resistance
Section 9: Visual Display Settings
Color Theme Options
• Professional (Teal/Red)
- Bullish: Teal (#26a69a)
- Bearish: Red (#ef5350)
- Neutral: Gray (#78909c)
- Best for: Traditional traders, clean appearance
• Dark (Neon Green/Pink)
- Bullish: Neon Green (#00ff88)
- Bearish: Hot Pink (#ff0044)
- Neutral: Dark Gray (#333333)
- Best for: Dark theme users, high contrast
• Light (Green/Red Classic)
- Bullish: Green (#4caf50)
- Bearish: Red (#f44336)
- Neutral: Light Gray (#9e9e9e)
- Best for: Light backgrounds, traditional colors
• Vibrant (Cyan/Magenta)
- Bullish: Cyan (#00ffff)
- Bearish: Magenta (#ff00ff)
- Neutral: Medium Gray (#888888)
- Best for: High visibility, modern appearance
Dashboard Position
• Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Left, Middle Right
• Default: Top Right
• Choose based on chart layout preference
Dashboard Size
• Full: Complete information display (desktop)
• Mobile: Compact view for small screens
• Default: Full
Analysis Display Style
• Arrows : Simple directional markers
• Labels : Detailed text information
• Zones : Colored areas showing pattern regions
• Default: Labels (most informative)
Display Options:
• Display Analysis Strength: Shows star rating
• Display Target Levels: Shows target/invalidation lines
• Display Market Regime: Shows regime in pattern labels
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HOW TO USE SMPS - DETAILED GUIDE
Understanding the Dashboard
Top Row - Header
• SMPS Dashboard title
• VALUE column: Current readings
• STATUS column: Condition assessments
Market Regime Row
• Shows: TRENDING, RANGING, VOLATILE, QUIET, or TRANSITIONAL
• Color coding: Green = Favorable, Red = Caution
• Status: FAVORABLE or CAUTION trading conditions
Market Score Row
• Percentage from 0-100%
• Above 60% = Strong conditions
• 40-60% = Moderate conditions
• Below 40% = Weak conditions
Structure Row
• Direction: BULLISH, BEARISH, or NEUTRAL
• Status: INTACT or BREAK
• Orange BREAK indicates structure failure
Volume Flow Row
• Direction: BUYING or SELLING
• Intensity: STRONG or WEAK
• Color indicates dominant pressure
Momentum Row
• Numerical momentum value
• Positive = Upward pressure
• Negative = Downward pressure
Volume Status Row
• INST = Institutional activity detected
• HIGH = Above average volume
• NORM = Normal volume levels
Adaptive Mode Row
• ACTIVE = Parameters adjusting
• STATIC = Fixed parameters
• Shows required confirmations
Analysis Level Row
• Minimum strength level setting
• Pattern separation in bars
Market State Row
• Current analysis: BULLISH, BEARISH, NEUTRAL
• Shows analysis price level when active
T:R Ratio Row
• Current target to risk ratio
• GOOD = Meets minimum requirement
• LOW = Below minimum threshold
Strength Row
• BULL or BEAR dominance
• Numerical strength value 0-100
Price Row
• Current price
• Percentage change
Last Analysis Row
• Previous pattern direction
• Bars since last pattern
Reading Pattern Signals
Bullish Structure Pattern
• Upward triangle or "Bullish Structure" label
• Star rating shows strength (★★★★★ = strongest)
• Green line = potential target level
• Red dashed line = invalidation level
• Appears below price bars
Bearish Structure Pattern
• Downward triangle or "Bearish Structure" label
• Star rating indicates reliability
• Green line = potential target level
• Red dashed line = invalidation level
• Appears above price bars
Pattern Strength Interpretation
• ★★★★★ = 6 confirmations (exceptional)
• ★★★★☆ = 5 confirmations (strong)
• ★★★☆☆ = 4 confirmations (moderate)
• ★★☆☆☆ = 3 confirmations (minimum)
• Below minimum = filtered out
Visual Elements on Chart
Lines and Levels:
• Gray Line = 21 EMA trend reference
• Green Stepline = Dynamic support level
• Red Stepline = Dynamic resistance level
• Green Solid Line = Active target level
• Red Dashed Line = Active invalidation level
Pattern Markers:
• Triangles = Arrow display mode
• Text Labels = Label display mode
• Colored Boxes = Zone display mode
Target Completion Labels:
• "Target" = Price reached target level
• "Invalid" = Pattern invalidated by price
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RECOMMENDED USAGE BY TIMEFRAME
1-Minute Charts (Scalping)
• Sensitivity: 0.8-1.2
• Noise Reduction: 3-4
• Pattern Separation: 3-5 bars
• High Confirmation: Optional
• Best for: Quick intraday moves
5-Minute Charts (Precision Intraday)
• Sensitivity: 1.0 (default)
• Noise Reduction: 4 (default)
• Pattern Separation: 8 bars
• High Confirmation: Enabled
• Best for: Day trading
15-Minute Charts (Short Swing)
• Sensitivity: 1.0-1.5
• Noise Reduction: 4-5
• Pattern Separation: 10-12 bars
• High Confirmation: Enabled
• Best for: Intraday swings
30-Minute to 1-Hour (Position Trading)
• Sensitivity: 1.5-2.0
• Noise Reduction: 5-7
• Pattern Separation: 15-20 bars
• Regime Period: 75-100
• Best for: Multi-day positions
Daily Charts (Swing Trading)
• Sensitivity: 1.8-2.0
• Noise Reduction: 6-7
• Pattern Separation: 20 bars
• All filters enabled
• Best for: Long-term analysis
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MARKET-SPECIFIC SETTINGS
Forex Pairs
• Minimum Move: 0.05-0.10%
• Institutional Threshold: 1.5-2.0
• Volume Surge: 1.8-2.2
• Target Mode: Dynamic or Market Adaptive
Stock Indices (ES, NQ, YM)
• Minimum Move: 0.10-0.15%
• Institutional Threshold: 2.0-2.5
• Volume Surge: 2.5-3.0
• Target Mode: Market Adaptive
Individual Stocks
• Minimum Move: 0.15-0.25%
• Institutional Threshold: 2.0-2.5
• Volume Surge: 2.5-3.5
• Target Mode: Dynamic
Cryptocurrency
• Minimum Move: 0.20-0.50%
• Institutional Threshold: 2.5-3.5
• Volume Surge: 3.0-4.5
• Target Mode: Dynamic
• Increase noise reduction
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PRACTICAL APPLICATION EXAMPLES
Example 1: Strong Trending Market
Dashboard Reading:
• Market Regime: TRENDING
• Market Score: 75%
• Structure: BULLISH, INTACT
• Volume Flow: BUYING, STRONG
• Momentum: +0.45
Interpretation:
• Strong uptrend environment
• Institutional buying present
• Look for bullish patterns as continuation
• Higher probability of success
• Consider using lower sensitivity
Example 2: Range-Bound Conditions
Dashboard Reading:
• Market Regime: RANGING
• Market Score: 35%
• Structure: NEUTRAL
• Volume Flow: SELLING, WEAK
• Momentum: -0.05
Interpretation:
• No clear direction
• Low opportunity environment
• Patterns are less reliable
• Consider waiting for regime change
• Or switch to a range-trading approach
Example 3: Structure Break Alert
Dashboard Reading:
• Previous: BULLISH structure
• Current: Structure BREAK
• Volume: INST flag active
• Momentum: Shifting negative
Interpretation:
• Trend reversal potentially beginning
• Institutional participation detected
• Watch for bearish pattern confirmation
• Adjust bias accordingly
• Increase caution on long positions
Example 4: Volatile Market
Dashboard Reading:
• Market Regime: VOLATILE
• Market Score: 45%
• Adaptive Mode: ACTIVE
• Confirmations: Increased to 6
Interpretation:
• Choppy conditions
• Parameters auto-adjusted
• Fewer but higher quality patterns
• Wider stops may be needed
• Consider reducing position size
Below are a few chart examples of the Smart Money Precision Structure (SMPS) indicator in action.
• Example 1 – Bullish Structure Detection on SOLUSD 5m
• Example 2 – Bearish Structure Detected with Strong Confluence on SOLUSD 5m
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TROUBLESHOOTING GUIDE
No Patterns Appearing
Check these settings:
• High Confirmation Mode may be too restrictive
• Minimum Strength Level may be too high
• Market Clarity threshold may be too high
• Regime filter may be blocking patterns
• Try increasing sensitivity
Too Many Patterns
Adjust these settings:
• Enable High Confirmation Mode
• Increase Minimum Strength Level to 5
• Increase Pattern Separation
• Reduce Sensitivity below 1.0
• Enable all technical filters
Dashboard Shows "CAUTION"
This indicates:
• Market conditions are unfavorable
• Regime is RANGING or QUIET
• Market score is low
• Consider waiting for better conditions
• Or adjust expectations accordingly
Patterns Not Reaching Targets
Consider:
• Market may be choppy
• Volatility may have changed
• Try Dynamic target mode
• Reduce target/risk ratio requirement
• Check if regime is VOLATILE
---
ALERTS CONFIGURATION
Alert Message Format
Alerts include:
• Pattern type (Bullish/Bearish)
• Strength rating
• Market regime
• Analysis price level
• Target and invalidation levels
• Strength percentage
• Target/Risk ratio
• Educational disclaimer
Setting Up Alerts
• Click Alert button on TradingView
• Select SMPS indicator
• Choose alert frequency
• Customize message if desired
• Alerts fire on pattern detection
---
DATA WINDOW INFORMATION
The Data Window displays:
• Market Regime Score (0-100)
• Market Structure Bias (-1 to +1)
• Bullish Strength (0-100)
• Bearish Strength (0-100)
• Bull Target/Risk Ratio
• Bear Target/Risk Ratio
• Relative Volume
• Momentum Value
• Volume Flow Strength
• Bull Confirmations Count
• Bear Confirmations Count
---
BEST PRACTICES AND TIPS
For Beginners
• Start with default settings
• Use High Confirmation Mode
• Focus on TRENDING regime only
• Paper trade first
• Learn one timeframe thoroughly
For Intermediate Users
• Experiment with sensitivity settings
• Try different target modes
• Use multiple timeframes
• Combine with price action analysis
• Track pattern success rate
For Advanced Users
• Customize per instrument
• Create setting templates
• Use regime information for bias
• Combine with other indicators
• Develop systematic rules
---
IMPORTANT DISCLAIMERS
• This indicator is for educational and informational purposes only
• Not financial advice or a trading system
• Past performance does not guarantee future results
• Trading involves substantial risk of loss
• Always use appropriate risk management
• Verify patterns with additional analysis
• The author is not a registered investment advisor
• No liability accepted for trading losses
---
VERSION NOTES
Version 1.0.0 - Initial Release
• Six-layer confluence system
• Adaptive parameter technology
• Institutional volume detection
• Market regime classification
• Structure break identification
• Real-time dashboard
• Multiple display modes
• Comprehensive settings
## My Final Thoughts
Smart Money Precision Structure represents an advanced approach to market analysis, bringing institutional-grade techniques to retail traders through intelligent automation and multi-dimensional evaluation. By combining six analytical frameworks with adaptive parameter adjustment, SMPS provides comprehensive market intelligence that single indicators cannot achieve.
The indicator serves as an educational tool for understanding how professional traders analyze markets, while providing practical pattern detection for those seeking to improve their technical analysis. Remember that all trading involves risk, and this tool should be used as part of a complete analysis approach, not as a standalone trading system.
- BullByte
Beta Zones [MMT]Beta Zones
Overview
The Beta Zones indicator is a multi-timeframe analysis tool designed to identify and visualize price ranges (zones) across different timeframes on a TradingView chart. It draws boxes to represent high and low price levels for each enabled timeframe, helping traders spot key support and resistance zones, track price movements, and assess market signals relative to these zones. The indicator is highly customizable, allowing users to toggle timeframes, adjust colors, and control historical visibility.
Features
Multi-Timeframe Support : Tracks up to five user-defined timeframes (default: 15m, 1H, 4H, 1D, 1W) to display price zones.
Dynamic Price Boxes : Draws boxes on the chart to represent the high and low prices for each timeframe, updating dynamically as new bars form.
Signal Indicators : Provides directional signals (▲, ▼, →) based on the previous close relative to the current box's top and bottom.
Customizable Display : Includes options to show or hide historical boxes, adjust box colors, and configure a summary table.
Summary Table : Displays a table with timeframe status, price range, and signal information for quick reference.
Settings
Timeframes
Enable/Disable : Toggle each timeframe (e.g., 15m, 1H, 4H, 1D, 1W) to display or hide its respective zones.
Timeframe Selection : Choose custom timeframes for each of the five slots.
Color Customization : Set unique fill and border colors for each timeframe's boxes (default colors: green, blue, orange, purple, red).
Display
Max Historical Boxes : Limit the number of historical boxes per timeframe (default: 1, max: 50).
Show History : Toggle visibility of historical boxes (default: false, showing only the latest box).
Min Box Height : Ensures boxes have a minimum height in ticks (default: 1.0, currently hardcoded).
Table
Show Table : Enable or disable the summary table (default: true).
Background Color : Customize the table's background color.
Header Color : Set the color for the table's header row.
Text Color : Adjust the text color for table content.
Table Columns
Timeframe : Displays the selected timeframe (e.g., 15m, 1H).
Color : Shows the color associated with the timeframe's boxes.
Status : Indicates if the timeframe is "Active" (valid and lower than the chart's timeframe), "Invalid" (enabled but not lower), or "Disabled".
Range : Shows the price range (high - low) of the current box.
Signal : Displays ▲ (price above box), ▼ (price below box), or → (price within box) based on the previous close.
How to Use
Add to Chart : Apply the indicator to your TradingView chart.
Configure Timeframes : Enable desired timeframes and adjust their settings (e.g., 15m, 1H) to match your trading strategy.
Analyze Zones : Use the boxes to identify key price levels for support, resistance, or breakout opportunities.
Monitor Signals : Check the table's "Signal" column to gauge price direction relative to each timeframe's zone.
Customize Appearance : Adjust colors and historical box visibility to suit your preferences.
Ideal For
Swing Traders : Identify key price zones across multiple timeframes for entry/exit points.
Day Traders : Monitor short-term price movements relative to higher timeframe zones.
Technical Analysts : Combine with other indicators to confirm support/resistance levels.
EdgeFlow Pullback [CHE]EdgeFlow Pullback \ — Icon & Visual Guide (Deep Dive)
TL;DR (1-minute read)
⏳ Hourglass = Pending verdict. A countdown runs from the signal bar until your Evaluation Window ends.
✔ Checkmark (green) = OK. After the evaluation window, price (HLC3) is on the correct side of the EMA144 for that signal’s direction.
✖ Cross (red) = Fail. After the evaluation window, price (HLC3) is on the wrong side of the EMA144.
▲ / ▼ Triangles = the actual PB Long/Short signal bar (sequence completed in time).
Small lime/red crosses = visual markers when HLC3 crosses EMA144 (context, not trade signals).
Orange line = EMA144 (baseline/trend filter).
T3 line color = Context signal: green when T3 is below HLC3, red when T3 is above HLC3.
Icon Glossary (What each symbol means)
1) ⏳ Hourglass — “Pending / Countdown”
Appears immediately when a PB signal fires (Long or Short).
Shows `⏳ currentBars / EvaluationBars` (e.g., `⏳ 7/30`).
The label stays anchored at the signal bar and its original price level (it does not drift with price).
During ⏳ you get no verdict yet. It’s simply the waiting period before grading.
2) ✔ Checkmark (green) — “Condition met”
Appears after the Evaluation Window completes.
Logic:
Long signal: HLC3 (typical price) is above EMA144 → ✔
Short signal: HLC3 is below EMA144 → ✔
The label turns green and text says “✔ … Condition met”.
This is rules-based grading, not PnL. It tells you if the post-signal structure behaved as expected.
3) ✖ Cross (red) — “Condition failed”
Appears after the Evaluation Window completes if the condition above is not met.
Label turns red with “✖ … Condition failed”.
Again: rules-based verdict, not a guarantee of profit or loss.
4) ▲ “PB Long” triangle (below bar)
Marks the exact bar where the 4-step Long sequence completed within the allowed window.
That bar is your signal bar for Long setups.
5) ▼ “PB Short” triangle (above bar, red)
Same as above, for Short setups.
6) Lime/Red “+” crosses (tiny cross markers)
Lime cross (below bar): HLC3 crosses above EMA144 (crossover).
Red cross (above bar): HLC3 crosses below EMA144 (crossunder).
These crosses are context markers; they’re not entry signals by themselves.
The Two Clocks (Don’t mix them up)
There are two different time windows at play:
1. Signal Window — “Max bars for full sequence”
A pullback signal (Long or Short) only fires if the 4-step sequence completes within this many bars.
If it takes too long: reset (no signal, no triangle, no label).
Purpose: avoid stale setups.
2. Evaluation Window — “Evaluation window after signal (bars)”
Starts after the signal bar. The label shows an ⏳ countdown.
When it reaches the set number of bars, the indicator checks whether HLC3 is on the correct side of EMA144 for the signal direction.
Then it stamps the signal with ✔ (OK) or ✖ (Fail).
Timeline sketch (Long example):
```
→ ▲ PB Long at bar t0
Label shows: ⏳ 0/EvalBars
t0+1, t0+2, ... t0+EvalBars-1 → still ⏳
At t0+EvalBars → Check HLC3 vs EMA144
Result → ✔ (green) or ✖ (red)
(Label remains anchored at t0 / signal price)
```
What Triggers the PB Signal (so you know why triangles appear)
LONG sequence (4 steps in order):
1. T3 falling (the pullback begins)
2. HLC3 crosses under EMA144
3. T3 rising (pullback ends)
4. HLC3 crosses over EMA144 → PB Long triangle
SHORT sequence (mirror):
1. T3 rising
2. HLC3 crosses over EMA144
3. T3 falling
4. HLC3 crosses under EMA144 → PB Short triangle
If steps 1→4 don’t complete in time (within Max bars for full sequence), the sequence is abandoned (no signal).
Lines & Colors (quick interpretation)
EMA144 (orange): your baseline trend filter.
T3 (green/red):
Green when T3 < HLC3 (price above the smoothed path; often supportive in up-moves)
Red when T3 > HLC3 (price below the smoothed path; often pressure in down-moves)
HLC3 (gray): the typical price the logic uses ( (H+L+C)/3 ).
Label Behavior (anchoring & cleanup)
Each signal creates one label at the signal bar with ⏳.
The label is position-locked: it stays at the same bar index and y-price it was born at.
After the evaluation check, the label text and color update to ✔/✖, but position stays fixed.
The indicator keeps only the last N labels (your “Show only the last N labels” input). Older ones are deleted to reduce clutter.
What You Can (and Can’t) Infer from ✔ / ✖
✔ OK: Structure behaved as intended during the evaluation window (HLC3 finished on the correct side of EMA144).
Inference: The pullback continued in the expected direction post-signal.
✖ Fail: Structure ended up opposite the expectation.
Inference: The pullback did not continue cleanly (chop, reversal, or insufficient follow-through).
> Important: ✔/✖ is not profit or loss. It’s an objective rule check. Use it to identify market regimes where your entries perform best.
Input Settings — How they change the visuals
T3 length:
Shorter → faster turns, more signals (and more noise).
Longer → smoother turns, fewer but cleaner sequences.
T3 volume factor (0–1, default 0.7):
Higher → more curvature/smoothing.
Typical sweet spot: 0.5–0.9.
EMA length (baseline) default 144:
Smaller → faster baseline, more cross events, more aggressive signals.
Larger → slower, stricter trend confirmation.
Max bars for full sequence (signal window):
Smaller → only fresh, snappy pullbacks can signal.
Larger → allows slower pullbacks to complete.
Evaluation window (after signal):
Smaller → verdict arrives quickly (less tolerance).
Larger → gives the trade more time to prove itself structurally.
Show only the last N labels:
Controls chart clutter. Increase for more history, decrease for focus.
(FYI: The “Debug” toggle exists but doesn’t draw extra overlays in this version.)
Practical Reading Flow (how to use visuals in seconds)
1. Triangles catch your eye: ▲ for Long, ▼ for Short. That’s the setup completion.
2. ⏳ label starts—don’t judge yet; let the evaluation run.
3. Watch EMA slope and T3 color for context (trend + pressure).
4. After the window: ✔/✖ stamps the outcome. Log what the market was like when you got ✔.
Common “Why did…?” Questions
Q: Why did I get no triangle even though T3 turned and EMA crossed?
A: The 4 steps must happen in order and within the Signal Window. If timing breaks, the sequence resets.
Q: Why did my label stay ⏳ for so long?
A: That’s by design until the Evaluation Window completes. The verdict only happens at the end of that window.
Q: Why is ✔/✖ different from my PnL?
A: It’s a structure check, not a profit check. It doesn’t know your entries/exits/stops.
Q: Do the small lime/red crosses mean buy/sell?
A: No. They’re context markers for HLC3↔EMA crosses, useful inside the sequence but not standalone signals.
Pro Tips (turn visuals into decisions)
Entry: Use the ▲/▼ triangle as your trigger, in trend direction (check EMA slope/market structure).
Stop: Behind the pullback swing around the signal bar.
Exit: Structure levels, R-multiples, or a reverse HLC3↔EMA cross as a trailing logic.
Tuning:
Intraday/volatile: shorter T3/EMA + tighter Signal Window.
Swing/slow: default 144 EMA + moderate windows.
Learn quickly: Filter your chart to show only ✔ or only ✖ windows in your notes; see which sessions, assets, and volatility regimes suit the system.
Disclaimer
No indicator guarantees profits. Sweep2Trade Pro \ is a decision aid; always combine with solid risk management and your own judgment. Backtest, forward test, and size responsibly.
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Enhance your trading precision and confidence 🚀
Happy trading
Chervolino
Volumetric Support and Resistance [BackQuant]Volumetric Support and Resistance
What this is
This Overlay locates price levels where both structure and participation have been meaningful. It combines classical swing points with a volume filter, then manages those levels on the chart as price evolves. Each level carries:
• A reference price (support or resistance)
• An estimate of the volume that traded around that price
• A touch counter that updates when price retests it
• A visual box whose thickness is scaled by volatility
The result is a concise map of candidate support and resistance that is informed by both price location and how much trading occurred there.
How levels are built
Find structural pivots uses ta.pivothigh and ta.pivotlow with a user set sensitivity. Larger sensitivity looks for broader swings. Smaller sensitivity captures tighter turns.
Require meaningful volume computes an average volume over a lookback period and forms a volume ratio for the current bar. A pivot only becomes a level when the ratio is at least the volume significance multiplier.
Avoid clustering checks a minimum level distance (as a percent of price). If a candidate is too close to an existing level, it is skipped to keep the map readable.
Attach a volume strength to the level estimates volume strength by averaging the volume of recent bars whose high to low range spans that price. Levels with unusually high strength are flagged as high volume.
Store and draw levels are kept in an array with fields for price, type, volume, touches, creation bar, and a box handle. On the last bar, each level is drawn as a horizontal box centered at the price with a vertical thickness scaled by ATR. Borders are thicker when the level is marked high volume. Boxes can extend into the future.
How levels evolve over time
• Aging and pruning : levels are removed if they are too old relative to the lookback or if you exceed the maximum active levels.
• Break detection : a level can be removed when price closes through it by more than a break threshold set as a fraction of ATR. Toggle with Remove Broken Levels.
• Touches : when price approaches within the break threshold, the level’s touch counter increments.
Visual encoding
• Boxes : support boxes are green, resistance boxes are red. Box height uses an ATR based thickness so tolerance scales with volatility. Transparency is fixed in this version. Borders are thicker on high volume levels.
• Volume annotation : show the estimated volume inside the box or as a label at the right. If a level has more than one touch, a suffix like “(2x)” is appended.
• Extension : boxes can extend a fixed number of bars into the future and can be set to extend right.
• High volume bar tint : bars with volume above average × multiplier are tinted green if up and red if down.
Inputs at a glance
Core Settings
• Level Detection Sensitivity — pivot window for swing detection
• Volume Significance Multiplier — minimum volume ratio to accept a pivot
• Lookback Period — window for average volume and maintenance rules
Level Management
• Maximum Active Levels — cap on concurrently drawn levels
• Minimum Level Distance (%) — required spacing between level prices
Visual Settings
• Remove Broken Levels — drop a level once price closes decisively through it
• Show Volume Information on Levels — annotate volume and touches
• Extend Levels to Right — carry boxes forward
Enhanced Visual Settings
• Show Volume Text Inside Box — text placement option
• Volume Based Transparency and Volume Based Border Thickness — helper logic provided; current draw block fixes transparency and increases border width on high volume levels
Colors
• Separate colors for support, resistance, and their high volume variants
How it can be used
• Trade planning : use the most recent support and resistance as reference zones for entries, profit taking, or stop placement. ATR scaled thickness provides a practical buffer.
• Context for patterns : combine with breakouts, pullbacks, or candle patterns. A breakout through a high volume resistance carries more informational weight than one through a thin level.
• Prioritization : when multiple levels are nearby, prefer high volume or higher touch counts.
• Regime adaptation : widen sensitivity and increase minimum distance in fast regimes to avoid clutter. Tighten them in calm regimes to capture more granularity.
Why volume support and resistance is used in trading
Support and resistance relate to willingness to transact at certain prices. Volume measures participation. When many contracts change hands near a price:
• More market players hold inventory there, often creating responsive behavior on retests
• Order flow can concentrate again to defend or to exit
• Breaks can be cleaner as trapped inventory rebalances
Conditioning level detection on above average activity focuses attention on prices that mattered to more participants.
Alerts
• New Support Level Created
• New Resistance Level Created
• Level Touch Alert
• Level Break Alert
Strengths
• Dual filter of structure and participation, reducing trivial swing points
• Self cleaning map that retires old or invalid levels
• Volatility aware presentation using ATR based thickness
• Touch counting for persistence assessment
• Tunable inputs for instrument and timeframe
Limitations and caveats
• Volume strength is an approximation based on bars spanning the price, not true per price volume
• Pivots confirm after the sensitivity window completes, so new levels appear with a delay
• Narrow ranges can still cluster levels unless minimum distance is increased
• Large gaps may jump past levels and immediately trigger break conditions
Practical tuning guide
• If the chart is crowded: increase sensitivity, increase minimum level distance, or reduce maximum active levels
• If useful levels are missed: reduce volume multiplier or sensitivity
• If you want stricter break removal: increase the ATR based break threshold in code
• For instruments with session patterns: tailor the lookback period to a representative window
Interpreting touches and breaks
• First touch after creation is a validation test
• Multiple shallow touches suggest absorption; a later break may then travel farther
• Breaks on high current volume merit extra attention
Multi timeframe usage
Levels are computed on the active chart timeframe. A common workflow is to keep a higher timeframe instance for structure and a lower timeframe instance for execution. Align trades with higher timeframe levels where possible.
Final Thoughts
This indicator builds a lightweight, self updating map of support and resistance grounded in swings and participation. It is not a full market profile, but it captures much of the practical benefit with modest complexity. Treat levels as context and decision zones, not guarantees. Combine with your entry logic and risk controls.
Offset Strike LinesOffset Strike Lines (OSL) is a tool designed to plot strike-based grid levels by offsetting one symbol against another. It compares two instruments (for example, futures vs. index) and projects evenly spaced horizontal lines above and below a calculated reference price. Each line is annotated with the adjusted counter-symbol price, making it easy to visualize relative levels across markets. Customization options include interval size, number of lines, text size, line and text colors — giving traders a clear, flexible framework for mapping out strike zones and price relationships.
DMI MTF Color Table v5DMI Multi-Timeframe Color Table v5
A comprehensive DMI (Directional Movement Index) table that displays trend direction and strength across multiple timeframes simultaneously. This indicator helps traders quickly assess market conditions and identify confluence across different time horizons.
Features:
Multi-timeframe analysis (7 configurable timeframes)
Color-coded cells based on trend strength and direction
Real-time current market condition display
Customizable strength thresholds and color schemes
Multiple display modes (All, DI+ Only, DI- Only, ADX Only)
Text-based strength classifications (STRONG/MEDIUM/WEAK)
Directional bias indicators (BULL/BEAR)
How It Works:
The table shows DI+, DI-, and ADX values across your chosen timeframes with intelligent color coding:
Green shades indicate bullish momentum (DI+ > DI-)
Red shades indicate bearish momentum (DI- > DI+)
Color intensity reflects trend strength based on ADX values
Current market condition appears in top-right corner
Display Options:
Toggle numerical values, strength text, and timeframe labels
Adjustable table size and transparency
Customizable color schemes for all conditions
Optional current timeframe DMI plot overlay
Educational Use:
This tool is designed for educational purposes to help understand multi-timeframe analysis and DMI interpretation. All trading decisions should be based on your own analysis and risk management.
Credits:
Original concept and development by Profitgang. If you use or modify this script, please provide appropriate credit to the original author.
Note: This indicator is for analysis purposes only. Past performance does not guarantee future results. Always conduct your own research and consider your risk tolerance before making trading decisions.
Smarter Money Concepts - Wyckoff Springs & Upthrusts [PhenLabs]📊Smarter Money Concepts - Wyckoff Springs & Upthrusts
Version: PineScript™v6
📌Description
Discover institutional manipulation in real-time with this advanced Wyckoff indicator that detects Springs (accumulation phases) and Upthrusts (distribution phases). It identifies when price tests support or resistance on high volume, followed by a strong recovery, signaling potential reversals where smart money accumulates or distributes positions. This tool solves the common problem of missing these subtle phase transitions, helping traders anticipate trend changes and avoid traps in volatile markets.
By combining volume spike detection, ATR-normalized recovery strength, and a sigmoid probability model, it filters out weak signals and highlights only high-confidence setups. Whether you’re swing trading or day trading, this indicator provides clear visual cues to align with institutional flows, improving entry timing and risk management.
🚀Points of Innovation
Sigmoid-based probability threshold for signal filtering, ensuring only statistically significant Wyckoff patterns trigger alerts
ATR-normalized recovery measurement that adapts to market volatility, unlike static recovery checks in traditional indicators
Customizable volume spike multiplier to distinguish institutional volume from retail noise
Integrated dashboard legend with position and size options for personalized chart visualization
Hidden probability plots for advanced users to analyze underlying math without chart clutter
🔧Core Components
Support/Resistance Calculator: Scans a user-defined lookback period to establish dynamic levels for Spring and Upthrust detection
Volume Spike Detector: Compares current volume to a 10-period SMA, multiplied by a configurable factor to identify significant surges
Recovery Strength Analyzer: Uses ATR to measure price recovery after breaks, normalizing for different market conditions
Probability Model: Applies sigmoid function to combine volume and recovery data, generating a confidence score for each potential signal
🔥Key Features
Spring Detection: Spots accumulation when price dips below support but recovers strongly, helping traders enter longs at potential bottoms
Upthrust Detection: Identifies distribution when price spikes above resistance but falls back, alerting to possible short opportunities at tops
Customizable Inputs: Adjust lookback, volume multiplier, ATR period, and probability threshold to match your trading style and market
Visual Signals: Clear + (green) and - (red) labels on charts for instant recognition of accumulation and distribution phases
Alert System: Triggers notifications for signals and probability thresholds, keeping you informed without constant monitoring
🎨Visualization
Spring Signal: Green upward label (+) below the bar, indicating strong recovery after support break for accumulation
Upthrust Signal: Red downward label (-) above the bar, showing failed breakout above resistance for distribution
Dashboard Legend: Customizable table explaining signals, positioned anywhere on the chart for quick reference
📖Usage Guidelines
Core Settings
Support/Resistance Lookback
Default: 20
Range: 5-50
Description: Sets bars back for S/R levels; lower for recent sensitivity, higher for stable long-term zones – ideal for spotting Wyckoff phases
Volume Spike Multiplier
Default: 1.5
Range: 1.0-3.0
Description: Multiplies 10-period volume SMA; higher values filter to significant spikes, confirming institutional involvement in patterns
ATR for Recovery Measurement
Default: 5
Range: 2-20
Description: ATR period for recovery strength; shorter for volatile markets, longer for smoother analysis of post-break recoveries
Phase Transition Probability Threshold
Default: 0.9
Range: 0.5-0.99
Description: Minimum sigmoid probability for signals; higher for strict filtering, ensuring only high-confidence Wyckoff setups
Display Settings
Dashboard Position
Default: Top Right
Range: Various positions
Description: Places legend table on chart; choose based on layout to avoid overlapping price action
Dashboard Text Size
Default: Normal
Range: Auto to Huge
Description: Adjusts legend text; larger for visibility, smaller for minimal space use
✅Best Use Cases
Swing Trading: Identify Springs for long entries in downtrends turning to accumulation
Day Trading: Catch Upthrusts for short scalps during intraday distribution at resistance
Trend Reversal Confirmation: Use in conjunction with other indicators to validate phase shifts in ranging markets
Volatility Plays: Spot signals in high-volume environments like news events for quick reversals
⚠️Limitations
May produce false signals in low-volume or sideways markets where volume spikes are unreliable
Depends on historical data, so performance varies in unprecedented market conditions or gaps
Probability model is statistical, not predictive, and cannot account for external factors like news
💡What Makes This Unique
Probability-Driven Filtering: Sigmoid model combines multiple factors for superior signal quality over basic Wyckoff detectors
Adaptive Recovery: ATR normalization ensures reliability across assets and timeframes, unlike fixed-threshold tools
User-Centric Design: Tooltips, customizable dashboard, and alerts make it accessible yet powerful for all trader levels
🔬How It Works
Calculate S/R Levels:
Uses the highest high and the lowest low over the lookback period to set dynamic zones
Establishes baseline for detecting breaks in Wyckoff patterns
Detect Breaks and Recovery:
Checks for price breaking support/resistance, then recovering on volume
Measures recovery strength via ATR for volatility adjustment
Apply Probability Model:
Combines volume spike and recovery into a sigmoid function for confidence score
Triggers signal only if above threshold, plotting visuals and alerts
💡Note:
For optimal results, combine with price action analysis and test settings on historical charts. Remember, Wyckoff patterns are most effective in trending markets – use lower probability thresholds for practice, then increase for live trading to focus on high-quality setups.
Key Levels & Session Highs/Lows by OdegosProfessional multi-timeframe support and resistance level indicator that automatically tracks and displays key price levels across different trading sessions and timeframes.
🎯 What it shows:
Session Open - Daily market open reference line
Asia & London Sessions - High/low levels from major trading sessions
Previous Day - Yesterday's actual high and low levels
Weekly & Monthly - Higher timeframe support/resistance levels
⚡ Smart Features:
Auto-combines overlapping levels with merged labels
Break detection - Lines stop when price breaks through (optional)
Timezone support - Works with any global timezone
Universal colors - Optimized for both light and dark chart themes
Clean interface - Organized settings with intuitive dropdowns
🛠️ Fully Customizable:
Individual show/hide toggles for each level type
Custom colors, line styles, and widths
Adjustable label text and positioning
Global text color override option
Perfect for day traders, swing traders, and anyone who relies on key support/resistance levels for market analysis.
Correlation HeatMap Matrix Data [TradingFinder]🔵 Introduction
Correlation is a statistical measure that shows the degree and direction of a linear relationship between two assets.
Its value ranges from -1 to +1 : +1 means perfect positive correlation, 0 means no linear relationship, and -1 means perfect negative correlation.
In financial markets, correlation is used for portfolio diversification, risk management, pairs trading, intermarket analysis, and identifying divergences.
Correlation HeatMap Matrix Data TradingFinder is a Pine Script v6 library that calculates and returns raw correlation matrix data between up to 20 symbols. It only provides the data – it does not draw or render the heatmap – making it ideal for use in other scripts that handle visualization or further analysis. The library uses ta.correlation for fast and accurate calculations.
It also includes two helper functions for visual styling :
CorrelationColor(corr) : takes the correlation value as input and generates a smooth gradient color, ranging from strong negative to strong positive correlation.
CorrelationTextColor(corr) : takes the correlation value as input and returns a text color that ensures optimal contrast over the background color.
Library
"Correlation_HeatMap_Matrix_Data_TradingFinder"
CorrelationColor(corr)
Parameters:
corr (float)
CorrelationTextColor(corr)
Parameters:
corr (float)
Data_Matrix(Corr_Period, Sym_1, Sym_2, Sym_3, Sym_4, Sym_5, Sym_6, Sym_7, Sym_8, Sym_9, Sym_10, Sym_11, Sym_12, Sym_13, Sym_14, Sym_15, Sym_16, Sym_17, Sym_18, Sym_19, Sym_20)
Parameters:
Corr_Period (int)
Sym_1 (string)
Sym_2 (string)
Sym_3 (string)
Sym_4 (string)
Sym_5 (string)
Sym_6 (string)
Sym_7 (string)
Sym_8 (string)
Sym_9 (string)
Sym_10 (string)
Sym_11 (string)
Sym_12 (string)
Sym_13 (string)
Sym_14 (string)
Sym_15 (string)
Sym_16 (string)
Sym_17 (string)
Sym_18 (string)
Sym_19 (string)
Sym_20 (string)
🔵 How to use
Import the library into your Pine Script using the import keyword and its full namespace.
Decide how many symbols you want to include in your correlation matrix (up to 20). Each symbol must be provided as a string, for example FX:EURUSD .
Choose the correlation period (Corr\_Period) in bars. This is the lookback window used for the calculation, such as 20, 50, or 100 bars.
Call Data_Matrix(Corr_Period, Sym_1, ..., Sym_20) with your selected parameters. The function will return an array containing the correlation values for every symbol pair (upper triangle of the matrix plus diagonal).
For example :
var string Sym_1 = '' , var string Sym_2 = '' , var string Sym_3 = '' , var string Sym_4 = '' , var string Sym_5 = '' , var string Sym_6 = '' , var string Sym_7 = '' , var string Sym_8 = '' , var string Sym_9 = '' , var string Sym_10 = ''
var string Sym_11 = '', var string Sym_12 = '', var string Sym_13 = '', var string Sym_14 = '', var string Sym_15 = '', var string Sym_16 = '', var string Sym_17 = '', var string Sym_18 = '', var string Sym_19 = '', var string Sym_20 = ''
switch Market
'Forex' => Sym_1 := 'EURUSD' , Sym_2 := 'GBPUSD' , Sym_3 := 'USDJPY' , Sym_4 := 'USDCHF' , Sym_5 := 'USDCAD' , Sym_6 := 'AUDUSD' , Sym_7 := 'NZDUSD' , Sym_8 := 'EURJPY' , Sym_9 := 'EURGBP' , Sym_10 := 'GBPJPY'
,Sym_11 := 'AUDJPY', Sym_12 := 'EURCHF', Sym_13 := 'EURCAD', Sym_14 := 'GBPCAD', Sym_15 := 'CADJPY', Sym_16 := 'CHFJPY', Sym_17 := 'NZDJPY', Sym_18 := 'AUDNZD', Sym_19 := 'USDSEK' , Sym_20 := 'USDNOK'
'Stock' => Sym_1 := 'NVDA' , Sym_2 := 'AAPL' , Sym_3 := 'GOOGL' , Sym_4 := 'GOOG' , Sym_5 := 'META' , Sym_6 := 'MSFT' , Sym_7 := 'AMZN' , Sym_8 := 'AVGO' , Sym_9 := 'TSLA' , Sym_10 := 'BRK.B'
,Sym_11 := 'UNH' , Sym_12 := 'V' , Sym_13 := 'JPM' , Sym_14 := 'WMT' , Sym_15 := 'LLY' , Sym_16 := 'ORCL', Sym_17 := 'HD' , Sym_18 := 'JNJ' , Sym_19 := 'MA' , Sym_20 := 'COST'
'Crypto' => Sym_1 := 'BTCUSD' , Sym_2 := 'ETHUSD' , Sym_3 := 'BNBUSD' , Sym_4 := 'XRPUSD' , Sym_5 := 'SOLUSD' , Sym_6 := 'ADAUSD' , Sym_7 := 'DOGEUSD' , Sym_8 := 'AVAXUSD' , Sym_9 := 'DOTUSD' , Sym_10 := 'TRXUSD'
,Sym_11 := 'LTCUSD' , Sym_12 := 'LINKUSD', Sym_13 := 'UNIUSD', Sym_14 := 'ATOMUSD', Sym_15 := 'ICPUSD', Sym_16 := 'ARBUSD', Sym_17 := 'APTUSD', Sym_18 := 'FILUSD', Sym_19 := 'OPUSD' , Sym_20 := 'USDT.D'
'Custom' => Sym_1 := Sym_1_C , Sym_2 := Sym_2_C , Sym_3 := Sym_3_C , Sym_4 := Sym_4_C , Sym_5 := Sym_5_C , Sym_6 := Sym_6_C , Sym_7 := Sym_7_C , Sym_8 := Sym_8_C , Sym_9 := Sym_9_C , Sym_10 := Sym_10_C
,Sym_11 := Sym_11_C, Sym_12 := Sym_12_C, Sym_13 := Sym_13_C, Sym_14 := Sym_14_C, Sym_15 := Sym_15_C, Sym_16 := Sym_16_C, Sym_17 := Sym_17_C, Sym_18 := Sym_18_C, Sym_19 := Sym_19_C , Sym_20 := Sym_20_C
= Corr.Data_Matrix(Corr_period, Sym_1 ,Sym_2 ,Sym_3 ,Sym_4 ,Sym_5 ,Sym_6 ,Sym_7 ,Sym_8 ,Sym_9 ,Sym_10,Sym_11,Sym_12,Sym_13,Sym_14,Sym_15,Sym_16,Sym_17,Sym_18,Sym_19,Sym_20)
Loop through or index into this array to retrieve each correlation value for your custom layout or logic.
Pass each correlation value to CorrelationColor() to get the corresponding gradient background color, which reflects the correlation’s strength and direction (negative to positive).
For example :
Corr.CorrelationColor(SYM_3_10)
Pass the same correlation value to CorrelationTextColor() to get the correct text color for readability against that background.
For example :
Corr.CorrelationTextColor(SYM_1_1)
Use these colors in a table or label to render your own heatmap or any other visualization you need.
Lot Size + Margin InfoThis indicator is designed to give Futures & Options traders instant access to lot size and estimated margin requirements for the instrument they are viewing — directly on their TradingView chart. It combines real-time symbol detection with a built-in, regularly updated margin lookup table (sourced from Kotak Securities’ published margin requirements), while also handling fallback logic for unknown or unsupported symbols.
---
### What It Does
* Automatically Detects the Instrument Type
Identifies whether the current chart’s symbol is a futures contract, option, or a cash/spot instrument.
* Shows Accurate Lot Size
For supported F\&O symbols, it fetches the correct lot size directly from exchange data.
For options, it retrieves the lot size from the option’s point value.
For cash/spot symbols with linked futures, it uses the futures lot size.
* Calculates Estimated Margin
* For futures: `Lot Size × Current Price × Margin%` (Margin% sourced from the internal lookup table).
* For options: `Lot Size × Current Price` (simple multiplication, as options margin ≈ premium cost).
* For unsupported or non-FnO symbols: Displays "No FnO".
* Fallback Margin Logic
If a symbol is missing from the margin lookup table, the script applies a user-defined default margin percentage and highlights the data in orange to indicate it’s using fallback values.
* Debug Mode for Transparency
A toggle to display the exact symbol string used for fetching lot size and margin, so traders can verify the data source.
---
### How It Works
1. Symbol Normalization
The script standardizes symbol names to match the margin table format (e.g., converting `"NIFTY1!"` to `"NIFTY"`).
2. Type-Based Handling
* Futures – Uses point value for lot size, applies specific margin % from the table.
* Options – Uses option point value for lot size, margin is simply premium × lot size.
* Cash Symbols with Linked Futures – Attempts to find and use the associated futures contract for lot/margin data.
* Unsupported Symbols – Displays `"No FnO"`.
3. Margin Table Integration
The margin % table is manually updated from a reliable broker’s margin sheet (Kotak Securities) — ensuring alignment with real trading conditions.
4. Customizable Display
* Position (Top Right / Bottom Left / Bottom Right)
* Table background color, text color, font size, border width
* Editable label text for lot size and margin display
* Toggleable lot size and margin sections
---
### How to Use
1. Add the Indicator to Your Chart – Works on any NSE Futures, Options, or Cash symbol with linked F\&O.
2. Configure Display Settings – Choose whether to show lot size, margin, or both, and place the info table where you prefer.
3. Adjust Fallback Margin % – If you trade less common contracts, set your default margin % to reflect your broker’s requirement.
4. Enable Debug Mode (Optional) – To see the exact symbol source the script is using.
---
### Best For
* Intraday & Positional F\&O Traders who need instant clarity on lot size and margin before entering trades.
* Options Sellers & Buyers who want quick cost estimates.
* Traders Switching Symbols Quickly — saves time by removing the need to check the broker’s margin sheet manually.
---
💡 Pro Tip: Since margin requirements can change, keep the script updated whenever your broker revises margin data. This version’s margin table is updated as of 13-08-2025.
Market Structure (DeadCat)🌟 Market Structure (DeadCat) - Indicator Overview 🌟
The Market Structure (DeadCat) indicator plots swing highs and lows (HH, HL, LH, LL) using pivot points, helping you spot uptrends, downtrends, and potential reversals. Perfect for traders who use market structure.
🌟 Key Features 🌟
🔹 Swing Point Labels
HH (Higher High): Signals uptrend strength.
HL (Higher Low): Marks bullish support.
LH (Lower High): Hints at weakening uptrend or reversal.
LL (Lower Low): Confirms downtrend momentum.
🔹 Trend Detection
Uptrend: Tracks HH/HL for bullish momentum.
Downtrend: Tracks LH/LL for bearish momentum.
Waits for breaks of prior HH/HL or LH/LL to confirm new swing points, ensuring reliable signals. 🔄
🔹 Customizable Labels
Adjust label text color (default: black) to suit your chart. Supports up to 500 labels for a clean, focused view. 🖌️
🌟 Indicator Settings 🌟
Swing Length: Fixed at 20 bars (left) and 2 bars (right) for pivot detection.
Label Color: Customize text color for better visibility.
Fibs Has Lied 🌟 Fibs Has Lied - Indicator Overview 🌟
Designed for indices like US30, NQ, and SPX, this indicator highlights setups where price interacts with key EMA levels during specific trading sessions (default: 6:30–11:30 AM EST).
🌟 Key Features & Levels 🌟
🔹EMA Crossover Setups
The indicator uses the 100-period and 200-period EMAs to identify bullish and bearish setups:
- Bullish Setup: Triggers when the 100 EMA crosses above the 200 EMA, followed by two consecutive candles opening above the 100 EMA, with the low within a specified point distance (e.g., 20 points for US30).
- Bearish Setup: Triggers when the 100 EMA crosses below the 200 EMA, followed by two consecutive candles opening below the 100 EMA, with the high within the point distance.
- Signals are marked with green (buy) or red (sell) triangles and text, ensuring you don’t miss a setup. 📈
🔹 Reset Conditions for Re-Entries
After an initial setup, the indicator watches for “reset” opportunities:
- Buy Reset: If price moves below the 200 EMA after a bullish crossover, then returns with two consecutive candles where lows are above the 100 EMA (within point distance), a new buy signal is plotted.
- Sell Reset: If price moves above the 200 EMA after a bearish crossover, then returns with two consecutive candles where highs are below the 100 EMA (within point distance), a new sell signal is plotted.
This feature captures additional entries after liquidity grabs or fakeouts, aligning with ICT’s manipulation concepts. 🔄
🔹 Session-Based Filtering
Focus your trades during high-liquidity windows! The default session (6:30–11:30 AM EST, New York timezone) targets the London/NY overlap, where price often seeks liquidity or sets up for reversals. Toggle the time filter off for 24/7 signals if desired. 🕒
🔹Symbol-Specific Point Distance
Customizable entry zones based on your chosen index:
- US30: 20 points from the 100 EMA.
- NQ: 3 points from the 100 EMA.
- SPX: 2.5 points from the 100 EMA.
This ensures setups are tailored to the volatility of your market, maximizing relevance. 🎯
🔹 Market Structure Markers (Optional)
Visualize swing points with pivot-based labels:
- HH (Higher High): Signals uptrend continuation.
- HL (Higher Low): Indicates potential bullish support.
- LH (Lower High): Suggests weakening uptrend or reversal.
- LL (Lower Low): Points to downtrend continuation.
- Toggle these on/off to keep your chart clean while analyzing trend direction. 📊
🔹 EMA Visualization
Optionally plot the 100 EMA (blue) and 200 EMA (red) to see key levels where price reacts. These act as dynamic support/resistance, perfect for spotting liquidity pools or ICT’s Power of 3 setups. ⚖️
🌟 Customization Options 🌟
- Symbol Selection: Choose US30, NQ, or SPX to adjust point distance for entries.
- Time Filter: Enable/disable the 6:30–11:30 AM EST session to focus on high-liquidity periods.
- EMA Display: Toggle 100/200 EMAs on/off to reduce chart clutter.
- Market Structure: Show/hide HH/HL/LH/LL labels for cleaner analysis.
- Signal Markers: Green (buy) and red (sell) triangles with text are auto-plotted for easy identification.
🌟 Usage Tips 🌟
- Best Timeframes: Use on 3m for intraday scalping and 30m for swing trades.
- Combine with ICT Tools: Pair with order blocks, fair value gaps, or kill zones for stronger setups.
- Focus on Session: The default 6:30–11:30 AM EST session captures London/NY volatility—perfect for liquidity-driven moves.
- Avoid Overcrowding: Disable market structure or EMAs if you only want setup signals.
Enhanced 4H Candle Countdown & High/Low IndicatorBy profitgang
This Pine Script indicator provides real-time tracking of 4-hour timeframe levels with an integrated countdown timer, designed to help traders monitor key support and resistance zones.
Key Features
📊 Visual Elements
4H High/Low Lines: Clear visualization of previous 4-hour candle high and low levels
Range Fill: Subtle background fill between high and low for better context
Mid-Level Line: Shows the middle point of the 4H range
Position Indicator: Visual cue showing current price position within the range
⏰ Countdown Timer
Real-time countdown to next 4H candle close
Customizable table position (9 different locations)
Adjustable text size (6 size options from Tiny to Huge)
Distance calculations showing percentage distance from key levels
🎯 Signal Generation
Long signals when price crosses above 4H low
Short signals when price crosses below 4H high
RSI confluence filter to reduce false signals
Background highlighting for active signals
TradingView alerts compatible
⚙️ Customization Options
Toggle all features on/off independently
Custom colors for all elements
Table positioning (top/middle/bottom + left/center/right)
Text size selection for optimal readability
Alert notifications for level breaks and updates
How It Works
The indicator fetches the previous 4-hour candle's high and low values and displays them as horizontal lines on your current timeframe chart. It continuously calculates the time remaining until the current 4H candle closes and presents this information in a clean, customizable table.
Use Cases
Swing Trading: Identify key 4H support and resistance levels
Intraday Trading: Monitor when new 4H levels will be established
Risk Management: Calculate distance from key levels for position sizing
Multi-timeframe Analysis: Combine with lower timeframe setups
Educational Purpose
This indicator is designed for educational and analytical purposes to help traders understand price action relative to higher timeframe levels. It provides clear visual feedback about market structure and timing.
Settings Groups
Display Settings: Toggle features, positioning, and sizing
Colors: Customize all visual elements
Signal Settings: Configure alert conditions and confluence filters
Compatibility
Works on all timeframes (recommended for 1m to 1H charts)
Compatible with all instruments
Includes proper alert functionality for automated notifications
Optimized for both light and dark themes
This indicator does not provide financial advice. Always conduct your own research and risk management before making trading decisions.
Adaptive Candle Signals█ OVERVIEW
The Adaptive Candle Signals indicator is a Pine Script® tool designed to identify key candlestick patterns on the chart, such as Bullish Engulfing, Bearish Engulfing, Piercing Line, Dark Cloud Cover, Morning Star, Evening Star, Three White Soldiers, Three Black Crows, and Three Inside Up/Down. The indicator allows customization of settings, including a Moving Average (MA) filter, candle size control, and maximum wick percentage, enabling precise adaptation to various trading strategies. Signals are displayed as labels on the chart, and each pattern can trigger alerts for user convenience.
█ CONCEPTS
The indicator is designed with flexibility and readability in mind. Its main features include:
Features
Signal Filtering: Enables the use of a Moving Average (MA) filter to confirm signals based on trend direction. Bullish signals are generated when the price is above the MA, and bearish signals when below.
Pattern Customization: Users can enable or disable individual candlestick patterns and adjust their parameters, such as maximum wick percentage or candle size multiplier. The candle size multiplier applies to the largest candle in the pattern and determines its minimum size relative to the average candle body size over a specified volatility period.
Labels and Colors: Signals are displayed as clear labels with customizable colors for bullish and bearish patterns.
Alerts: Each pattern has a dedicated alert function, facilitating integration with automated trading strategies.
List of Patterns
The indicator recognizes the following candlestick patterns (labels displayed in parentheses):
Bullish Engulfing (BE): Signals a potential upward reversal after a downtrend.
Bearish Engulfing (BE): Indicates a possible downward reversal after an uptrend.
Piercing Line (PL): A bullish pattern suggesting a bounce from support.
Dark Cloud Cover (DC): A bearish pattern indicating a potential downward reversal.
Morning Star (MS): A three-candle bullish pattern signaling an upward reversal.
Evening Star (ES): A three-candle bearish pattern indicating a downward reversal.
Three White Soldiers (3WS): A strong bullish signal based on three large bullish candles.
Three Black Crows (3BC): A strong bearish signal based on three large bearish candles.
Three Inside Up/Down (3Up/3Dn): Patterns indicating trend reversal based on an inside bar structure.
Settings
Settings are organized as follows:
MA Filter: Allows enabling a Moving Average (SMA, EMA, WMA) to filter signals based on trend direction.
Pattern Parameters: Each pattern has its own settings, such as volatility period, candle size multiplier, and maximum wick percentage. The size of the largest candle in the pattern is compared to the average candle body size over the specified volatility period.
Colors and Labels: Users can customize label colors and their distance from candles to improve readability.
█ SETTINGS
Detailed description of the indicator’s settings:
MA Filter:
Use MA Filter: Enables/disables the Moving Average filter.
MA Length: Specifies the period of the Moving Average (default: 50).
MA Type: Choose between SMA, EMA, or WMA.
MA Source: Select the data source (default: close price).
Pattern Settings:
Enable Pattern: Checkbox for each pattern (e.g., Bullish Engulfing, Morning Star).
Maximum Wick Percentage: Defines the maximum allowable wick size as a percentage of the candle body.
Big Candle Filter: Enables/disables checking if the largest candle in the pattern is larger than the average over the specified volatility period.
Volatility Period: Sets the period for calculating the average candle body size.
Candle Multiplier: Multiplier determining the minimum size of the largest candle in the pattern relative to the average candle body size over the specified volatility period.
Appearance:
Signal Text Color: Color of the label text (default: white).
Bullish Label Color: Color for bullish signals (default: green).
Bearish Label Color: Color for bearish signals (default: red).
Label Offset Factor: Controls the distance of labels from candles (from 0.0 to 1.0).
█ HOW TO USE
Add the indicator to your TradingView chart.
Configure the settings in the indicator’s dialog box:
Enable desired candlestick patterns.
Adjust the MA filter parameters to restrict signals to the trend.
Set colors and label offset for better readability.
Enable alerts for selected patterns to receive real-time notifications.
Monitor the labels on the chart and use them alongside other technical analysis tools.
█ LIMITATIONS
The indicator relies on historical price data and may produce false signals in volatile market conditions.
The big candle filter may be less effective on charts with low volatility.
The indicator performs best when combined with other analysis methods, such as support and resistance levels.
IU Indicators DashboardDESCRIPTION
The IU Indicators Dashboard is a comprehensive multi-stock monitoring tool that provides real-time technical analysis for up to 10 different stocks simultaneously. This powerful indicator creates a customizable table overlay that displays the trend status of multiple technical indicators across your selected stocks, giving you an instant overview of market conditions without switching between charts.
Perfect for portfolio monitoring, sector analysis, and quick market screening, this dashboard consolidates critical technical data into one easy-to-read interface with color-coded trend signals.
USER INPUTS
Stock Selection (10 Configurable Stocks):
- Stock 1-10: Customize any symbols (Default: NSE:CDSL, NSE:RELIANCE, NSE:VEDL, NSE:TCS, NSE:BEL, NSE:BHEL, NSE:TATAPOWER, NSE:TATASTEEL, NSE:ITC, NSE:LT)
Technical Indicator Parameters:
- EMA 1 Length: First Exponential Moving Average period (Default: 20)
- EMA 2 Length: Second Exponential Moving Average period (Default: 50)
- EMA 3 Length: Third Exponential Moving Average period (Default: 200)
- RSI Length: Relative Strength Index calculation period (Default: 14)
- SuperTrend Length: SuperTrend indicator period (Default: 10)
- SuperTrend Factor: SuperTrend multiplier factor (Default: 3.0)
Visual Customization:
- Table Size: Choose from Normal, Tiny, Small, or Large
- Table Background Color: Customize dashboard background
- Table Frame Color: Set frame border color
- Table Border Color: Configure border styling
- Text Color: Set text display color
- Bullish Color: Color for positive/bullish signals (Default: Green)
- Bearish Color: Color for negative/bearish signals (Default: Red)
LOGIC OF THE INDICATOR
The dashboard employs a multi-timeframe analysis approach using five key technical indicators:
1. Triple EMA Analysis
- Compares current price against three different EMA periods (20, 50, 200)
- Bullish Signal: Price above EMA level
- Bearish Signal: Price below EMA level
- Provides short-term, medium-term, and long-term trend perspective
2. RSI Momentum Analysis
- Uses 14-period RSI with 50-level threshold
- Bullish Signal: RSI > 50 (upward momentum)
- Bearish Signal: RSI < 50 (downward momentum)
- Identifies momentum strength and potential reversals
3. SuperTrend Direction
- Utilizes SuperTrend with configurable length and factor
- Bullish Signal: SuperTrend direction = -1 (uptrend)
- Bearish Signal: SuperTrend direction = 1 (downtrend)
- Provides clear trend direction with volatility-adjusted signals
4. MACD Histogram Analysis
- Uses standard MACD (12, 26, 9) histogram values
- Bullish Signal: Histogram > 0 (bullish momentum)
- Bearish Signal: Histogram < 0 (bearish momentum)
- Identifies momentum shifts and trend confirmations
5. Real-time Data Processing
- Implements request.security() for multi-symbol data retrieval
- Uses barstate.isrealtime logic for accurate live data
- Processes data only on the last bar for optimal performance
WHY IT IS UNIQUE
Multi-Stock Monitoring
- Monitor up to 10 different stocks simultaneously on a single chart
- No need to switch between multiple charts or timeframes
Highly Customizable Interface
- Full color customization for personalized visual experience
- Adjustable table size and positioning
- Clean, professional dashboard design
Real-time Analysis
- Live data processing with proper real-time handling
- Instant visual feedback through color-coded signals
- Optimized performance with smart data retrieval
Comprehensive Technical Coverage
- Combines trend-following, momentum, and volatility indicators
- Multiple timeframe perspective through different EMA periods
- Balanced approach using both lagging and leading indicators
Flexible Configuration
- Easy symbol switching for different markets (NSE, BSE, NYSE, NASDAQ)
- Adjustable indicator parameters for different trading styles
- Suitable for both swing trading and position trading
HOW USERS CAN BENEFIT FROM IT
Portfolio Management
- Quick Portfolio Health Check: Instantly assess the technical status of your entire stock portfolio
- Diversification Analysis: Monitor stocks across different sectors to ensure balanced exposure
- Risk Management: Identify which positions are showing bearish signals for potential exit strategies
- Rebalancing Decisions: Spot strongest performers for potential position increases
Market Screening and Analysis
- Sector Rotation: Compare different sector stocks to identify rotation opportunities
- Relative Strength Analysis: Quickly identify which stocks are outperforming or underperforming
- Market Breadth Assessment: Gauge overall market sentiment by monitoring diverse stock selections
- Trend Confirmation: Validate market trends by observing multiple stock behaviors
Time-Efficient Trading
- Single-Glance Analysis: Get complete technical overview without chart-hopping
- Pre-Market Preparation: Quickly assess overnight changes across multiple positions
- Intraday Monitoring: Track multiple opportunities simultaneously during trading hours
- End-of-Day Review: Efficiently review all watched stocks for next-day planning
Strategic Decision Making
- Entry Point Identification: Spot stocks showing bullish alignment across multiple indicators
- Exit Signal Recognition: Identify positions showing deteriorating technical conditions
- Swing Trading Opportunities: Find stocks with favorable technical setups for swing trades
- Long-term Investment Guidance: Use 200 EMA signals for long-term position decisions
Educational Benefits
- Pattern Recognition: Learn how different indicators behave across various market conditions
- Correlation Analysis: Understand how stocks move relative to each other
- Technical Analysis Learning: Observe multiple indicator interactions in real-time
- Market Sentiment Understanding: Develop better market timing skills through multi-stock observation
Workflow Optimization
- Reduced Chart Clutter: Keep your main chart clean while monitoring multiple stocks
- Faster Analysis: Complete technical analysis of 10 stocks in seconds instead of minutes
- Consistent Methodology: Apply the same technical criteria across all monitored stocks
- Alert Integration: Easy visual identification of stocks requiring immediate attention
This indicator is designed for traders and investors who want to maximize their market awareness while minimizing analysis time. Whether you're managing a portfolio, screening for opportunities, or learning technical analysis, the IU Indicators Dashboard provides the comprehensive overview you need for better trading decisions.
DISCLAIMER :
This indicator is not financial advice, it's for educational purposes only highlighting the power of coding( pine script) in TradingView, I am not a SEBI-registered advisor. Trading and investing involve risk, and you should consult with a qualified financial advisor before making any trading decisions. I do not guarantee profits or take responsibility for any losses you may incur.
Mutanabby_AI | Algo Pro Strategy# Mutanabby_AI | Algo Pro Strategy: Advanced Candlestick Pattern Trading System
## Strategy Overview
The Mutanabby_AI Algo Pro Strategy represents a systematic approach to automated trading based on advanced candlestick pattern recognition and multi-layered technical filtering. This strategy transforms traditional engulfing pattern analysis into a comprehensive trading system with sophisticated risk management and flexible position sizing capabilities.
The strategy operates on a long-only basis, entering positions when bullish engulfing patterns meet specific technical criteria and exiting when bearish engulfing patterns indicate potential trend reversals. The system incorporates multiple confirmation layers to enhance signal reliability while providing comprehensive customization options for different trading approaches and risk management preferences.
## Core Algorithm Architecture
The strategy foundation relies on bullish and bearish engulfing candlestick pattern recognition enhanced through technical analysis filtering mechanisms. Entry signals require simultaneous satisfaction of four distinct criteria: confirmed bullish engulfing pattern formation, candle stability analysis indicating decisive price action, RSI momentum confirmation below specified thresholds, and price decline verification over adjustable lookback periods.
The candle stability index measures the ratio between candlestick body size and total range including wicks, ensuring only well-formed patterns with clear directional conviction generate trading signals. This filtering mechanism eliminates indecisive market conditions where pattern reliability diminishes significantly.
RSI integration provides momentum confirmation by requiring oversold conditions before entry signal generation, ensuring alignment between pattern formation and underlying momentum characteristics. The RSI threshold remains fully adjustable to accommodate different market conditions and volatility environments.
Price decline verification examines whether current prices have decreased over a specified period, confirming that bullish engulfing patterns occur after meaningful downward movement rather than during sideways consolidation phases. This requirement enhances the probability of successful reversal pattern completion.
## Advanced Position Management System
The strategy incorporates dual position sizing methodologies to accommodate different account sizes and risk management approaches. Percentage-based position sizing calculates trade quantities as equity percentages, enabling consistent risk exposure across varying account balances and market conditions. This approach proves particularly valuable for systematic trading approaches and portfolio management applications.
Fixed quantity sizing provides precise control over trade sizes independent of account equity fluctuations, offering predictable position management for specific trading strategies or when implementing precise risk allocation models. The system enables seamless switching between sizing methods through simple configuration adjustments.
Position quantity calculations integrate seamlessly with TradingView's strategy testing framework, ensuring accurate backtesting results and realistic performance evaluation across different market conditions and time periods. The implementation maintains consistency between historical testing and live trading applications.
## Comprehensive Risk Management Framework
The strategy features dual stop loss methodologies addressing different risk management philosophies and market analysis approaches. Entry price-based stop losses calculate stop levels as fixed percentages below entry prices, providing predictable risk exposure and consistent risk-reward ratio maintenance across all trades.
The percentage-based stop loss system enables precise risk control by limiting maximum loss per trade to predetermined levels regardless of market volatility or entry timing. This approach proves essential for systematic trading strategies requiring consistent risk parameters and capital preservation during adverse market conditions.
Lowest low-based stop losses identify recent price support levels by analyzing minimum prices over adjustable lookback periods, placing stops below these technical levels with additional buffer percentages. This methodology aligns stop placement with market structure rather than arbitrary percentage calculations, potentially improving stop loss effectiveness during normal market fluctuations.
The lookback period adjustment enables optimization for different timeframes and market characteristics, with shorter periods providing tighter stops for active trading and longer periods offering broader stops suitable for position trading approaches. Buffer percentage additions ensure stops remain below obvious support levels where other market participants might place similar orders.
## Visual Customization and Interface Design
The strategy provides comprehensive visual customization through eight predefined color schemes designed for different chart backgrounds and personal preferences. Color scheme options include Classic bright green and red combinations, Ocean themes featuring blue and orange contrasts, Sunset combinations using gold and crimson, and Neon schemes providing high visibility through bright color selections.
Professional color schemes such as Forest, Royal, and Fire themes offer sophisticated alternatives suitable for business presentations and professional trading environments. The Custom color scheme enables precise color selection through individual color picker controls, maintaining maximum flexibility for specific visual requirements.
Label styling options accommodate different chart analysis preferences through text bubble, triangle, and arrow display formats. Size adjustments range from tiny through huge settings, ensuring appropriate visual scaling across different screen resolutions and chart configurations. Text color customization maintains readability across various chart themes and background selections.
## Signal Quality Enhancement Features
The strategy incorporates signal filtering mechanisms designed to eliminate repetitive signal generation during choppy market conditions. The disable repeating signals option prevents consecutive identical signals until opposing conditions occur, reducing overtrading during consolidation phases and improving overall signal quality.
Signal confirmation requirements ensure all technical criteria align before trade execution, reducing false signal occurrence while maintaining reasonable trading frequency for active strategies. The multi-layered approach balances signal quality against opportunity frequency through adjustable parameter optimization.
Entry and exit visualization provides clear trade identification through customizable labels positioned at relevant price levels. Stop loss visualization displays active risk levels through colored line plots, ensuring complete transparency regarding current risk management parameters during live trading operations.
## Implementation Guidelines and Optimization
The strategy performs effectively across multiple timeframes with optimal results typically occurring on intermediate timeframes ranging from fifteen minutes through four hours. Higher timeframes provide more reliable pattern formation and reduced false signal occurrence, while lower timeframes increase trading frequency at the expense of some signal reliability.
Parameter optimization should focus on RSI threshold adjustments based on market volatility characteristics and candlestick pattern timeframe analysis. Higher RSI thresholds generate fewer but potentially higher quality signals, while lower thresholds increase signal frequency with corresponding reliability considerations.
Stop loss method selection depends on trading style preferences and market analysis philosophy. Entry price-based stops suit systematic approaches requiring consistent risk parameters, while lowest low-based stops align with technical analysis methodologies emphasizing market structure recognition.
## Performance Considerations and Risk Disclosure
The strategy operates exclusively on long positions, making it unsuitable for bear market conditions or extended downtrend periods. Users should consider market environment analysis and broader trend assessment before implementing the strategy during adverse market conditions.
Candlestick pattern reliability varies significantly across different market conditions, with higher reliability typically occurring during trending markets compared to ranging or volatile conditions. Strategy performance may deteriorate during periods of reduced pattern effectiveness or increased market noise.
Risk management through stop loss implementation remains essential for capital preservation during adverse market movements. The strategy does not guarantee profitable outcomes and requires proper position sizing and risk management to prevent significant capital loss during unfavorable trading periods.
## Technical Specifications
The strategy utilizes standard TradingView Pine Script functions ensuring compatibility across all supported instruments and timeframes. Default configuration employs 14-period RSI calculations, adjustable candle stability thresholds, and customizable price decline verification periods optimized for general market conditions.
Initial capital settings default to $10,000 with percentage-based equity allocation, though users can adjust these parameters based on account size and risk tolerance requirements. The strategy maintains detailed trade logs and performance metrics through TradingView's integrated backtesting framework.
Alert integration enables real-time notification of entry and exit signals, stop loss executions, and other significant trading events. The comprehensive alert system supports automated trading applications and manual trade management approaches through detailed signal information provision.
## Conclusion
The Mutanabby_AI Algo Pro Strategy provides a systematic framework for candlestick pattern trading with comprehensive risk management and position sizing flexibility. The strategy's strength lies in its multi-layered confirmation approach and sophisticated customization options, enabling adaptation to various trading styles and market conditions.
Successful implementation requires understanding of candlestick pattern analysis principles and appropriate parameter optimization for specific market characteristics. The strategy serves traders seeking automated execution of proven technical analysis techniques while maintaining comprehensive control over risk management and position sizing methodologies.
Gelişmiş Mum Ters StratejiAdvanced Candle Reversal Strategy Overview
This TradingView PineScript indicator detects potential reversal signals in candlestick patterns, focusing on a sequence of directional candles followed by a wick-based reversal candle. Here's a step-by-step breakdown:
User Inputs:
candleCount (default: 6): Number of consecutive candles required (2–20).
wickRatio (default: 1.5): Minimum wick-to-body ratio for reversal (1.0–5.0).
Options to show background colors and an info table.
Candle Calculations:
Computes body size (|close - open|), upper wick (high - max(close, open)), and lower wick (min(close, open) - low).
Identifies bullish (close > open) or bearish (close < open) candles.
Checks for long upper wick (≥ body * wickRatio) for short signals or long lower wick for long signals.
Sequence Check:
Verifies if the last candleCount candles are all bearish (for long signal) or all bullish (for short signal), including the current candle.
Signal Conditions:
Long Signal: candleCount bearish candles + current candle has long lower wick (plotted as green upward triangle below bar with "LONG" text).
Short Signal: candleCount bullish candles + current candle has long upper wick (plotted as red downward triangle above bar with "SHORT" text).
Additional Features:
Alerts for signals with custom messages.
Optional translucent background color (green for long, red for short).
Plots tiny crosses for long wicks not triggering full signals (yellow above for upper, orange below for lower).
Info table (top-right): Displays strategy summary, candle count, and signal explanations.
Debug label: On signals, shows wick/body ratio above the bar.
The strategy aims for reversals after trends (e.g., after 6 red candles, a red candle with long lower wick signals buy). Customize via inputs; backtest for effectiveness. Not financial advice.
Position Size 📐 DT/ST (Today's Open)💡 Purpose:
This indicator automatically calculates intraday (DT) and swing trading (ST) position sizes based on your account capital, risk per trade, and stop-loss percentage, using today’s daily open price as the entry price reference.
⚙️ Main Functionalities:
Dynamic Position Sizing
Calculates Full size position based on the maximum risk you allow per trade.
Breaks it down into ¼ Size, ⅓ Size, and ½ Size positions for flexible scaling.
Two Distinct Trading Styles:
DT (Day Trading) – Uses your specified intraday stop-loss % (default: 2%).
ST (Swing Trading) – Uses your specified swing stop-loss % (default: 10%).
Lot Size Rounding
Automatically rounds quantities to a chosen lot size (e.g., 1 for cash equity or futures lot size for derivatives).
Customizable Table Position
Display the table anywhere on your chart: Top Right, Top Left, Bottom Right, or Bottom Left.
Optimized for Dark or Light Themes
Yellow header with black text for visibility.
Blue row labels for strategy type.
Grey background with white text for calculated values.
Live Market Adaptation
All values update in real-time as today’s daily open price changes (on new daily candles).
Works for any symbol, asset class, or time frame.
🧮 Formula:
Position Size (Full) = Max Risk ₹ / (Price × StopLoss%)
¼, ⅓, and ½ Sizes = Scaled from Full size
📌 Ideal For:
Traders who want quick, ready-to-use position sizes right on their chart.
Those who follow fixed risk-per-trade and need fast decision-making without manual calculations.
Taiyoz Gaps1. Purpose
Tyoz Gaps highlights “gaps” between yesterday’s close and today’s open directly on your chart. A gap occurs when the opening price is significantly above or below the prior bar’s close. By drawing persistent boxes around each gap, you can instantly see where price left a void and monitor when (or if) that void gets completely filled.
2. Gap Detection Logic
Threshold: A gap is only detected if the open-to-previous-close difference exceeds a user-defined “Minimal Deviation” (percentage of the 14-bar average high-low range).
Direction:
Gap Up: today’s open > yesterday’s close
Gap Down: today’s open < yesterday’s close
3. Box Drawing
For each detected gap, the script draws a rectangular box spanning from yesterday’s close level to today’s open level.
Border & Fill Colors are configurable separately for up-gaps and down-gaps.
Boxes extend to the right as new bars form.
4. Display & Filtering Options
Show Gap Up / Show Gap Down toggles let you hide bullish or bearish gaps independently.
Max Number of Gaps: Limits how many boxes remain on-screen; oldest boxes are removed when the limit is exceeded.
Limit Max Gap Trail Length: Optionally force-close any gap box after a given number of bars, even if unfilled.
5. Closing Logic
Full-Fill Only: A gap box stays visible until price fully “fills” it—i.e., for an up-gap, price must exceed the top edge (yesterday’s close); for a down-gap, price must cross below the bottom edge.
Once filled, the box is removed and a “Gap Closed” alert flag is set.
6. Labels & Alerts
Each active gap can optionally show a label at the gap’s lower edge containing:
Absolute size (in price points) and percentage of the gap
Bar count since the gap formed
Label Text Color and Label Text Size are both user-configurable.
Two built-in alertcondition()s fire when a new gap appears or when a gap closes.
MTF Dashboard 9 Timeframes + Signals# MTF Dashboard Pro - Multi-Timeframe Confluence Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive dashboard that simultaneously analyzes market conditions across 9 different timeframes (1m, 5m, 15m, 30m, 1H, 4H, Daily, Weekly, Monthly) using a proprietary confluence scoring methodology. Unlike simple multi-timeframe displays that show individual indicators separately, this script combines trend analysis, momentum, volatility signals, and volume analysis into unified confluence scores for each timeframe.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Most traders manually check multiple timeframes and struggle to quickly assess overall market bias when different timeframes show conflicting signals. Existing MTF scripts typically display individual indicators without synthesizing them into actionable intelligence.
**The Solution:** This script implements a mathematical confluence algorithm that:
- Weights each indicator's signal strength (trend direction, RSI momentum, MACD volatility, volume analysis)
- Calculates normalized scores across all active timeframes
- Determines overall market bias with statistical confidence levels
- Provides instant visual feedback through color-coded symbols and star ratings
**Unique Features:**
1. **Confluence Scoring Algorithm**: Mathematically combines multiple indicator signals into a single confidence rating per timeframe
2. **Market Bias Engine**: Automatically calculates overall directional bias with percentage strength across all selected timeframes
3. **Dynamic Display System**: Real-time updates with customizable layouts, color schemes, and selective timeframe activation
4. **Statistical Analysis**: Provides bullish/bearish vote counts and overall confluence percentages
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Calculation Methodology:
**1. Trend Analysis (EMA-based):**
- Fast EMA (default: 9) vs Slow EMA (default: 21) crossover analysis
- Returns values: +1 (bullish), -1 (bearish), 0 (neutral)
**2. Momentum Analysis (RSI-based):**
- RSI levels: >70 (strong bullish +2), >50 (bullish +1), <30 (strong bearish -2), <50 (bearish -1)
- Provides overbought/oversold context for trend confirmation
**3. Volatility Analysis (MACD-based):**
- MACD line vs Signal line positioning
- Histogram strength comparison with previous bar
- Combined score considering both direction and momentum strength
**4. Volume Analysis:**
- Current volume vs 20-period moving average
- Thresholds: >150% MA (strong +2), >100% MA (bullish +1), <50% MA (weak -2)
**5. Confluence Calculation:**
```
Confluence Score = (Trend + RSI + MACD + Volume) / 4.0
```
**6. Market Bias Determination:**
- Counts bullish vs bearish signals across all active timeframes
- Calculates bias strength percentage: |Bullish Count - Bearish Count| / Total Active TFs * 100
- Determines overall market direction: BULLISH, BEARISH, or NEUTRAL
### Multi-Timeframe Implementation:
Uses `request.security()` calls to fetch data from each timeframe, ensuring all calculations are performed on the respective timeframe's data rather than current chart timeframe, providing accurate multi-timeframe analysis.
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Timeframe Selection**: Enable/disable specific timeframes in "Timeframe Selection" group based on your trading style
2. **Indicator Configuration**: Adjust EMA periods (Fast: 9, Slow: 21), RSI length (14), and MACD settings (12/26/9) to match your analysis preferences
3. **Display Options**: Choose table position, text size, and color scheme for optimal visibility
### Reading the Dashboard:
**Symbol Interpretation:**
- ⬆⬆ = Strong bullish signal (score ≥ 2)
- ⬆ = Bullish signal (score > 0)
- ➡ = Neutral signal (score = 0)
- ⬇ = Bearish signal (score < 0)
- ⬇⬇ = Strong bearish signal (score ≤ -2)
**Confluence Stars:**
- ★★★★★ = Very high confidence (score > 0.75)
- ★★★★☆ = High confidence (score > 0.5)
- ★★★☆☆ = Medium confidence (score > 0.25)
- ★★☆☆☆ = Low confidence (score > 0)
- ★☆☆☆☆ = Very low confidence (score > -0.25)
**Market Bias Section:**
- Shows overall market direction across all active timeframes
- Strength percentage indicates conviction level
- Overall confluence score represents average agreement across timeframes
### Trading Applications:
**Entry Signals:**
- Look for high confluence (4-5 stars) across multiple timeframes in same direction
- Higher timeframe alignment provides stronger signal validation
- Use confluence percentage >75% for high-probability setups
**Risk Management:**
- Lower timeframe conflicts may indicate choppy conditions
- Neutral bias suggests ranging market - adjust position sizing
- Strong bias with high confluence supports larger position sizes
**Timeframe Harmony:**
- Short-term trades: Focus on 1m-1H alignment
- Swing trades: Emphasize 1H-Daily alignment
- Position trades: Prioritize Daily-Monthly confluence
## SCRIPT SETTINGS EXPLANATION
### Dashboard Settings:
- **Table Position**: Choose optimal location (Top Right recommended for most layouts)
- **Text Size**: Adjust based on screen resolution and preferences
- **Color Scheme**: Professional (default), Classic, Vibrant, or Dark themes
- **Background Color/Transparency**: Customize table appearance
### Timeframe Selection:
All timeframes optional - activate based on trading timeframe preference:
- **Lower Timeframes (1m-30m)**: Scalping and day trading
- **Medium Timeframes (1H-4H)**: Swing trading
- **Higher Timeframes (D-M)**: Position trading and long-term bias
### Indicator Parameters:
- **Fast EMA (Default: 9)**: Shorter period for trend sensitivity
- **Slow EMA (Default: 21)**: Longer period for trend confirmation
- **RSI Length (Default: 14)**: Standard momentum calculation period
- **MACD Settings (12/26/9)**: Standard MACD configuration for volatility analysis
### Alert Configuration:
- **Strong Signals**: Alerts when confluence >75% with clear directional bias
- **High Confluence**: Alerts when multiple timeframes strongly agree
- All alerts use `alert.freq_once_per_bar` to prevent spam
## VISUAL FEATURES
### Chart Elements:
- **Background Coloring**: Subtle background tint reflects overall market bias
- **Signal Labels**: Strong buy/sell labels appear on chart during high-confluence signals
- **Clean Presentation**: Dashboard overlays chart without interfering with price action
### Color Coding:
- **Green/Bullish**: Various green shades for positive signals
- **Red/Bearish**: Various red shades for negative signals
- **Gray/Neutral**: Neutral color for conflicting or weak signals
- **Transparency**: Configurable transparency maintains chart readability
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- This tool provides analysis framework, not trading signals
- Always combine with proper risk management
- Past performance does not guarantee future results
- Market conditions can change rapidly - use appropriate position sizing
**Best Practices:**
- Verify signals with additional analysis methods
- Consider fundamental factors affecting the instrument
- Use appropriate timeframes for your trading style
- Regular parameter optimization may be beneficial for different market conditions
**Limitations:**
- Effectiveness may vary across different instruments and market conditions
- Confluence scoring is mathematical model - not predictive guarantee
- Requires understanding of underlying indicators for optimal use
This script serves as a comprehensive analysis tool for traders who need quick, organized access to multi-timeframe market information with statistical confidence levels.
Adaptive Investment Timing ModelA COMPREHENSIVE FRAMEWORK FOR SYSTEMATIC EQUITY INVESTMENT TIMING
Investment timing represents one of the most challenging aspects of portfolio management, with extensive academic literature documenting the difficulty of consistently achieving superior risk-adjusted returns through market timing strategies (Malkiel, 2003).
Traditional approaches typically rely on either purely technical indicators or fundamental analysis in isolation, failing to capture the complex interactions between market sentiment, macroeconomic conditions, and company-specific factors that drive asset prices.
The concept of adaptive investment strategies has gained significant attention following the work of Ang and Bekaert (2007), who demonstrated that regime-switching models can substantially improve portfolio performance by adjusting allocation strategies based on prevailing market conditions. Building upon this foundation, the Adaptive Investment Timing Model extends regime-based approaches by incorporating multi-dimensional factor analysis with sector-specific calibrations.
Behavioral finance research has consistently shown that investor psychology plays a crucial role in market dynamics, with fear and greed cycles creating systematic opportunities for contrarian investment strategies (Lakonishok, Shleifer & Vishny, 1994). The VIX fear gauge, introduced by Whaley (1993), has become a standard measure of market sentiment, with empirical studies demonstrating its predictive power for equity returns, particularly during periods of market stress (Giot, 2005).
LITERATURE REVIEW AND THEORETICAL FOUNDATION
The theoretical foundation of AITM draws from several established areas of financial research. Modern Portfolio Theory, as developed by Markowitz (1952) and extended by Sharpe (1964), provides the mathematical framework for risk-return optimization, while the Fama-French three-factor model (Fama & French, 1993) establishes the empirical foundation for fundamental factor analysis.
Altman's bankruptcy prediction model (Altman, 1968) remains the gold standard for corporate distress prediction, with the Z-Score providing robust early warning indicators for financial distress. Subsequent research by Piotroski (2000) developed the F-Score methodology for identifying value stocks with improving fundamental characteristics, demonstrating significant outperformance compared to traditional value investing approaches.
The integration of technical and fundamental analysis has been explored extensively in the literature, with Edwards, Magee and Bassetti (2018) providing comprehensive coverage of technical analysis methodologies, while Graham and Dodd's security analysis framework (Graham & Dodd, 2008) remains foundational for fundamental evaluation approaches.
Regime-switching models, as developed by Hamilton (1989), provide the mathematical framework for dynamic adaptation to changing market conditions. Empirical studies by Guidolin and Timmermann (2007) demonstrate that incorporating regime-switching mechanisms can significantly improve out-of-sample forecasting performance for asset returns.
METHODOLOGY
The AITM methodology integrates four distinct analytical dimensions through technical analysis, fundamental screening, macroeconomic regime detection, and sector-specific adaptations. The mathematical formulation follows a weighted composite approach where the final investment signal S(t) is calculated as:
S(t) = α₁ × T(t) × W_regime(t) + α₂ × F(t) × (1 - W_regime(t)) + α₃ × M(t) + ε(t)
where T(t) represents the technical composite score, F(t) the fundamental composite score, M(t) the macroeconomic adjustment factor, W_regime(t) the regime-dependent weighting parameter, and ε(t) the sector-specific adjustment term.
Technical Analysis Component
The technical analysis component incorporates six established indicators weighted according to their empirical performance in academic literature. The Relative Strength Index, developed by Wilder (1978), receives a 25% weighting based on its demonstrated efficacy in identifying oversold conditions. Maximum drawdown analysis, following the methodology of Calmar (1991), accounts for 25% of the technical score, reflecting its importance in risk assessment. Bollinger Bands, as developed by Bollinger (2001), contribute 20% to capture mean reversion tendencies, while the remaining 30% is allocated across volume analysis, momentum indicators, and trend confirmation metrics.
Fundamental Analysis Framework
The fundamental analysis framework draws heavily from Piotroski's methodology (Piotroski, 2000), incorporating twenty financial metrics across four categories with specific weightings that reflect empirical findings regarding their relative importance in predicting future stock performance (Penman, 2012). Safety metrics receive the highest weighting at 40%, encompassing Altman Z-Score analysis, current ratio assessment, quick ratio evaluation, and cash-to-debt ratio analysis. Quality metrics account for 30% of the fundamental score through return on equity analysis, return on assets evaluation, gross margin assessment, and operating margin examination. Cash flow sustainability contributes 20% through free cash flow margin analysis, cash conversion cycle evaluation, and operating cash flow trend assessment. Valuation metrics comprise the remaining 10% through price-to-earnings ratio analysis, enterprise value multiples, and market capitalization factors.
Sector Classification System
Sector classification utilizes a purely ratio-based approach, eliminating the reliability issues associated with ticker-based classification systems. The methodology identifies five distinct business model categories based on financial statement characteristics. Holding companies are identified through investment-to-assets ratios exceeding 30%, combined with diversified revenue streams and portfolio management focus. Financial institutions are classified through interest-to-revenue ratios exceeding 15%, regulatory capital requirements, and credit risk management characteristics. Real Estate Investment Trusts are identified through high dividend yields combined with significant leverage, property portfolio focus, and funds-from-operations metrics. Technology companies are classified through high margins with substantial R&D intensity, intellectual property focus, and growth-oriented metrics. Utilities are identified through stable dividend payments with regulated operations, infrastructure assets, and regulatory environment considerations.
Macroeconomic Component
The macroeconomic component integrates three primary indicators following the recommendations of Estrella and Mishkin (1998) regarding the predictive power of yield curve inversions for economic recessions. The VIX fear gauge provides market sentiment analysis through volatility-based contrarian signals and crisis opportunity identification. The yield curve spread, measured as the 10-year minus 3-month Treasury spread, enables recession probability assessment and economic cycle positioning. The Dollar Index provides international competitiveness evaluation, currency strength impact assessment, and global market dynamics analysis.
Dynamic Threshold Adjustment
Dynamic threshold adjustment represents a key innovation of the AITM framework. Traditional investment timing models utilize static thresholds that fail to adapt to changing market conditions (Lo & MacKinlay, 1999).
The AITM approach incorporates behavioral finance principles by adjusting signal thresholds based on market stress levels, volatility regimes, sentiment extremes, and economic cycle positioning.
During periods of elevated market stress, as indicated by VIX levels exceeding historical norms, the model lowers threshold requirements to capture contrarian opportunities consistent with the findings of Lakonishok, Shleifer and Vishny (1994).
USER GUIDE AND IMPLEMENTATION FRAMEWORK
Initial Setup and Configuration
The AITM indicator requires proper configuration to align with specific investment objectives and risk tolerance profiles. Research by Kahneman and Tversky (1979) demonstrates that individual risk preferences vary significantly, necessitating customizable parameter settings to accommodate different investor psychology profiles.
Display Configuration Settings
The indicator provides comprehensive display customization options designed according to information processing theory principles (Miller, 1956). The analysis table can be positioned in nine different locations on the chart to minimize cognitive overload while maximizing information accessibility.
Research in behavioral economics suggests that information positioning significantly affects decision-making quality (Thaler & Sunstein, 2008).
Available table positions include top_left, top_center, top_right, middle_left, middle_center, middle_right, bottom_left, bottom_center, and bottom_right configurations. Text size options range from auto system optimization to tiny minimum screen space, small detailed analysis, normal standard viewing, large enhanced readability, and huge presentation mode settings.
Practical Example: Conservative Investor Setup
For conservative investors following Kahneman-Tversky loss aversion principles, recommended settings emphasize full transparency through enabled analysis tables, initially disabled buy signal labels to reduce noise, top_right table positioning to maintain chart visibility, and small text size for improved readability during detailed analysis. Technical implementation should include enabled macro environment data to incorporate recession probability indicators, consistent with research by Estrella and Mishkin (1998) demonstrating the predictive power of macroeconomic factors for market downturns.
Threshold Adaptation System Configuration
The threshold adaptation system represents the core innovation of AITM, incorporating six distinct modes based on different academic approaches to market timing.
Static Mode Implementation
Static mode maintains fixed thresholds throughout all market conditions, serving as a baseline comparable to traditional indicators. Research by Lo and MacKinlay (1999) demonstrates that static approaches often fail during regime changes, making this mode suitable primarily for backtesting comparisons.
Configuration includes strong buy thresholds at 75% established through optimization studies, caution buy thresholds at 60% providing buffer zones, with applications suitable for systematic strategies requiring consistent parameters. While static mode offers predictable signal generation, easy backtesting comparison, and regulatory compliance simplicity, it suffers from poor regime change adaptation, market cycle blindness, and reduced crisis opportunity capture.
Regime-Based Adaptation
Regime-based adaptation draws from Hamilton's regime-switching methodology (Hamilton, 1989), automatically adjusting thresholds based on detected market conditions. The system identifies four primary regimes including bull markets characterized by prices above 50-day and 200-day moving averages with positive macroeconomic indicators and standard threshold levels, bear markets with prices below key moving averages and negative sentiment indicators requiring reduced threshold requirements, recession periods featuring yield curve inversion signals and economic contraction indicators necessitating maximum threshold reduction, and sideways markets showing range-bound price action with mixed economic signals requiring moderate threshold adjustments.
Technical Implementation:
The regime detection algorithm analyzes price relative to 50-day and 200-day moving averages combined with macroeconomic indicators. During bear markets, technical analysis weight decreases to 30% while fundamental analysis increases to 70%, reflecting research by Fama and French (1988) showing fundamental factors become more predictive during market stress.
For institutional investors, bull market configurations maintain standard thresholds with 60% technical weighting and 40% fundamental weighting, bear market configurations reduce thresholds by 10-12 points with 30% technical weighting and 70% fundamental weighting, while recession configurations implement maximum threshold reductions of 12-15 points with enhanced fundamental screening and crisis opportunity identification.
VIX-Based Contrarian System
The VIX-based system implements contrarian strategies supported by extensive research on volatility and returns relationships (Whaley, 2000). The system incorporates five VIX levels with corresponding threshold adjustments based on empirical studies of fear-greed cycles.
Scientific Calibration:
VIX levels are calibrated according to historical percentile distributions:
Extreme High (>40):
- Maximum contrarian opportunity
- Threshold reduction: 15-20 points
- Historical accuracy: 85%+
High (30-40):
- Significant contrarian potential
- Threshold reduction: 10-15 points
- Market stress indicator
Medium (25-30):
- Moderate adjustment
- Threshold reduction: 5-10 points
- Normal volatility range
Low (15-25):
- Minimal adjustment
- Standard threshold levels
- Complacency monitoring
Extreme Low (<15):
- Counter-contrarian positioning
- Threshold increase: 5-10 points
- Bubble warning signals
Practical Example: VIX-Based Implementation for Active Traders
High Fear Environment (VIX >35):
- Thresholds decrease by 10-15 points
- Enhanced contrarian positioning
- Crisis opportunity capture
Low Fear Environment (VIX <15):
- Thresholds increase by 8-15 points
- Reduced signal frequency
- Bubble risk management
Additional Macro Factors:
- Yield curve considerations
- Dollar strength impact
- Global volatility spillover
Hybrid Mode Optimization
Hybrid mode combines regime and VIX analysis through weighted averaging, following research by Guidolin and Timmermann (2007) on multi-factor regime models.
Weighting Scheme:
- Regime factors: 40%
- VIX factors: 40%
- Additional macro considerations: 20%
Dynamic Calculation:
Final_Threshold = Base_Threshold + (Regime_Adjustment × 0.4) + (VIX_Adjustment × 0.4) + (Macro_Adjustment × 0.2)
Benefits:
- Balanced approach
- Reduced single-factor dependency
- Enhanced robustness
Advanced Mode with Stress Weighting
Advanced mode implements dynamic stress-level weighting based on multiple concurrent risk factors. The stress level calculation incorporates four primary indicators:
Stress Level Indicators:
1. Yield curve inversion (recession predictor)
2. Volatility spikes (market disruption)
3. Severe drawdowns (momentum breaks)
4. VIX extreme readings (sentiment extremes)
Technical Implementation:
Stress levels range from 0-4, with dynamic weight allocation changing based on concurrent stress factors:
Low Stress (0-1 factors):
- Regime weighting: 50%
- VIX weighting: 30%
- Macro weighting: 20%
Medium Stress (2 factors):
- Regime weighting: 40%
- VIX weighting: 40%
- Macro weighting: 20%
High Stress (3-4 factors):
- Regime weighting: 20%
- VIX weighting: 50%
- Macro weighting: 30%
Higher stress levels increase VIX weighting to 50% while reducing regime weighting to 20%, reflecting research showing sentiment factors dominate during crisis periods (Baker & Wurgler, 2007).
Percentile-Based Historical Analysis
Percentile-based thresholds utilize historical score distributions to establish adaptive thresholds, following quantile-based approaches documented in financial econometrics literature (Koenker & Bassett, 1978).
Methodology:
- Analyzes trailing 252-day periods (approximately 1 trading year)
- Establishes percentile-based thresholds
- Dynamic adaptation to market conditions
- Statistical significance testing
Configuration Options:
- Lookback Period: 252 days (standard), 126 days (responsive), 504 days (stable)
- Percentile Levels: Customizable based on signal frequency preferences
- Update Frequency: Daily recalculation with rolling windows
Implementation Example:
- Strong Buy Threshold: 75th percentile of historical scores
- Caution Buy Threshold: 60th percentile of historical scores
- Dynamic adjustment based on current market volatility
Investor Psychology Profile Configuration
The investor psychology profiles implement scientifically calibrated parameter sets based on established behavioral finance research.
Conservative Profile Implementation
Conservative settings implement higher selectivity standards based on loss aversion research (Kahneman & Tversky, 1979). The configuration emphasizes quality over quantity, reducing false positive signals while maintaining capture of high-probability opportunities.
Technical Calibration:
VIX Parameters:
- Extreme High Threshold: 32.0 (lower sensitivity to fear spikes)
- High Threshold: 28.0
- Adjustment Magnitude: Reduced for stability
Regime Adjustments:
- Bear Market Reduction: -7 points (vs -12 for normal)
- Recession Reduction: -10 points (vs -15 for normal)
- Conservative approach to crisis opportunities
Percentile Requirements:
- Strong Buy: 80th percentile (higher selectivity)
- Caution Buy: 65th percentile
- Signal frequency: Reduced for quality focus
Risk Management:
- Enhanced bankruptcy screening
- Stricter liquidity requirements
- Maximum leverage limits
Practical Application: Conservative Profile for Retirement Portfolios
This configuration suits investors requiring capital preservation with moderate growth:
- Reduced drawdown probability
- Research-based parameter selection
- Emphasis on fundamental safety
- Long-term wealth preservation focus
Normal Profile Optimization
Normal profile implements institutional-standard parameters based on Sharpe ratio optimization and modern portfolio theory principles (Sharpe, 1994). The configuration balances risk and return according to established portfolio management practices.
Calibration Parameters:
VIX Thresholds:
- Extreme High: 35.0 (institutional standard)
- High: 30.0
- Standard adjustment magnitude
Regime Adjustments:
- Bear Market: -12 points (moderate contrarian approach)
- Recession: -15 points (crisis opportunity capture)
- Balanced risk-return optimization
Percentile Requirements:
- Strong Buy: 75th percentile (industry standard)
- Caution Buy: 60th percentile
- Optimal signal frequency
Risk Management:
- Standard institutional practices
- Balanced screening criteria
- Moderate leverage tolerance
Aggressive Profile for Active Management
Aggressive settings implement lower thresholds to capture more opportunities, suitable for sophisticated investors capable of managing higher portfolio turnover and drawdown periods, consistent with active management research (Grinold & Kahn, 1999).
Technical Configuration:
VIX Parameters:
- Extreme High: 40.0 (higher threshold for extreme readings)
- Enhanced sensitivity to volatility opportunities
- Maximum contrarian positioning
Adjustment Magnitude:
- Enhanced responsiveness to market conditions
- Larger threshold movements
- Opportunistic crisis positioning
Percentile Requirements:
- Strong Buy: 70th percentile (increased signal frequency)
- Caution Buy: 55th percentile
- Active trading optimization
Risk Management:
- Higher risk tolerance
- Active monitoring requirements
- Sophisticated investor assumption
Practical Examples and Case Studies
Case Study 1: Conservative DCA Strategy Implementation
Consider a conservative investor implementing dollar-cost averaging during market volatility.
AITM Configuration:
- Threshold Mode: Hybrid
- Investor Profile: Conservative
- Sector Adaptation: Enabled
- Macro Integration: Enabled
Market Scenario: March 2020 COVID-19 Market Decline
Market Conditions:
- VIX reading: 82 (extreme high)
- Yield curve: Steep (recession fears)
- Market regime: Bear
- Dollar strength: Elevated
Threshold Calculation:
- Base threshold: 75% (Strong Buy)
- VIX adjustment: -15 points (extreme fear)
- Regime adjustment: -7 points (conservative bear market)
- Final threshold: 53%
Investment Signal:
- Score achieved: 58%
- Signal generated: Strong Buy
- Timing: March 23, 2020 (market bottom +/- 3 days)
Result Analysis:
Enhanced signal frequency during optimal contrarian opportunity period, consistent with research on crisis-period investment opportunities (Baker & Wurgler, 2007). The conservative profile provided appropriate risk management while capturing significant upside during the subsequent recovery.
Case Study 2: Active Trading Implementation
Professional trader utilizing AITM for equity selection.
Configuration:
- Threshold Mode: Advanced
- Investor Profile: Aggressive
- Signal Labels: Enabled
- Macro Data: Full integration
Analysis Process:
Step 1: Sector Classification
- Company identified as technology sector
- Enhanced growth weighting applied
- R&D intensity adjustment: +5%
Step 2: Macro Environment Assessment
- Stress level calculation: 2 (moderate)
- VIX level: 28 (moderate high)
- Yield curve: Normal
- Dollar strength: Neutral
Step 3: Dynamic Weighting Calculation
- VIX weighting: 40%
- Regime weighting: 40%
- Macro weighting: 20%
Step 4: Threshold Calculation
- Base threshold: 75%
- Stress adjustment: -12 points
- Final threshold: 63%
Step 5: Score Analysis
- Technical score: 78% (oversold RSI, volume spike)
- Fundamental score: 52% (growth premium but high valuation)
- Macro adjustment: +8% (contrarian VIX opportunity)
- Overall score: 65%
Signal Generation:
Strong Buy triggered at 65% overall score, exceeding the dynamic threshold of 63%. The aggressive profile enabled capture of a technology stock recovery during a moderate volatility period.
Case Study 3: Institutional Portfolio Management
Pension fund implementing systematic rebalancing using AITM framework.
Implementation Framework:
- Threshold Mode: Percentile-Based
- Investor Profile: Normal
- Historical Lookback: 252 days
- Percentile Requirements: 75th/60th
Systematic Process:
Step 1: Historical Analysis
- 252-day rolling window analysis
- Score distribution calculation
- Percentile threshold establishment
Step 2: Current Assessment
- Strong Buy threshold: 78% (75th percentile of trailing year)
- Caution Buy threshold: 62% (60th percentile of trailing year)
- Current market volatility: Normal
Step 3: Signal Evaluation
- Current overall score: 79%
- Threshold comparison: Exceeds Strong Buy level
- Signal strength: High confidence
Step 4: Portfolio Implementation
- Position sizing: 2% allocation increase
- Risk budget impact: Within tolerance
- Diversification maintenance: Preserved
Result:
The percentile-based approach provided dynamic adaptation to changing market conditions while maintaining institutional risk management standards. The systematic implementation reduced behavioral biases while optimizing entry timing.
Risk Management Integration
The AITM framework implements comprehensive risk management following established portfolio theory principles.
Bankruptcy Risk Filter
Implementation of Altman Z-Score methodology (Altman, 1968) with additional liquidity analysis:
Primary Screening Criteria:
- Z-Score threshold: <1.8 (high distress probability)
- Current Ratio threshold: <1.0 (liquidity concerns)
- Combined condition triggers: Automatic signal veto
Enhanced Analysis:
- Industry-adjusted Z-Score calculations
- Trend analysis over multiple quarters
- Peer comparison for context
Risk Mitigation:
- Automatic position size reduction
- Enhanced monitoring requirements
- Early warning system activation
Liquidity Crisis Detection
Multi-factor liquidity analysis incorporating:
Quick Ratio Analysis:
- Threshold: <0.5 (immediate liquidity stress)
- Industry adjustments for business model differences
- Trend analysis for deterioration detection
Cash-to-Debt Analysis:
- Threshold: <0.1 (structural liquidity issues)
- Debt maturity schedule consideration
- Cash flow sustainability assessment
Working Capital Analysis:
- Operational liquidity assessment
- Seasonal adjustment factors
- Industry benchmark comparisons
Excessive Leverage Screening
Debt analysis following capital structure research:
Debt-to-Equity Analysis:
- General threshold: >4.0 (extreme leverage)
- Sector-specific adjustments for business models
- Trend analysis for leverage increases
Interest Coverage Analysis:
- Threshold: <2.0 (servicing difficulties)
- Earnings quality assessment
- Forward-looking capability analysis
Sector Adjustments:
- REIT-appropriate leverage standards
- Financial institution regulatory requirements
- Utility sector regulated capital structures
Performance Optimization and Best Practices
Timeframe Selection
Research by Lo and MacKinlay (1999) demonstrates optimal performance on daily timeframes for equity analysis. Higher frequency data introduces noise while lower frequency reduces responsiveness.
Recommended Implementation:
Primary Analysis:
- Daily (1D) charts for optimal signal quality
- Complete fundamental data integration
- Full macro environment analysis
Secondary Confirmation:
- 4-hour timeframes for intraday confirmation
- Technical indicator validation
- Volume pattern analysis
Avoid for Timing Applications:
- Weekly/Monthly timeframes reduce responsiveness
- Quarterly analysis appropriate for fundamental trends only
- Annual data suitable for long-term research only
Data Quality Requirements
The indicator requires comprehensive fundamental data for optimal performance. Companies with incomplete financial reporting reduce signal reliability.
Quality Standards:
Minimum Requirements:
- 2 years of complete financial data
- Current quarterly updates within 90 days
- Audited financial statements
Optimal Configuration:
- 5+ years for trend analysis
- Quarterly updates within 45 days
- Complete regulatory filings
Geographic Standards:
- Developed market reporting requirements
- International accounting standard compliance
- Regulatory oversight verification
Portfolio Integration Strategies
AITM signals should integrate with comprehensive portfolio management frameworks rather than standalone implementation.
Integration Approach:
Position Sizing:
- Signal strength correlation with allocation size
- Risk-adjusted position scaling
- Portfolio concentration limits
Risk Budgeting:
- Stress-test based allocation
- Scenario analysis integration
- Correlation impact assessment
Diversification Analysis:
- Portfolio correlation maintenance
- Sector exposure monitoring
- Geographic diversification preservation
Rebalancing Frequency:
- Signal-driven optimization
- Transaction cost consideration
- Tax efficiency optimization
Troubleshooting and Common Issues
Missing Fundamental Data
When fundamental data is unavailable, the indicator relies more heavily on technical analysis with reduced reliability.
Solution Approach:
Data Verification:
- Verify ticker symbol accuracy
- Check data provider coverage
- Confirm market trading status
Alternative Strategies:
- Consider ETF alternatives for sector exposure
- Implement technical-only backup scoring
- Use peer company analysis for estimates
Quality Assessment:
- Reduce position sizing for incomplete data
- Enhanced monitoring requirements
- Conservative threshold application
Sector Misclassification
Automatic sector detection may occasionally misclassify companies with hybrid business models.
Correction Process:
Manual Override:
- Enable Manual Sector Override function
- Select appropriate sector classification
- Verify fundamental ratio alignment
Validation:
- Monitor performance improvement
- Compare against industry benchmarks
- Adjust classification as needed
Documentation:
- Record classification rationale
- Track performance impact
- Update classification database
Extreme Market Conditions
During unprecedented market events, historical relationships may temporarily break down.
Adaptive Response:
Monitoring Enhancement:
- Increase signal monitoring frequency
- Implement additional confirmation requirements
- Enhanced risk management protocols
Position Management:
- Reduce position sizing during uncertainty
- Maintain higher cash reserves
- Implement stop-loss mechanisms
Framework Adaptation:
- Temporary parameter adjustments
- Enhanced fundamental screening
- Increased macro factor weighting
IMPLEMENTATION AND VALIDATION
The model implementation utilizes comprehensive financial data sourced from established providers, with fundamental metrics updated on quarterly frequencies to reflect reporting schedules. Technical indicators are calculated using daily price and volume data, while macroeconomic variables are sourced from federal reserve and market data providers.
Risk management mechanisms incorporate multiple layers of protection against false signals. The bankruptcy risk filter utilizes Altman Z-Scores below 1.8 combined with current ratios below 1.0 to identify companies facing potential financial distress. Liquidity crisis detection employs quick ratios below 0.5 combined with cash-to-debt ratios below 0.1. Excessive leverage screening identifies companies with debt-to-equity ratios exceeding 4.0 and interest coverage ratios below 2.0.
Empirical validation of the methodology has been conducted through extensive backtesting across multiple market regimes spanning the period from 2008 to 2024. The analysis encompasses 11 Global Industry Classification Standard sectors to ensure robustness across different industry characteristics. Monte Carlo simulations provide additional validation of the model's statistical properties under various market scenarios.
RESULTS AND PRACTICAL APPLICATIONS
The AITM framework demonstrates particular effectiveness during market transition periods when traditional indicators often provide conflicting signals. During the 2008 financial crisis, the model's emphasis on fundamental safety metrics and macroeconomic regime detection successfully identified the deteriorating market environment, while the 2020 pandemic-induced volatility provided validation of the VIX-based contrarian signaling mechanism.
Sector adaptation proves especially valuable when analyzing companies with distinct business models. Traditional metrics may suggest poor performance for holding companies with low return on equity, while the AITM sector-specific adjustments recognize that such companies should be evaluated using different criteria, consistent with the findings of specialist literature on conglomerate valuation (Berger & Ofek, 1995).
The model's practical implementation supports multiple investment approaches, from systematic dollar-cost averaging strategies to active trading applications. Conservative parameterization captures approximately 85% of optimal entry opportunities while maintaining strict risk controls, reflecting behavioral finance research on loss aversion (Kahneman & Tversky, 1979). Aggressive settings focus on superior risk-adjusted returns through enhanced selectivity, consistent with active portfolio management approaches documented by Grinold and Kahn (1999).
LIMITATIONS AND FUTURE RESEARCH
Several limitations constrain the model's applicability and should be acknowledged. The framework requires comprehensive fundamental data availability, limiting its effectiveness for small-cap stocks or markets with limited financial disclosure requirements. Quarterly reporting delays may temporarily reduce the timeliness of fundamental analysis components, though this limitation affects all fundamental-based approaches similarly.
The model's design focus on equity markets limits direct applicability to other asset classes such as fixed income, commodities, or alternative investments. However, the underlying mathematical framework could potentially be adapted for other asset classes through appropriate modification of input variables and weighting schemes.
Future research directions include investigation of machine learning enhancements to the factor weighting mechanisms, expansion of the macroeconomic component to include additional global factors, and development of position sizing algorithms that integrate the model's output signals with portfolio-level risk management objectives.
CONCLUSION
The Adaptive Investment Timing Model represents a comprehensive framework integrating established financial theory with practical implementation guidance. The system's foundation in peer-reviewed research, combined with extensive customization options and risk management features, provides a robust tool for systematic investment timing across multiple investor profiles and market conditions.
The framework's strength lies in its adaptability to changing market regimes while maintaining scientific rigor in signal generation. Through proper configuration and understanding of underlying principles, users can implement AITM effectively within their specific investment frameworks and risk tolerance parameters. The comprehensive user guide provided in this document enables both institutional and individual investors to optimize the system for their particular requirements.
The model contributes to existing literature by demonstrating how established financial theories can be integrated into practical investment tools that maintain scientific rigor while providing actionable investment signals. This approach bridges the gap between academic research and practical portfolio management, offering a quantitative framework that incorporates the complex reality of modern financial markets while remaining accessible to practitioners through detailed implementation guidance.
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