3D Institutional Battlefield [SurgeGuru]Professional Presentation: 3D Institutional Flow Terrain Indicator
Overview
The 3D Institutional Flow Terrain is an advanced trading visualization tool that transforms complex market structure into an intuitive 3D landscape. This indicator synthesizes multiple institutional data points—volume profiles, order blocks, liquidity zones, and voids—into a single comprehensive view, helping you identify high-probability trading opportunities.
Key Features
🎥 Camera & Projection Controls
Yaw & Pitch: Adjust viewing angles (0-90°) for optimal perspective
Scale Controls: Fine-tune X (width), Y (depth), and Z (height) dimensions
Pro Tip: Increase Z-scale to amplify terrain features for better visibility
🌐 Grid & Surface Configuration
Resolution: Adjust X (16-64) and Y (12-48) grid density
Visual Elements: Toggle surface fill, wireframe, and node markers
Optimization: Higher resolution provides more detail but requires more processing power
📊 Data Integration
Lookback Period: 50-500 bars of historical analysis
Multi-Source Data: Combine volume profile, order blocks, liquidity zones, and voids
Weighted Analysis: Each data source contributes proportionally to the terrain height
How to Use the Frontend
💛 Price Line Tracking (Your Primary Focus)
The yellow price line is your most important guide:
Monitor Price Movement: Track how the yellow line interacts with the 3D terrain
Identify Key Levels: Watch for these critical interactions:
Order Blocks (Green/Red Zones):
When yellow price line enters green zones = Bullish order block
When yellow price line enters red zones = Bearish order block
These represent institutional accumulation/distribution areas
Liquidity Voids (Yellow Zones):
When yellow price line enters yellow void areas = Potential acceleration zones
Voids indicate price gaps where minimal trading occurred
Price often moves rapidly through voids toward next liquidity pool
Terrain Reading:
High Terrain Peaks: High volume/interest areas (support/resistance)
Low Terrain Valleys: Low volume areas (potential breakout zones)
Color Coding:
Green terrain = Bullish volume dominance
Red terrain = Bearish volume dominance
Purple = Neutral/transition areas
📈 Volume Profile Integration
POC (Point of Control): Automatically marks highest volume level
Volume Bins: Adjust granularity (10-50 bins)
Height Weight: Control how much volume affects terrain elevation
🏛️ Order Block Detection
Detection Length: 5-50 bar lookback for block identification
Strength Weighting: Recent blocks have greater impact on terrain
Candle Body Option: Use full candles or body-only for block definition
💧 Liquidity Zone Tracking
Multiple Levels: Track 3-10 key liquidity zones
Buy/Sell Side: Different colors for bid/ask liquidity
Strength Decay: Older zones have diminishing terrain impact
🌊 Liquidity Void Identification
Threshold Multiplier: Adjust sensitivity (0.5-2.0)
Height Amplification: Voids create significant terrain depressions
Acceleration Zones: Price typically moves quickly through void areas
Practical Trading Application
Bullish Scenario:
Yellow price line approaches green order block terrain
Price finds support in elevated bullish volume areas
Terrain shows consistent elevation through key levels
Bearish Scenario:
Yellow price line struggles at red order block resistance
Price falls through liquidity voids toward lower terrain
Bearish volume peaks dominate the landscape
Breakout Setup:
Yellow price line consolidates in flat terrain
Minimal resistance (low terrain) in projected direction
Clear path toward distant liquidity zones
Pro Tips
Start Simple: Begin with default settings, then gradually customize
Focus on Yellow Line: Your primary indicator of current price position
Combine Timeframes: Use the same terrain across multiple timeframes for confluence
Volume Confirmation: Ensure terrain peaks align with actual volume spikes
Void Anticipation: When price enters voids, prepare for potential rapid movement
Order Blocks & Voids Architecture
Order Blocks Calculation
Trigger: Price breaks fractal swing points
Bullish OB: When close > swing high → find lowest low in lookback period
Bearish OB: When close < swing low → find highest high in lookback period
Strength: Based on price distance from block extremes
Storage: Global array maintains last 50 blocks with FIFO management
Liquidity Voids Detection
Trigger: Price gaps exceeding ATR threshold
Bull Void: Low - high > (ATR200 × multiplier)
Bear Void: Low - high > (ATR200 × multiplier)
Validation: Close confirms gap direction
Storage: Global array maintains last 30 voids
Key Design Features
Real-time Updates: Calculated every bar, not just on last bar
Global Persistence: Arrays maintain state across executions
FIFO Management: Automatic cleanup of oldest entries
Configurable Sensitivity: Adjustable lookback periods and thresholds
Scientific Testing Framework
Hypothesis Testing
Primary Hypothesis: 3D terrain visualization improves detection of institutional order flow vs traditional 2D charts
Testable Metrics:
Prediction Accuracy: Does terrain structure predict future support/resistance?
Reaction Time: Faster identification of key levels vs conventional methods
False Positive Reduction: Lower rate of failed breakouts/breakdowns
Control Variables
Market Regime: Trending vs ranging conditions
Asset Classes: Forex, equities, cryptocurrencies
Timeframes: M5 to H4 for intraday, D1 for swing
Volume Conditions: High vs low volume environments
Data Collection Protocol
Terrain Features to Quantify:
Slope gradient changes at price inflection points
Volume peak clustering density
Order block terrain elevation vs subsequent price action
Void depth correlation with momentum acceleration
Control Group: Traditional support/resistance + volume profile
Experimental Group: 3D Institutional Flow Terrain
Statistical Measures
Signal-to-Noise Ratio: Terrain features vs random price movements
Lead Time: Terrain formation ahead of price confirmation
Effect Size: Performance difference between groups (Cohen's d)
Statistical Power: Sample size requirements for significance
Validation Methodology
Blind Testing:
Remove price labels from terrain screenshots
Have traders identify key levels from terrain alone
Measure accuracy vs actual price action
Backtesting Framework:
Automated terrain feature extraction
Correlation with future price reversals/breakouts
Monte Carlo simulation for significance testing
Expected Outcomes
If hypothesis valid:
Significant improvement in level prediction accuracy (p < 0.05)
Reduced latency in institutional level identification
Higher risk-reward ratios on terrain-confirmed trades
Research Questions:
Does terrain elevation reliably indicate institutional interest zones?
Are liquidity voids statistically significant momentum predictors?
Does multi-timeframe terrain analysis improve signal quality?
How does terrain persistence correlate with level strength?
LuxAlgo BigBeluga hapharmonic
Cerca negli script per "Fractal"
Chart Info Display (HOKO) 2It displays 3 things on the screen in order: symbol, date, time frame. You can use it to capture educational videos to make your chart more beautiful, more private, and more practical.
Hoko Quarterly Theory is it this Quarterly Theory but for faraz................................................................................................................................................................................................................
HOKO Doubling Theorythis script is like Quarterly theory but with bigger box .............................................................................................................................
Chart Info Display (HOKO)this script show you three information , symbol , date , time frame .........................................................................................................................................................
Opposing Candle V2🟩 OC (Opposing Candle) Multi–Timeframe Framework
🔍 Overview
The OC Indicator automatically detects and displays Opposing Candles (OCs) across up to three timeframes.
An Opposing Candle is a candle that fully engulfs the previous one, signaling a potential shift in control — either a trend continuation or a trend reversal.
This multi–timeframe framework gives traders a structured way to visualize displacement, pullbacks, and momentum shifts between timeframes.
⚙️ How It Works
Each OC is drawn as a box showing:
High & Low → The candle’s full range
Open Line (black) → Key control level
Midline (white) → Candle equilibrium
Optional labels for timeframe and session
You can enable up to 3 timeframes (e.g., 30m / 1H / 4H) and adjust how many OCs to display for each.
📈 Trading Framework
🔹 Continuation Setup (Trend Following)
1. 4H Bias → Bullish or Bearish
Identify clear trend structure (HH/HL = bullish, LH/LL = bearish).
Confirm strong displacement and visible gaps between OCs — signs of momentum and healthy trend continuation.
2. 1H Confirmation OC
OC forms in the direction of the 4H bias, confirming control.
3. 30min Pullback OC
Opposite–colored OC appears → represents the pullback.
4. Entry Trigger
A yellow candle closes beyond the 30min OC open line, confirming the end of the pullback.
→ Enter in trend direction.
🎯 Targets
Target 1: Next 1H OC high or low (in trend direction)
Target 2: Next 4H OC high or low
🛑 Stop: Beyond the 30min OC’s opposite wick
🔹 Reversal Setup (Trend Shift)
1. 4H Structure → Extended or Losing Momentum
When there are no higher–timeframe gaps and no displacement, momentum weakens — often a sign of potential reversal.
2. Opposing OC Forms on HTF
A strong engulfing OC appears against the previous trend at a key structural level.
3. Lower–Timeframe Alignment
1H and 30min OCs begin forming in the new direction, confirming control shift.
4. Entry Trigger
Break of the lower–timeframe OC open line signals the reversal confirmation.
🟢 Example: Bullish Reversal
4H downtrend shows compression (no displacement)
4H bullish OC forms at support
30min breaks above a bearish OC’s open line → Go long
🔴 Example: Bearish Reversal
4H uptrend stalls at resistance
4H bearish OC forms
30min breaks below a bullish OC’s open line → Go short
🎯 Targets
Target 1: Nearest opposing 1H OC high/low
Target 2: Major 4H structural high/low
🛑 Stop: Beyond the reversal OC wick
🧠 Key Concepts
Displacement = Strength. Strong, impulsive moves with clear gaps between OCs show continuation.
Compression = Weakness. Overlapping candles and no HTF displacement often hint at reversal.
OC = Control Candle. The open line is the “line in the sand” — when price breaks it, control flips.
Multi–TF Confluence = Precision. 4H → 1H → 30m gives you structure → confirmation → entry accuracy.
🎨 Features
✅ Multi–Timeframe OC detection (default: 30m / 1H / 4H)
✅ Bullish & Bearish boxes with open and midlines
✅ Break candles highlighted yellow
✅ Optional labels (timeframe + session)
✅ Session filters (Asia, London, NYAM, NYPM)
✅ Fully customizable visuals and extension lengths
Aperturas Semanales Precisas (corregido)Identifica aperturas semanales del precio y resalta aperturas mensuales
Apertura SemanalIdentifica las aperturas semanales de cada grafico y resalta las aperturas mensuales
Previous D/W/M HLOCHey traders,
Here's a simple Multi-Timeframe indicator that essentially turns time and price into a box. It'll take the previous high, low, opening price, or closing price from one of the three timeframes of your choice (day, week, or month). For whatever reason I can't get the opening price to function consistently so if you find improvements feel free to let me know, this will help traders who prefer to use opening price over closing price.
Naturally this form of charting is classical and nature and some key figures you could use to study its usage are
- Richard W. Schabacker (1930s)
- Edwards & Magee (1948)
- Peter Brandt
- Stacey Burke (more on the intraday side - typically our preference)
It's usage put plainly:
- Quantifying Accumulation or Distribution
- Revealing Energy Build-Up (Compression)
- Framing Breakouts and False Breakouts
- Structuring Time
- Identifying opportunities to trade a daily, weekly, or monthly range.
Candle Color Difference Marker (PSP)This indicator shows when the colors of the candles on two or three charts are different.
Buy/Sell Signals [WynTrader]My name is WynTrader. I cumulate 24 years of experience.
This Indicator produces Buy/Sell Signals using these features:
- Fast and Slow Moving averages (modifiable) optimized at EMA-8 and SMA-35
- Bollinger Bands (modifiable) optimized at Basis-18 and Multiplier-1
Also, the Buy/Sell Signals are conditioned by three Filters (optionable, modifiable) :
. Bollinger-Bands Lookback
. High-Low vs Candle Range %
. Distance from Fast and Slow Moving averages %
The Results Calculation presented in a Table are based :
- on the Current Chart Visible Range (optionable)
or
- on the specified TIme Frame Start and End Dates (modifiable)
The Table shows Calculation Results of the Buy and Sell Signals that are activated on the chart, with the Number of Trades (Signals), the Winning Points and the Win Rate %. The Buy&Hold starts calculation at the first Buy encountered.
So be surprised by my Buy/Sell Indicator. But always remember that the world is not perfect. The Graal Indicator, even with AI, doesn't already exist, maybe one day (all of us richier...), but not now. , depending on the chart product (stocks...), volatility, probabilities, unpredictable behaviour. , the moves, etc.
Enjoy
WynTrader
P. s. :
My name is WynTrader. I cumulate 24 years of experience. In 2001, I took an intensive technical analysis course taught by an exceptional friend, Cyril, who taught me everything I know. The foundation I gained through his teaching remains solid and relevant to this day, never failing me.
Before i made this Indicator, I have used many Trading View Buy/Sell Indicators using alone or combined RSI, SMI, OBV, MACD ATR, ADX, Neural, Fractal, Geometry, etc., that are already available for the Trading View community. A great thanks to those who give their time that help me build this tool.
Note that I'm not a programmer, so... ;-)
GpPa - Φ Frames (V5.0.1)# GpPa — Φ Frames (V5.0.1)
**What it does**
This tool overlays nine “Phi Frames” on your chart. Each frame builds a dynamic price **box** from the **highest high** and **lowest low** over a user-defined lookback on a fixed timeframe. The boxes help you read structure, extremes, and balance zones across multiple scales in one view. No signals are generated.
**How it works (simple)**
* For every frame, the script requests data at a fixed resolution (e.g., 1D, 610m, 233m, 89m, etc.).
* It scans the last *N* bars at that resolution (your input).
* It draws a box from the start of that window to the current time, bounded by the window’s high and low.
* Optional “Re-Analysis Zone” guides project a vertical line into the future at a user-set offset, giving you a planning marker.
**Frames included**
* **M1** – 1D resolution (default length 258 bars)
* **M2** – 1D resolution (default length 160 bars)
* **M3** – 610-minute resolution (default length 233 bars)
* **M4** – 233-minute resolution (default length 377 bars)
* **M5** – 89-minute resolution (default length 610 bars)
* **M6** – 34-minute resolution (default length 987 bars)
* **M7** – 13-minute resolution (default length 1597 bars)
* **M8** – 5-minute resolution (default length 2584 bars)
* **M9** – 2-minute resolution (default length 4181 bars)
These durations follow a Fibonacci/Φ scheme. Using multiple frames together reveals confluence and nested ranges.
**Inputs & customization**
* **Per-frame controls:**
* *Length (bars)* — lookback window at the frame’s resolution.
* *Show/Hide* — toggle a frame on or off.
* *Color* — box border color.
* **Re-Analysis Zone (M4, M5, M6):**
* *Offset (bars)* — projects a future reference time from the right edge of the box.
* *Show/Hide* and *Color.*
* The line spans slightly above and below the box (+/-10% of its height) for visibility.
**Tips**
* Start with 2–3 frames to reduce clutter. Add more as needed.
* On lower chart resolutions, higher-timeframe boxes will “step” at their own closes.
* Use frames as context for your own entries, risk, and targets.
* Colors are semi-transparent by design so overlaps remain readable.
**Behavior & notes**
* Boxes update intrabar; values settle when the source timeframe closes.
* No alerts, signals, or strategy logic are included.
* Works on any symbol and timeframe.
* Overlay: **true**.
**Disclaimer**
This tool is for educational and informational purposes only. It is not financial advice. Always do your own research and manage risk.
**Credits**
Pine Script™ v6. © thewayofrichie.
Bridge Bands ATR (Overlay) ShaneHurst-Adaptive Volatility Bands
A fractal-inspired evolution of Bollinger and Keltner bands that adapts dynamically to both volatility and trend persistence.
This indicator estimates the Hurst exponent (H) — a measure of market memory — and adjusts a standard volatility band to lean in the direction of the prevailing trend.
When H > 0.5, markets exhibit persistence (trending behavior); the bands shift in the trend’s direction.
When H < 0.5, markets are mean-reverting; the bands flatten and recent extremes become potential fade zones.
Band width scales with recent volatility (σ), expanding in turbulent conditions and contracting during calm periods.
Key Features:
Adaptive offset using the Hurst exponent
Volatility-sensitive width for dynamic market regimes
EMA baseline with directional bias
Clear visual separation between trending and choppy phases
Inspired by Benoit Mandelbrot’s The Misbehavior of Markets and H.E. Hurst’s original work on long-term memory in time series.
Use it to identify regime shifts, trend-following entries, and volatility-adjusted stop levels.
Credit for this script goes to a number of people including Steve B, MichaalAngle, doc and joecat808. 500 day DEMA (double EMA) can be used as a longer term momentum line.
MACD Enhanced [DCAUT]█ MACD Enhanced
📊 ORIGINALITY & INNOVATION
The MACD Enhanced represents a significant improvement over traditional MACD implementations. While Gerald Appel's original MACD from the 1970s was limited to exponential moving averages (EMA), this enhanced version expands algorithmic options by supporting 21 different moving average calculations for both the main MACD line and signal line independently.
This improvement addresses an important limitation of traditional MACD: the inability to adapt the indicator's mathematical foundation to different market conditions. By allowing traders to select from algorithms ranging from simple moving averages (SMA) for stability to advanced adaptive filters like Kalman Filter for noise reduction, this implementation changes MACD from a fixed-algorithm tool into a flexible instrument that can be adjusted for specific market environments and trading strategies.
The enhanced histogram visualization system uses a four-color gradient that helps communicate momentum strength and direction more clearly than traditional single-color histograms.
📐 MATHEMATICAL FOUNDATION
The core calculation maintains the proven MACD formula: Fast MA(source, fastLength) - Slow MA(source, slowLength), but extends it with algorithmic flexibility. The signal line applies the selected smoothing algorithm to the MACD line over the specified signal period, while the histogram represents the difference between MACD and signal lines.
Available Algorithms:
The implementation supports a comprehensive spectrum of technical analysis algorithms:
Basic Averages: SMA (arithmetic mean), EMA (exponential weighting), RMA (Wilder's smoothing), WMA (linear weighting)
Advanced Averages: HMA (Hull's low-lag), VWMA (volume-weighted), ALMA (Arnaud Legoux adaptive)
Mathematical Filters: LSMA (least squares regression), DEMA (double exponential), TEMA (triple exponential), ZLEMA (zero-lag exponential)
Adaptive Systems: T3 (Tillson T3), FRAMA (fractal adaptive), KAMA (Kaufman adaptive), MCGINLEY_DYNAMIC (reactive to volatility)
Signal Processing: ULTIMATE_SMOOTHER (low-pass filter), LAGUERRE_FILTER (four-pole IIR), SUPER_SMOOTHER (two-pole Butterworth), KALMAN_FILTER (state-space estimation)
Specialized: TMA (triangular moving average), LAGUERRE_BINOMIAL_FILTER (binomial smoothing)
Each algorithm responds differently to price action, allowing traders to match the indicator's behavior to market characteristics: trending markets benefit from responsive algorithms like EMA or HMA, while ranging markets require stable algorithms like SMA or RMA.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Histogram Interpretation:
Positive Values: Indicate bullish momentum when MACD line exceeds signal line, suggesting upward price pressure and potential buying opportunities
Negative Values: Reflect bearish momentum when MACD line falls below signal line, indicating downward pressure and potential selling opportunities
Zero Line Crosses: MACD crossing above zero suggests transition to bullish bias, while crossing below indicates bearish bias shift
Momentum Changes: Rising histogram (regardless of positive/negative) signals accelerating momentum in the current direction, while declining histogram warns of momentum deceleration
Advanced Signal Recognition:
Divergences: Price making new highs/lows while MACD fails to confirm often precedes trend reversals
Convergence Patterns: MACD line approaching signal line suggests impending crossover and potential trade setup
Histogram Peaks: Extreme histogram values often mark momentum exhaustion points and potential reversal zones
🎯 STRATEGIC APPLICATIONS
Comprehensive Trend Confirmation Strategies:
Primary Trend Validation Protocol:
Identify primary trend direction using higher timeframe (4H or Daily) MACD position relative to zero line
Confirm trend strength by analyzing histogram progression: consistent expansion indicates strong momentum, contraction suggests weakening
Use secondary confirmation from MACD line angle: steep angles (>45°) indicate strong trends, shallow angles suggest consolidation
Validate with price structure: trending markets show consistent higher highs/higher lows (uptrend) or lower highs/lower lows (downtrend)
Entry Timing Techniques:
Pullback Entries in Uptrends: Wait for MACD histogram to decline toward zero line without crossing, then enter on histogram expansion with MACD line still above zero
Breakout Confirmations: Use MACD line crossing above zero as confirmation of upward breakouts from consolidation patterns
Continuation Signals: Look for MACD line re-acceleration (steepening angle) after brief consolidation periods as trend continuation signals
Advanced Divergence Trading Systems:
Regular Divergence Recognition:
Bullish Regular Divergence: Price creates lower lows while MACD line forms higher lows. This pattern is traditionally considered a potential upward reversal signal, but should be combined with other confirmation signals
Bearish Regular Divergence: Price makes higher highs while MACD shows lower highs. This pattern is traditionally considered a potential downward reversal signal, but trading decisions should incorporate proper risk management
Hidden Divergence Strategies:
Bullish Hidden Divergence: Price shows higher lows while MACD displays lower lows, indicating trend continuation potential. Use for adding to existing long positions during pullbacks
Bearish Hidden Divergence: Price creates lower highs while MACD forms higher highs, suggesting downtrend continuation. Optimal for adding to short positions during bear market rallies
Multi-Timeframe Coordination Framework:
Three-Timeframe Analysis Structure:
Primary Timeframe (Daily): Determine overall market bias and major trend direction. Only trade in alignment with daily MACD direction
Secondary Timeframe (4H): Identify intermediate trend changes and major entry opportunities. Use for position sizing decisions
Execution Timeframe (1H): Precise entry and exit timing. Look for MACD line crossovers that align with higher timeframe bias
Timeframe Synchronization Rules:
Daily MACD above zero + 4H MACD rising = Strong uptrend context for long positions
Daily MACD below zero + 4H MACD declining = Strong downtrend context for short positions
Conflicting signals between timeframes = Wait for alignment or use smaller position sizes
1H MACD signals only valid when aligned with both higher timeframes
Algorithm Considerations by Market Type:
Trending Markets: Responsive algorithms like EMA, HMA may be considered, but effectiveness should be tested for specific market conditions
Volatile Markets: Noise-reducing algorithms like KALMAN_FILTER, SUPER_SMOOTHER may help reduce false signals, though results vary by market
Range-Bound Markets: Stability-focused algorithms like SMA, RMA may provide smoother signals, but individual testing is required
Short Timeframes: Low-lag algorithms like ZLEMA, T3 theoretically respond faster but may also increase noise
Important Note: All algorithm choices and parameter settings should be thoroughly backtested and validated based on specific trading strategies, market conditions, and individual risk tolerance. Different market environments and trading styles may require different configuration approaches.
📋 DETAILED PARAMETER CONFIGURATION
Comprehensive Source Selection Strategy:
Price Source Analysis and Optimization:
Close Price (Default): Most commonly used, reflects final market sentiment of each period. Best for end-of-day analysis, swing trading, daily/weekly timeframes. Advantages: widely accepted standard, good for backtesting comparisons. Disadvantages: ignores intraday price action, may miss important highs/lows
HL2 (High+Low)/2: Midpoint of the trading range, reduces impact of opening gaps and closing spikes. Best for volatile markets, gap-prone assets, forex markets. Calculation impact: smoother MACD signals, reduced noise from price spikes. Optimal when asset shows frequent gaps, high volatility during specific sessions
HLC3 (High+Low+Close)/3: Weighted average emphasizing the close while including range information. Best for balanced analysis, most asset classes, medium-term trading. Mathematical effect: 33% weight to high/low, 33% to close, provides compromise between close and HL2. Use when standard close is too noisy but HL2 is too smooth
OHLC4 (Open+High+Low+Close)/4: True average of all price points, most comprehensive view. Best for complete price representation, algorithmic trading, statistical analysis. Considerations: includes opening sentiment, smoothest of all options but potentially less responsive. Optimal for markets with significant opening moves, comprehensive trend analysis
Parameter Configuration Principles:
Important Note: Different moving average algorithms have distinct mathematical characteristics and response patterns. The same parameter settings may produce vastly different results when using different algorithms. When switching algorithms, parameter settings should be re-evaluated and tested for appropriateness.
Length Parameter Considerations:
Fast Length (Default 12): Shorter periods provide faster response but may increase noise and false signals, longer periods offer more stable signals but slower response, different algorithms respond differently to the same parameters and may require adjustment
Slow Length (Default 26): Should maintain a reasonable proportional relationship with fast length, different timeframes may require different parameter configurations, algorithm characteristics influence optimal length settings
Signal Length (Default 9): Shorter lengths produce more frequent crossovers but may increase false signals, longer lengths provide better signal confirmation but slower response, should be adjusted based on trading style and chosen algorithm characteristics
Comprehensive Algorithm Selection Framework:
MACD Line Algorithm Decision Matrix:
EMA (Standard Choice): Mathematical properties: exponential weighting, recent price emphasis. Best for general use, traditional MACD behavior, backtesting compatibility. Performance characteristics: good balance of speed and smoothness, widely understood behavior
SMA (Stability Focus): Equal weighting of all periods, maximum smoothness. Best for ranging markets, noise reduction, conservative trading. Trade-offs: slower signal generation, reduced sensitivity to recent price changes
HMA (Speed Optimized): Hull Moving Average, designed for reduced lag. Best for trending markets, quick reversals, active trading. Technical advantage: square root period weighting, faster trend detection. Caution: can be more sensitive to noise
KAMA (Adaptive): Kaufman Adaptive MA, adjusts smoothing based on market efficiency. Best for varying market conditions, algorithmic trading. Mechanism: fast smoothing in trends, slow smoothing in sideways markets. Complexity: requires understanding of efficiency ratio
Signal Line Algorithm Optimization Strategies:
Matching Strategy: Use same algorithm for both MACD and signal lines. Benefits: consistent mathematical properties, predictable behavior. Best when backtesting historical strategies, maintaining traditional MACD characteristics
Contrast Strategy: Use different algorithms for optimization. Common combinations: MACD=EMA, Signal=SMA for smoother crossovers, MACD=HMA, Signal=RMA for balanced speed/stability, Advanced: MACD=KAMA, Signal=T3 for adaptive behavior with smooth signals
Market Regime Adaptation: Trending markets: both fast algorithms (EMA/HMA), Volatile markets: MACD=KALMAN_FILTER, Signal=SUPER_SMOOTHER, Range-bound: both slow algorithms (SMA/RMA)
Parameter Sensitivity Considerations:
Impact of Parameter Changes:
Length Parameter Sensitivity: Small parameter adjustments can significantly affect signal timing, while larger adjustments may fundamentally change indicator behavior characteristics
Algorithm Sensitivity: Different algorithms produce different signal characteristics. Thoroughly test the impact on your trading strategy before switching algorithms
Combined Effects: Changing multiple parameters simultaneously can create unexpected effects. Recommendation: adjust parameters one at a time and thoroughly test each change
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Response Characteristics by Algorithm:
Fastest Response: ZLEMA, HMA, T3 - minimal lag but higher noise
Balanced Performance: EMA, DEMA, TEMA - good trade-off between speed and stability
Highest Stability: SMA, RMA, TMA - reduced noise but increased lag
Adaptive Behavior: KAMA, FRAMA, MCGINLEY_DYNAMIC - automatically adjust to market conditions
Noise Filtering Capabilities:
Advanced algorithms like KALMAN_FILTER and SUPER_SMOOTHER help reduce false signals compared to traditional EMA-based MACD. Noise-reducing algorithms can provide more stable signals in volatile market conditions, though results will vary based on market conditions and parameter settings.
Market Condition Adaptability:
Unlike fixed-algorithm MACD, this enhanced version allows real-time optimization. Trending markets benefit from responsive algorithms (EMA, HMA), while ranging markets perform better with stable algorithms (SMA, RMA). The ability to switch algorithms without changing indicators provides greater flexibility.
Comparative Performance vs Traditional MACD:
Algorithm Flexibility: 21 algorithms vs 1 fixed EMA
Signal Quality: Reduced false signals through noise filtering algorithms
Market Adaptability: Optimizable for any market condition vs fixed behavior
Customization Options: Independent algorithm selection for MACD and signal lines vs forced matching
Professional Features: Advanced color coding, multiple alert conditions, comprehensive parameter control
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions. Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always combine with proper risk management and thorough strategy testing.
Cycle VTLs – with Scaled Channels "Cycle VTLs – with Scaled Channels" for TradingView plots Valid Trend Lines (VTLs) based on Hurst's Cyclic Theory, connecting consecutive price peaks (downward VTLs) or troughs (upward VTLs) for specific cycles. It uses up to eight Simple Moving Averages (SMAs) (default lengths: 25, 50, 100, 200, 400, 800, 1600, 1600 bars) with customizable envelope bands to detect pivots and draw VTLs, enhanced by optional parallel channels scaled to envelope widths.
Key Features:
Valid Trend Lines (VTLs):
Upward VTLs: Connect consecutive cycle troughs, sloping upward.
Downward VTLs: Connect consecutive cycle peaks, sloping downward.
Hurst’s Rules:
Connects consecutive cycle peaks/troughs.
Must not cross price between points.
Downward VTLs:
No longer-cycle trough between peaks.
Invalid if slope is incorrect (upward VTL not up, downward VTL not down).
Expired VTLs: Historical VTLs (crossed by price) from up to three prior cycle waves.
SMA Cycles:
Eight customizable SMAs with envelope bands (offset × multiplier) for pivot detection.
Channels:
Optional parallel lines around VTLs, width set by channelFactor × envelope half-width.
Pivot Detection:
Fractal-based (pivotPeriod) on envelopes or price (usePriceFallback).
Customization:
Toggle cycles, VTLs, and channels.
Adjust SMA lengths, offsets, colors, line styles, and widths.
Enable centered envelopes, slope filtering, and limit stored lines (maxStoredLines).
Usage in Hurst’s Cyclic TheoryAnalysis:
VTLs identify cycle trends; upward VTLs suggest bullish momentum, downward VTLs bearish.
Price crossing below an upward VTL confirms a peak in the next longer cycle; crossing above a downward VTL confirms a trough.
Trading:
Buy: Price bounces off upward VTL or breaks above downward VTL.
Sell: Price rejects downward VTL or breaks below upward VTL.
Use channels for support/resistance, breakouts, or stop-loss/take-profit levels.
Workflow:
Add indicator on TradingView.
Enable desired cycles (e.g., 50-bar, 1600-bar), adjust pivotPeriod, channelFactor, and showOnlyCorrectSlope.
Monitor VTL crossings and channels for trade signals.
NotesOptimized for performance with line limits.
Ideal for cycle-based trend analysis across markets (stocks, forex, crypto).
Debug labels show pivot counts and VTL status.
This indicator supports Hurst’s Cyclic Theory for trend identification and trading decisions with flexible, cycle-based VTLs and channels.
Use global variable to scale to chart. best results use factors of 2 and double. try 2, 4, 8, 16...128, 256, etc until price action fits 95% in smallest cycle.
Ram HTF Direction & Market ProfileRam HTF Direction & Markey Profile.
I am trying to identify the HTF(Daily) Direction and Market profiles POC,VAL,VAH to trade on 1HR.
Market Structure Report Library [TradingFinder]🔵 Introduction
Market Structure is one of the most fundamental concepts in Price Action and Smart Money theory. In simple terms, it represents how price moves between highs and lows and reveals which phase of the market cycle we are currently in uptrend, downtrend, or transition.
Each structure in the market is formed by a combination of Breaks of Structure (BoS) and Changes of Character (CHoCH) :
BoS occurs when the market breaks a previous high or low, confirming the continuation of the current trend.
CHoCH occurs when price breaks in the opposite direction for the first time, signaling a potential trend reversal.
Since price movement is inherently fractal, market structure can be analyzed on two distinct levels :
Major / External Structure: represents the dominant macro trend.
Minor / Internal Structure: represents corrective or smaller-scale movements within the larger trend.
🔵 Library Purpose
The “Market Structure Report Library” is designed to automatically detect the current market structure type in real time.
Without drawing or displaying any visuals, it analyzes raw price data and returns a series of logical and textual outputs (Return Values) that describe the current structural state of the market.
It provides the following information :
Trend Type :
External Trend (Major): Up Trend, Down Trend, No Trend
Internal Trend (Minor): Up Trend, Down Trend, No Trend
Structure Type :
BoS : Confirms trend continuation
CHoCH : Indicates a potential trend reversal
Consecutive BoS Counter : Measures trend strength on both Major and Minor levels.
Candle Type : Returns the current candle’s condition(Bullish, Bearish, Doji)
This library is specifically designed for use in Smart Money–based screeners, indicators, and algorithmic strategies.
It can analyze multiple symbols and timeframes simultaneously and return the exact structure type (BoS or CHoCH) and trend direction for each.
🔵 Function Outputs
The function MS() processes the price data and returns seven key outputs,
each representing a distinct structural state of the market. These values can be used in indicators, strategies, or multi-symbol screeners.
🟣 ExternalTrend
Type : string
Description : Represents the direction of the Major (External) market structure.
Possible values :
Up Trend
Down Trend
No Trend
This is determined based on the behavior of Major Pivots (swing highs/lows).
🟣 InternalTrend
Type : string
Description : Represents the direction of the Minor (Internal) market structure.
Possible values :
Up Trend
Down Trend
No Trend
🟣 M_State
Type : string
Description : Specifies the type of the latest Major Structure event.
Possible values :
BoS
CHoCH
🟣 m_State
Type : string
Description : Specifies the type of the latest Minor Structure event.
Possible values :
BoS
CHoCH
🟣 MBoS_Counter
Type : integer
Description : Counts the number of consecutive structural breaks (BoS) in the Major structure.
Useful for evaluating trend strength :
Increasing count: indicates trend continuation.
Reset to zero: typically occurs after a CHoCH.
🟣 mBoS_Counter
Type : integer
Description : Counts the number of consecutive structural breaks in the Minor structure.
Helps analyze the micro structure of the market on lower timeframes.
Higher value : strong internal trend.
Reset : indicates a minor pullback or reversal.
🟣 Candle_Type
Type : string
Description : Represents the type of the current candle.
Possible values :
Bullish
Bearish
Doji
import TFlab/Market_Structure_Report_Library_TradingFinder/1 as MSS
PP = input.int (5 , 'Market Structure Pivot Period' , group = 'Symbol 1' )
= MSS.MS(PP)
Intraday Key OpensIntraday Key Opens plots the key session and cycle opening prices: 90-minute cycles opens, New York open, Asia open, and 9:30 US market open. Each line is labeled, color-coded, and can be toggled on/off independently. Designed for intraday traders to quickly identify important price levels and session pivots.
ICT 369 Sniper MSS Indicator (HTF Bias) - H2LThis script is an ICT (Inner Circle Trader) concept-based trading indicator designed to identify high-probability reversal or continuation setups, primarily focusing on intraday trading using a Higher Timeframe (HTF) directional bias.
Here are the four core components of the indicator:
Higher Timeframe (HTF) Bias Filter (Market Structure Shift - MSS): It determines the overall trend by checking if the current price has broken the most recent high or low swing point of a larger timeframe (e.g., 4H). This establishes a Bullish or Bearish bias, ensuring trades align with the dominant trend.
Fair Value Gap (FVG) and OTE: It identifies price imbalances (FVGs) and calculates the Optimal Trade Entry (OTE) levels (50%, 62%, 70.5%, etc.) within those gaps, looking for price to retrace into these specific areas.
Kill Zones (Timing): It incorporates specific time windows (London and New York Kill Zones, based on NY Time) where institutional trading activity is high, only allowing entry signals during these defined periods.
Signal and Targets: It triggers a Long or Short signal when all criteria are met (HTF Bias, FVG, OTE retracement, and Kill Zone timing). It then calculates and plots suggested trade levels, including a Stop Loss (SL) and three Take Profit targets (TP1, TP2, and a dynamic Runner Target based on the weekly Average True Range or ATR).
In summary, it's a comprehensive tool for traders following ICT principles, automating the confluence check across trend, structure, liquidity, and timing.
ORB 15m + MAs (v4.1)Session ORB Live Pro — Pre-Market Boxes & MA Suite (v4.1)
What it is
A precision Opening Range Breakout (ORB) tool that anchors every session to one specific 15-minute candle—then projects that same high/low onto lower timeframes so your 1m/5m levels always match the source 15m bar. Perfect for scalpers who want session structure without drift.
What it draws
Asia, Pre-London, London, Pre-New York, New York session boxes.
On 15m: only the high/low of the first 15-minute bar of each window (optionally persists for extra bars).
On 5m: mirrors the same 15m range, visible up to 10 bars.
On 1m: mirrors the same 15m range, visible up to 15 bars.
Levels update live while the 15m candle is forming, then lock.
Fully editable windows (easy UX)
Change session times with TradingView’s native input.session fields using the familiar format HHMM-HHMM:1234567. You can tweak each window independently:
Asia
Pre-London
London
Pre-New York
New York
Multi-TF logic (no guesswork)
Designed to show only on 1m, 5m, 15m (by default).
15m = ground truth. Lower timeframes never “recalculate a different range”—they mirror the 15m bar for that session, exactly.
Alerts
Optional breakout alerts when price closes above/below the session range.
Clean visuals
Per-session color controls (box + lines). Boxes extend only for the configured number of bars per timeframe, keeping charts uncluttered.
Built-in MA suite
SMA 50 and RMA 200.
Three extra MAs (SMA/EMA/RMA/WMA/HMA) with selectable color, width, and style (line, stepline, circles).
Why traders like it
Consistency: Lower-TF ranges always match the 15m source bar.
Speed: You see structure immediately—no waiting for N bars.
Control: Edit session times directly; tune how long boxes stay on chart per TF.
Clarity: Minimal, purposeful plotting with alerts when it matters.
Quick start
Set your session times via the five input.session fields.
Choose how long boxes persist on 1m/5m/15m.
Enable alerts if you want instant breakout notifications.
(Optional) Configure the MA suite for trend/bias context.
Best for
Intraday traders and scalpers who rely on repeatable session behavior and demand exact cross-TF alignment of ORB levels.
Multi Timeframe BOS & rBOSThis is the same Multi-Timeframe Break of Structure and Market Structure Shift posted by Lenny_Kiruthu. However, the only difference is the naming of Market Structure Shift to rBOS (Break of Structure Reverse). To me, they are all break of structures when previous peaks or valleys are violated. The only difference is in sequence. Once a sequence of BOS reverses, then a new sequence begins. To me, this simplifies the various terminology incorporated by different systems such as ICT or SMT which adds unnecessary complexity.
eT
AVGO Advanced Day Trading Strategy📈 Overview
The AVGO Advanced Day Trading Strategy is a comprehensive, multi-timeframe trading system designed for active day traders seeking consistent performance with robust risk management. Originally optimized for AVGO (Broadcom), this strategy adapts well to other liquid stocks and can be customized for various trading styles.
🎯 Key Features
Multiple Entry Methods
EMA Crossover: Classic trend-following signals using fast (9) and medium (16) EMAs
MACD + RSI Confluence: Momentum-based entries combining MACD crossovers with RSI positioning
Price Momentum: Consecutive price action patterns with EMA and RSI confirmation
Hybrid System: Advanced multi-trigger approach combining all methodologies
Advanced Technical Arsenal
When enabled, the strategy analyzes 8+ additional indicators for confluence:
Volume Price Trend (VPT): Measures volume-weighted price momentum
On-Balance Volume (OBV): Tracks cumulative volume flow
Accumulation/Distribution Line: Identifies institutional money flow
Williams %R: Momentum oscillator for entry timing
Rate of Change Suite: Multi-timeframe momentum analysis (5, 14, 18 periods)
Commodity Channel Index (CCI): Cyclical turning points
Average Directional Index (ADX): Trend strength measurement
Parabolic SAR: Dynamic support/resistance levels
🛡️ Risk Management System
Position Sizing
Risk-based position sizing (default 1% per trade)
Maximum position limits (default 25% of equity)
Daily loss limits with automatic position closure
Multiple Profit Targets
Target 1: 1.5% gain (50% position exit)
Target 2: 2.5% gain (30% position exit)
Target 3: 3.6% gain (20% position exit)
Configurable exit percentages and target levels
Stop Loss Protection
ATR-based or percentage-based stop losses
Optional trailing stops
Dynamic stop adjustment based on market volatility
📊 Technical Specifications
Primary Indicators
EMAs: 9 (Fast), 16 (Medium), 50 (Long)
VWAP: Volume-weighted average price filter
RSI: 6-period momentum oscillator
MACD: 8/13/5 configuration for faster signals
Volume Confirmation
Volume filter requiring 1.6x average volume
19-period volume moving average baseline
Optional volume confirmation bypass
Market Structure Analysis
Bollinger Bands (20-period, 2.0 multiplier)
Squeeze detection for breakout opportunities
Fractal and pivot point analysis
⏰ Trading Hours & Filters
Time Management
Configurable trading hours (default: 9:30 AM - 3:30 PM EST)
Weekend and holiday filtering
Session-based trade management
Market Condition Filters
Trend alignment requirements
VWAP positioning filters
Volatility-based entry conditions
📱 Visual Features
Information Dashboard
Real-time display of:
Current entry method and signals
Bullish/bearish signal counts
RSI and MACD status
Trend direction and strength
Position status and P&L
Volume and time filter status
Chart Visualization
EMA plots with customizable colors
Entry signal markers
Target and stop level lines
Background color coding for trends
Optional Bollinger Bands and SAR display
🔔 Alert System
Entry Alerts
Customizable alerts for long and short entries
Method-specific alert messages
Signal confluence notifications
Advanced Alerts
Strong confluence threshold alerts
Custom alert messages with signal counts
Risk management alerts
⚙️ Customization Options
Strategy Parameters
Enable/disable long or short trades
Adjustable risk parameters
Multiple entry method selection
Advanced indicator on/off toggle
Visual Customization
Color schemes for all indicators
Dashboard position and size options
Show/hide various chart elements
Background color preferences
📋 Default Settings
Initial Capital: $100,000
Commission: 0.1%
Default Position Size: 10% of equity
Risk Per Trade: 1.0%
RSI Length: 6 periods
MACD: 8/13/5 configuration
Stop Loss: 1.1% or ATR-based
🎯 Best Use Cases
Day Trading: Designed for intraday opportunities
Swing Trading: Adaptable for longer-term positions
Momentum Trading: Excellent for trending markets
Risk-Conscious Trading: Built-in risk management protocols
⚠️ Important Notes
Paper Trading Recommended: Test thoroughly before live trading
Market Conditions: Performance varies with market volatility
Customization: Adjust parameters based on your risk tolerance
Educational Purpose: Use as a learning tool and customize for your needs
🏆 Performance Features
Detailed performance metrics
Trade-by-trade analysis capability
Customizable risk/reward ratios
Comprehensive backtesting support
This strategy is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and consider your financial situation before trading.






















