Hi-Lo TrendThis script uses the most recent low/high and candle size to determine trend breakouts.
The trend is determined buy whether the most recent price extreme within the Lookback period is a high or low. If it is a most recent high, it is an uptrend, if it is a lwo, a downtrend.
Bands are created using the average absolute difference of current minus previous close over the MABandPeriod, multiplied by the MABandMultiplier.
If the current close minus previous close is above/below the band, then a blue dot is painted and it is a breakout.
a buy alert fires when a downtrend becomes an uptrend and a breakout above the bands happens.
A sell alert fires when an uptrend becomes a downtrend and a breakout below the bands happns.
Cari dalam skrip untuk "breakout"
2 Candles Inside ATR2 agitated candles falling inside ATR range, awaiting possibly a big move.
Buy / Sell signals at combined high / low can be used as order with other as stop loss.
Counter trade, when this minimal stop loss is hit, is also as useful. However, wait till the SL candle closes, before opening position on the other side.
Works quite well on 15 mins chart, with settings of ATR duration 25 and multiplier 0.6. These settings are configurable, so feel free.
Smoothed CandlesHello Traders,
This is " Smoothed Candles " script to get rid of noises and to get a smoothed chart to figure out breakouts and price movements easily.
There are three scaling methods: User Defined, Dynamic (ATR) and Percentage
Optionally you can add 2 Simple Moving Averages and 2 Exponential Moving Averages
Optionally you can hide the Wicks, example:
You can add moving averages:
Easily find breakouts:
Enjoy!
Hikkake PatternLifted description from web:
Hikkake means to trap, trick, or ensnare. Primarily, this price pattern seeks to identify inside bar breakouts and profit from their failures.
An inside bar is a price bar that is entirely within the range of the preceding price bar. Inside bars are typical on price charts of most timeframes.
While you’ll often find inside bars in congested markets, they also offer a low-risk entry point for price action traders. The contracted range of an inside bar offers a natural tight stop-loss.
Hence, inside bar breakouts seem attractive. However, if you are patient and focus on identifying false breakouts, you might be able to find more reliable trading setups in the form of Hikkakes.
In a nutshell, the Hikkake pattern offers a systematic approach to trading false inside bar breakouts.
As a filter I incorporated VWAP into the code to only trigger Bullish / Bearish signals when price is Above/Below VWAP respectively. The ATR is used to create a Stop buffer (red cross) for the Entry signal ( green dot ). The R1 and R2 (orange squares) are two possible profit targets that are customizable to different Risk multiples based upon the difference between Entry and Stop.
Pure Price Zone Flow🔎 What this indicator is
It’s a price-action-based zone indicator. Unlike moving average systems, this one relies only on:
1. Swing Highs & Swing Lows → The highest and lowest points within a recent lookback period (like "mini support & resistance").
2. ATR (Average True Range) → A volatility measure that expands the zone, making it more adaptive to different market conditions.
3. Breakouts & Retests → When price breaks above a swing high (bullish) or below a swing low (bearish), the indicator marks it and highlights the new trend.
👉 The goal is to spot clean structure shifts and define clear trend zones where traders can position themselves.
________________________________________
⚙️ How it is calculated
1. Swing High & Swing Low
o We look back len candles (default 20).
o Find the highest high (swingHigh) and the lowest low (swingLow) in that window.
o This forms the price range zone.
2. ATR Expansion
o We calculate ATR over the same len.
o Add/subtract it (multiplied by atrMult) to the zone edges to expand them.
o This ensures the zones breathe with volatility (tight in quiet markets, wide in choppy ones).
3. Mid-Zone
o Simply the average of swingHigh and swingLow.
o If price is above mid → bullish bias.
o If below mid → bearish bias.
o This gives us the trend color for candles.
4. Breakouts
o If the close crosses above swingHigh, we mark a bullish breakout with a label.
o If the close crosses below swingLow, we mark a bearish breakdown.
________________________________________
📊 How it helps traders
This indicator helps by:
1. Identifying Structure Shifts
o Many traders watch swing highs/lows for breakouts or reversals.
o This automates the process and visually confirms when structure is broken.
2. Dynamic Zone Trading
o Instead of fixed support/resistance, the ATR expansion adapts to volatility.
o This avoids false signals in high-volatility conditions.
3. Trend Bias at a Glance
o Candle coloring instantly tells you whether price is in bullish or bearish territory relative to the mid-zone.
4. Breakout Confirmation
o The labels show when a breakout has occurred, so traders can react quickly (e.g., enter with trend, wait for retest, or avoid fading moves).
________________________________________
🌍 Markets it works best in
• Crypto (Bitcoin, Ethereum, etc.): Very effective since crypto is breakout-driven and respects swing levels.
• Forex: Good for volatility-adaptive structure analysis, especially in trending pairs.
• Indices (SPX, NASDAQ, DAX, NIFTY): Useful for breakout trading during session opens or key news events.
• Commodities (Gold, Oil, Silver): Works well to define intraday ranges and breakout levels.
⚠️ Less useful in low-volatility, mean-reverting assets (like some penny stocks or sideways ranges), because breakouts may be rare or fake.
________________________________________
💡 How it adds value
• Strips away unnecessary complexity (no lagging averages).
• Focuses directly on what price is doing structurally.
• Adaptive → works across different markets & timeframes.
• Easy visualization → zones, trend coloring, breakout markers.
• Helps traders trade with the flow of the market, instead of guessing tops/bottoms.
________________________________________
👉 In short:
This indicator turns raw price action into clear, actionable zones.
It highlights when the market shifts from balance to breakout, so traders can align with momentum rather than fighting it.
🏛️ INSTITUTIONAL TRENDLINE v8 • Open Source🏛️ INSTITUTIONAL TRENDLINE v8 • Open Source
Adaptive S/R discovery with ML scoring, MTF confluence, and event-driven alerts
What it does (in one breath):
This indicator auto-discovers institutional-grade trendlines / dynamic support & resistance, scores them for quality using a dual-regime ML model (trend vs. range), validates them with multiple techniques (Theil–Sen, Huber, ATR/RSI/MACD/EMA, MTF confluence), then tracks breakouts, retests, failed breaks, proximity/touch events, and learns from outcomes to adapt over time. A visual panel summarizes stats, and optional heatmap/zones show where price is most “supported” or “capped”.
🚀 Quick Start (2 minutes)
Add to chart and leave defaults.
At the top of Inputs:
🎛️ Preset → choose your style: Scalper, Swing, Investor (or Custom).
🧬 Market Profile → pick Crypto/FX/Stocks + style or “Auto by Timeframe”.
Keep 🎯 Accuracy Mode = Quantum AI and ⚡ Performance = Maximum Quality if your device handles it.
Turn on 💥 Breakout Signals and 🚨 Alerts if you want notifications.
Read the right-side panel: Active Lines, Avg Q, Best Line, Market State, Nearest S/R, Top-3 lines, Pattern, Touch counts.
That’s it. You’ll see thinner, professional trendlines, small labels, optional zones, and tasteful break/retest markers.
🧠 How it works (plain English)
Discovery: It samples price pairs (with a swing-pivot bias) and fits many candidate lines.
Inlier-only R²: Instead of punishing outliers, it measures how tight touching bars are to a line.
ML Quality (0–100): Six signals (Touches, Volume @ touches, RSI, MACD, Volatility, Duration) are weighted differently for Trend vs Range regimes.
Validation: Rejects lines that disagree across Theil–Sen and Huber regressions (>15% slope deviation), fail slope/ATR filters, or lack MTF confluence.
Live tracking: Once a line is on the chart, the script watches for Breakouts → Retests → Failed breaks, and logs outcomes to continually re-weight the ML model (if enabled).
🎛️ Inputs (top section first)
1) Presets & Profiles (at the top)
🎛️ Preset
Scalper – lower lookbacks, faster, more signals.
Swing – balanced lookbacks, 2–4 lines per window.
Investor – longer lookbacks, fewer but stronger lines.
Custom – you control everything below.
🧬 Market Profile
Tailors thresholds for Crypto / FX / Stocks and your style (Scalper / Swing / Investor). Choose Auto by Timeframe to adapt from your chart resolution.
These two choices set “effective” requirements under the hood (min quality, R², proximity windows, cleanup cadence, etc.) so you don’t have to micromanage.
2) 🤖 Machine Learning Engine
Enable ML Enhancement – turns the adaptive scoring on/off.
ML Sensitivity – caps the maximum achievable score (lower = stricter).
Adaptive Learning – updates weights after each confirmed outcome.
Outcome Window (bars) & Target (ATR) – define when a breakout is counted as success or fail for learning.
Dual-Regime Models – separate weight sets for Trend and Range.
Tip: If results look “too picky,” raise ML Sensitivity slightly (e.g., 0.85→0.95).
3) 🎯 Accuracy & Filters
Minimum Touch Points / Quality / R² – base requirements for new lines.
Multi-Algorithm Validation – confirms slope across three regressions.
Volume / RSI / MACD / EMA / ATR filters – optional evidence checks.
No-Repaint Strict (HTF closed only) – for purists; fewer but cleaner MTF confirmations.
4) 🧠 Pro Logic / MTF
Swing-Anchored Sampling Bias – increases hits on meaningful swings.
HTF 1 / HTF 2 – reference frames for confluence (e.g., 4H & 1D).
HTF Bars to Scan / Touches Needed – how much agreement to demand.
Geometric Midline Agreement – proximity to HTF midlines (20-SMA).
Midline Distance Threshold (×ATR) – how strict that midline check is.
5) 💎 Visual System
Display Trendlines / Zones / Smart Labels / Breakout Signals / Heatmap – toggle pieces on/off.
Visual Theme & Color Intensity – pick a palette; v8 lines are thinner with subtle gradients.
Highlight Top-3 Lines – faint halo on the three highest-quality lines.
Limit Signal Markers / Bar – prevents clutter in fast moves.
Tip: For the cleanest chart: show Trendlines + Breakouts, keep Zones semi-transparent, and enable Heatmap only when you want confluence context.
6) 🚨 Alerts
Enable Smart Alerts – master switch.
Alert Quality Threshold – only alert for lines ≥ this Q%.
Base Proximity (ATR) & Slope-Adaptive Proximity – how close is “near”.
Retest / Failed-Break Windows – how long after a break to track.
Per-Line Cool-Off (bars) – spacing to avoid spam.
Consolidated JSON Alert/Bar – single JSON payload with all events per bar (great for bots).
Fire Inline Alerts (verbose) – pop real-time alerts the moment events occur.
Alert names (mapped to alertconditions):
🆕 New S/R Created
📍 Approaching Trendline
🎯 Touching Trendline
🟢 Bullish Breakout / 🔴 Bearish Breakdown
♻️ Bullish Retest / ♻️ Bearish Retest
⛔ Failed Break
7) ⚡ Performance
Performance Mode – quality vs speed.
Max New Lines per Lookback/Bar – caps how many fresh lines a bar can add.
Cleanup Interval (bars) & Max Lines to Keep – automatic memory & clutter control.
Theil–Sen Sampled Pairs – fewer = faster; more = robust.
📈 How to read the chart
Lines:
Color = Support (green) or Resistance (red) at current price.
Thickness/Style = relates to Quality and Touches (higher Q = slightly bolder).
Labels show a badge (💎 🏆 ⭐ ✅ 📊) with Q%. Tooltip lists touches, R², price@line, lookback, and which evidences are ON.
Zones: Soft confidence corridors around lines (ATR-scaled).
Heatmap: A faint background tint—dominant support, resistance, or neutral/confluence.
Break markers: tiny ▲ / ▼ (or 🚀/💀 when very strong). Retests and failed breaks are tagged separately.
Top-3 glow: subtle halo on the three best lines right now.
🧭 Trading workflow (example)
Scenario A – Trend continuation
Market panel shows TREND; Top-3 lines include two rising supports ≥90% Q.
Price approaches one of them → Touch → Bullish breakout above a local resistance line.
Wait for ♻️ Retest of that broken line from above; if RSI>50 & MACD>0 (shown in panel), open a long with stop just under the line or zone.
Exit partials at next resistance line; trail under the line.
Scenario B – Range fade
Panel says RANGE; heatmap is neutral/confluence.
Price tags a high-Q red line and prints Touch without breakout, while RSI>60 cools off.
Enter a mean-revert short with stop above the line; target midrange or next green line.
If a Bullish breakout fires during the trade → respect the Failed Break logic; exit quickly.
Scenario C – Breakout trader
Filter only lines with Q ≥ 90% and alerts ON.
When Breakout triggers with strength ≥ 4/7 (see panel), take a starter.
Add on Retest if it prints within your retest window and confluence still looks good.
Manage risk with ATR or zone width.
This is a levels & event indicator. It doesn’t replace your system; it gives objective lines and objective events around those lines.
✅ Best-practice setup
Presets/Profiles: Start with Swing + your Market Profile.
ML Sensitivity: 0.90–0.95 for most markets.
Alerts: Set Alert Quality ≥ 85–90, Cool-Off = 4–6 bars.
MTF: Use 4H + 1D on intraday; 1D + 1W on daily charts.
Clutter control: Max Lines ~200, Cleanup ~50 bars, Signal cap 6/bar (defaults are sensible).
No-repaint strict: Turn on for signal review; turn off if you want more frequent MTF confirmations in real time.
🔬 Research Mode (optional)
Enable 🧪 Research Mode to track win-rates by quality buckets. The panel shows Win% so you can calibrate your thresholds per market.
⚠️ Notes & limitations
This is open-source research software. Past performance ≠ future results.
Learning requires time: the ML engine adapts after outcomes; don’t expect instant magic.
Very low-liquidity symbols may produce fewer reliable lines; increase lookbacks or tighten filters.
MTF data uses request.security with no lookahead; turning No-Repaint Strict on can further reduce signals.
🧩 Troubleshooting
“Too many lines.” Raise Min Quality / R², lower Max Lines, or reduce cap per lookback.
“Too few lines.” Lower Min Quality a bit, raise ML Sensitivity, or choose an easier Preset/Market Profile.
“Alerts are spammy.” Raise Alert Quality, increase Cool-Off, increase Proximity threshold.
“Performance is slow.” Use Balanced / Fast, reduce Theil–Sen pairs, or extend Cleanup Interval.
📦 Included alertconditions (for one-click alert rules)
New S/R Created
Approaching Trendline
Touching Trendline
Bullish Breakout / Bearish Breakdown
Bullish Retest / Bearish Retest
Failed Break
Enjoy, share feedback, and feel free to fork.
If you publish ideas using it, please credit “INSTITUTIONAL TRENDLINE v8 • OS” so other traders can find the open-source original. Happy trading! 🫶
Hawkes Volatility Exit IndicatorOverview
The Hawkes Volatility Exit Indicator is a powerful tool designed to help traders capitalize on volatility breakouts and exit positions when momentum fades. Built on the Hawkes process, it models volatility clustering to identify optimal entry points after quiet periods and exit signals during volatility cooling. Designed to be helpful for swing traders and trend followers across markets like stocks, forex, and crypto.
Key Features Volatility-Based Entries: Detects breakouts when volatility spikes above the 95th percentile (adjustable) after quiet periods (below 5th percentile).
This indicator is probably better on exits than entries.
Smart Exit Signals: Triggers exits when volatility drops below a customizable threshold (default: 30th percentile) after a minimum hold period.
Hawkes Process: Uses a decay-based model (kappa) to capture volatility clustering, making it responsive to market dynamics.
Visual Clarity: Includes a volatility line, exit threshold, percentile bands, and intuitive markers (triangles for entries, X for exits).
Status Table: Displays real-time data on position (LONG/SHORT/FLAT), volatility regime (HIGH/LOW/NORMAL), bars held, and exit readiness.
Customizable Alerts: Set alerts for breakouts and exits to stay on top of trading opportunities.
How It Works Quiet Periods: Identifies low volatility (below 5th percentile) that often precede significant moves.
Breakout Entries: Signals bullish (triangle up) or bearish (triangle down) entries when volatility spikes post-quiet period.
Exit Signals: Suggests exiting when volatility cools below the exit threshold after a minimum hold (default: 3 bars).
Visuals & Table: Tracks volatility, position status, and signals via lines, shaded zones, and a detailed status table.
Settings
Hawkes Kappa (0.1): Adjusts volatility decay (lower = smoother, higher = more sensitive).
Volatility Lookback (168): Sets the period for percentile calculations.
ATR Periods (14): Normalizes volatility using Average True Range.
Breakout Threshold (95%): Volatility percentile for entries.
Exit Threshold (30%): Volatility percentile for exits.
Quiet Threshold (5%): Defines quiet periods.
Minimum Hold Bars (3): Ensures positions are held before exiting.
Alerts: Enable/disable breakout and exit alerts.
How to Use
Entries: Look for triangle markers (up for long, down for short) and confirm with the status table showing "ENTRY" and "LONG"/"SHORT."
Exits: Exit on X cross markers when the status table shows "EXIT" and "Exit Ready: YES."
Monitoring: Use the status table to track position, bars held, and volatility regime (HIGH/LOW/NORMAL).
Combine: Pair with price action, support/resistance, or other indicators for better context.
Tips : Adjust thresholds for your market: lower breakout thresholds for more signals, higher exit thresholds for earlier exits.
Test on your asset to ensure compatibility (best for markets with volatility clustering).
Use alerts to automate signal detection.
Limitations Requires sufficient data (default: 168 bars) for reliable signals. Check "Data Status" in the table.
Focuses on volatility, not price direction—combine with trend tools.
May lag slightly due to the smoothing nature of the Hawkes process.
Why Use It?
The Hawkes Volatility Exit Indicator offers a unique, data-driven approach to timing trades based on volatility dynamics. Its clear visuals, customizable settings, and real-time status table make it a valuable addition to any trader’s toolkit. Try it to catch breakouts and exit with precision!
This indicator is based on neurotrader888's python repo. All credit to him. All mistakes mine.
This conversion published for wider attention to the Hawkes method.
Liquidity Spectrum Visualizer [BigBeluga]🔵 OVERVIEW
The Liquidity Spectrum Visualizer is a smart tool for exposing hidden liquidity zones by combining a dynamic volume profile, clear liquidity levels, and intuitive volume bubbles directly on your price chart. It shows you exactly where significant volume is clustering inside your chosen lookback period — highlighting where big market participants may be defending price or planning breakouts.
🔵 CONCEPTS
Volume Profile Bins: Breaks your custom lookback range into 100 fine price bins, calculating total volume per bin to create a precise vertical liquidity histogram.
Liquidity Levels: Bins with high relative volume automatically plot as horizontal lines — thicker and brighter lines signal stronger liquidity concentrations.
Dynamic Coloring: Profile bins and liquidity levels adjust their colors live based on whether current price is trading above (support) or below (resistance).
Volume Bubbles: Each candle displays a bubble at its HLC3 price —
- The bubble’s size shows relative candle volume.
- Its color gradient indicates bullish or bearish volume: greenish for bullish candles, orange for bearish.
Bubble Labels: The largest bubbles automatically label the actual volume amount, revealing big hidden flows.
Range Box High/Low: Marks the absolute swing high and low inside the lookback window, clearly framing the active liquidity zone.
🔵 FEATURES
Smart, auto-scaled volume profile up to 200 candles (or custom).
Liquidity levels with dynamic thickness and color based on real-time volume.
Bubbles sized and colored to show both volume magnitude and bullish/bearish bias.
Largest bubbles labeled for fast detection of high-impact bars.
High and low price labels clearly show the analyzed range.
Toggle Volume Profile, Liquidity Levels, and Bubbles independently.
🔵 HOW TO USE
Watch for thick, bright liquidity levels — these zones mark where large orders or stop clusters are likely hidden.
Use dynamic coloring: if price is above a level, it’s support; if below, it’s resistance.
Pay special attention to big bubbles: these mark sudden spikes in traded volume and can signal absorption, traps, breakouts or significant price levels.
Combine with your existing confluence tools to confirm breakouts or fakeouts around visible liquidity clusters.
🔵 CONCLUSION
The Liquidity Spectrum Visualizer transforms hidden order flow into an intuitive, color-coded map. You see at a glance where price is absorbing, consolidating, or ready to break — all powered by real-time volume behavior and smart visuals. It’s a must-have tool for traders who want to read liquidity and react ahead of the crowd.
Hull For LoopHull For Loop is a sophisticated trend-following indicator that combines the smoothness of Hull Moving Averages with advanced trend detection algorithms and robust confirmation mechanisms.
## How It Works
At its foundation, Hull For Loop employs a custom-calculated Hull Moving Average using weighted moving average for-loops to achieve optimal smoothness and responsiveness. The system operates through three distinct layers: Hull MA calculation with adjustable smoothing multipliers, advanced trend detection using ATR-based slope thresholds, and multi-bar trend confirmation to filter false breakouts.
The logic flow is elegantly simple yet powerful:
- Hull Calculation combines half-period and full-period weighted moving averages, then applies square-root smoothing for enhanced responsiveness
- Trend Detection analyzes Hull slope against dynamic ATR-based thresholds, classifying market direction as bullish, bearish, or neutral
- Confirmation System requires sustained directional movement across multiple bars before triggering signals, dramatically reducing whipsaws
When Hull slope exceeds the positive threshold, bullish conditions emerge. When it falls below the negative threshold, bearish momentum takes control. The multi-bar confirmation ensures only sustained moves generate actionable signals, making this system ideal for trend-following strategies across volatile markets.
The advanced slope analysis mechanism adapts to market volatility through ATR integration, ensuring sensitivity remains optimal during both high-volatility breakouts and low-volatility consolidations, delivering consistent performance across varying market conditions.
## Features
- Custom Hull Implementation : For-loop calculations for precise weighted moving average control and enhanced smoothness
- Dynamic Trend Detection : ATR-based slope analysis automatically adjusts sensitivity to market volatility conditions
- Multi-Bar Confirmation : Configurable confirmation periods (1-5 bars) eliminate false signals and reduce trading noise
- Advanced Visual System : Dynamic color coding, optional arrows, and statistics table for comprehensive market visualization
- Optimized for Bitcoin : Extensively backtested parameters delivering 128.58% returns with 55% drawdown reduction versus buy-and-hold
- Flexible Configuration : Hull length (1-200), smoothing multiplier (0.1-3.0), sensitivity (1-10), and confirmation settings
- Professional Alerts : Comprehensive alert system for trend changes and entry signals with strength percentages
- Real-time Analytics : Optional statistics table displaying trend direction, strength, Hull value, and current price
## Signal Generation
Hull For Loop generates multiple signal types for comprehensive trend analysis and precise entry/exit timing:
Primary Signals : Confirmed trend changes from bullish to bearish or vice versa - highest probability directional moves
Entry Signals : Initial trend confirmation after multi-bar validation - optimal position entry points
Strength Indicators : Real-time trend strength percentages based on directional momentum over lookback periods
Visual Confirmations : Color-coded Hull line providing instant visual trend status
The confirmation system adds crucial reliability - signals must persist through the specified confirmation period before activation, ensuring only sustained moves trigger trading decisions rather than temporary price fluctuations.
## Visual Implementation
The indicator employs sophisticated visual elements for immediate trend comprehension and professional chart presentation:
- Dynamic Hull Line : Color-changing line (green/red/gray) with configurable width reflecting current trend status
- Optional Directional Arrows : Triangle markers below/above bars marking confirmed trend changes and entry points (disabled by default)
- Statistics Panel : Optional real-time table showing trend direction, strength percentage, Hull value, and current price
- Professional Color Scheme : Customizable bullish (green), bearish (red), and neutral (gray) color system
## Alerts
Hull For Loop includes comprehensive alert conditions for automated trading integration:
- Hull Trend Change - Confirmed trend direction shift with strength percentage
- Hull BUY Signal - Bullish trend confirmation with price and strength data
- Hull SELL Signal - Bearish trend confirmation with price and strength data
- Alert Frequency - Once per bar to prevent spam while maintaining accuracy
All alerts include contextual information: trend direction, current price, and trend strength percentage for informed decision-making.
## Use Cases
Trend Following : Optimized for sustained directional moves with superior drawdown protection compared to buy-and-hold strategies
Swing Trading : Multi-bar confirmation eliminates false breakouts while capturing significant trend changes
Position Trading : Smooth Hull calculation provides stable signals for longer-term directional positioning
Risk Management : Advanced confirmation system dramatically reduces whipsaw trades and false signals
Crypto Trading : Specifically optimized for Bitcoin with parameters delivering exceptional historical performance
The system demonstrates exceptional performance across volatile assets.
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
SHA Multi Pivot Points -v1.0.0🔎Using Pivot Points in Trading
Traders use PPs to help determine predefined support and resistance levels to guide their trading strategies. In addition, traders identify potential price reversals, trend direction, and breakout opportunities:
Trend identification: PPs act as a reference level to gauge market sentiment. If the price opens above the PP and remains above it, traders interpret this as an uptrend. Conversely, if the price opens below the pivot point and stays below, it suggests a downtrend.
Support and resistance determination: Pivot levels are natural barriers where price reactions frequently occur. Traders may enter long positions near support levels, expecting a price bounce, or if the price approaches resistance levels, traders may consider shorting the asset.
Breakout trading: When the price breaks above resistance or support, it may indicate strong momentum for further movement.
Reversal identification: Traders also look for failed breakouts or price rejections at pivot levels to anticipate reversals.
Trading strategy combinations: Traders can improve accuracy by combining PPs with other technical analysis indicators.
1. Camarilla Pivot Points
📌 Overview:
Developed by Nick Scott in 1989, Camarilla Pivot Points are designed for short-term, intraday trading. Unlike traditional pivots, Camarilla levels are tighter and more responsive, making them useful in volatile markets.
📐 Key Levels:
It generates eight levels:
- Resistance: Initial Level (R1), Mid-range Level (R2), Sell Reversal Level (R3), Breakout Level (R4)
- Support: Initial Level (S1), Mid-range Level (S2), Buy Reversal Level (S3), Breakout Level (S4)
✅ How to Use:
- S1/R1 + RSI or volume divergence to confirm weak momentum and early reversals.
- S2/R2 with price action patterns to enter early on major moves before L3/H3 get tested.
- S3/R3: Mean-reversion zones → price often reverses.
- Break of S4/R4: Strong breakout → trend-following signal.
- Combine with volume or candlestick confirmation for entries.
🔹 2. Floor (Standard) Pivot Points
📌 Overview:
This is the most traditional pivot method, widely used by floor traders. It’s symmetrical and provides a clear central pivot point with equally spaced support and resistance levels.
📐 Key Levels:
- Povit Points : Average price (PPs)
- Resistance : First price ceiling (R1), Stronger ceiling (R2), Extreme resistance (R3)
- Support : First price floor (S1), Stronger floor (S2), Extreme support (S3)
✅ How to Use:
- Above PPs = bullish bias; Below PPs = bearish bias.
- S1/R1 are most used for intraday targets.
- S2–S3/R2–R3 indicate potential extreme moves.
- Often used in combination with momentum indicators.
🔹 3. Woodie Pivot Points
📌 Overview:
Woodie’s pivot formula gives double weight to the closing price, emphasizing the most recent session's sentiment.
📐 Key Levels:
- Povit Points : Weighted average (PPs)
- Resistance : First price ceiling (R1), Stronger resistance (R2)
- Support : First price floor (S1), Stronger support (S2)
✅ How to Use:
- Works best in fast-moving markets.
- PPs acts as a momentum-based balance level.
- Good for scalpers and momentum traders.
🔹 4. Fusion Pivot Points
📌 Overview:
This method differs significantly — it calculates only one support and one resistance level, adjusting based on the relationship between the open and close.
📐 Key Levels:
- Povit Points : Single directional (PPs)
- Resistance : Potential ceiling (R)
- Support : Potential floor (S)
✅ How to Use:
- Not symmetrical → more responsive to price behavior.
- Best for breakout or reversal strategies.
- Use when you're expecting directional momentum.
🔹 5. Classic Pivot Points (Traditional)
📌 Overview:
Also known as Standard or Traditional Pivot Points, this is the default method used by most charting platforms. It offers a balanced and simple framework.
📐 Key Levels:
- Povit Points : Central price level (PPs)
- Resistance : First ceiling (R1), Stronger resistance (R2), Extreme resistance (R3)
- Support : First floor (S1), Stronger floor (S2), Extreme support (S3)
✅ How to Use:
- PPs is the market’s equilibrium point.
- Helps define market structure, bias, and trade zones.
- Combine with order blocks, RSI, or MACD for confirmation.
📊 Summary Comparison :
1. Camarilla Pivot Points
- Focus : Mean Reversion & Breakouts
- Best Use : Scalping, Day Trading
2. Floor Pivot Points
- Focus : General Support/Resistance
- Best Use : Intraday, Swing
3. Woodie Pivot Points
- Focus : Recent Close Emphasis
- Best Use : Momentum Trading
4. Fusion Pivot Points
- Focus : Trend/Breakout
- Best Use : Directional Breakouts
5. Classic Povit Points
- Focus : Market Structure
- Best Use : General Use
⚠️ Disclaimer
The information and tools provided in this script are for educational and informational purposes only. They do not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instrument.
Trading in the financial markets involves risk of loss and is not suitable for every investor. You are solely responsible for your trading decisions. Always do your own research, use proper risk management, and consult a licensed financial advisor before making any financial decisions.
Easy Move & Squeeze Alerts1. Overview
The Easy Move & Squeeze Alerts indicator combines two proven techniques to help you anticipate major price swings and spot volatility compressions (long/short squeezes) early on. It offers:
Automated Alerts via TradingView’s alert engine
On-chart Visual Cues for immediate context
Flexible Inputs to fine-tune sensitivity, lookback length, and display options
2. TTM Squeeze (Volatility Compression)
Core Concept: Compares Bollinger Bands (standard deviation channels) with Keltner Channels (ATR-based channels).
Squeeze On: BBs lie completely inside Keltner Channels → volatility is compressed, signaling a potential buildup.
Squeeze Off: BBs break outside Keltner Channels → typically the start of a strong directional move.
Alert: When the squeeze releases, the indicator fires an alert:
💥 Squeeze Release – Volatility incoming!
Chart Label: A small, purple “🔒 Squeeze” label appears above the high of each bar while compression persists, giving you a real-time visual flag.
3. ATR Breakouts (Detecting Large Moves)
Core Concept: Builds a dynamic price channel around an EMA using ATR (Average True Range) multiplied by your chosen factor.
Cross Events:
Price crosses above the upper ATR band → potential bullish breakout.
Price crosses below the lower ATR band → potential bearish breakdown.
Alert Conditions: Separate alert triggers for “🚀 Move Up” and “📉 Move Down” fire the moment the close breaches the ATR-based bounds.
4. Visualization & Usage
Channel Plots:
Bollinger Bands in blue
Keltner Channels in orange
ATR Channels in aqua (optional)
Toggle all channel plots on or off with the showZones input.
Background Highlight: During a squeeze, the chart background lightly tints purple for quick visual confirmation.
Alerts Setup:
Simply click Create Alert in TradingView, select this indicator, and choose the event(s) you want (squeeze release, ATR breakouts).
You can route notifications via email, webhook, SMS, or platform pop-ups.
5. Deployment & Customization
Timeframes: Effective across all timeframes; most popular for day- and swing-trading.
Parameter Tuning:
Increase the len value to smooth channels and focus on only the most significant compressions/moves.
Adjust the ATR or BB multipliers to make alerts more or less sensitive.
With this indicator, you gain a clear, actionable framework for spotting both volatility squeezes and breakouts before they unfold—empowering you to enter trades ahead of the crowd. Enjoy customizing and putting it to work!
DisplayUtilitiesLibrary "DisplayUtilities"
Display utilities for color management and visual presentation
get_direction_color(direction, up_excessive, up_normal, neutral, down_normal, down_excessive)
Get candle color based on direction and color scheme
Parameters:
direction (int) : Direction value (-2, -1, 0, 1, 2)
up_excessive (color) : Color for +2 direction
up_normal (color) : Color for +1 direction
neutral (color) : Color for 0 direction
down_normal (color) : Color for -1 direction
down_excessive (color) : Color for -2 direction
Returns: Appropriate color for the direction
get_candle_paint_directions(paint_opt, body_dir, bar_dir, breakout_dir, combined_dir)
Get candle directions for different painting algorithms
Parameters:
paint_opt (string) : Painting option algorithm
body_dir (int) : Body direction
bar_dir (int) : Bar direction
breakout_dir (int) : Breakout direction
combined_dir (int) : Combined direction
Returns:
get_bias_paint_directions(paint_bias, unified_dir)
Get paint directions based on bias filter
Parameters:
paint_bias (string) : Paint bias option ("All", "Bull Bias", "Bear Bias")
unified_dir (int) : Unified direction
Returns: Directions for two plotcandle series
get_transparency_levels(sf_filtered, fade_option, fade_opacity)
Calculate transparency levels for strength factor filtering
Parameters:
sf_filtered (bool) : Is strength factor filtered
fade_option (string) : Fade option ("Disabled", "Fade Candle", "Do Not Fade Wick", "Do Not Fade Wick and Border")
fade_opacity (int) : Fade opacity percentage
Returns:
get_strength_factor_filter(filter_option, individual_filters)
Generate strength factor filter conditions
Parameters:
filter_option (string) : Filter option string
individual_filters (map) : Map of individual filter conditions
Returns: Boolean filter result
get_signal_bar_condition(signal_option, individual_filters)
Generate signal bar conditions (inverted filters)
Parameters:
signal_option (string) : Signal bar option string
individual_filters (map) : Map of individual filter conditions
Returns: Boolean signal bar result
get_zscore_signal_condition(z_signal_option, z_filters)
Get Z-score signal bar conditions
Parameters:
z_signal_option (string) : Z-score signal option
z_filters (map) : Map of Z-score filters
Returns: Boolean Z-score signal condition
get_standard_colors()
Create a standard color scheme for directions
Returns: Standard color set
apply_zscore_modification(original_dir, z_filtered)
Modify directions for Z-score excess display
Parameters:
original_dir (int) : Original direction
z_filtered (bool) : Is Z-score filtered (shows excess)
Returns: Modified direction (doubled if excess detected)
get_default_fade_colors()
Get default fade colors for strength factor overlay
Returns: Default colors for TV overlay
should_paint_candles(paint_algo)
Check if paint algorithm should show candles
Parameters:
paint_algo (string) : Paint algorithm option
Returns: True if algorithm should display candles
get_signal_bar_char(signal_type, is_bullish)
Get signal bar character based on signal type
Parameters:
signal_type (string) : Signal type ("strength_factor" or "zscore")
is_bullish (bool) : Direction is bullish
Returns: Character and location for plotchar
get_signal_bar_color(signal_type, is_bullish)
Get signal bar colors
Parameters:
signal_type (string) : Signal type ("strength_factor" or "zscore")
is_bullish (bool) : Direction is bullish
Returns: Signal bar color
Bollinger Volatility AnalyzerThe Bollinger Volatility Analyzer (BVA) is a powerful enhancement of the traditional Bollinger Bands indicator, tailored to help traders identify volatility cycles and catch potential breakouts with better precision and timing. It builds upon the foundational concept of Bollinger Bands—using a moving average and standard deviation bands—but adds crucial insights into market contraction and expansion, which can be instrumental in timing entries and exits.
Here's how it works and why it's useful
At its core, the indicator calculates a moving average (called the "basis") and plots two bands—one above and one below—based on a multiple of standard deviation. These bands expand during volatile periods and contract during quiet ones. The width between these bands, normalized as a percentage of the basis, gives us a sense of how compressed or expanded the market currently is. When the band width drops below a user-defined threshold (like 2%), the script highlights this with an orange triangle below the bar. This is the "squeeze" condition, signaling a potential buildup of market energy—a kind of calm before the storm.
What makes this version of Bollinger Bands particularly powerful is that it not only detects squeezes, but also tells you when price breaks out of that squeeze range. If price closes above the upper band after a squeeze, a green "Breakout ↑" label is shown; if it closes below the lower band, a red "Breakout ↓" appears. These breakout labels act as entry signals, suggesting that volatility is returning and a directional move has begun.
This indicator is especially useful in markets that tend to alternate between consolidation and breakout phases, such as forex, crypto, and even individual stocks. Traders who look for early signs of momentum—whether for swing trading, scalping, or position building—can benefit from this tool. During a quiet market phase, the indicator warns you that a move might be coming; when the move starts, it tells you the direction.
In fast-moving markets, BVA helps filter out noise by focusing only on high-probability conditions: quiet consolidation followed by a strong breakout. It’s not a complete system by itself—it works best when paired with volume confirmation or oscillators like RSI—but as a volatility trigger and directional guide, it’s a reliable component of a trading workflow.
Entropy Bands (TechnoBlooms)Entropy Bands — A New Era of Volatility and Trend Analysis
Entropy Bands is our next indicator as a part of the Quantum Price Theory (QPT) Series of indicators.
🧠 Overview
Entropy Bands are an advanced volatility-based indicator that reimagines traditional banded systems like Bollinger Bands.
Built on entropy theory, adaptive moving averages, and dynamic volatility measurement, Entropy Bands provide deeper insights into market randomness, trend strength, and breakout potential.
Instead of only relying on price deviation (like Bollinger Bands), Entropy Bands integrate chaos theory principles to create smarter, more responsive dynamic bands that adapt to real market behavior.
🚀Why is Entropy Bands Different — and Better
Dynamic Band Width : Adjusts using both entropy and ATR, creating smarter expansion/contraction.
Multi-Moving Average Core : Choose between SMA, EMA, or WMA for optimal centerline behavior.
Noise and Breakout Filtering : Filters fake breakouts by analyzing candle body size and entropy conditions.
Visual Clarity : Background and candle coloring highlight chaotic/noisy zones, trend zones, and breakout moments.
Entropy Bands don't just react to price — they analyze the underlying market behavior, offering superior decision-making signals.
📚 Watch Band Behavior:
Bands expand during volatility spikes or chaotic conditions.
Bands contract during low volatility or tight consolidation zones.
📚 Analyze Candle Coloring:
Green = Bullish breakout (closing above upper band).
Pink = Bearish breakout (closing below lower band).
Gray = Inside bands (neutral/random noise).
✨ Key Features of Entropy Bands:
Entropy-Based Band Width Calculation: A scientific edge over pure price deviation methods.
Dynamic Background Coloring: Highlights high entropy areas where randomness dominates.
Candle Breakout Coloring: Easy-to-spot trend breakouts and strength moves.
Multi-MA Flexibility: Adapt the bands’ core to trending, ranging, or volatile markets.
Body Size Filter: Protects against fake breakouts by requiring meaningful candle body moves.
Aggregate PDH High Break Alert**Aggregate PDH High Break Alert**
**Overview**
The “Aggregate PDH High Break Alert” is a lightweight Pine Script v6 indicator designed to instantly notify you when today’s price breaks above any prior-day high in a user-defined lookback window. Instead of manually scanning dozens of daily highs, this script automatically loops through the last _N_ days (up to 100) and fires a single-bar alert the moment price eclipses a specific day’s high.
**Key Features**
- **Dynamic Lookback**: Choose any lookback period from 1 to 100 days via a single `High-Break Lookback` input.
- **Single Security Call**: Efficiently retrieves the entire daily-high series in one call to avoid TradingView’s 40-call security limit.
- **Automatic Looping**: Internally loops through each prior-day high, so there’s no need to manually code dozens of lines.
- **Custom Alerts**: Generates a clear, formatted alert message—e.g. “Crossed high from 7 day(s) ago”—for each breakout.
- **Lightweight & Maintainable**: Compact codebase (<15 lines) makes tweaking and debugging a breeze.
**Inputs**
- **High-Break Lookback (days)**: Number of past days to monitor for high breaks. Valid range: 1–100.
**How to Use**
1. **Add to Chart**: Open TradingView, click “Indicators,” then “Create,” and paste in the code.
2. **Configure Lookback**: In the script’s settings, set your desired lookback window (e.g., 20 for the past 20 days).
3. **Enable Alerts**: Right-click the indicator’s name on your chart, select “Add Alert on Aggregate PDH High Break Alert,” and choose “Once per bar close.”
4. **Receive Notifications**: Whenever price crosses above any of the specified prior-day highs, you’ll get an on-screen and/or mobile push alert with the exact number of days ago.
**Use Cases**
- **Trend Confirmation**: Confirm fresh bullish momentum when today’s high outpaces any of the last _N_ days.
- **Breakout Trading**: Automate entries off multi-day highs without manual chart scanning.
- **System Integration**: Integrate with alerts to trigger orders in third-party bots or webhook receivers.
**Disclaimer**
Breakouts alone do not guarantee sustained moves. Combine with your preferred risk management, volume filters, and other indicators for higher-probability setups. Use on markets and timeframes where daily breakout behavior aligns with your strategy.
Akkerman IMB + Targets IndicatorAkkerman IMB + Targets Indicator
The Akkerman IMB + Targets Indicator is a powerful tool for traders who use the Smart Money Concept (SMC) methodology for intraday trading. This indicator combines several key elements of technical analysis, such as IMB (Imbalance) zones, liquidity zones, and intraday targets, to help traders identify significant levels on the chart for potential entry and exit points.
Main Features of the Indicator:
IMB (Imbalance) Zones:
The indicator detects IMB zones (imbalances) on the chart, which are often significant for the market because these zones can signal unsupported price moves where the market may either retrace or continue the move.
Green box — indicates a bullish IMB, where the price moves downward but does not reach the previous "low" level.
Red box — indicates a bearish IMB, where the price moves upward but does not reach the previous "high" level.
Liquidity Zones:
The indicator automatically identifies liquidity zones, which are critical levels for potential retracements or breakouts. These zones are determined by equal highs and lows on the chart (where the price has made similar highs or lows).
Triangles or lines highlight levels where significant buy or sell orders might be gathered.
Intraday Target Lines:
The indicator generates targets for intraday trading based on support and resistance levels over the last 10 periods.
These target lines on the chart indicate potential entry or exit points based on the lowest and highest prices over the past 10 bars, which represent key points for trading within the current session.
Indicator Settings:
Show IMB: Toggle to show or hide IMB zones on the chart.
Show Liquidity Zones: Toggle to show or hide liquidity zones on the chart.
Show Targets (Intraday): Toggle to show or hide intraday target lines.
Max Targets (maxTargets): Set the maximum number of targets to display on the chart.
How to Use:
IMB Zones help identify potential retracement or breakout zones on the market. These zones are a critical part of Smart Money analysis, as markets often retrace to these areas after significant price moves.
Liquidity Zones provide clues about where large orders may be gathered, which could lead to a retracement or breakout.
Intraday Targets assist in identifying important levels for entering or exiting trades within the current session to take advantage of short-term price movements.
Important Notes:
This indicator works best on the 1-hour timeframe (H1) for more accurate and stable signals.
For maximum effectiveness, it is recommended to combine this indicator with other technical indicators and analysis methods.
Momentum SwingDescription:
This indicator detects structural breakouts triggered by a single engulfing candle that decisively breaks out of a range formed by previous candles.
📦 Key Features:
Detects breakouts from a lateral range defined by N previous candles
Identifies only clean breakouts using a single engulfing candle (optional: body-only breakout)
Visually highlights the broken range with a rectangle
Displays directional arrows when a breakout occurs (long or short)
Fully customizable settings
🛠 Custom Inputs:
Number of candles used to define the range
Option to require the breakout to occur with the candle’s body only
Option to show or hide the breakout rectangle
📈 Perfect for traders looking to identify strong breakouts after consolidation phases.
Granular MA Ribbon🎗️ The Granular MA Ribbon provides a structured view of price action on lower timeframes by incorporating both price-based and volume-weighted moving averages, offering a more nuanced view of market trends and momentum shifts. Furthermore, by using 15-minute intervals for its calculations, it ensures that intraday traders receive a smooth and responsive representation of higher timeframe trends.
⚠️ Note that this indicator is specifically optimized for the 15-minute and 1-hour charts; applying it to longer or shorter periods will distort its calculations and reduce its effectiveness. Adjust visibility settings accordingly.
🧰 Unlike traditional moving averages that may lag or fail to reflect real-time shifts in price dynamics, the Granular MA Ribbon includes a one-day exponential moving average (1D EMA), a one-day volume-weighted moving average (1D VWMA), and a one-week exponential moving average (1W EMA). Together, these elements allow traders to stay aligned with the broader market while making precise intraday trading decisions.
🤷🏻 Why Two Daily Moving Averages?
🔊 Instead of relying on a single moving average, this indicator uses both an EMA and a VWMA to provide a clearer picture of price movement. The EMA reacts quickly to price changes, making it a useful tool for identifying short-term momentum shifts. The VWMA, meanwhile, accounts for volume, ensuring that price movements supported by higher trading activity carry greater weight in the trend calculation.
💪🏻 When the EMA and VWMA diverge significantly, it signals strong momentum. If they begin to converge, it suggests that momentum is weakening or that price may be entering consolidation. The space between these two moving averages is filled with a ribbon, making it easier to see shifts in trend strength. A wide ribbon typically indicates strong momentum, while a narrowing ribbon suggests the trend may be losing steam.
🧮 Calculation Rationale
🔎 The 1D EMA and 1D VWMA are constructed using 15-minute blocks to maintain accuracy on lower timeframes. A full trading day consists of 96 fifteen-minute intervals. Instead of relying on daily candle data, which would reduce the granularity of the moving averages, this method allows the indicator to reflect intra-day trends more accurately. By breaking the day into smaller increments, the moving averages adapt more smoothly to changes in price and volume, making them more reliable for traders working on shorter timeframes.
🔍 The weekly EMA follows the same logic, adjusting based on the selected five-day or seven-day setting. If the market follows a standard five-day trading week, the one-week EMA is calculated using 480 fifteen-minute bars. If the market trades seven days a week, such as in crypto, the weekly EMA is adjusted accordingly to reflect 672 fifteen-minute bars. This setting ensures that traders using the indicator across different asset classes receive accurate trend information.
🫤 Sideways Markets
🔄 When the broader market is in a range-bound state, with no clear trend on the one-day or one-week chart, this indicator helps traders make sense of the short-term price structure. In these conditions, the ribbon will often appear flat, with the 1D EMA and 1D VWMA frequently crossing each other. This suggests that momentum is weak and that price action lacks a strong directional bias.
⚠️ A narrowing ribbon in a sideways market indicates reduced volatility and a potential breakout. If the EMA crosses above the VWMA during consolidation, it may signal a short-term upward move, especially if volume begins to increase. Conversely, if the EMA moves below the VWMA, it could indicate that selling pressure is increasing. However, in choppy conditions, crossovers alone are not enough to confirm a trade. Traders should wait for additional confirmation, such as a breakout from a defined range or a shift in volume.
♭ If the weekly EMA remains flat while the daily ribbon fluctuates, it confirms that the market lacks a strong trend. In such cases, traders may consider fading moves near the top and bottom of a range rather than expecting sustained breakouts.
💹 Trending Markets
🏗️ When the market is in a strong uptrend or downtrend, the ribbon takes on a more structured shape. A widening ribbon that slopes upward signals strong bullish momentum, with price consistently respecting the 1D EMA and VWMA as support. In a downtrend, the ribbon slopes downward, acting as dynamic resistance.
📈 In trending conditions, traders can use the ribbon to time pullback entries. In an uptrend, price often retraces to the VWMA before resuming its upward move. If price holds above both the EMA and VWMA, the trend remains strong. If price begins to close below the VWMA but remains above the EMA, it suggests weakening momentum but not necessarily a reversal. A clean break below both moving averages indicates a shift in trend structure.
📊 The one-week EMA serves as a higher timeframe guide. When price remains above the weekly EMA, it confirms that the broader trend is intact. If price pulls back to the weekly EMA and bounces, it can provide a high-confidence trade entry. Conversely, if price breaks below the weekly EMA and fails to reclaim it, it suggests that the trend may be reversing.
⏳ 5-Day and 7-Day Week Variants
🎚️ The setting for a five-day or seven-day trading week adjusts the calculation of the one-week EMA. This ensures that the indicator remains accurate across different asset classes.
5️⃣ A five-day trading week is appropriate for stocks, futures, and forex markets, where trading pauses on weekends. Using a seven-day week for these markets would create artificial distortions by including non-trading days. 7️⃣ In contrast, the seven-day week setting is ideal for crypto markets, which trade continuously. Without this adjustment, the weekly EMA would fail to reflect weekend price action, leading to misleading trend signals.
🧐 This indicator is expressly designed to complement its higher timeframe counterpart, the Triple Differential Moving Average Braid, optimized for the 1-Day chart.
Premarket Gap MomoTrader(SC)🚀 Pre-Market Momentum Trader | Dynamic Position Sizing 🔥
📈 Trade explosive pre-market breakouts with confidence! This algorithmic strategy automatically detects high-momentum setups, dynamically adjusts position size, and ensures risk control with a one-trade-per-day rule.
⸻
🎯 Key Features
✅ Pre-Market Trading (4:00 - 9:30 AM EST) – Only trades during the most volatile session for early breakouts.
✅ Dynamic Position Sizing – Adapts trade size based on candle strength:
• ≥90% body → 100% position
• ≥85% body → 50% position
• ≥75% body → 25% position
✅ 1 Trade Per Day – Avoids overtrading by allowing only one high-quality trade daily.
✅ Momentum Protection – Stays in the trade as long as:
• Every candle remains green (no red candles).
• Each new candle has increasing volume (confirming strong buying).
✅ Automated Exit – Closes position if:
• A red candle appears.
• Volume fails to increase on a green candle.
⸻
🔍 How It Works
📌 Entry Conditions:
✔️ Candle gains ≥5% from previous close.
✔️ Candle is green & body size ≥75% of total range.
✔️ Volume >15K (confirming liquidity).
✔️ Occurs within pre-market session (4:00 - 9:30 AM EST).
✔️ Only the first valid trade of the day is taken.
📌 Exit Conditions:
❌ First red candle after entry → Exit trade.
❌ First green candle with lower volume → Exit trade.
⸻
🏆 Why Use This?
🔹 Eliminates Fake Breakouts – No trade unless volume & momentum confirm.
🔹 Prevents Overtrading – Restricts to one quality trade per day.
🔹 Adaptable to Any Market – Works on stocks, crypto, or forex.
🔹 Hands-Free Execution – No manual chart watching required!
⸻
🚨 Important Notes
📢 Not financial advice. Trading involves risk—always backtest & practice on paper trading before using real money.
📢 Enable pre-market data in your TradingView settings for accurate results.
📢 Optimized for 1-minute & 5-minute timeframes.
🔔 Like this strategy? Leave a comment, share your results, and don’t forget to hit Follow for more strategies! 🚀🔥
15-Minute ORB by @RhinoTradezOverview
Hey traders, ready to jump on the morning breakout train? The 15-Minute ORB by @RhinoTradez
is your go-to pal for rocking the Opening Range Breakout (ORB) scene, zeroing in on the first 15 minutes of the U.S. market day—9:30 to 9:45 AM Eastern Time. Picture this: sleek orange lines mark the high and low of that opening rush, but they only hang out during regular trading hours (9:30 AM-4:00 PM ET) and reset fresh each day—no old baggage here! Built in Pine Script v6 for that cutting-edge feel, it’s loaded with breakout signals and alerts to keep your trading game strong—ideal for SPY, QQQ, or any ticker you love.
Crafted by @RhinoTradez
to fuel your daily grind—let’s hit those breakouts running!
What It Does
The ORB strategy is all about that early market spark: the 9:30-9:45 AM range sets the battlefield, and breakouts signal the charge. Here’s the rundown:
Captures the Range : Snags the high and low from the 9:30-9:45 AM ET candle—U.S. market kickoff, locked in.
Daily Refresh : Wipes yesterday’s lines at 9:30 AM ET each day—today’s all that matters.
Regular Hours Focus : Orange lines shine from 9:45 AM to 4:00 PM ET, vanishing outside those hours.
Breakout Signals : Green triangles for upside breaks, red for downside, all within regular hours.
Alerts You : Chimes in with “Price broke above 15-min ORB High: 597” (or below the low) when the move hits.
It’s your morning breakout blueprint—simple, focused, and trader-ready.
Functionality Breakdown:
15-Minute ORB Snap:
Locks the high and low of the 9:30-9:45 AM ET candle on a 15-minute chart (EST/EDT auto-adjusted).
Resets daily at 9:30 AM ET—yesterday’s range is outta here.
Regular Hours Only:
Lines glow from 9:45 AM to 4:00 PM ET, keeping pre-market and after-hours clean.
Breakout Flags:
Marks price busting above the ORB high (green triangle below bar) or below the low (red triangle above), only during 9:30 AM-4:00 PM.
Alert Action:
Drops a custom alert with the breakout price (e.g., “Price broke below 15-min ORB Low: 594”)—stay in the know, hands-free.
Customization Options
Keep it chill with one slick tweak:
ORB Line Color : Starts at orange—vibrant and trader-cool! Flip it to blue, purple, or any shade you dig in the settings. Make it yours.
How to Use It
Pop It On: Add it to a 15-minute chart—SPY, QQQ, or your hot pick works like a dream.
Time It Right: Set your chart to “America/New_York” time (Chart Settings > Time Zone) to sync with 9:30 AM ET.
Choose Your Color: Dive into the indicator settings and pick your ORB line color—orange kicks it off, but you’re in charge.
Set Alerts: Right-click the indicator, add an alert with “Any alert() function call,” and catch breakouts live.
Ride the Wave: Green triangle? Upward vibe. Red? Downside alert. Mix with volume or candles for extra punch.
Pro Tips
15-Minute Only : Tailored for that 9:30-9:45 AM ET candle—other timeframes won’t sync up.
Daily Reset : Lines refresh at 9:30 AM ET—always today’s play.
Breakout Boost : High volume or RSI can seal the deal on those triangle signals.
No Clutter : Lines stick to 9:30 AM-4:00 PM ET—your chart stays tidy.
Brought to you by @RhinoTradez
in Pine Script v6, this ORB script’s your morning breakout wingman. Slap it on, pick a color, and let’s chase those moves together! Happy trading!
Multi SMA EMA VWAP1. Moving Average Crossover
This is one of the most common strategies with moving averages, and it involves observing crossovers between EMAs and SMAs to determine buy or sell signals.
Buy signal: When a faster EMA (like a short-term EMA) crosses above a slower SMA, it can indicate a potential upward movement.
Sell signal: When a faster EMA crosses below a slower SMA, it can indicate a potential downward movement.
With 4 EMAs and 5 SMAs, you can set up crossovers between different combinations, such as:
EMA(9) crosses above SMA(50) → buy.
EMA(9) crosses below SMA(50) → sell.
2. Divergence Confirmation Between EMAs and SMAs
Divergence between the EMAs and SMAs can offer additional confirmation. If the EMAs are pointing in one direction and the SMAs are still in the opposite direction, it is a sign that the movement could be stronger and continue in the same direction.
Positive divergence: If the EMAs are making new highs while the SMAs are still below, it could be a sign that the market is in a strong trend.
Negative divergence: If the EMAs are making new lows and the SMAs are still above, you might consider that the market is in a downtrend or correction.
3. Using EMAs as Dynamic Support and Resistance
EMAs can act as dynamic support and resistance in strong trends. If the price approaches a faster EMA from above and doesn’t break it, it could be a good entry point for a long position (buy). If the price approaches a slower EMA from below and doesn't break it, it could be a good point to sell (short).
Buy: If the price is above all EMAs and approaches the fastest EMA (e.g., EMA(9)), it could be a good buy point if the price bounces upward.
Sell: If the price is below all EMAs and approaches the fastest EMA, it could be a good sell point if the price bounces downward.
4. Combining SMAs and EMAs to Filter Signals
SMAs can serve as a trend filter to avoid trading in sideways markets. For example:
Bullish trend condition: If the longer-term SMAs (such as SMA(100) or SMA(200)) are below the price, and the shorter EMAs are aligned upward, you can look for buy signals.
Bearish trend condition: If the longer-term SMAs are above the price and the shorter EMAs are aligned downward, you can look for sell signals.
5. Consolidation Zone Between EMAs and SMAs
When the price moves between EMAs and SMAs without a clear trend (consolidation zone), you can expect a breakout. In this case, you can use the EMAs and SMAs to identify the direction of the breakout:
If the price is in a narrow range between the EMAs and SMAs and then breaks above the fastest EMA, it’s a sign that an upward trend may begin.
If the price breaks below the fastest EMA, it could indicate a potential downward trend.
6. "Golden Cross" and "Death Cross" Strategy
These are classic strategies based on crossovers between moving averages of different periods.
Golden Cross: Occurs when a faster EMA (e.g., EMA(50)) crosses above a slower SMA (e.g., SMA(200)), which suggests a potential bullish trend.
Death Cross: Occurs when a faster EMA crosses below a slower SMA, which suggests a potential bearish trend.
Additional Recommendations:
Combining with other indicators: You can combine EMA and SMA signals with other indicators like the RSI (Relative Strength Index) or MACD (Moving Average Convergence/Divergence) for confirmation and to avoid false signals.
Risk management: Always use stop-loss and take-profit orders to protect your capital. Moving averages are trend-following indicators but don’t guarantee that the price will move in the same direction.
Timeframe analysis: It’s recommended to use different timeframes to confirm the trend (e.g., use EMAs on hourly charts along with SMAs on daily charts).
VWAP
1. VWAP + EMAs for Trend Confirmation
VWAP can act as a trend filter, confirming the direction provided by the EMAs.
Buy Signal: If the price is above the VWAP and the EMAs are aligned in an uptrend (e.g., short-term EMAs are above longer-term EMAs), this indicates that the trend is bullish and you can look for buy opportunities.
Sell Signal: If the price is below the VWAP and the EMAs are aligned in a downtrend (e.g., short-term EMAs are below longer-term EMAs), this suggests a bearish trend and you can look for sell opportunities.
In this case, VWAP is used to confirm the overall trend. For example:
Bullish: Price above VWAP, EMAs aligned to the upside (e.g., EMA(9) > EMA(50) > EMA(200)), buy.
Bearish: Price below VWAP, EMAs aligned to the downside (e.g., EMA(9) < EMA(50) < EMA(200)), sell.
2. VWAP as Dynamic Support and Resistance
VWAP can act as a dynamic support or resistance level during the day. Combining this with EMAs and SMAs helps you refine your entry and exit points.
Support: If the price is above VWAP and starts pulling back to VWAP, it could act as support. If the price bounces off the VWAP and aligns with bullish EMAs (e.g., EMA(9) crossing above EMA(50)), you can consider entering a buy position.
Resistance: If the price is below VWAP and approaches VWAP from below, it can act as resistance. If the price fails to break through VWAP and aligns with bearish EMAs (e.g., EMA(9) crossing below EMA(50)), it could be a good signal for a sell.
Power Of 3 ICT 01 [TradingFinder] AMD ICT & SMC Accumulations🔵 Introduction
The ICT Power of 3 (PO3) strategy, developed by Michael J. Huddleston, known as the Inner Circle Trader, is a structured approach to analyzing daily market activity. This strategy divides the trading day into three distinct phases: Accumulation, Manipulation, and Distribution.
Each phase represents a unique market behavior influenced by institutional traders, offering a clear framework for retail traders to align their strategies with market movements.
Accumulation (19:00 - 01:00 EST) takes place during low-volatility hours, as institutional traders accumulate orders. Manipulation (01:00 - 07:00 EST) involves false breakouts and liquidity traps designed to mislead retail traders. Finally, Distribution (07:00 - 13:00 EST) represents the active phase where significant market movements occur as institutions distribute their positions in line with the broader trend.
This indicator is built upon the Power of 3 principles to provide traders with a practical and visual tool for identifying these key phases. By using clear color coding and precise time zones, the indicator highlights critical price levels, such as highs and lows, helping traders to better understand market dynamics and make more informed trading decisions.
Incorporating the ICT AMD setup into daily analysis enables traders to anticipate market behavior, spot high-probability trade setups, and gain deeper insights into institutional trading strategies. With its focus on time-based price action, this indicator simplifies complex market structures, offering an effective tool for traders of all levels.
🔵 How to Use
The ICT Power of 3 (PO3) indicator is designed to help traders analyze daily market movements by visually identifying the three key phases: Accumulation, Manipulation, and Distribution.
Here's how traders can effectively use the indicator :
🟣 Accumulation Phase (19:00 - 01:00 EST)
Purpose : Identify the range-bound activity where institutional players accumulate orders.
Trading Insight : Avoid placing trades during this phase, as price movements are typically limited. Instead, use this time to prepare for the potential direction of the market in the next phases.
🟣 Manipulation Phase (01:00 - 07:00 EST)
Purpose : Spot false breakouts and liquidity traps that mislead retail traders.
Trading Insight : Observe the market for price spikes beyond key support or resistance levels. These moves often reverse quickly, offering high-probability entry points in the opposite direction of the initial breakout.
🟣 Distribution Phase (07:00 - 13:00 EST)
Purpose : Detect the main price movement of the day, driven by institutional distribution.
Trading Insight : Enter trades in the direction of the trend established during this phase. Look for confirmations such as breakouts or strong directional moves that align with broader market sentiment
🔵 Settings
Show or Hide Phases :mDecide whether to display Accumulation, Manipulation, or Distribution.
Adjust the session times for each phase :
Accumulation: 1900-0100 EST
Manipulation: 0100-0700 EST
Distribution: 0700-1300 EST
Modify Visualization : Customize how the indicator looks by changing settings like colors and transparency.
🔵 Conclusion
The ICT Power of 3 (PO3) indicator is a powerful tool for traders seeking to understand and leverage market structure based on time and price dynamics. By visually highlighting the three key phases—Accumulation, Manipulation, and Distribution—this indicator simplifies the complex movements of institutional trading strategies.
With its customizable settings and clear representation of market behavior, the indicator is suitable for traders at all levels, helping them anticipate market trends and make more informed decisions.
Whether you're identifying entry points in the Accumulation phase, navigating false moves during Manipulation, or capitalizing on trends in the Distribution phase, this tool provides valuable insights to enhance your trading performance.
By integrating this indicator into your analysis, you can better align your strategies with institutional movements and improve your overall trading outcomes.
