Anomalous Holonomy Field Theory🌌 Anomalous Holonomy Field Theory (AHFT) - Revolutionary Quantum Market Analysis
Where Theoretical Physics Meets Trading Reality
A Groundbreaking Synthesis of Differential Geometry, Quantum Field Theory, and Market Dynamics
🔬 THEORETICAL FOUNDATION - THE MATHEMATICS OF MARKET REALITY
The Anomalous Holonomy Field Theory represents an unprecedented fusion of advanced mathematical physics with practical market analysis. This isn't merely another indicator repackaging old concepts - it's a fundamentally new lens through which to view and understand market structure .
1. HOLONOMY GROUPS (Differential Geometry)
In differential geometry, holonomy measures how vectors change when parallel transported around closed loops in curved space. Applied to markets:
Mathematical Formula:
H = P exp(∮_C A_μ dx^μ)
Where:
P = Path ordering operator
A_μ = Market connection (price-volume gauge field)
C = Closed price path
Market Implementation:
The holonomy calculation measures how price "remembers" its journey through market space. When price returns to a previous level, the holonomy captures what has changed in the market's internal geometry. This reveals:
Hidden curvature in the market manifold
Topological obstructions to arbitrage
Geometric phase accumulated during price cycles
2. ANOMALY DETECTION (Quantum Field Theory)
Drawing from the Adler-Bell-Jackiw anomaly in quantum field theory:
Mathematical Formula:
∂_μ j^μ = (e²/16π²)F_μν F̃^μν
Where:
j^μ = Market current (order flow)
F_μν = Field strength tensor (volatility structure)
F̃^μν = Dual field strength
Market Application:
Anomalies represent symmetry breaking in market structure - moments when normal patterns fail and extraordinary opportunities arise. The system detects:
Spontaneous symmetry breaking (trend reversals)
Vacuum fluctuations (volatility clusters)
Non-perturbative effects (market crashes/melt-ups)
3. GAUGE THEORY (Theoretical Physics)
Markets exhibit gauge invariance - the fundamental physics remains unchanged under certain transformations:
Mathematical Formula:
A'_μ = A_μ + ∂_μΛ
This ensures our signals are gauge-invariant observables , immune to arbitrary market "coordinate changes" like gaps or reference point shifts.
4. TOPOLOGICAL DATA ANALYSIS
Using persistent homology and Morse theory:
Mathematical Formula:
β_k = dim(H_k(X))
Where β_k are the Betti numbers describing topological features that persist across scales.
🎯 REVOLUTIONARY SIGNAL CONFIGURATION
Signal Sensitivity (0.5-12.0, default 2.5)
Controls the responsiveness of holonomy field calculations to market conditions. This parameter directly affects the threshold for detecting quantum phase transitions in price action.
Optimization by Timeframe:
Scalping (1-5min): 1.5-3.0 for rapid signal generation
Day Trading (15min-1H): 2.5-5.0 for balanced sensitivity
Swing Trading (4H-1D): 5.0-8.0 for high-quality signals only
Score Amplifier (10-200, default 50)
Scales the raw holonomy field strength to produce meaningful signal values. Higher values amplify weak signals in low-volatility environments.
Signal Confirmation Toggle
When enabled, enforces additional technical filters (EMA and RSI alignment) to reduce false positives. Essential for conservative strategies.
Minimum Bars Between Signals (1-20, default 5)
Prevents overtrading by enforcing quantum decoherence time between signals. Higher values reduce whipsaws in choppy markets.
👑 ELITE EXECUTION SYSTEM
Execution Modes:
Conservative Mode:
Stricter signal criteria
Higher quality thresholds
Ideal for stable market conditions
Adaptive Mode:
Self-adjusting parameters
Balances signal frequency with quality
Recommended for most traders
Aggressive Mode:
Maximum signal sensitivity
Captures rapid market moves
Best for experienced traders in volatile conditions
Dynamic Position Sizing:
When enabled, the system scales position size based on:
Holonomy field strength
Current volatility regime
Recent performance metrics
Advanced Exit Management:
Implements trailing stops based on ATR and signal strength, with mode-specific multipliers for optimal profit capture.
🧠 ADAPTIVE INTELLIGENCE ENGINE
Self-Learning System:
The strategy analyzes recent trade outcomes and adjusts:
Risk multipliers based on win/loss ratios
Signal weights according to performance
Market regime detection for environmental adaptation
Learning Speed (0.05-0.3):
Controls adaptation rate. Higher values = faster learning but potentially unstable. Lower values = stable but slower adaptation.
Performance Window (20-100 trades):
Number of recent trades analyzed for adaptation. Longer windows provide stability, shorter windows increase responsiveness.
🎨 REVOLUTIONARY VISUAL SYSTEM
1. Holonomy Field Visualization
What it shows: Multi-layer quantum field bands representing market resonance zones
How to interpret:
Blue/Purple bands = Primary holonomy field (strongest resonance)
Band width = Field strength and volatility
Price within bands = Normal quantum state
Price breaking bands = Quantum phase transition
Trading application: Trade reversals at band extremes, breakouts on band violations with strong signals.
2. Quantum Portals
What they show: Entry signals with recursive depth patterns indicating momentum strength
How to interpret:
Upward triangles with portals = Long entry signals
Downward triangles with portals = Short entry signals
Portal depth = Signal strength and expected momentum
Color intensity = Probability of success
Trading application: Enter on portal appearance, with size proportional to portal depth.
3. Field Resonance Bands
What they show: Fibonacci-based harmonic price zones where quantum resonance occurs
How to interpret:
Dotted circles = Minor resonance levels
Solid circles = Major resonance levels
Color coding = Resonance strength
Trading application: Use as dynamic support/resistance, expect reactions at resonance zones.
4. Anomaly Detection Grid
What it shows: Fractal-based support/resistance with anomaly strength calculations
How to interpret:
Triple-layer lines = Major fractal levels with high anomaly probability
Labels show: Period (H8-H55), Price, and Anomaly strength (φ)
⚡ symbol = Extreme anomaly detected
● symbol = Strong anomaly
○ symbol = Normal conditions
Trading application: Expect major moves when price approaches high anomaly levels. Use for precise entry/exit timing.
5. Phase Space Flow
What it shows: Background heatmap revealing market topology and energy
How to interpret:
Dark background = Low market energy, range-bound
Purple glow = Building energy, trend developing
Bright intensity = High energy, strong directional move
Trading application: Trade aggressively in bright phases, reduce activity in dark phases.
📊 PROFESSIONAL DASHBOARD METRICS
Holonomy Field Strength (-100 to +100)
What it measures: The Wilson loop integral around price paths
>70: Strong positive curvature (bullish vortex)
<-70: Strong negative curvature (bearish collapse)
Near 0: Flat connection (range-bound)
Anomaly Level (0-100%)
What it measures: Quantum vacuum expectation deviation
>70%: Major anomaly (phase transition imminent)
30-70%: Moderate anomaly (elevated volatility)
<30%: Normal quantum fluctuations
Quantum State (-1, 0, +1)
What it measures: Market wave function collapse
+1: Bullish eigenstate |↑⟩
0: Superposition (uncertain)
-1: Bearish eigenstate |↓⟩
Signal Quality Ratings
LEGENDARY: All quantum fields aligned, maximum probability
EXCEPTIONAL: Strong holonomy with anomaly confirmation
STRONG: Good field strength, moderate anomaly
MODERATE: Decent signals, some uncertainty
WEAK: Minimal edge, high quantum noise
Performance Metrics
Win Rate: Rolling performance with emoji indicators
Daily P&L: Real-time profit tracking
Adaptive Risk: Current risk multiplier status
Market Regime: Bull/Bear classification
🏆 WHY THIS CHANGES EVERYTHING
Traditional technical analysis operates on 100-year-old principles - moving averages, support/resistance, and pattern recognition. These work because many traders use them, creating self-fulfilling prophecies.
AHFT transcends this limitation by analyzing markets through the lens of fundamental physics:
Markets have geometry - The holonomy calculations reveal this hidden structure
Price has memory - The geometric phase captures path-dependent effects
Anomalies are predictable - Quantum field theory identifies symmetry breaking
Everything is connected - Gauge theory unifies disparate market phenomena
This isn't just a new indicator - it's a new way of thinking about markets . Just as Einstein's relativity revolutionized physics beyond Newton's mechanics, AHFT revolutionizes technical analysis beyond traditional methods.
🔧 OPTIMAL SETTINGS FOR MNQ 10-MINUTE
For the Micro E-mini Nasdaq-100 on 10-minute timeframe:
Signal Sensitivity: 2.5-3.5
Score Amplifier: 50-70
Execution Mode: Adaptive
Min Bars Between: 3-5
Theme: Quantum Nebula or Dark Matter
💭 THE JOURNEY - FROM IMPOSSIBLE THEORY TO TRADING REALITY
Creating AHFT was a mathematical odyssey that pushed the boundaries of what's possible in Pine Script. The journey began with a seemingly impossible question: Could the profound mathematical structures of theoretical physics be translated into practical trading tools?
The Theoretical Challenge:
Months were spent diving deep into differential geometry textbooks, studying the works of Chern, Simons, and Witten. The mathematics of holonomy groups and gauge theory had never been applied to financial markets. Translating abstract mathematical concepts like parallel transport and fiber bundles into discrete price calculations required novel approaches and countless failed attempts.
The Computational Nightmare:
Pine Script wasn't designed for quantum field theory calculations. Implementing the Wilson loop integral, managing complex array structures for anomaly detection, and maintaining computational efficiency while calculating geometric phases pushed the language to its limits. There were moments when the entire project seemed impossible - the script would timeout, produce nonsensical results, or simply refuse to compile.
The Breakthrough Moments:
After countless sleepless nights and thousands of lines of code, breakthrough came through elegant simplifications. The realization that market anomalies follow patterns similar to quantum vacuum fluctuations led to the revolutionary anomaly detection system. The discovery that price paths exhibit holonomic memory unlocked the geometric phase calculations.
The Visual Revolution:
Creating visualizations that could represent 4-dimensional quantum fields on a 2D chart required innovative approaches. The multi-layer holonomy field, recursive quantum portals, and phase space flow representations went through dozens of iterations before achieving the perfect balance of beauty and functionality.
The Balancing Act:
Perhaps the greatest challenge was maintaining mathematical rigor while ensuring practical trading utility. Every formula had to be both theoretically sound and computationally efficient. Every visual had to be both aesthetically pleasing and information-rich.
The result is more than a strategy - it's a synthesis of pure mathematics and market reality that reveals the hidden order within apparent chaos.
📚 INTEGRATED DOCUMENTATION
Once applied to your chart, AHFT includes comprehensive tooltips on every input parameter. The source code contains detailed explanations of the mathematical theory, practical applications, and optimization guidelines. This published description provides the overview - the indicator itself is a complete educational resource.
⚠️ RISK DISCLAIMER
While AHFT employs advanced mathematical models derived from theoretical physics, markets remain inherently unpredictable. No mathematical model, regardless of sophistication, can guarantee future results. This strategy uses realistic commission ($0.62 per contract) and slippage (1 tick) in all calculations. Past performance does not guarantee future results. Always use appropriate risk management and never risk more than you can afford to lose.
🌟 CONCLUSION
The Anomalous Holonomy Field Theory represents a quantum leap in technical analysis - literally. By applying the profound insights of differential geometry, quantum field theory, and gauge theory to market analysis, AHFT reveals structure and opportunities invisible to traditional methods.
From the holonomy calculations that capture market memory to the anomaly detection that identifies phase transitions, from the adaptive intelligence that learns and evolves to the stunning visualizations that make the invisible visible, every component works in mathematical harmony.
This is more than a trading strategy. It's a new lens through which to view market reality.
Trade with the precision of physics. Trade with the power of mathematics. Trade with AHFT.
I hope this serves as a good replacement for Quantum Edge Pro - Adaptive AI until I'm able to fix it.
— Dskyz, Trade with insight. Trade with anticipation.
Volatilidade
Approximate Entropy Zones [PhenLabs]Version: PineScript™ v6
Description
This indicator identifies periods of market complexity and randomness by calculating the Approximate Entropy (ApEn) of price action. As the movement of the market becomes complex, it means the current trend is losing steam and a reversal or consolidation is likely near. The indicator plots high-entropy periods as zones on your chart, providing a graphical suggestion to anticipate a potential market direction change. This indicator is designed to help traders identify favorable times to get in or out of a trade by highlighting when the market is in a state of disarray.
Points of Innovation
Advanced Complexity Analysis: Instead of relying on traditional momentum or trend indicators, this tool uses Approximate Entropy to quantify the unpredictability of price movements.
Dynamic Zone Creation: It automatically plots zones on the chart during periods of high entropy, providing a clear and intuitive visual guide.
Customizable Sensitivity: Users can fine-tune the ‘Entropy Threshold’ to adjust how frequently zones appear, allowing for calibration to different assets and timeframes.
Time-Based Zone Expiration: Zones can be set to expire after a specific time, keeping the chart clean and relevant.
Built-in Zone Size Filter: Excludes zones that form on excessively large candles, filtering out noise from extreme volatility events.
On-Chart Calibration Guide: A persistent note on the chart provides simple instructions for adjusting the entropy threshold, making it easy for users to optimize the indicator’s performance.
Core Components
Approximate Entropy (ApEn) Calculation: The core of the indicator, which measures the complexity or randomness of the price data.
Zone Plotting: Creates visual boxes on the chart when the calculated ApEn value exceeds a user-defined threshold.
Dynamic Zone Management: Manages the lifecycle of the zones, from creation to expiration, ensuring the chart remains uncluttered.
Customizable Settings: A comprehensive set of inputs that allow users to control the indicator’s sensitivity, appearance, and time-based behavior.
Key Features
Identifies Potential Reversals: The high-entropy zones can signal that a trend is nearing its end, giving traders an early warning.
Works on Any Timeframe: The indicator can be applied to any chart timeframe, from minutes to days.
Customizable Appearance: Users can change the color and transparency of the zones to match their chart’s theme.
Informative Labels: Each zone can display the calculated entropy value and the direction of the candle on which it formed.
Visualization
Entropy Zones: Shaded boxes that appear on the chart, highlighting candles with high complexity.
Zone Labels: Text within each zone that displays the ApEn value and a directional arrow (e.g., “0.525 ↑”).
Calibration Note: A small table in the top-right corner of the chart with instructions for adjusting the indicator’s sensitivity.
Usage Guidelines
Entropy Analysis
Source: The price data used for the ApEn calculation. (Default: close)
Lookback Length: The number of bars used in the ApEn calculation. (Default: 20, Range: 10-50)
Embedding Dimension (m): The length of patterns to be compared; a standard value for financial data. (Default: 2)
Tolerance Multiplier (r): Adjusts the tolerance for pattern matching; a larger value makes matching more lenient. (Default: 0.2)
Entropy Threshold: The ApEn value that must be exceeded to plot a zone. Increase this if too many zones appear; decrease it if too few appear. (Default: 0.525)
Time Settings
Analysis Timeframe: How long a zone remains on the chart after it forms. (Default: 1D)
Custom Period (Bars): The zone’s lifespan in bars if “Analysis Timeframe” is set to “Custom”. (Default: 1000)
Zone Settings
Zone Fill Color: The color of the entropy zones. (Default: #21f38a with 80% transparency)
Maximum Zone Size %: Filters out zones on candles that are larger than this percentage of their low price. (Default: 0.5)
Display Options
Show Entropy Label: Toggles the visibility of the text label inside each zone. (Default: true)
Label Text Position: The horizontal alignment of the text label. (Default: Right)
Show Calibration Note: Toggles the visibility of the calibration note in the corner of the chart. (Default: true)
Best Use Cases
Trend Reversal Trading: Identifying when a strong trend is likely to reverse or pause.
Breakout Confirmation: Using the absence of high entropy to confirm the strength of a breakout.
Ranging Market Identification: Periods of high entropy can indicate that a market is transitioning into a sideways or choppy phase.
Limitations
Not a Standalone Signal: This indicator should be used in conjunction with other forms of analysis to confirm trading signals.
Lagging Nature: Like all indicators based on historical data, ApEn is a lagging measure and does not predict future price movements with certainty.
Calibration Required: The effectiveness of the indicator is highly dependent on the “Entropy Threshold” setting, which needs to be adjusted for different assets and timeframes.
What Makes This Unique
Quantifies Complexity: It provides a numerical measure of market complexity, offering a different perspective than traditional indicators.
Clear Visual Cues: The zones make it easy to see when the market is in a state of high unpredictability.
User-Friendly Design: With features like the on-chart calibration note, the indicator is designed to be easy to use and optimize.
How It Works
Calculate Standard Deviation: The indicator first calculates the standard deviation of the source price data over a specified lookback period.
Calculate Phi: It then calculates a value called “phi” for two different pattern lengths (embedding dimensions ‘m’ and ‘m+1’). This involves comparing sequences of data points to see how many are “similar” within a certain tolerance (determined by the standard deviation and the ‘r’ multiplier).
Calculate ApEn: The Approximate Entropy is the difference between the two phi values. A higher ApEn value indicates greater irregularity and unpredictability in the data.
Plot Zones: If the calculated ApEn exceeds the user-defined ‘Entropy Threshold’, a zone is plotted on the chart.
Note: The “Entropy Threshold” is the most important setting to adjust. If you see too many zones, increase the threshold. If you see too few, decrease it.
Moving Averages with ADR%/ATR/52W/Market Cap TableThis one indicator covers all major aspects for a trader like moving averages (which you can choose as per the time frame), Average Dynamic Range (it should be above 5% on a 20 day period), CMP position from 52 Weeks High / Low and Market Capitalization of the company.
Directional Movement IndexDirectional Movement Index with an adjustable bar
It is simply a DMI indicator with an adjustable bar to be able to mark a single personalized one to see if the volatility goes above a defined point to be able to start having an interest in a trade
COV Bands ~ C H I P ACOV Bands ~ C H I P A is a custom volatility and trend identification tool designed to capture directional shifts using the Coefficient of Variation (COV), calculated from standard deviation relative to a mean price baseline.
Key features include:
A configurable SMA-based mean baseline to anchor volatility measurements clearly.
Adjustable upper and lower band multipliers to independently calibrate sensitivity and responsiveness for bullish or bearish breakouts.
Dynamic bands derived from price-relative volatility (COV), enabling adaptive identification of significant price deviations.
User-controlled standard deviation length to manage sensitivity and smoothness of volatility signals.
Direct candle coloring, providing immediate visual feedback using vibrant electric blue for bullish momentum and bright red for bearish momentum.
This indicator is particularly useful for detecting meaningful price movements, breakout signals, and potential reversals when the market moves significantly beyond its typical volatility boundaries.
Note: This indicator has not undergone formal robustness or optimization testing. Therefore, future performance in live trading environments isn't guaranteed.
Price Deviation from SMA/EMA with % Threshold HighlightSelect between SMA or EMA.
Adjustable length (default is 20).
Visual deviation band from price.
Plot of absolute deviation on a separate line.
Adding a threshold input. The threshold input is in percentage (%), e.g., 2.5 means 2.5% deviation. The deviation is compared to ma * (thresholdPercent / 100).
Highlights bars where the absolute deviation exceeds the percentage of the MA value.
Highlighting bars where the absolute deviation from the moving average exceeds the threshold.
If thresholdPct = 2.0 and the EMA is 100, then the deviation threshold is 2.0, and bars with absolute deviation > 2.0 will be highlighted.
You can set the threshold manually as a parameter.
The bars will be highlighted (colored) when deviation is outside the threshold range.
The threshold lets you define a "normal" deviation range. Any bars outside of this range are potential outliers — and are now visually flagged.
Normalized Volume & True RangeThis indicator solves a fundamental challenge that traders face when trying to analyze volume and volatility together on their charts. Traditionally, volume and price volatility exist on completely different scales, making direct comparison nearly impossible. Volume might range from thousands to millions of shares, while volatility percentages typically stay within single digits. This indicator brings both measurements onto a unified scale from 0 to 100 percent, allowing you to see their relationship clearly for the first time.
The core innovation lies in the normalization process, which automatically calculates appropriate scaling factors for both volume and volatility based on their historical statistical properties. Rather than using arbitrary fixed scales that might work for one stock but fail for another, this system adapts to each instrument's unique characteristics. The indicator establishes baseline averages for both measurements and then uses statistical analysis to determine reasonable maximum values, ensuring that extreme outliers don't distort the overall picture.
You can choose from three different volatility calculation methods depending on your analytical preferences. The "Body" option measures the distance between opening and closing prices, focusing on the actual trading range that matters most for price action. The "High/Low" method captures the full daily range including wicks and shadows, giving you a complete picture of intraday volatility. The "Close/Close" approach compares consecutive closing prices, which can be particularly useful for identifying gaps and overnight price movements.
The indicator displays volume as colored columns that match your candlestick colors, making it intuitive to see whether high volume occurred during up moves or down moves. Volatility appears as a gray histogram, providing a clean background reference that doesn't interfere with volume interpretation. Both measurements are clipped at 100 percent, which represents their calculated maximum normal values, so any readings near this level indicate unusually high activity in either volume or volatility.
The baseline reference line shows you what "normal" volume looks like for the current instrument, helping you quickly identify when trading activity is above or below average. Optional moving averages for both volume and volatility are available if you prefer smoothed trend analysis over raw daily values. The entire system updates in real-time as new data arrives, continuously refining its statistical calculations to maintain accuracy as market conditions evolve.
This two-in-one indicator provides a straightforward way to examine how price movements relate to trading volume by presenting both measurements on the same normalized scale, making it easier to spot patterns and relationships that might otherwise remain hidden when analyzing these metrics separately.
BB Oscillator - Price Relative to Bollinger BandsThis Bollinger Band Oscillator visualizes where the current price sits relative to its Bollinger Bands, scaled between 0 and 100. It helps identify overbought and oversold conditions based on the price’s position within the bands and provides dynamic signals when momentum shifts occur.
Features
Price Relative to Bollinger Bands
The main oscillator plots the price’s relative position within the Bollinger Bands on a scale from 0 (lower band) to 100 (upper band), giving an intuitive view of where price stands.
Customizable Moving Average Overlay
An optional moving average (SMA or EMA) smooths the oscillator for trend analysis, with adjustable length and color options.
Crossover & Crossunder Signals
Alerts and background highlights trigger when the oscillator crosses over or under its moving average, signaling potential momentum shifts or trend changes.
Fully Customizable Colors
Choose your preferred colors for the oscillator line, moving average and crossover signals to match your charting style.
This tool offers a unique oscillator view of Bollinger Bands, combining volatility context with momentum signals for clearer decision-making.
FIVEXFIVEX doesn’t look at the market through the lens of just one indicator — it combines the insights of six powerful tools working together in harmony. This system brings together RSI, EMA, Bollinger Bands, OBV, MACD, and Fibonacci-based Pivot levels to deliver highly accurate signals for both trend direction and momentum.
Each indicator evaluates the chart based on its own logic and produces a decision: LONG, SHORT, or NEUTRAL. FIVEX collects these individual insights and only generates a trading signal when at least three indicators agree on the same direction. This significantly reduces false signals caused by random price movements.
At a glance, the table in the top right corner of your chart shows exactly what each indicator is thinking in real-time. Background color changes only occur when the signal is strong and stable — this keeps your screen clean and your decisions clear. If a signal appears, you'll immediately understand why.
Thanks to dynamic parameter adjustments based on timeframes, FIVEX behaves more aggressively on 15-minute charts and more refined on daily charts. It’s compatible with every trading style — from scalping to swing trading.
FIVEX isn’t just an indicator; it’s a consensus engine.
It questions, waits for confirmation, and shows only what’s truly strong.
It doesn’t shout the final word — it delivers the collective judgment of market logic.
Adaptive Momentum Scalper (AMS) - Prop Firm Safe**This has only been used in TV strategy testing and has not been used by me on a live account yet.**
This is a strategy is a quick momentum trading with a close stop loss. This scalping strategy looks for big candles and momentum and enters a quick trade. SL and TP are ATR based and the duration of open time is limited to the number of candles entered in the settings.
Please take a look and let me know your thoughts. If anyone can collect some solid data on forward testing please let me know.
SLTP v3Sometimes when you are entrying a position or placing a limit/stop order, you only see one or even none key price level to set as TP (Take Profit) or SL (Stop Loss) conditional orders. You can use this SLTP to choose proper price levels to set as TP or SL. This indicator is highly custom. Remember to alter the color of the short side to your background color when you are about to long a security and do the same to the long side when you are about to short.
By the way the reference levels are based on volatility of last 14 bars of your security.
Will keep updating this indicator with high pratical value but not today. Peace out
有时当你进入一个头寸或设置限价/止损订单时，你可能只看到一个甚至没有关键价格水平可以设置为获利（Take Profit，TP）或止损（Stop Loss，SL）条件订单。你可以使用这个SLTP指标来选择合适的价格水平设置为TP或SL。这个指标高度可定制。当你打算买入证券时，记得将空头一侧的颜色改为与背景颜色一致；当你打算做空时，也对多头一侧做同样的调整。
顺便说一下，参考水平是基于证券最近14根K线的波动率来计算的。
我会持续更新这个具有高实用价值的指标，但不是今天。
祝好！
VWAP %BVWAP %B - Volume Weighted Average Price Percent B
The VWAP %B indicator combines the reliability of VWAP (Volume Weighted Average Price) with the analytical power of %B oscillators, similar to Bollinger Bands %B but using volume-weighted statistics.
## How It Works
This indicator calculates where the current price sits relative to VWAP-based standard deviation bands, expressed as a percentage from 0 to 1:
• **VWAP Calculation**: Uses volume-weighted average price as the center line
• **Standard Deviation Bands**: Creates upper and lower bands using standard deviation around VWAP
• **%B Formula**: %B = (Price - Lower Band) / (Upper Band - Lower Band)
## Key Levels & Interpretation
• **Above 1.0**: Price is trading above the upper VWAP band (strong bullish momentum)
• **0.8 - 1.0**: Overbought territory, potential resistance
• **0.5**: Price exactly at VWAP (equilibrium)
• **0.2 - 0.0**: Oversold territory, potential support
• **Below 0.0**: Price is trading below the lower VWAP band (strong bearish momentum)
## Trading Applications
**Trend Following**: During strong trends, breaks above 1.0 or below 0.0 often signal continuation rather than reversal.
**Mean Reversion**: In ranging markets, extreme readings (>0.8 or <0.2) may indicate potential reversal points.
**Volume Context**: Unlike traditional %B, this incorporates volume weighting, making it more reliable during high-volume periods.
## Parameters
• **Length (20)**: Period for standard deviation calculation
• **Standard Deviation Multiplier (2.0)**: Controls band width
• **Source (close)**: Price input for calculations
## Visual Features
• Reference lines at key levels (0, 0.2, 0.5, 0.8, 1.0)
• Background highlighting for extreme breaks
• Real-time values table
• Clean oscillator format below price chart
Perfect for intraday traders and swing traders who want to combine volume analysis with momentum oscillators.
Adaptive Momentum Scalper (AMS) - ADX/RSI Filters Fixed### 📘 Strategy Description: **Adaptive Momentum Scalper (AMS) – Prop Firm Edition**
The **Adaptive Momentum Scalper (AMS)** is a breakout-based trend-following strategy designed with **prop firm trading rules and risk management** in mind. It combines volatility, momentum, and trend filters with dynamic sizing to manage risk across changing market conditions.
#### ✅ Core Features:
* **Breakout Logic**: Enters long or short when price breaks above/below a short-term range.
* **Momentum Filter**: Confirms breakouts with ATR-based price momentum.
* **Trend Filter**: Uses EMA(20) to ensure directional bias.
* **Volatility Filter**: Requires ATR > ATR average to avoid choppy zones.
* **ADX Filter (Optional)**: Confirms strength of trend (default ADX > 20).
* **RSI Zone Filter (Optional)**: Limits long trades to RSI > 50, shorts to RSI < 50.
* **Dynamic Position Sizing**: Risk-based lot sizing tied to ATR and account equity.
* **Hard SL/TP or Time-Based Exit**: Trades close by target, stop, or max bars in trade.
* **Session Filtering**: Trade only within configured hours (to avoid high spread periods).
* **Prop Firm Safety-Oriented**: Configurable to stay within max drawdown rules.
---
### ⚙️ Settings:
* **Risk per Trade** (% of equity)
* **ATR multipliers** for stop loss and take profit
* **Trading hours** (e.g. 1 AM to 10 PM EST)
* **Max bars in trade before exit**
* **Enable/disable**:
* ADX filter
* RSI filter
---
### 🎯 Ideal Use:
* Scalping on **Gold (XAUUSD)** or other volatile assets.
* Forward testing under prop firm conditions (3% daily / 6% max drawdown).
* Identifying breakout opportunities with strong trend and momentum backing.
Toolbar-FrenToolbar-Fren is a comprehensive, data-rich toolbar designed to present a wide array of key metrics in a compact and intuitive format. The core philosophy of this indicator is to maximize the amount of relevant, actionable data available to the trader while occupying minimal chart space. It leverages a dynamic color-coded system to provide at-a-glance insights into market conditions, instantly highlighting positive/negative values, trend strength, and proximity to important technical levels.
Features and Data Displayed
The toolbar displays a vertical column of critical data points, primarily calculated on the Daily timeframe to give a broader market context. Each cell is color-coded for quick interpretation.
DAY:
The percentage change of the current price compared to the previous day's close. The cell is colored green for a positive change and red for a negative one.
LOD:
The current price's percentage distance from the Low of the Day.
HOD
The current price's percentage distance from the High of the Day.
MA Distances (9/21 or 10/20, 50, 200)
These cells show how far the current price is from key Daily moving averages (MAs).
The values are displayed either as a percentage distance or as a multiple of the Average Daily Range (ADR), which can be toggled in the settings.
The cells are colored green if the price is above the corresponding MA (bullish) and red if it is below (bearish).
ADR
Shows the 14-period Average Daily Range as a percentage of the current price. The cell background uses a smooth gradient from green (low volatility) to red (high volatility) to visualize the current daily range expansion.
ADR%/50: A unique metric showing the distance from the Daily 50 SMA, measured in multiples of the 14-period Average True Range (ATR). This helps quantify how extended the price is from its mean. The cell is color-coded from green (close to the mean) to red (highly extended).
RSI
The standard 14-period Relative Strength Index calculated on the Daily timeframe. The background color changes to indicate potentially overbought (orange/red) or oversold (green) conditions.
ADX
The 14-period Average Directional Index (ADX) from the Daily timeframe, which measures trend strength. The cell is colored to reflect the strength of the trend (e.g., green for a strong trend, red for a weak/non-trending market). An arrow (▲/▼) is also displayed to indicate if the ADX value is sloping up or down.
User Customization
The indicator offers several options for personalization to fit your trading style and visual preferences:
MA Type
Choose between using Exponential Moving Averages (EMA 9/21) or Simple Moving Averages (SMA 10/20) for the primary MA calculations.
MA Distance Display
Toggle the display of moving average distances between standard percentage values and multiples of the Average Daily Range (ADR).
Display Settings
Fully customize the on-chart appearance by selecting the table's position (e.g., Top Right, Bottom Left) and the text size. An option for a larger top margin is also available.
Colors
Personalize the core Green, Yellow, Orange, and Red colors used throughout the indicator to match your chart's theme.
Technical Parameters
Fine-tune the length settings for the ADX and DI calculations.
Demo GPT - Bollinger Bands StrategyHere’s a professional and detailed description for publishing your **"iNsTiNcT - Bollinger Bands Strategy"** on TradingView:
---
### **Strategy Description: iNsTiNcT - Bollinger Bands Strategy**
#### **Overview**
This strategy uses **Bollinger Bands®** to identify potential breakouts and trend reversals. It goes **long** when the price closes **above the upper band** (indicating strong bullish momentum) and **exits the position** when the price closes **below the lower band** (signaling a potential reversal or weakness).
Unlike traditional Bollinger Bands strategies that may trade both long and short, this version **only takes long positions**, making it suitable for trending markets while avoiding short-side risks.
---
### **Key Features**
✅ **Long-Only Trend Strategy** – Capitalizes on strong uptrends when price breaks above the upper band.
✅ **Clear Exit Signal** – Closes the trade when price falls below the lower band, locking in profits or cutting losses.
✅ **Customizable Parameters** – Adjustable length, standard deviation multiplier, and MA type for different market conditions.
✅ **Date Range Filter** – Test or trade between **January 2018 and December 2069**.
✅ **Professional Risk Management** – **0.1% commission** and **zero slippage** for realistic backtesting.
✅ **Visual Preservation** – Maintains the original Bollinger Bands indicator plots for easy comparison.
---
### **Input Parameters**
| Parameter | Description | Default Value |
|-----------|------------|--------------|
| **Start Date** | Backtest/trade start date | Jan 1, 2018 |
| **End Date** | Backtest/trade end date | Dec 31, 2069 |
| **Length** | Period for Bollinger Bands calculation | 20 |
| **Basis MA Type** | Type of moving average (SMA, EMA, SMMA, WMA, VWMA) | SMA |
| **Source** | Price source for calculations | Close |
| **StdDev** | Multiplier for standard deviation | 2.0 |
| **Offset** | Shifts bands forward/backward | 0 |
---
### **Strategy Logic**
#### **Entry Condition (Long)**
➡ **Buy Signal:** `Close > Upper Bollinger Band`
#### **Exit Condition (Close Long)**
➡ **Sell Signal:** `Close < Lower Bollinger Band`
*(No short trades are taken—only long and flat positions.)*
---
### **How to Use This Strategy**
1. **Apply to Chart** – Works on any timeframe (best on **1H, 4H, or Daily** for swing trading).
2. **Optimize Settings** – Adjust `Length` and `StdDev` for different volatility conditions.
3. **Combine with Filters** – Add volume confirmation or RSI for stronger signals.
4. **Backtest** – Use the **date range** to test different market cycles.
---
### **Risk & Limitations**
⚠ **Works Best in Trending Markets** – May produce false signals in choppy or sideways conditions.
⚠ **Single Indicator Reliance** – Consider adding confirmation filters (e.g., RSI, MACD).
⚠ **No Stop-Loss by Default** – Exits only when price touches the lower band.
---
### **Final Notes**
This strategy is designed for **educational and experimental purposes**. Always conduct **forward testing** before live trading.
🔹 **Happy Trading!** 🚀
---
### **Publishing Tags (For SEO)**
`Bollinger Bands Strategy`, `Trend Following`, `Breakout Trading`, `Long-Only Strategy`, `Technical Analysis`, `TradingView Strategy`, `Pine Script v6`, `Swing Trading`
---
This description is **clear, engaging, and optimized for TradingView’s audience**. It highlights the strategy’s logic, strengths, and limitations while encouraging users to experiment with it.
Would you like any refinements?
ATR-Stop-SurvivalHow to Use the ATR-Stop-Survival Indicator
This indicator was designed to prioritize functionality, removing unnecessary elements and focusing only on what is essential for survival in the financial market. It is easy to understand for both beginner and experienced traders, avoiding visual clutter and unnecessary buttons.
Key Features:
Uses only 1 indicator on the chart, unlike the previous version, which consumed 2 indicators.
Recommended for 4-hour timeframes. If desired, it can also be used in 2-hour or 3-hour intervals.
Not recommended for daily, weekly, or monthly timeframes, as they are too long and may lead to significant financial losses due to stop-loss activation.
ATR Period Adjustment: The default is 14, but it can be set to 20, if preferred.
ATR Multiplier Settings:
1.5 (Conservative) → For calm and stable assets.
2.0 (Aggressive) → For volatile, fast-moving assets with high candle retracement.
This indicator is a practical tool that ensures clarity and efficiency, allowing traders to focus only on critical market movements without distractions.
HA EMA Cross MTF Strategy + ATR SL/TP + Visuals📜 Strategy Description: HA EMA Cross MTF Strategy + ATR SL/TP + Visuals
Hello Traders,
This is a multi-timeframe, Heikin Ashi-based trend-following strategy that integrates EMA crossovers and ATR-driven exits. The goal is to filter out noise, confirm directional bias using higher timeframe structure, and manage risk through volatility-adaptive exits.
🔍 How the Strategy Works
* Heikin Ashi candles help smooth out minor price fluctuations, allowing for clearer trend detection.
* A Fast EMA crossing above or below a Slow EMA determines the local trend bias.
* A Higher Timeframe Heikin Ashi confirmation is used to validate entries only when both timeframes agree in direction.
* Session filters can restrict trading to custom hours (e.g., U.S. market open).
⚙️ Risk Management Features
This strategy includes optional ATR-based Stop-Loss and Take-Profit logic, designed to adapt dynamically to market volatility:
* ATR Stop-Loss: Based on a user-defined multiplier (default: 1.5×ATR)
* ATR Take-Profit: Based on a separate multiplier (default: 2.5×ATR)
* Users can toggle this logic on/off and customize ATR length and multipliers in the settings.
📊 Visual Aids Included
To help understand market behavior and trade execution visually, the script includes:
* Entry arrows (long and short)
* Real-time Fast EMA / Slow EMA overlays
* Stop-Loss / Take-Profit level plots
* Optional Heikin Ashi Close line for trend visualization
🔧 Customization Parameters
Users can adjust:
* EMA periods (fast and slow)
* ATR period and multipliers for SL/TP
* Session time filters
* Higher timeframe input
* Toggle ATR logic and visual overlays
🧪 Backtest Defaults (for reference only)
* Initial Capital: $10,000
* Order Size: 100% of equity
* Slippage: 1 tick
* Commission: 0.075%
* Recommended Timeframe: 1H or 15min
* Minimum Trades Suggested: 100+
* All these values can be adjusted in the strategy settings panel.
⚠️ Disclaimer
This strategy is provided for educational and research purposes only. It does not constitute financial advice, nor does it guarantee future performance. Please forward-test and adapt to your own risk tolerance before using in live trading.
This strategy is fully open-source and editable. Feel free to customize it for your use case and timeframes.
Institutional Key Levels + VWAP Alerts (Labeled)🧠 Description:
This free version of the Institutional Key Levels + VWAP script gives you instant, auto-updating visibility on the most important price zones for intraday and swing trading.
✅ Designed for traders who want clean, data-driven levels without daily redrawing.
🧱 What It Shows:
Prior Day High (PDH)
Prior Day Low (PDL)
Prior Day Close (PDC)
Live VWAP
Color-coded horizontal lines + optional chart labels
Built-in alert conditions for:
Breakout above PDH
Breakdown below PDL
VWAP Reclaim or Rejection
📊 Ideal for:
Futures traders (MNQ, ES, MGC, etc.)
Equity scalpers
Options traders using directional bias
Traders who use VWAP as a dynamic S/R guide
🔧 No need to draw lines manually. This script updates daily with zero maintenance and lets you stay focused on execution.
ATR Keltner Channels [iryna]Hello!
I’m excited to share my custom ATR Keltner Channel script, built around a 21-period EMA and ATR-based volatility bands. I am using this tool myself for watching price behavior, any pullbacks or breakouts, and to visualize dynamic support and resistance.
How it works:
• The centerline is a 21-day Exponential Moving Average (EMA), giving you a smooth sense of the trend.
• The upper and lower bands are calculated using Average True Range (ATR), so they expand and contract based on volatility.
• The upper and lower bands are x1ATR, x2ATR, x3ATR.
All my knowledge comes from SpikeTrade community, where I am learning from Kerry Lovvorn and Alexander Elder.
Let me know if you have any suggestions to improve or update!
Have a fruitful trading session!
- Iryna
ADR Pivot LevelsThe ADR (Average Daily Range) indicator shows the average range of price movement over a trading day. The ADR is used to estimate volatility and to determine target levels. It helps to set Take-Profit and Stop-Loss orders. It is suitable for intraday trading on lower time frames.
The “ADR Pivot Levels” produces a sequence of horizontal line levels above and below the Center Line (reference level). They are sized based on the instrument's volatility, representing the average historical price movement on a selected higher timeframe using the average daily range (ADR) indicator.
Candle Overlap DegreeThis indicator gives the ratio of max(0, min High - max Low) to (max High - min Low) over n-day.
Letzte Open Rays (18:00, 00:00, 10:00 UTC-4)super diese gute opening ray, opening rays bei den 10,18 und 0 open nur die letzten möglichen
TitanGrid L/S SuperEngineTitanGrid L/S SuperEngine
Experimental Trend-Aligned Grid Signal Engine for Long & Short Execution
🔹 Overview
TitanGrid is an advanced, real-time signal engine built around a tactical grid structure.
It manages Long and Short trades using trend-aligned entries, layered scaling, and partial exits.
Unlike traditional strategy() -based scripts, TitanGrid runs as an indicator() , but includes its own full internal simulation engine.
This allows it to track capital, equity, PnL, risk exposure, and trade performance bar-by-bar — effectively simulating a custom backtest, while remaining compatible with real-time alert-based execution systems.
The concept was born from the fusion of two prior systems:
Assassin’s Grid (grid-based execution and structure) + Super 8 (trend-filtering, smart capital logic), both developed under the AssassinsGrid framework.
🔹 Disclaimer
This is an experimental tool intended for research, testing, and educational use.
It does not provide guaranteed outcomes and should not be interpreted as financial advice.
Use with demo or simulated accounts before considering live deployment.
🔹 Execution Logic
Trend direction is filtered through a custom SuperTrend engine. Once confirmed:
• Long entries trigger on pullbacks, exiting progressively as price moves up
• Short entries trigger on rallies, exiting as price declines
Grid levels are spaced by configurable percentage width, and entries scale dynamically.
🔹 Stop Loss Mechanism
TitanGrid uses a dual-layer stop system:
• A static stop per entry, placed at a fixed percentage distance matching the grid width
• A trend reversal exit that closes the entire position if price crosses the SuperTrend in the opposite direction
Stops are triggered once per cycle, ensuring predictable and capital-aware behavior.
🔹 Key Features
• Dual-side grid logic (Long-only, Short-only, or Both)
• SuperTrend filtering to enforce directional bias
• Adjustable grid spacing, scaling, and sizing
• Static and dynamic stop-loss logic
• Partial exits and reset conditions
• Webhook-ready alerts (browser-based automation compatible)
• Internal simulation of equity, PnL, fees, and liquidation levels
• Real-time dashboard for full transparency
🔹 Best Use Cases
TitanGrid performs best in structured or mean-reverting environments.
It is especially well-suited to assets with the behavioral profile of ETH — reactive, trend-intraday, and prone to clean pullback formations.
While adaptable to multiple timeframes, it shows strongest performance on the 15-minute chart , offering a balance of signal frequency and directional clarity.
🔹 License
Published under the Mozilla Public License 2.0 .
You are free to study, adapt, and extend this script.
🔹 Panel Reference
The real-time dashboard displays performance metrics, capital state, and position behavior:
• Asset Type – Automatically detects the instrument class (e.g., Crypto, Stock, Forex) from symbol metadata
• Equity – Total simulated capital: realized PnL + floating PnL + remaining cash
• Available Cash – Capital not currently allocated to any position
• Used Margin – Capital locked in open trades, based on position size and leverage
• Net Profit – Realized gain/loss after commissions and fees
• Raw Net Profit – Gross result before trading costs
• Floating PnL – Unrealized profit or loss from active positions
• ROI – Return on initial capital, including realized and floating PnL. Leverage directly impacts this metric, amplifying both gains and losses relative to account size.
• Long/Short Size & Avg Price – Open position sizes and volume-weighted average entry prices
• Leverage & Liquidation – Simulated effective leverage and projected liquidation level
• Hold – Best-performing hold side (Long or Short) over the session
• Hold Efficiency – Performance efficiency during holding phases, relative to capital used
• Profit Factor – Ratio of gross profits to gross losses (realized)
• Payoff Ratio – Average profit per win / average loss per loss
• Win Rate – Percent of profitable closes (including partial exits)
• Expectancy – Net average result per closed trade
• Max Drawdown – Largest recorded drop in equity during the session
• Commission Paid – Simulated trading costs: maker, taker, funding
• Long / Short Trades – Count of entry signals per side
• Time Trading – Number of bars spent in active positions
• Volume / Month – Extrapolated 30-day trading volume estimate
• Min Capital – Lowest equity level recorded during the session
🔹 Reference Ranges by Strategy Type
Use the following metrics as reference depending on the trading style:
Grid / Mean Reversion
• Profit Factor: 1.2 – 2.0
• Payoff Ratio: 0.5 – 1.2
• Win Rate: 50% – 70% (based on partial exits)
• Expectancy: 0.05% – 0.25%
• Drawdown: Moderate to high
• Commission Impact: High
Trend-Following
• Profit Factor: 1.5 – 3.0
• Payoff Ratio: 1.5 – 3.5
• Win Rate: 30% – 50%
• Expectancy: 0.3% – 1.0%
• Drawdown: Low to moderate
Scalping / High-Frequency
• Profit Factor: 1.1 – 1.6
• Payoff Ratio: 0.3 – 0.8
• Win Rate: 80% – 95%
• Expectancy: 0.01% – 0.05%
• Volume / Month: Very high
Breakout Strategies
• Profit Factor: 1.4 – 2.2
• Payoff Ratio: 1.2 – 2.0
• Win Rate: 35% – 60%
• Expectancy: 0.2% – 0.6%
• Drawdown: Can be sharp after failed breakouts
🔹 Note on Performance Simulation
TitanGrid includes internal accounting of fees, slippage, and funding costs.
While its logic is designed for precision and capital efficiency, performance is naturally affected by exchange commissions.
In frictionless environments (e.g., zero-fee simulation), its high-frequency logic could — in theory — extract substantial micro-edges from the market.
However, real-world conditions introduce limits, and all results should be interpreted accordingly.
Mandelbrot Risk Bands (Dynamic Chart-Scaled)I used Chatgpt to come up with a Madelbrot style risk bands. Thought process is similar to how Hedgeye thinks about the markets. I am currently having issues with the script not updating or scaling so if there are any ideas please let me know.
