Dynamic Laguerre Filter Bands | OttoThis indicator combines trend-following and volatility analysis by enhancing the traditional Laguerre filter with a dynamic, volatility-adjusted band system. Instead of using fixed thresholds, the bands adapt in real-time to changing market conditions by applying smoothed standard deviation calculations. This design keeps the indicator responsive to significant price movements while effectively filtering out short-term market noise, resulting in more accurate trend identification and breakout signals.
Core Concept
The indicator is built around the following key components:
Laguerre Filter:
The Laguerre filter is designed to smooth out price data by reducing market noise while still being quick enough to detect real changes in price direction. Its goal is to create a clear, smooth trend line that helps traders/investors focus on the overall market trend without getting distracted by small, random price swings.
It uses a parameter called gamma to control how it balances smoothness and responsiveness:
A lower gamma gives more weight to recent price data, making the filter react faster to new price changes. This means the trend line is more sensitive but may also be less smooth and more prone to small fluctuations.
A higher gamma gives more weight to past price data, making the filter smoother and less sensitive to quick changes. This helps reduce noise and produces a steadier trend line, but it also introduces more lag, meaning the filter reacts slower to new price moves.
By adjusting gamma, the Laguerre filter lets you choose the balance between following price changes quickly and having a stable, noise-free trend signal.
Standard Deviation:
shows how much price varies from the mean. In this indicator, it’s used to measure market volatility.
Volatility Bands: The upper and lower bands are based on an EMA-smoothed standard deviation of price. The EMA reduces sudden jumps in volatility, creating smoother and more stable bands that still respond to changing market conditions. These bands are plotted around the Laguerre filter line, expanding and contracting in a controlled way to stay aligned with real market movement while avoiding short-term noise.
Signal Logic:
A long signal is triggered when the close price crosses above the upper band.
A short signal occurs when the close price falls below the lower band.
⚙️ Inputs
Source: Price source used in calculations
Gamma: Adjusts how much the Laguerre filter responds to price changes. Lower gamma values make the filter react more to recent prices, while higher values give more influence to older data, making the line smoother but slower to respond.
Volatility Length: Period used to calculate standard deviation
Volatility Smoothing Length: EMA smoothing length for standard deviation
Multiplier: Scales the width of the bands based on volatility
📈 Visual Output
Laguerre Filter Line: Plots the laguerre filter line, colored dynamically based on signal direction (green for bullish, purple for bearish)
Upper & Lower Bands: Volatility-based bands that adjust with market conditions. (green for bullish, purple for bearish)
Glow Effect: Optional glow layer to enhance visibility of the laguerre filter trend line (green for bullish, purple for bearish)
Bar Coloring: Candlesticks and bar colors reflect the active signal state for fast visual interpretation (green for bullish, purple for bearish)
How to Use
Apply the indicator to your chart and monitor for signal events:
Long Signal: When price closes above the upper band
Short Signal: When price closes below the lower band
🔔 Alerts
This indicator supports optional alert conditions you can enable for:
Long Signal: Close price crossing above the upper band
Short Signal: Close price crossing below the lower band
⚠️ Disclaimer:
This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Volatilità
VWAP Multi-Timeframe VWAP Multi-Timeframe - Complete Professional Indicator
🚀 WHAT IS IT?
The VWAP Multi-Timeframe is an advanced indicator that combines 5 different VWAP periods in a single tool, providing a complete view of market fair value levels across multiple time scales.
⭐ KEY FEATURES
📊 5 Configurable VWAPs:
🟡 Daily VWAP - Ideal for day trading and intraday operations
🟠 Weekly VWAP - Perfect for swing trading
🔵 Monthly VWAP - Excellent for medium-term analysis
🔴 Quarterly VWAP - Essential for quarterly strategies
🟢 Yearly VWAP - Fundamental for long-term investments
🎯 Multiple Price Sources:
Choose the source that best fits your strategy:
Close - Closing price (most common)
OHLC4 - Complete average (smoother)
HLC3 - Typical price (default)
HL2 - Period midpoint
Open/High/Low - Specific prices
💡 HOW TO USE
For Day Traders:
Use Daily VWAP as main fair value reference
Prices above = buying pressure / Prices below = selling pressure
For Swing Traders:
Combine Weekly and Monthly VWAP to identify trends
Look for confluences between different timeframes
For Investors:
Quarterly and Yearly VWAP show long-term value levels
Excellent for identifying entry points in investments
🔧 TECHNICAL FEATURES
✅ Pine Script v6 - Latest and optimized version
✅ Clean Interface - User-friendly design
Adaptive Normalized Global Liquidity OscillatorAdaptive Normalized Global Liquidity Oscillator
A dynamic, non-repainting oscillator built on real central bank balance sheet data. This tool visualizes global liquidity shifts by aggregating monetary asset flows from the world’s most influential central banks.
🔍 What This Script Does:
Aggregates Global Liquidity:
Includes Federal Reserve (FED) assets and subtracts liabilities like the Treasury General Account (TGA) and Reverse Repo Facility (RRP), combined with asset positions from the ECB, BOJ, PBC, BOE, and over 10 other central banks. All data is normalized into USD using FX rates.
Adaptive Normalization:
Optimizes the lookback period dynamically based on rate-of-change stability—no fixed lengths, enabling adaptation across macro conditions.
Self-Optimizing Weighting:
Applies inverse standard deviation to balance raw liquidity, smoothed momentum (HMA), and standardized deviation from the mean.
Percentile-Ranked Highlights:
Liquidity readings are ranked relative to history—extremes are visually emphasized using gradient color and adaptive transparency.
Non-Repainting Design:
Data is anchored with bar index awareness and offset techniques, ensuring no forward-looking bias. What you see is what was known at that time.
⚠️ Important Interpretation Note:
This is not a zero-centered oscillator like RSI or MACD. The signal line does not represent neutrality at zero.
Instead, a dynamic baseline is calculated using a rolling mean of scaled liquidity.
0 is irrelevant on its own—true directional signals come from crosses above or below this adaptive baseline.
Even negative values may signal strength if they are rising above the moving average of past liquidity conditions.
✅ What to Watch For:
Crossover Above Dynamic Baseline:
Indicates liquidity is expanding relative to recent conditions—supports a risk-on interpretation.
Crossover Below Dynamic Baseline:
Suggests deteriorating liquidity conditions—may align with risk-off shifts.
Percentile Extremes:
Readings near the top or bottom historical percentiles can act as contrarian or confirmation signals, depending on momentum.
⚙️ How It Works:
Bounded Normalization:
The final oscillator is passed through a tanh function, keeping values within and reducing distortion.
Adaptive Transparency:
The strength of deviations dynamically adjusts plot intensity—visually highlighting stronger liquidity shifts.
Fully Customizable:
Toggle which banks are included, adjust dynamic optimization ranges, and control visual display options for plot and background layers.
🧠 How to Use:
Trend Confirmation:
Sustained rises in the oscillator above baseline suggest underlying monetary support for asset prices.
Macro Turning Points:
Reversals or divergences, especially near OB/OS zones, can foreshadow broader risk regime changes.
Visual Context:
Use the dynamic baseline to see if liquidity is supportive or suppressive relative to its own adaptive history.
📌 Disclaimer:
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always consult a qualified financial advisor before making trading or investment decisions.
Adaptive RSI Oscillator📌 Adaptive RSI Oscillator
This indicator transforms the classic RSI into a fully adaptive, self-optimizing oscillator — normalized between -1 and 1, dynamically smoothed, and enhanced with divergence detection.
🔧 Key Features
Self-Optimizing RSI: Automatically selects the optimal RSI lookback length based on return stability (no hardcoded periods).
Dynamic Smoothing: Adapts to market conditions using a fraction of the optimized length.
Normalized Output : Converts traditional RSI to a consistent scale across all assets and timeframes.
Divergence Detection: Compares RSI behavior vs. price percentile ranks and scales the signal accordingly.
Gradient Visualization: Color-coded background and plot lines reflect the strength and direction of the signal with soft transitions.
Neutral Zone Adaptation: Dynamically widens or narrows the zone of inaction based on volatility, reducing noise.
🎯 Use Cases
Identify extreme momentum zones without relying on fixed 70/30 RSI levels
Detect divergences early with adaptive filtering
Highlight potential exhaustion or continuation
⚠️ Disclaimer: This indicator is for informational and educational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security. Always conduct your own research and consult a licensed financial advisor before making investment decisions. Use at your own risk.
ATR % Line from Day LowHow can you make sure that you're not buying a stock that is too extended?
By limiting your buys to within a certain percentage of either the low-of-the-day (LoD) if you're going long, or to the high-of-the-day (HoD) if you're shorting a stock. This script will help you do just that.
Limiting stock purchases to within a certain percentage of the Average True Range (ATR) from the day's low or high is a risk management technique that offers several key benefits:
Risk Control and Position Sizing
By using ATR as a boundary, you're essentially creating a volatility-adjusted buffer. Since ATR measures recent price volatility, this approach prevents you from buying into stocks that have already moved significantly beyond their normal trading range. This helps avoid entering positions when the stock might be overextended and due for a pullback.
Improved Entry Timing
This strategy encourages patience and discipline. Rather than chasing a stock that's already run up substantially from its low, you wait for better entry points. For example, if you set a limit of 50% of ATR from the day's low, you're only buying when the stock hasn't moved more than half its typical daily range from the bottom.
Volatility Awareness
ATR naturally adjusts for each stock's individual volatility characteristics. A high-volatility stock might have an ATR of $2, while a low-volatility stock might have an ATR of $0.50. This approach scales your entry criteria appropriately for each security rather than using arbitrary dollar amounts.
Reduced Emotional Trading
Having a systematic rule removes the temptation to chase momentum or buy at poor technical levels. It forces you to wait for the stock to come back to more reasonable levels relative to its recent trading behavior.
Better Risk-Reward Ratios
By entering closer to the day's low (within your ATR percentage), you're typically getting a better risk-reward setup. Your stop loss (often placed below the day's low) will be tighter, while your potential upside remains intact.
This approach works particularly well for swing traders and those looking to enter positions on pullbacks or during consolidation periods rather than breakout scenarios.
To save valuable real estate on your chart, there's also an option that can give you a compact version of this indicator which will show only the "Current Day's Low/High" and "Target Price". "Target Price" being the price at which your max buy limit is based on the % ATR you choose in settings.
X-Day Capital Efficiency ScoreThis indicator helps identify the Most Profitable Movers for Your fixed Capital (ie, which assets offer the best average intraday profit potential for a fixed capital).
Unlike traditional volatility indicators (like ATR or % change), this script calculates how much real dollar profit you could have made each day over a custom lookback period — assuming you deployed your full capital into that ticker daily.
How it works:
Calculates the daily intraday range (high − low)
Filters for clean candles (where body > 60% of the candle range)
Assumes you invested the full amount of capital ($100K set as default) on each valid day
Computes an average daily profit score based on price action over the selected period (default set to 20 days)
Plots the score in dollars — higher = more efficient use of capital
Why It’s Useful:
Compare tickers based on real dollar return potential — not just % volatility
Spot low-priced, high-volatility stocks that are better suited for intraday or momentum trading
Inputs:
Capital ($): Amount you're hypothetically deploying (e.g., 100,000)
Look Back Period: Number of past days to average over (e.g., 20)
Haven Average Daily RangeOverview
This indicator is an enhanced version of the traditional ADR tool that adapts to intraday price movements. Unlike static ADR levels, this indicator dynamically adjusts its range boundaries based on real-time price action while maintaining the original ADR calculation framework.
Key Features
ADR calculation based on multiple periods (5, 10, and 20 days)
ADR levels displayed with automatic style changes upon range reach
Customizable display settings (color, line style)
Price labels for better visualization
The indicator helps traders assess the instrument's volatility, identify potential reversal zones, and plan daily trading targets.
Suitable for all timeframes up to D1 and any trading instrument.
How It Works
Session Start (UTC+0): Calculates ADR based on historical data and sets initial High/Low levels
Dynamic Phase: Monitors price action and adjusts the opposite boundary (ADR Low or High) when new extremes are reached.
When price creates new Day high price above the opening price, the ADR Low level moves upward proportionally.
When price creates new Day low price below the opening price, the ADR High level moves downward proportionally.
Completion Phase: Stops adjustments and highlights breach when price reaches either boundary
Trading Application
Entry and Exit Signals
The ADR boundaries serve as key decision points for trade execution. When price approaches the upper ADR boundary, it often signals a potential selling zone, particularly when confluence exists with other overbought indicators such as RSI divergence or resistance levels. Conversely, price reaching the lower ADR boundary frequently indicates potential buying opportunities, especially when supported by oversold conditions or support confluences.
Trend Continuation Assessment
One of the most valuable applications is gauging the probability of continued directional movement. When the current session's price action has not yet reached either ADR boundary, statistical probability favors trend continuation in the established direction. This information helps traders stay with profitable positions longer rather than exiting prematurely.
Reversal and Consolidation Zones
The visual color change to orange when ADR boundaries are reached provides immediate feedback that the normal daily range has been exhausted. At this point, the probability of trend reversal or sideways consolidation increases significantly. This signal helps traders prepare for potential position adjustments or new counter-trend opportunities.
[Smith] VWAP Deviation + VWAP Deviation +
Short Description:
Advanced VWAP indicator with deviation bands, smart signal filtering, and session-based performance tracking. Features log-space scaling, RSI confirmation, volume filters, and market regime detection.
Full Description:
The VWAP Deviation + is a comprehensive trading indicator that combines Volume Weighted Average Price (VWAP) analysis with advanced signal filtering to identify high-probability trade opportunities. This indicator goes beyond basic VWAP by incorporating multiple confirmation layers and intelligent market analysis.
🎯 Key Features
Core VWAP Analysis:
- Custom volume-weighted mean calculation with deviation bands (2σ and 3σ)
- Optional log-space scaling for proportional price movements
- Real-time VWAP line with customizable visibility
Smart Signal Detection:
- RSI confirmation for all trade signals
- Volume filter requiring above-average trading activity
- Market regime detection (trending vs ranging markets)
- Optional RSI divergence analysis
Advanced Filtering:
- Multi-condition signal validation
- Session-based performance tracking (Asian, London, NY)
- Real-time win rate calculation
- Strong vs regular signal classification
Visual Features:
- Clean, professional interface with customizable colors
- Optional signal shapes and annotations
- Performance statistics table
- Filled deviation bands for easy visualization
📊 How It Works
The indicator identifies trade opportunities when:
1. Price touches VWAP deviation bands (2σ or 3σ)
2. RSI confirms oversold/overbought conditions
3. Volume exceeds the specified threshold
4. Market regime conditions are favorable
Signal Types:
- LONG : Price at lower bands + RSI oversold + volume confirmation
- SHORT : Price at upper bands + RSI overbought + volume confirmation
- STRONG : Same conditions but at 3σ bands for higher conviction trades
⚙️ Customization Options
Core Settings:
- VWAP length and source selection
- Adjustable deviation multipliers
- Log-space scaling toggle
Signal Filters:
- RSI length and threshold levels
- Volume filter with customizable multiplier
- Market type filtering options
Advanced Features:
- Session statistics tracking
- RSI divergence detection
- Market regime analysis
Visual Controls:
- Show/hide individual components
- Custom color schemes
- Signal display toggles
🔔 Alert System
Built-in alerts for:
- Long and short trade opportunities
- Strong signal confirmations
- RSI divergence signals
💡 Best Practices
- Use higher timeframes (15m+) for more reliable signals
- Combine with additional confirmation indicators
- Pay attention to session statistics for timing optimization
- Monitor market regime indicators for context
This indicator is suitable for day traders, swing traders, and anyone looking to improve their VWAP-based trading strategies with advanced filtering and market analysis.
Adaptive Signal Oscillator (ASO)📘 Adaptive Signal Oscillator (ASO)
A fully dynamic, self-calibrating oscillator that adapts to any asset or timeframe by optimizing for real-time signal stability and volatility structure — without relying on static parameters or hardcoded thresholds.
🔍 Overview
The Adaptive Signal Oscillator (ASO) is a next-generation technical analysis tool designed to provide context-aware long/short signals across crypto, equities, or forex markets. Unlike traditional oscillators (RSI, Stochastics, MACD), ASO requires no manual tuning of lookback periods or overbought/oversold zones — it self-optimizes based on current market behavior.
🧠 How It Works
✅ 1. Dynamic Lookback Optimization
ASO evaluates a range of lookback lengths between user-defined minLen and maxLen. For each length, it calculates the standard deviation of returns and finds the one with the least volatility change (i.e., the most stable structure). This length is dynamically assigned as bestLen, recalculated on every bar.
✅ 2. Multi-Layer Signal Composition
Four independent signal layers are computed using bestLen:
RSI Layer: Measures relative price strength via a custom dynamic RSI.
Z-Score Layer: Standardized deviation of price from its mean.
Volatility Layer: Standard deviation of log or percent returns.
Price Position Layer: Current price percentile within the lookback window.
Each of these layers is transformed into a percentile score scaled to the range .
✅ 3. Volatility-Based Weighting
The standard deviation (volatility) of each signal layer is computed. Less volatile layers are weighted more heavily, ensuring the final composite signal prioritizes stable, consistent inputs.
Weights are normalized and combined to form a composite score, representing a dynamically blended, noise-weighted signal across the four layers.
✅ 4. Optional Adaptive Smoothing
A boolean toggle lets users apply smoothing to the final score. The smoothing window scales proportionally to bestLen, preserving adaptiveness even during trend transitions.
✅ 5. Percentile-Based Thresholding
Rather than using arbitrary fixed thresholds, ASO converts the composite score into a ranked percentile. Long/short signals are then generated based on user-defined percentile bands, adapting naturally to each asset’s behavior.
📈 Interpreting ASO
Score > Threshold → Strong long signal (highlighted in aqua).
Score < Threshold → Strong short signal (highlighted in fuchsia).
Crossing h_thresh (e.g., 0) → Neutral-to-bias change; useful for early trend cues.
The background and label update in real time to reflect the current regime and bestLen.
⚙️ Inputs
minLen, maxLen, step: Define the search range for optimal lookback length.
retMethod: Choose between log or percent return calculations.
threshHigh, threshLow: Define signal zones using percentiles.
smooth: Enable dynamic score smoothing.
h_thresh: Midline crossover zone for directional context.
⚠️ Disclaimer
This tool is designed for exploratory and educational purposes only. It does not offer financial advice or trading recommendations. Past performance is not indicative of future results.
Always consult a licensed financial advisor before making investment decisions.
OBV with MA & Bollinger Bands by Marius1032OBV with MA & Bollinger Bands by Marius1032
This script adds customizable moving averages and Bollinger Bands to the classic OBV (On Balance Volume) indicator. It helps identify volume-driven momentum and trend strength.
Features:
OBV-based trend tracking
Optional smoothing: SMA, EMA, RMA, WMA, VWMA
Optional Bollinger Bands with SMA
Potential Combinations and Trading Strategies:
Breakouts: Look for price breakouts from the Bollinger Bands, and confirm with a rising OBV for an uptrend or falling OBV for a downtrend.
Trend Reversals: When the price touches a Bollinger Band, examine the OBV for divergence. A bullish divergence (price lower low, OBV higher low) near the lower band could signal a reversal.
Volume Confirmation: Use OBV to confirm the strength of the trend indicated by Bollinger Bands. For example, if the BBs indicate an uptrend and OBV is also rising, it reinforces the bullish signal.
1. On-Balance Volume (OBV):
Purpose: OBV is a momentum indicator that uses volume flow to predict price movements.
Calculation: Volume is added on up days and subtracted on down days.
Interpretation: Rising OBV suggests potential upward price movement. Falling OBV suggests potential lower prices.
Divergence: Divergence between OBV and price can signal potential trend reversals.
2. Moving Average (MA):
Purpose: Moving Averages smooth price fluctuations and help identify trends.
Combination with OBV: Pairing OBV with MAs helps confirm trends and identify potential reversals. A crossover of the OBV line and its MA can signal a trend reversal or continuation.
3. Bollinger Bands (BB):
Purpose: BBs measure market volatility and help identify potential breakouts and trend reversals.
Structure: They consist of a moving average (typically 20-period) and two standard deviation bands.
Combination with OBV: Combining BBs with OBV allows for a multifaceted approach to market analysis. For example, a stock hitting the lower BB with a rising OBV could indicate accumulation and a potential upward reversal.
Created by: Marius1032
Flux Capacitor (FC)# Flux Capacitor
**A volume-weighted, outlier-resistant momentum oscillator designed to expose hidden directional pressure from institutional participants.**
---
### Why "Flux Capacitor"?
The name pays homage to the fictional energy core in *Back to the Future* — an invisible engine that powers movement. Similarly, this indicator detects whether price movement is being powered by real market participation (volume) or if it's coasting without conviction.
---
### Methodology
The Flux Capacitor fuses three statistical layers:
- **Normalized Momentum**: `(Close – Open) / ATR`
Controls for raw price size and volatility.
- **Volume Scaling**:
Amplifies the effect of price moves that occur with elevated volume.
- **Robust Normalization**:
- *Winsorization* caps outlier spikes.
- *MAD-Z scoring* normalizes the signal across assets (crypto, futures, stocks).
- This produces consistent scaling across timeframes and symbols.
The result is a smooth oscillator that reliably indicates **liquidity-backed momentum** — not just price movement.
---
### Signal Events
- **Divergence (D)**: Price makes higher highs or lower lows, but Flux does not.
- **Absorption (A)**: Candle shows high volume and small body, while Flux opposes the candle direction — indicates smart money stepping in.
- **Compression (◆)**: High volume with low momentum — potential breakout zone.
- **Zero-Cross**: Indicates directional regime flip.
- **Flux Acceleration**: Histogram shows pressure rate of change.
- **Regime Background**: Color fades with weakening trend conviction.
All signals are color-coded and visually compact for easy pattern recognition.
---
### Interpreting Divergence & Absorption Correctly
Signal strength improves significantly when it appears **in the correct zone**:
#### Divergence:
| Signal | Zone | Meaning | Strength |
|--------|------------|------------------------------------------|--------------|
| Green D | Below 0 | Bullish reversal forming in weakness | **Strong** |
| Green D | Above 0 | Bullish, but less convincing | Moderate |
| Red D | Above 0 | Bearish reversal forming in strength | **Strong** |
| Red D | Below 0 | Bearish continuation — low warning value | Weak |
#### Absorption:
| Signal | Zone | Meaning | Strength |
|--------|------------|-----------------------------------------|--------------|
| Green A | Below 0 | Buyers absorbing panic-selling | **Strong** |
| Green A | Above 0 | Support continuation | Moderate |
| Red A | Above 0 | Sellers absorbing FOMO buying | **Strong** |
| Red A | Below 0 | Trend continuation — not actionable | Weak |
Look for **absorption or divergence signals in “enemy territory”** for the most actionable entries.
---
### Reducing Visual Footprint
If your chart shows a long line of numbers across the top of the Flux Capacitor pane (e.g. "FC 14 20 9 ... Bottom Right"), it’s due to TradingView’s *status line input display*.
**To fix this**:
Right-click the indicator pane → **Settings** → **Status Line** tab → uncheck “Show Indicator Arguments”.
This frees up vertical space so top-edge signals (like red `D` or yellow `◆`) remain visible and unobstructed.
---
### Features
- Original MAD-Z based momentum design
- True volume-based divergence and absorption logic
- Built-in alerts for all signal types
- Works across timeframes (1-min to weekly)
- Minimalist, responsive layout
- 25+ customizable parameters
- No future leaks, no repainting
---
### Usage Scenarios
- **Trend confirmation**: Flux > 0 confirms bullish trend strength
- **Reversal detection**: Divergence or absorption in opposite territory = high-probability reversal
- **Breakout anticipation**: Compression signal inside range often precedes directional move
- **Momentum shifts**: Watch for zero-crosses + flux acceleration spikes
---
### ⚠ Visual Note for BTC, ETH, Crude Oil & Futures
These high-priced or rapidly accelerating instruments can visually compress any linear oscillator. You may notice the Flux Capacitor’s line appears "flat" or muted on these assets — especially over long lookbacks.
> **This does not affect signal validity.** Divergence, absorption, and compression triggers still fire based on underlying logic — only the line’s amplitude appears reduced due to scaling constraints.
---
### Disclaimer
This indicator is for educational purposes only. It is not trading advice. Past results do not guarantee future performance. Use in combination with your own risk management and analysis.
ATR-Multiple from 50SMAThis indicator provides a nuanced view of price extension by calculating the distance between the current price and its 50-period Simple Moving Average. This distance is not measured in simple percentage terms but is quantified in multiples of the Average True Range (ATR), offering a volatility-adjusted perspective on how far an asset has moved from its mean.
The primary goal is to help traders identify potentially overextended conditions, which can often precede price consolidation or reversals. As a general guideline, when an asset's price stretches to multiples of 7 ATRs or more above its 50-day SMA, it often enters a zone where significant profit-taking may occur. By visualizing this extension, the indicator can serve as a powerful tool for gauging when to consider taking profits on existing long positions. Furthermore, it can act as a cautionary signal, helping traders avoid initiating new long positions in assets that are already significantly stretched and may be poised for a pullback.
Features
Volatility-Adjusted Extension
Measures the distance from the 50 SMA in terms of ATR multiples, providing a more standardized way to compare extension across different assets and time periods.
Daily Timeframe Consistency
By default, the indicator uses the daily SMA and ATR for its calculations, regardless of the chart's current timeframe. This ensures a consistent and meaningful measure of extension rooted in the daily trend.
Histogram Visualization
Displays the result as a clear histogram in a separate pane, making it easy to track the extension level over time and identify historical extremes.
Dynamic Color-Coding
The histogram bars are color-coded to visually highlight different levels of extension. The colors shift as the price moves further from the mean, providing an intuitive at-a-glance reading.
Key Threshold Markers
Includes pre-set horizontal lines at the 7 and 10 ATR multiples to clearly mark the zones of potential profit-taking and extreme extension, respectively.
Built-in Alerts
Comes with configurable alert conditions that can notify you when the price reaches the "profit-taking" threshold (7 ATRs) or the "extreme extension" threshold (10 ATRs).
Customization Options
MA & ATR Periods
You can adjust the length for the Simple Moving Average (default 50) and the Average True Range (default 14) to suit your specific analytical needs.
Timeframe Source
A toggle allows you to switch between always calculating using daily data (the default and recommended setting) or using the data from the current chart's timeframe.
Color Display Style
You can choose between a smooth color gradient that transitions elegantly with the extension level or a distinct, step-based color display for a clearer visual separation of the defined zones.
Full Color Scheme Control
Every visual element is fully customizable. You can change the colors for the regular extension, the "get ready," "profit-taking," and "extreme" levels, as well as the horizontal reference lines.
HOG Liquidity HunterHOG Liquidity Hunter – Pivot‑Based Liquidity Zones
📌 Overview
Plots dynamic support and resistance zones on swing pivots with an ATR‑based buffer. Anchored only when pivots are confirmed, the zones stay close to current price levels—ideal for spotting liquidity runs or traps.
🔧 How It Works
Detects swing highs and lows using ta.pivothigh() / ta.pivotlow() with a user‑defined lookback.
After a pivot is confirmed, calculates BSL/SSL zone = pivot ± (ATR * margin).
Zones update only on confirmed pivots—no repainting on open bars.
⚙️ Inputs
Lookback: bars to confirm pivots (e.g. 10–20).
ATR Margin Multiplier: buffer width (e.g. 1.25).
✅ Benefits
Structure‑focused: Zones align with real swing points.
Responsive yet stable: Tight ATR margin keeps zones precise, only updating on valid pivots.
Clean visuals: Two uncluttered zones—easy to interpret.
🛠 How to Use
Detect near‑zone bounce entries or exits on 4H/1D charts.
Combine with trend or volume indicators for stronger setups.
Use zones to identify potential stop‑run, liquidity re‑tests, or range turns.
⚠️ Notes & Disclaimers
Zones base off historical pivots; may lag until confirmed.
No future-looking data—relying entirely on closing bar confirmation.
Use alongside a complete trading framework; this is not a standalone signal.
Squeeze Pro Momentum BAR color - KLTDescription:
The Squeeze Pro Momentum indicator is a powerful tool designed to detect volatility compression ("squeeze" zones) and visualize momentum shifts using a refined color-based system. This script blends the well-known concepts of Bollinger Bands and Keltner Channels with an optimized momentum engine that uses dynamic color gradients to reflect trend strength, direction, and volatility.
It’s built for traders who want early warning of potential breakouts and clearer insight into underlying market momentum.
🔍 How It Works:
📉 Squeeze Detection:
This indicator identifies "squeeze" conditions by comparing Bollinger Bands and Keltner Channels:
When Bollinger Bands are inside Keltner Channels → Squeeze is ON
When Bollinger Bands expand outside Keltner Channels → Squeeze is OFF
You’ll see squeeze zones classified as:
Wide
Normal
Narrow
Each represents varying levels of compression and breakout potential.
⚡ Momentum Engine:
Momentum is calculated using linear regression of the price's deviation from a dynamic average of highs, lows, and closes. This gives a more accurate representation of directional pressure in the market.
🧠 Smart Candle Coloring (Optimized):
The momentum color logic is inspired by machine learning principles (no hardcoded thresholds):
EMA smoothing and rate of change (ROC) are used to detect momentum acceleration.
ATR-based filters help remove noise and false signals.
Colors are dynamically assigned based on both direction and trend strength.
🧪 How to Use It:
Look for Squeeze Conditions — especially narrow squeezes, which tend to precede high-momentum breakouts.
Confirm with Momentum Color — strong colors often indicate trend continuation; fading colors may signal exhaustion.
Combine with Price Action — use this tool with support/resistance or patterns for higher probability setups.
Recommended For:
Trend Traders
Breakout Traders
Volatility Strategy Users
Anyone who wants visual clarity on trend strength
📌 Tip: This indicator works great when layered with volume and price action patterns. It is fully non-repainting and supports overlay on price charts.
Volatility Quality [Alpha Extract]The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
vqiRaw = ta.ema(weightedVol, vqiLen)
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
vqiStdev = ta.stdev(vqiSmoothed, vqiLen)
upperBand1 = vqiSmoothed + (vqiStdev * stdevMultiplier1)
upperBand2 = vqiSmoothed + (vqiStdev * stdevMultiplier2)
upperBand3 = vqiSmoothed + (vqiStdev * stdevMultiplier3)
lowerBand1 = vqiSmoothed - (vqiStdev * stdevMultiplier1)
lowerBand2 = vqiSmoothed - (vqiStdev * stdevMultiplier2)
lowerBand3 = vqiSmoothed - (vqiStdev * stdevMultiplier3)
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Fibonacci Entry Bands [AlgoAlpha]OVERVIEW
This script plots Fibonacci Entry Bands, a trend-following and mean-reversion hybrid system built around dynamic volatility-adjusted bands scaled using key Fibonacci levels. It calculates a smoothed basis line and overlays multiple bands at fixed Fibonacci multipliers of either ATR or standard deviation. Depending on the trend direction, specific upper or lower bands become active, offering a clear framework for entry timing, trend identification, and profit-taking zones.
CONCEPTS
The core idea is to use Fibonacci levels—0.618, 1.0, 1.618, and 2.618—as multipliers on a volatility measure to form layered price bands around a trend-following moving average. Trends are defined by whether the basis is rising or falling. The trend determines which side of the bands is emphasized: upper bands for downtrends, lower bands for uptrends. This approach captures both directional bias and extreme price extensions. Take-profit logic is built in via crossovers relative to the outermost bands, scaled by user-selected aggressiveness.
FEATURES
Basis Line – A double EMA smoothing of the source defines trend direction and acts as the central mean.
Volatility Bands – Four levels per side (based on selected ATR or stdev) mark the Fibonacci bands. These become visible only when trend direction matches the side (e.g., only lower bands plot in an uptrend).
Bar Coloring – Bars are shaded with adjustable transparency depending on distance from the basis, with color intensity helping gauge overextension.
Entry Arrows – A trend shift triggers either a long or short signal, with a marker at the outermost band with ▲/▼ signs.
Take-Profit Crosses – If price rejects near the outer band (based on aggressiveness setting), a cross appears marking potential profit-taking.
Bounce Signals – Minor pullbacks that respect the basis line are marked with triangle arrows, hinting at continuation setups.
Customization – Users can toggle bar coloring, signal markers, and select between ATR/stdev as well as take-profit aggressiveness.
Alerts – All major signals, including entries, take-profits, and bounces, are available as alert conditions.
USAGE
To use this tool, load it on your chart, adjust the inputs for volatility method and aggressiveness, and wait for entries to form on trend changes. Use TP crosses and bounce arrows as potential exit or scale-in signals.
SPX Weekly Expected Moves# SPX Weekly Expected Moves Indicator
A professional Pine Script indicator for TradingView that displays weekly expected move levels for SPX based on real options data, with integrated Fibonacci retracement analysis and intelligent alerting system.
## Overview
This indicator helps options and equity traders visualize weekly expected move ranges for the S&P 500 Index (SPX) by plotting historical and current week expected move boundaries derived from weekly options pricing. Unlike theoretical volatility calculations, this indicator uses actual market-based expected move data that you provide from options platforms.
## Key Features
### 📈 **Expected Move Visualization**
- **Historical Lines**: Display past weeks' expected moves with configurable history (10, 26, or 52 weeks)
- **Current Week Focus**: Highlighted current week with extended lines to present time
- **Friday Close Reference**: Orange baseline showing the previous Friday's close price
- **Timeframe Independent**: Works consistently across all chart timeframes (1m to 1D)
### 🎯 **Fibonacci Integration**
- **Five Fibonacci Levels**: 23.6%, 38.2%, 50%, 61.8%, 76.4% between Friday close and expected move boundaries
- **Color-Coded Levels**:
- Red: 23.6% & 76.4% (outer levels)
- Blue: 38.2% & 61.8% (golden ratio levels)
- Black: 50% (midpoint - most critical level)
- **Current Week Only**: Fibonacci levels shown only for active trading week to reduce clutter
### 📊 **Real-Time Information Table**
- **Current SPX Price**: Live market price
- **Expected Move**: ±EM value for current week
- **Previous Close**: Friday close price (baseline for calculations)
- **100% EM Levels**: Exact upper and lower boundary prices
- **Current Location**: Real-time position within the EM structure (e.g., "Above 38.2% Fib (upper zone)")
### 🚨 **Intelligent Alert System**
- **Zone-Aware Alerts**: Separate alerts for upper and lower zones
- **Key Level Breaches**: Alerts for 23.6% and 76.4% Fibonacci level crossings
- **Bar Close Based**: Alerts trigger on confirmed bar closes, not tick-by-tick
- **Customizable**: Enable/disable alerts through settings
## How It Works
### Data Input Method
The indicator uses a **manual data entry approach** where you input actual expected move values obtained from options platforms:
```pinescript
// Add entries using the options expiration Friday date
map.put(expected_moves, 20250613, 91.244) // Week ending June 13, 2025
map.put(expected_moves, 20250620, 95.150) // Week ending June 20, 2025
```
### Weekly Structure
- **Monday 9:30 AM ET**: Week begins
- **Friday 4:00 PM ET**: Week ends
- **Lines Extend**: From Monday open to Friday close (historical) or current time + 5 bars (current week)
- **Timezone Handling**: Uses "America/New_York" for proper DST handling
### Calculation Logic
1. **Base Price**: Previous Friday's SPX close price
2. **Expected Move**: Market-derived ±EM value from weekly options
3. **Upper Boundary**: Friday Close + Expected Move
4. **Lower Boundary**: Friday Close - Expected Move
5. **Fibonacci Levels**: Proportional levels between Friday close and EM boundaries
## Setup Instructions
### 1. Data Collection
Obtain weekly expected move values from options platforms such as:
- **ThinkOrSwim**: Use thinkBack feature to look up weekly expected moves
- **Tastyworks**: Check weekly options expected move data
- **CBOE**: Reference SPX weekly options data
- **Manual Calculation**: (ATM Call Premium + ATM Put Premium) × 0.85
### 2. Data Entry
After each Friday close, update the indicator with the next week's expected move:
```pinescript
// Example: On Friday June 7, 2025, add data for week ending June 13
map.put(expected_moves, 20250613, 91.244) // Actual EM value from your platform
```
### 3. Configuration
Customize the indicator through the settings panel:
#### Visual Settings
- **Show Current Week EM**: Toggle current week display
- **Show Past Weeks**: Toggle historical weeks display
- **Max Weeks History**: Choose 10, 26, or 52 weeks of history
- **Show Fibonacci Levels**: Toggle Fibonacci retracement levels
- **Label Controls**: Customize which labels to display
#### Colors
- **Current Week EM**: Default yellow for active week
- **Past Weeks EM**: Default gray for historical weeks
- **Friday Close**: Default orange for baseline
- **Fibonacci Levels**: Customizable colors for each level type
#### Alerts
- **Enable EM Breach Alerts**: Master toggle for all alerts
- **Specific Alerts**: Four alert types for Fibonacci level breaches
## Trading Applications
### Options Trading
- **Straddle/Strangle Positioning**: Visualize breakeven levels for neutral strategies
- **Directional Plays**: Assess probability of reaching target levels
- **Earnings Plays**: Compare actual vs. expected move outcomes
### Equity Trading
- **Support/Resistance**: Use EM boundaries and Fibonacci levels as key levels
- **Breakout Trading**: Monitor for moves beyond expected ranges
- **Mean Reversion**: Look for reversals at extreme Fibonacci levels
### Risk Management
- **Position Sizing**: Gauge likely price ranges for the week
- **Stop Placement**: Use Fibonacci levels for logical stop locations
- **Profit Targets**: Set targets based on EM structure probabilities
## Technical Implementation
### Performance Features
- **Memory Managed**: Configurable history limits prevent memory issues
- **Timeframe Independent**: Uses timestamp-based calculations for consistency
- **Object Management**: Automatic cleanup of drawing objects prevents duplicates
- **Error Handling**: Robust bounds checking and NA value handling
### Pine Script Best Practices
- **v6 Compliance**: Uses latest Pine Script version features
- **User Defined Types**: Structured data management with WeeklyEM type
- **Efficient Drawing**: Smart line/label creation and deletion
- **Professional Standards**: Clean code organization and comprehensive documentation
## Customization Guide
### Adding New Weeks
```pinescript
// Add after market close each Friday
map.put(expected_moves, YYYYMMDD, EM_VALUE)
```
### Color Schemes
Customize colors for different trading styles:
- **Dark Theme**: Use bright colors for visibility
- **Light Theme**: Use contrasting dark colors
- **Minimalist**: Use single color with transparency
### Label Management
Control label density:
- **Show Current Week Labels Only**: Reduce clutter for active trading
- **Show All Labels**: Full information for analysis
- **Selective Display**: Choose specific label types
## Troubleshooting
### Common Issues
1. **No Lines Appearing**: Check that expected move data is entered for current/recent weeks
2. **Wrong Time Display**: Ensure "America/New_York" timezone is properly handled
3. **Duplicate Lines**: Restart indicator if drawing objects appear duplicated
4. **Missing Fibonacci Levels**: Verify "Show Fibonacci Levels" is enabled
### Data Validation
- **Expected Move Format**: Use positive numbers (e.g., 91.244, not ±91.244)
- **Date Format**: Use YYYYMMDD format (e.g., 20250613)
- **Reasonable Values**: Verify EM values are realistic (typically 50-200 for SPX)
## Version History
### Current Version
- **Pine Script v6**: Latest version compatibility
- **Fibonacci Integration**: Five-level retracement analysis
- **Zone-Aware Alerts**: Upper/lower zone differentiation
- **Dynamic Line Management**: Smart current week extension
- **Professional UI**: Comprehensive information table
### Future Enhancements
- **Multiple Symbols**: Extend beyond SPX to other indices
- **Automated Data**: Integration with options data APIs
- **Statistical Analysis**: Success rate tracking for EM predictions
- **Additional Levels**: Custom percentage levels beyond Fibonacci
## License & Usage
This indicator is designed for educational and trading purposes. Users are responsible for:
- **Data Accuracy**: Ensuring correct expected move values
- **Risk Management**: Proper position sizing and risk controls
- **Market Understanding**: Comprehending options-based expected move concepts
## Support
For questions, issues, or feature requests related to this indicator, please refer to the code comments and documentation within the Pine Script file.
---
**Disclaimer**: This indicator is for informational purposes only. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
Multi TF Oscillators Screener [TradingFinder] RSI / ATR / Stoch🔵 Introduction
The oscillator screener is designed to simplify multi-timeframe analysis by allowing traders and analysts to monitor one or multiple symbols across their preferred timeframes—all at the same time. Users can track a single symbol through various timeframes simultaneously or follow multiple symbols in selected intervals. This flexibility makes the tool highly effective for analyzing diverse markets concurrently.
At the core of this screener lie two essential oscillators: RSI (Relative Strength Index) and the Stochastic Oscillator. The RSI measures the speed and magnitude of recent price movements and helps identify overbought or oversold conditions.
It's one of the most reliable indicators for spotting potential reversals. The Stochastic Oscillator, on the other hand, compares the current price to recent highs and lows to detect momentum strength and potential trend shifts. It’s especially effective in identifying divergences and short-term reversal signals.
In addition to these two primary indicators, the screener also displays helpful supplementary data such as the dominant candlestick type (Bullish, Bearish, or Doji), market volatility indicators like ATR and TR, and the four key OHLC prices (Open, High, Low, Close) for each symbol and timeframe. This combination of data gives users a comprehensive technical view and allows for quick, side-by-side comparison of symbols and timeframes.
🔵 How to Use
This tool is built for users who want to view the behavior of a single symbol across several timeframes simultaneously. Instead of jumping between charts, users can quickly grasp the state of a symbol like gold or Bitcoin across the 15-minute, 1-hour, and daily timeframes at a glance. This is particularly useful for traders who rely on multi-timeframe confirmation to strengthen their analysis and decision-making.
The tool also supports simultaneous monitoring of multiple symbols. Users can select and track various assets based on the timeframes that matter most to them. For example, if you’re looking for entry opportunities, the screener allows you to compare setups across several markets side by side—making it easier to choose the most favorable trade. Whether you’re a scalper focused on low timeframes or a swing trader using higher ones, the tool adapts to your workflow.
The screener utilizes the widely-used RSI indicator, which ranges from 0 to 100 and highlights market exhaustion levels. Readings above 70 typically indicate potential pullbacks, while values below 30 may suggest bullish reversals. Viewing RSI across timeframes can reveal meaningful divergences or alignments that improve signal quality.
Another key indicator in the screener is the Stochastic Oscillator, which analyzes the closing price relative to its recent high-low range. When the %K and %D lines converge and cross within the overbought or oversold zones, it often signals a momentum reversal. This oscillator is especially responsive in lower timeframes, making it ideal for spotting quick entries or exits.
Beyond these oscillators, the table includes other valuable data such as candlestick type (bullish, bearish, or doji), volatility measures like ATR and TR, and complete OHLC pricing. This layered approach helps users understand both market momentum and structure at a glance.
Ultimately, this screener allows analysts and traders to gain a full market overview with just one look—empowering faster, more informed, and lower-risk decision-making. It not only saves time but also enhances the precision and clarity of technical analysis.
🔵 Settings
🟣 Display Settings
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 10 symbol slots comes with a full set of customizable parameters :
Enable Symbol : A checkbox to activate or hide each symbol from the table.
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
RSI Length : Defines the period used in RSI calculation (default is 14).
Stochastic Length : Sets the period for the Stochastic Oscillator.
ATR Length : Sets the length used to calculate the Average True Range, a key volatility metric.
🔵 Conclusion
By combining powerful oscillators like RSI and Stochastic with full customization over symbols and timeframes, this tool provides a fast, flexible solution for technical analysts. Users can instantly monitor one or several assets across multiple timeframes without opening separate charts.
Individual configuration for each symbol, along with the inclusion of key metrics like candlestick type, ATR/TR, and OHLC prices, makes the tool suitable for a wide range of trading styles—from scalping to swing and position trading.
In summary, this screener enables traders to gain a clear, high-level view of various markets in seconds and make quicker, smarter, and lower-risk decisions. It saves time, streamlines analysis, and boosts overall efficiency and confidence in trading strategies.
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.
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.
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.
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.
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.
