TurboRSI Pro [JOAT]TurboRSI Pro - Multi-Length RSI Ensemble with Dynamic Momentum Analysis
Introduction
TurboRSI Pro is an open-source indicator that reimagines the classic RSI by calculating multiple RSI lengths simultaneously and combining them into a single, more reliable momentum reading. Instead of relying on a single RSI period that may lag or produce false signals, this indicator creates an ensemble of RSI values across a configurable range, providing a smoother and more robust momentum assessment.
The indicator is designed for traders who want deeper insight into momentum conditions without the noise that comes from single-period oscillators.
Originality and Purpose
This indicator is NOT a simple RSI with different settings. It is an original implementation that solves a fundamental problem with traditional RSI:
The Problem with Single-Period RSI: Traditional RSI uses a single lookback period (typically 14). The issue is that different market conditions favor different RSI lengths. A 14-period RSI might work well in one market phase but produce false signals in another. There's no "perfect" RSI length that works in all conditions.
The Multi-Length Solution: TurboRSI Pro calculates RSI across a range of lengths (default: 10 to 20) simultaneously, then averages all values to create a composite reading. This ensemble approach filters out period-specific noise while preserving genuine momentum shifts. When multiple RSI lengths agree, the signal is more reliable.
OB/OS Strength Percentage: The indicator tracks how many individual RSI lengths are in overbought or oversold territory. When 100% of lengths are overbought, it's a much stronger signal than when only 50% are. This percentage-based approach is original to this indicator and provides conviction assessment.
Candle Heatmap Innovation: An optional feature colors price bars based on deviation from a 200-bar linear regression line. This shows when price is statistically overextended (HOT/COLD) independent of RSI, providing another layer of analysis.
How the components work together:
Multi-length RSI ensemble provides a more robust momentum reading than single-period RSI
OB/OS Strength percentages quantify how many timeframes agree on the momentum condition
Dynamic channels expand/contract based on momentum strength across all calculated lengths
Candle heatmap adds statistical price deviation context independent of RSI
Core Concept: Multi-Length RSI Ensemble
Traditional RSI uses a single lookback period (typically 14). The problem is that different market conditions favor different RSI lengths. TurboRSI Pro solves this by:
Calculating RSI across a range of lengths (default: 10 to 20)
Averaging all RSI values to create a composite reading
Tracking how many individual RSI lengths are in overbought or oversold territory
Displaying this information as "OB Strength" and "OS Strength" percentages
This approach filters out noise while preserving genuine momentum shifts.
How the Multi-Length RSI Works
The calculation uses an efficient array-based approach:
int N = maxLength - minLength + 1
float diff = nz(srcInput - srcInput )
for i = 0 to N - 1
int len = minLength + i
float alpha = 1.0 / len
float numRma = alpha * diff + (1 - alpha) * array.get(numArr, i)
float denRma = alpha * math.abs(diff) + (1 - alpha) * array.get(denArr, i)
float rsiVal = denRma != 0 ? 50 * numRma / denRma + 50 : 50
avgRSI += rsiVal
Each RSI length is calculated using the RMA (Running Moving Average) formula, then all values are averaged. The result is a composite RSI that responds to momentum changes while filtering out period-specific noise.
Visual Components
1. Multi-Length RSI Line
The main oscillator line displays the averaged RSI value with a gradient color:
Green gradient when RSI is above 50 (bullish momentum)
Red gradient when RSI is below 50 (bearish momentum)
Color intensity increases as RSI approaches extreme levels
2. Dynamic Channels
Two adaptive channel lines track momentum extremes:
Upper Channel: Expands when multiple RSI lengths enter overbought territory
Lower Channel: Expands when multiple RSI lengths enter oversold territory
Channel width indicates momentum strength across all calculated lengths
3. Candle Heatmap
An optional feature that colors price bars based on deviation from a linear regression line:
Red/Orange bars: Price is significantly above the regression line (overextended to upside)
Blue bars: Price is significantly below the regression line (overextended to downside)
Yellow bars: Price is near the regression line (neutral)
The heatmap uses a 200-bar regression calculation to identify when price has deviated significantly from its statistical trend.
4. Reference Lines
Standard RSI reference levels are displayed:
80 and 20: Extreme overbought/oversold
70 and 30: Standard overbought/oversold thresholds
50: Neutral momentum line
5. Background Zones
Shaded areas indicate the percentage of RSI lengths in extreme territory:
Green shading from bottom: Percentage of lengths in overbought
Red shading from top: Percentage of lengths in oversold
Dashboard Panel
The dashboard displays real-time analysis in a 7-row table:
RSI Value: Current composite RSI reading (large text for visibility)
Momentum: Current state - OVERBOUGHT, OVERSOLD, BULLISH, BEARISH, or NEUTRAL
OB Strength: Percentage of RSI lengths currently above the overbought threshold
OS Strength: Percentage of RSI lengths currently below the oversold threshold
Heat Level: Current price deviation state - HOT, WARM, NEUTRAL, COOL, or COLD
Trend Bias: Overall trend assessment based on RSI level and channel direction
Optional Stochastic RSI
When enabled, an additional Stochastic RSI line is plotted. This applies the stochastic formula to the RSI itself, providing another layer of momentum analysis. The Stochastic RSI is more sensitive to short-term momentum shifts.
Input Parameters
RSI Settings:
Min RSI Length: Starting length for the RSI range (default: 10)
Max RSI Length: Ending length for the RSI range (default: 20)
Source: Price source for calculation (default: ohlc4)
Overbought: Upper threshold (default: 70)
Oversold: Lower threshold (default: 30)
Candle Heatmap:
Enable Heatmap: Toggle bar coloring on/off (default: enabled)
Regression Length: Lookback for linear regression calculation (default: 200)
Display:
Show Dashboard: Toggle the information panel (default: enabled)
Show Dynamic Channels: Toggle channel lines (default: enabled)
Show Stochastic RSI: Toggle additional Stoch RSI line (default: disabled)
Colors:
Bullish: Color for bullish conditions (default: teal)
Bearish: Color for bearish conditions (default: red)
Neutral: Color for neutral conditions (default: gray)
How to Use TurboRSI Pro
Identifying Momentum Shifts:
Watch for RSI crossing above 50 for bullish momentum confirmation
Watch for RSI crossing below 50 for bearish momentum confirmation
Use the gradient color to quickly assess momentum direction
Using OB/OS Strength:
When OB Strength reaches 100%, all RSI lengths are overbought - strong reversal potential
When OS Strength reaches 100%, all RSI lengths are oversold - strong bounce potential
Partial readings (e.g., 50%) indicate mixed conditions across timeframes
Heatmap Analysis:
HOT readings combined with high RSI suggest overextension - caution for longs
COLD readings combined with low RSI suggest oversold conditions - watch for reversal
Use heatmap divergence from RSI for additional confirmation
Channel Interpretation:
Expanding upper channel with rising RSI confirms strong bullish momentum
Expanding lower channel with falling RSI confirms strong bearish momentum
Channel contraction suggests momentum is weakening
Alert Conditions
Six alert conditions are available:
RSI Overbought: RSI crosses above overbought threshold
RSI Oversold: RSI crosses below oversold threshold
RSI Bullish Cross: RSI crosses above 50
RSI Bearish Cross: RSI crosses below 50
All RSI Overbought: Every RSI length is in overbought territory
All RSI Oversold: Every RSI length is in oversold territory
Best Practices
Use on higher timeframes (1H, 4H, Daily) for more reliable signals
Combine with price action analysis - RSI confirms, it does not predict
Pay attention to OB/OS Strength percentages for conviction assessment
The heatmap works best on assets with clear trending behavior
Adjust min/max RSI lengths based on your trading style - wider range for smoother signals
Limitations
Like all oscillators, can remain in overbought/oversold territory during strong trends
The heatmap regression may lag during rapid price movements
Multi-length calculation requires more processing than single RSI
Best suited for swing trading and position trading timeframes
Technical Notes
This indicator is written in Pine Script v6 and uses:
Array-based calculations for efficient multi-length RSI computation
Linear regression for heatmap deviation analysis
Gradient coloring for intuitive visual feedback
State management for dynamic channel calculations
The source code is open and available for review and modification.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management.
-Made with passion by officialjackofalltrades
在脚本中搜索"heatmap"
Aggregated Open Interest [Alpha Extract]The Aggregated Open Interest indicator provides a comprehensive view of open interest across multiple cryptocurrency exchanges, allowing traders to monitor institutional positioning and market sentiment. By aggregating data from major exchanges like Binance, BitMEX, and Kraken, this indicator offers valuable insights into potential price movements and market shifts.
🔶 CALCULATION
The indicator processes open interest data through multiple analytical methods:
Exchange Aggregation: Collects and normalizes open interest data from multiple exchanges (Binance, BitMEX, Kraken) with proper currency normalization.
Multi-Mode Analysis: Calculates various metrics including raw open interest values, OI change, OI delta, volume-weighted delta, and OI RSI.
Divergence Detection: Uses pivot point analysis to identify divergences between price action and open interest movements.
Activity Assessment: Tracks bullish and bearish activity patterns by correlating open interest changes with price movements.
Formula:
Aggregate OI = Sum of normalized open interest from selected exchanges
OI Change = Current OI - Previous OI
OI Delta = Net change in open interest across timeframes
OI Delta × Volume = OI Delta weighted by relative volume
OI RSI = Relative Strength Index applied to open interest values
OI Heatmap = Multi-timeframe visualization of OI changes across 7 distinct periods
🔶 DETAILS
Visual Features:
Open Interest: Candlestick representation of aggregated open interest
OI Change: Histogram showing period-to-period changes
OI Delta: Histogram displaying net OI movements
OI Delta × Volume: Volume-weighted OI delta for enhanced signals
OI RSI: Oscillator showing overbought/oversold OI conditions
OI Heatmap: Multi-timeframe visualization showing OI changes across 7 periods (3, 5, 8, 13, 21, 34, and 55 days)
Divergence Detection: Color-coded markers (teal for bullish, red for bearish) highlighting significant divergences between price and open interest
Analysis Table: Real-time summary of key metrics including aggregate OI, recent changes, and bullish/bearish activity.
Interpretation:
Increasing Open Interest + Rising Price: Strong bullish trend confirmation
Increasing Open Interest + Falling Price: Strong bearish trend confirmation
Decreasing Open Interest + Rising Price: Weak bullish trend (potential reversal)
Decreasing Open Interest + Falling Price: Weak bearish trend (potential reversal)
Divergences: Signal potential trend exhaustion and reversals when price moves in one direction while open interest moves in the opposite direction
Heatmap: Provides at-a-glance insight into open interest trends across multiple timeframes, with green bars indicating rising OI and red bars indicating falling OI
🔶 EXAMPLES
Trend Confirmation: Rising open interest accompanying a price increase confirms strong bullish momentum with institutional backing.
Example: During January-February 2025, rising OI during price advances confirms institutional participation in the uptrend.
Bearish Divergence: Price makes a higher high while open interest makes a lower high, signaling potential trend reversal.
Example: Red markers appear at market tops where price continues higher but open interest fails to confirm, preceding significant corrections.
Bullish Divergence : Price makes a lower low while open interest makes a higher low, indicating potential bottoming.
Example: Teal markers appear at market bottoms where price continues lower but open interest fails to confirm, preceding significant rallies.
OI Heatmap Analysis : Multiple timeframes showing consistent red signals across short to long-term periods indicate strong institutional selling pressure.
Example: When all 7 periods (3-55 days) show red during a price uptrend, this signals institutional selling into retail strength, often preceding major corrections.
🔶 SETTINGS
Customization Options:
Data Sources: Toggle different exchanges (Binance USDT/USD/BUSD, BitMEX USD/USDT, Kraken USD)
Display Mode: Choose between Open Interest, OI Change, OI Delta, OI Delta × Volume, OI RSI, and OI Heatmap
Currency Units: Display in USD or base cryptocurrency (COIN)
Analysis Tools: Moving Average (length and color), RSI (length and color)
Divergence Detection: Enable/disable signals, adjust lookback period and threshold percentage, customize bullish/bearish divergence colors
OI Heatmap Colors: Customize bullish (green) and bearish (red) signal colors for the multi-timeframe heatmap visualization
The Aggregated Open Interest indicator provides traders with comprehensive insights into institutional positioning across major exchanges, helping identify potential trend continuations, reversals, and key market turning points driven by smart money movements. The addition of the OI Heatmap feature enables traders to quickly visualize open interest trends across multiple timeframes, providing valuable context for institutional positioning over different market cycles.
Normalized Fisher Transformed VolumeGreetings Traders,
I am thrilled to introduce a game-changing tool that I've passionately developed to enhance your trading precision – the Normalized Fisher Transformed Volume indicator. Let's dive into the specifics and explore how this tool can empower you in the markets.
Unlocking Trading Precision:
Normalization and Transformation:
Normalize raw volume data to ensure a consistent scale for analysis.
The Fisher Transformation converts normalized volume data into a Gaussian distribution, providing enhanced insights into trend dynamics.
Flexible Modes for Tailored Strategies:
Choose from three distinct modes:
Volume T3 (MA) + Heatmap: Identify trends with T3 Moving Average and visualize volume strength with Heatmap.
Volume Percent Rank: Evaluate the position of current volume relative to historical data.
Volume T3 (MA) Percent Rank: Combine T3 Moving Average with percentile ranking for a comprehensive analysis.
Heatmap Visualization for Quick Insights:
Heatmap Zones and Lines visually represent volume strength relative to historical data.
Customize threshold multipliers and color options for precise Heatmap interpretation.
T3 Moving Average Integration:
Smoothed representation of volume trends with the T3 Moving Average enhances trend identification.
Percent Rank Analysis for Context:
Gauge the position of normalized volume within historical context using Percent Rank analysis.
User-Friendly Customization:
Easily adjust parameters such as length, T3 Moving Average length, Heatmap standard deviation length, and threshold multipliers.
Intuitive interface with colored bars and customizable background options for personalized analysis.
How to Use Effectively:
Mode Selection:
Identify your preferred trading strategy and select the mode that aligns with your approach.
Parameter Adjustment:
Fine-tune the indicator by adjusting parameters to match your preferred trading style.
Interpret Heatmap and T3 Analysis:
Leverage Heatmap and T3 Moving Average analysis to spot potential trend reversals, overbought/oversold conditions, and market sentiment shifts.
Conclusion:
The Normalized Fisher Transformed Volume indicator is not just a tool; it's your key to unlocking precision in trading. Crafted by Simwai, this indicator offers unique insights tailored to your specific trading needs. Dive in, explore its features, experiment with parameters, and let it guide you to more informed and precise trading decisions.
Trade wisely and prosper,
simwai
Osmosis [ChartPrime]Osmosis is a multi indicator, multi period heatmap. Lookback periods can be mysterious as it can tend to seem very arbitrary. This tool allows users to see how price/volume reacts to short to long periods by visualizing all of the periods at the same time. This is useful because small periods are only good for short term movements while long periods are useful for long term movements. This more detailed view of market trends is analogues of multi time frame analysis. The lookback periods are arranged from bottom up, where the bottom of the indicator is the shortest period while the top is the longest period.
One major feature of this indicator is its ability to signal potential trend reversals. For example, a shift in the direction at the lower end of the heatmap can indicate a weakening of the current trend, suggesting a possible reversal. On the other hand, when the heatmap is fully saturated at all levels, it may indicate a strong trend that could be nearing a reversal point.
Another important and unique aspect of the Osmosis indicator is its automatic highlighting feature. This feature emphasizes regions within the heatmap that score exceptionally high or low, drawing attention to significant market movements or potential anomalies.
All of the indicators are normalized using min/max scaling driven by the highest highs and lows. The period of this scaling is adjustable by changing the "Lookback" parameter under settings. Delta length changes the lookback for "MA Delta" and "Volume Delta". A longer period corresponds to a smoother output. Fast Mode scales back the range of the indicator, literally halving the increment.
Here is a short description of what each input does:
Alternate Source: A choice to use a different data source for the indicator.
Source: An option to turn on or off the alternate data source.
Style: A selection menu to choose the visual style of the indicator.
Lookback: Adjusts how far back in time the indicator looks for its calculations.
Delta Length: Changes the length of time over which changes are measured.
Fast Mode: A setting that adjusts the range of the indicator for quicker analysis.
Enable Smoothing: A choice to smooth out the data for a cleaner look.
Smooth: Activates the smoothing feature.
Max Region: Highlights the highest value regions in the heatmap.
Max Threshold: Sets the threshold for what counts as a 'max' region.
Minimum Max Width: Determines the smallest size for a 'max' region to be highlighted.
Max Region Color: Chooses the color for the maximum value regions.
Max Top Line Alpha: Adjusts the transparency of the top line in max regions.
Max Bottom Line Alpha: Adjusts the transparency of the bottom line in max regions.
Line Width: Sets the thickness of the lines in the max regions.
Region Start Indication: Specifies where the max region starts.
Fill Max: Decides if the max regions should be filled with color and sets the transparency level for the color fill in max regions.
Minimum Region: Highlights the lowest value regions in the heatmap.
Minimum Threshold: Sets the threshold for what counts as a 'min' region.
Minimum Minimum Width: Determines the smallest size for a 'min' region to be highlighted.
Minimum Region Color: Chooses the color for the minimum value regions.
Minimum Top Line Alpha: Adjusts the transparency of the top line in min regions.
Minimum Bottom Line Alpha: Adjusts the transparency of the bottom line in min regions.
Minimum Line Width: Sets the thickness of the lines in the min regions.
Minimum Region Start Indication: Specifies where the min region starts.
Fill Minimum: Decides if the min regions should be filled with color and sets the transparency level for the color fill in min regions.
Color Presets: Provides pre-set color schemes.
Invert Color Scale: Flips the color scale.
Gradient Colors: Customizes individual colors for the gradient scale.
Available styles include:
'MACD Histogram'
'Normalized MACD'
'Slow MACD'
'MACD Percent Rank'
'MA Delta' (Delta Length set to 2)
'BB Width'
'BB Width Percentile'
'Stochastic'
'RSI'
'True Range OSC'
'Normalized Volume'
'Volume Delta'
'True Range'
'Rate of Change' (Smoothing set to 1)
'OBV' (Smoothing set to 1)
'MFI' (Smoothing set to 1)
'Trend Angle' (Smoothing set to 2 and fast mode off)
Relative Strength Heat [InvestorUnknown]The Relative Strength Heat (RSH) indicator is a relative strength of an asset across multiple RSI periods through a dynamic heatmap and provides smoothed signals for overbought and oversold conditions. The indicator is highly customizable, allowing traders to adjust RSI periods, smoothing methods, and visual settings to suit their trading strategies.
The RSH indicator is particularly useful for identifying momentum shifts and potential reversal points by aggregating RSI data across a range of periods. It presents this data in a visually intuitive heatmap, with color-coded bands indicating overbought (red), oversold (green), or neutral (gray) conditions. Additionally, it includes signal lines for overbought and oversold indices, which can be smoothed using RAW, SMA, or EMA methods, and a table displaying the current index values.
Features
Dynamic RSI Periods: Calculates RSI across 31 periods, starting from a user-defined base period and incrementing by a specified step.
Heatmap Visualization: Displays RSI strength as a color-coded heatmap, with red for overbought, green for oversold, and gray for neutral zones.
Customizable Smoothing: Offers RAW, SMA, or EMA smoothing for overbought and oversold signals.
Signal Lines: Plots scaled overbought (purple) and oversold (yellow) signal lines with a midline for reference.
Information Table: Displays real-time overbought and oversold index values in a table at the top-right of the chart.
User-Friendly Inputs: Allows customization of RSI source, period ranges, smoothing length, and colors.
How It Works
The RSH indicator aggregates RSI calculations across 31 periods, starting from the user-defined Starting Period and incrementing by the Period Increment. For each period, it computes the RSI and determines whether the asset is overbought (RSI > threshold_ob) or oversold (RSI < threshold_os). These states are stored in arrays (ob_array for overbought, os_array for oversold) and used to generate the following outputs:
Heatmap: The indicator plots 31 horizontal bands, each representing an RSI period. The color of each band is determined by the f_col function:
Red if the RSI for that period is overbought (>threshold_ob).
Green if the RSI is oversold (
7 EMA CloudThe "7 EMA Cloud" script was likely flagged because it reuses the core concept of EMA clouds (shading areas between multiple EMAs to visualize trends, support/resistance, and momentum) without crediting the original inventor, Ripster (author ripster47 on TradingView). This concept is prominently associated with Ripster's "EMA Clouds" indicator, which popularized filling spaces between EMA pairs for trading signals. TradingView's house rules require crediting authors when reusing open-source ideas or code, even if not a direct copy-paste, and mandate significant improvements where the original forms a small proportion of the script. Your version adds features like multiple color modes (Classic rainbow, Monochrome, Heatmap), customizable signal sizes, and crossover alerts between the first and last EMA, which are enhancements, but the foundational EMA ribbon/cloud idea needs explicit attribution in the description and ideally code comments to comply.
Additionally, the description might be seen as not fully self-contained (e.g., it uses promotional language like "Advanced" and "Adaptive Trend & Signal Suite" without deeply explaining calculations or use cases), potentially violating rules against relying on code or external references for clarity.
To fix this, republish a new version with proper credits, ensure the description is detailed and standalone, and emphasize your improvements (e.g., the 7 Fibonacci-based EMAs, color modes, and signals). Do not reuse the flagged script—create a fresh one. Here's a compliant description you can use:
7 EMA Cloud Indicator
Overview
The 7 EMA Cloud overlays seven exponential moving averages (EMAs) with Fibonacci-inspired periods and fills the spaces between them with customizable "clouds" to visually represent trend strength, direction, and convergence/divergence. It includes crossover signals between the shortest and longest EMAs for potential entry/exit points, with adjustable visual modes for different trading styles. This helps traders identify bullish/bearish momentum, support/resistance zones, and overextensions in trending or ranging markets.
This script builds on the EMA cloud concept popularized by Ripster (ripster47) in their "EMA Clouds" indicatortradingview.com, where areas between EMA pairs are shaded for trend analysis. Improvements include a fixed set of 7 Fibonacci EMAs, multiple color schemes (Classic rainbow, Monochrome grayscale, Heatmap for intensity), user-selectable signal sizes, and transparency controls. Released under the Mozilla Public License 2.0.
Key Features
7 EMAs with Clouds: EMAs at periods 8, 13, 21, 34, 55, 89, and 144; clouds filled between consecutive pairs to show alignment (tight clouds for consolidation, wide for trends).
Color Modes:
Classic: Rainbow gradients (blue to purple) for vibrant distinction.
Monochrome: Grayscale shades for minimalistic charts.
Heatmap: Red-to-blue spectrum to highlight "hot" (volatile) vs. "cool" (stable) areas.
Crossover Signals: Triangle markers (up for bullish, down for bearish) when the shortest EMA crosses the longest; sizes from Tiny to Huge.
Display Options: Toggle EMA lines on/off, adjust cloud transparency (0-100%), and enable alerts for crossovers.
Alerts: Notifications for "Bullish EMA Crossover" (EMA1 > EMA7) and "Bearish EMA Crossover" (EMA1 < EMA7).
How It Works
EMA Calculations: Each EMA is computed using ta.ema(close, period), with periods based on Fibonacci sequences for natural market rhythm alignment.
Clouds: Filled via fill() between plot pairs, with colors derived from the selected mode and transparency applied.
Signals: Detected with ta.crossover(ema1, ema7) and ta.crossunder(ema1, ema7), plotted as shapes with mode-specific colors (e.g., green/lime for bull, red for bear).
Customization: Inputs grouped into EMA Settings (periods), Display Settings (visibility, colors, transparency), and Signal Settings (size).
Customization Options
EMA Periods: Individually adjustable (defaults: 8, 13, 21, 34, 55, 89, 144).
Show EMAs: Toggle to hide lines and focus on clouds.
Cloud Transparency: 0% for solid fills, 100% for invisible (default 80%).
Color Mode: Switch between Classic, Monochrome, or Heatmap.
Signal Size: Tiny, Small, Normal, Large, or Huge for crossover markers.
Ideal Use Case
Suited for swing or trend-following on any timeframe (e.g., 15m-1h for intraday, daily for swings) and assets (stocks, forex, crypto, futures). Enter long on bullish crossovers above aligned clouds; exit on bearish signals or cloud widenings. Use Monochrome for clean charts or Heatmap for volatility emphasis. Combine with volume or RSI for confirmation.
Why It's Valuable
By expanding Ripster's EMA cloud idea with multi-mode visuals and integrated signals, this indicator provides a versatile, at-a-glance tool for trend assessment—reducing noise while highlighting key shifts. It's more adaptive than basic MA ribbons, with Fibonacci periods adding a layer of harmonic analysis.
Note: Test on historical data or demo accounts. Not financial advice—incorporate risk management. Optimized for Pine Script v5; some features may vary on non-overlay charts.
BTC - FRIC: Friction & Realized Intensity CompositeTitle: BTC - FRIC: Friction & Realized Intensity Composite
Data: IntoTheBlock
Overview & Philosophy
FRIC (Friction & Realized Intensity Composite) is a specialized on-chain oscillator designed to visualize the "psychological battlegrounds" of the Bitcoin network.
Most indicators focus on Price or Momentum. FRIC focuses on Cost Basis. It operates on the thesis that the market experiences maximum "Friction" when the price revisits the cost basis of a large number of holders. These are the zones where investors are emotionally triggered to react—either to exit "at breakeven" after a loss (creating resistance) or to defend their entry (creating support).
This indicator answers two questions simultaneously:
Intensity: Is the market hitting a Wall (High Friction) or a Vacuum (Low Friction)?
Valuation: Is this happening at a market bottom or a top?
The "Alpha" (Wall vs. Vacuum)
Why we visualize both extremes: This indicator filters out the "Noise" (the middle range) to show you only the statistically significant anomalies.
1. The "Wall" (Positive Z-Score Bars)
What it is : A statistically high number of addresses are at breakeven.
The Implication : Expect a grind. Price action often slows down or reverses here because "Bag Holders" are selling into strength to get out flat, or new buyers are establishing a floor.
2. The "Vacuum" (Negative Z-Score Bars)
What it is : A statistically low number of addresses are at breakeven.
The Implication : Expect acceleration. The price is moving through a zone where very few people have a cost basis. With no natural "breakeven supply" to block the path, price often enters Price Discovery or Free Fall.
Methodology
The indicator constructs a composite view using two premium metrics from IntoTheBlock:
1. The "Activity" (Friction Z-Score): We utilize the Breakeven Addresses Percentage. This measures the % of all addresses where the current price equals the average cost basis.
- Normalization: We apply a rolling Z-Score (Standard Deviation) to this data.
- The Filter: We hide the "Noise" (e.g., Z-Scores between -2.0 and +2.0) to isolate only the events where market structure is truly stretched.
2. The "Context" (Valuation Heatmap): We utilize the MVRV Ratio to color-code the friction.
Deep Value (< 1.0): Price is below the average "Fair Value" of the network.
Overheated (> 3.0): Price is significantly extended above the "Fair Value."
Credit: The MVRV Ratio was originally conceptualized by Murad Mahmudov and David Puell. It remains one of the gold standards for detecting Bitcoin's fair value deviations.
How to Read the Indicator
The chart is visualized as a Noise-Filtered Heatmap.
1. The Bars (Intensity)
Bars Above Zero: High Friction (Congestion). The market is fighting through a supply wall.
Bars Below Zero: Low Friction (Vacuum). The market is accelerating through thin air.
Gray/Ghosted: Noise. Routine market activity; no significant signal.
2. The Colors (Valuation Context) The color tells you why the friction is happening:
🟦 Deep Blue (The "Capitulation Buy"):
Signal: High Friction + Low MVRV.
Meaning : Investors are panic-selling at breakeven/loss, but the asset is fundamentally undervalued. Historically, these are high-conviction cycle bottoms.
🟥 Dark Red (The "FOMO Sell"):
Signal: High Friction + High MVRV.
Meaning : Investors are churning at high valuations. Smart money is often distributing to late retail arrivers. Historically marks cycle tops.
🟨 Yellow/Orange (The "Trend Battle"):
Signal: High Friction + Neutral MVRV.
Meaning : The market is contesting a level within a trend (e.g., a mid-cycle correction).
Visual Guide & Features
10-Zone Heatmap: A granular color gradient that shifts from Dark Blue (Deep Value) → Sky Blue → Grey (Neutral) → Orange → Dark Red (Top).
Noise Filter
A unique feature that "ghosts out" insignificant data, leaving only the statistically relevant signals visible.
Data Check Monitor
A diagnostic table in the bottom-right corner that confirms the live connection to IntoTheBlock data streams and displays the current regime in real-time.
Settings
Lookback Period (Default: 90): The rolling window used for the Z-Score calculation. Shortening this (e.g., to 30) makes the indicator more sensitive to local volatility; lengthening it (e.g., to 365) aligns it with macro cycles.
Noise Threshold (Default: 2.0): The strictness of the filter. Only friction events exceeding this Z-Score will be highlighted in full color.
Show Status Table : Toggles the on-screen dashboard.
Disclaimer
This script is for research and educational purposes only. It relies on third-party on-chain data which may be subject to latency or revision. Past performance of on-chain metrics does not guarantee future price action.
Tags
bitcoin, btc, on-chain, mvrv, intotheblock, friction, z-score, fundamental, valuation, cycle
Open Interest RSI [BackQuant]Open Interest RSI
A multi-venue open interest oscillator that aggregates OI across major derivatives exchanges, converts it to coin or USD terms, and runs an RSI-style engine on that aggregated OI so you can track positioning pressure, crowding, and mean reversion in leverage flows, not just in price.
What this is
This tool is an RSI built on top of aggregated open interest instead of price. It pulls futures OI from several major exchanges, converts it into a unified unit (COIN or USD), sums it into a single synthetic OI candle, then applies RSI and smoothing to that combined series.
You can then render that Open Interest RSI in different visual modes:
Clean line or colored line for classic oscillator-style reads.
Column-style oscillator for impulse and compression views.
Flag mode that fills between OI RSI and its EMA for trend/mean reversion blends. See:
Heatmap mode that paints the panel based on OI RSI extremes, ideal for scanning. See:
On top of that it includes:
Aggregated OI source selection (Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit).
Choice of OI units (COIN or USD).
Reference lines and OB/OS zones.
Extreme highlighting for either trend or mean reversion.
A vertical OI RSI meter that acts as a quick strength gauge.
Aggregated open interest source
Under the hood, the indicator builds a synthetic open interest candle by:
Looping over a list of supported exchanges: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Looping over multiple contract suffixes (such as USDT.P, USD.P, USDC.P, USD.PM) to capture different contract types on each venue.
Requesting OI candles from each venue + contract combination for the same underlying symbol.
Converting each OI stream into a common unit: In COIN mode, everything is normalized into coin-denominated OI. In USD mode, coin OI is multiplied by price to approximate notional OI.
Summing up open, high, low and close of OI across venues into a single aggregated OI candle.
If no valid OI is available for the current symbol across all sources, the script throws a clear runtime error so you know you are on an unsupported market.
This gives you a single, exchange-agnostic open interest curve instead of being tied to one venue. That aggregated OI is then passed into the RSI logic.
How the OI RSI is calculated
The RSI side is straightforward, but it is applied to the aggregated OI close:
Compute a base RSI of aggregated OI using the Calculation Period .
Apply a simple moving average of length Smoothing Period (SMA) to reduce noise in the raw OI RSI.
Optionally apply an EMA on top of the smoothed OI RSI as a moving average signal line.
Key parameters:
Calculation Period – base RSI length for OI.
Smoothing Period (SMA) – extra smoothing on the RSI value.
EMA Period – EMA length on the smoothed OI RSI.
The result is:
oi_rsi – raw RSI of aggregated OI.
oi_rsi_s – SMA-smoothed OI RSI.
ma – EMA of the smoothed OI RSI.
Thresholds and extremes
You control three core thresholds:
Mid Point – central reference level, typically 50.
Extreme Upper Threshold – high-level OI RSI edge (for example 80).
Extreme Lower Threshold – low-level OI RSI edge (for example 20).
These thresholds are used for:
Reference lines or OB/OS zone fills.
Heatmap gradient bounds.
Background highlighting of extremes.
The Extreme Highlighting mode controls how extremes are interpreted:
None – do nothing special in extreme regions.
Mean-Rev – background turns red on high OI RSI and green on low OI RSI, framing extremes as contrarian zones.
Trend – background turns green on high OI RSI and red on low OI RSI, framing extremes as participation zones aligned with the prevailing move.
Reference lines and OB/OS zones
You can choose:
None – clean plotting without guides.
Basic Reference Lines – mid, upper and lower thresholds as simple gray horizontals.
OB/OS Levels – filled zones between:
Upper OB: from the upper threshold to 100, colored with the short/overbought color.
Lower OS: from 0 to the lower threshold, colored with the long/oversold color.
These guides help visually anchor the OI RSI within "normal" versus "extreme" regions.
Plotting modes
The Plotting Type input controls how OI RSI is drawn. All modes share the same underlying OI and RSI logic, but emphasise different aspects of the signal.
1) Line mode
This is the classic oscillator representation:
Plots the smoothed OI RSI as a simple line using RSI Line Color and RSI Line Width .
Optionally plots the EMA overlay on the same panel.
Works well when you want standard RSI-style signals on leverage flows: crosses of the midline, divergences versus price, and so on.
2) Colored Line mode
In this mode:
The OI RSI is plotted as a line, but its color is dynamic.
If the smoothed OI RSI is above the mid point, it uses the Long/OB Color .
If it is below the mid point, it uses the Short/OS Color .
This creates an instant visual regime switch between "bullish positioning pressure" and "bearish positioning pressure", while retaining the feel of a traditional RSI line.
3) Oscillator mode
Oscillator mode renders OI RSI as vertical columns around the mid level:
The smoothed OI RSI is plotted as columns using plot.style_columns .
The histogram base is fixed at 50, so bars extend above and below the mid line.
Bar color is dynamic, using long or short colors depending on which side of the mid point the value sits.
This representation makes impulse and compression in OI flows more obvious. It is especially useful when you want to focus on how quickly OI RSI is expanding or contracting around its neutral level. See:
4) Flag mode
Flag mode turns OI RSI and its EMA into a two-line band with a filled area between them:
The smoothed OI RSI and its EMA are both plotted.
A fill is drawn between them.
The fill color flips between the long color and the short color depending on whether OI RSI is above or below its EMA.
Black outlines are added to both lines to make the band clear against any background.
This creates a "flag" style region where:
Green fills show OI RSI leading its EMA, suggesting positive positioning momentum.
Red fills show OI RSI trailing below its EMA, suggesting negative positioning momentum.
Crossovers of the two lines can be read as shifts in OI momentum regime.
Flag mode is useful if you want a more structural view that combines both the level and slope behaviour of OI RSI. See:
5) Heatmap mode
Heatmap mode recasts OI RSI as a single-row gradient instead of a line:
A single row at level 1 is plotted using column style.
The color is pulled from a gradient between the lower and upper thresholds: Near the lower threshold it approaches the short/oversold color and near the upper threshold it approaches the long/overbought color.
The EMA overlay and reference lines are disabled in this mode to keep the panel clean.
This is a very compact way to track OI RSI state at a glance, especially when stacking it alongside other indicators. See:
OI RSI vertical meter
Beyond the main plot, the script can draw a small "thermometer" table showing the current OI RSI position from 0 to 100:
The meter is a two-column table with a configurable number of rows.
Row colors form an inverted gradient: red at the top (100) and green at the bottom (0).
The script clamps OI RSI between 0 and 100 and maps it to a row index.
An arrow marker "▶" is drawn next to the row corresponding to the current OI RSI value.
0 and 100 labels are printed at the ends of the scale for orientation.
You control:
Show OI RSI Meter – turn the meter on or off.
OI RSI Blocks – number of vertical blocks (granularity).
OI RSI Meter Position – panel anchor (top/bottom, left/center/right).
The meter is particularly helpful if you keep the main plot in a small panel but still want an intuitive strength gauge.
How to read it as a market pressure gauge
Because this is an RSI built on aggregated open interest, its extremes and regimes speak to positioning pressure rather than price alone:
High OI RSI (near or above the upper threshold) indicates that open interest has been increasing aggressively relative to its recent history. This often coincides with crowded leverage and a buildup of directional pressure.
Low OI RSI (near or below the lower threshold) indicates aggressive de-leveraging or closing of positions, often associated with flushes, forced unwinds or post-liquidation clean-ups.
Values around the mid point indicate more balanced positioning flows.
You can combine this with price action:
Price up with rising OI RSI suggests fresh leverage joining the move, a more persistent trend.
Price up with falling OI RSI suggests shorts covering or longs taking profit, more fragile upside.
Price down with rising OI RSI suggests aggressive new shorts or levered selling.
Price down with falling OI RSI suggests de-leveraging and potential exhaustion of the move.
Trading applications
Trend confirmation on leverage flows
Use OI RSI to confirm or question a price trend:
In an uptrend, rising OI RSI with values above the mid point indicates supportive leverage flows.
In an uptrend, repeated failures to lift OI RSI above mid point or persistent weakness suggest less committed participation.
In a downtrend, strong OI RSI on the downside points to aggressive shorting.
Mean reversion in positioning
Use thresholds and the Mean-Rev highlight mode:
When OI RSI spends extended time above the upper threshold, the crowd is extended on one side. That can set up squeeze risk in the opposite direction.
When OI RSI has been pinned low, it suggests heavy de-leveraging. Once price stabilises, a re-risking phase is often not far away.
Background colours in Mean-Rev mode help visually identify these periods.
Regime mapping with plotting modes
Different plotting modes give different perspectives:
Heatmap mode for dashboard-style use where you just need to know "hot", "neutral" or "cold" on OI flows at a glance.
Oscillator mode for short term impulses and compression reads around the mid line. See:
Flag mode for blending level and trend of OI RSI into a single banded visual. See:
Settings overview
RSI group
Plotting Type – None, Line, Colored Line, Oscillator, Flag, Heatmap.
Calculation Period – base RSI length for OI.
Smoothing Period (SMA) – smoothing on RSI.
Moving Average group
Show EMA – toggle EMA overlay (not used in heatmap).
EMA Period – length of EMA on OI RSI.
EMA Color – colour of EMA line.
Thresholds group
Mid Point – central reference.
Extreme Upper Threshold and Extreme Lower Threshold – OB/OS thresholds.
Select Reference Lines – none, basic lines or OB/OS zone fills.
Extreme Highlighting – None, Mean-Rev, Trend.
Extra Plotting and UI
RSI Line Color and RSI Line Width .
Long/OB Color and Short/OS Color .
Show OI RSI Meter , OI RSI Blocks , OI RSI Meter Position .
Open Interest Source
OI Units – COIN or USD.
Exchange toggles: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Notes
This is a positioning and pressure tool, not a complete system. It:
Models aggregated futures open interest across multiple centralized exchanges.
Transforms that OI into an RSI-style oscillator for better comparability across regimes.
Offers several visual modes to match different workflows, from detailed analysis to compact dashboards.
Use it to understand how leverage and positioning are evolving behind the price, to gauge when the crowd is stretched, and to decide whether to lean with or against that pressure. Attach it to your existing signals, not in place of them.
Also, please check out @NoveltyTrade for the OI Aggregation logic & pulling the data source!
Here is the original script:
Momentum Trajectory Suite📈 Momentum Trajectory Suite
🟢 Overview
Momentum Trajectory Suite is a multi-faceted indicator designed to help traders evaluate trend direction, volatility conditions, and behavioral sentiment in a single consolidated view.
By combining a customizable Trajectory EMA, adaptive Bollinger Bands, and a Greed vs. Fear heatmap, this tool empowers traders to identify directional bias, measure momentum strength, and spot potential reversals or continuation setups.
🧠 Concept
This indicator merges three classic techniques:
Trend Analysis: Trajectory EMA highlights the prevailing directional momentum by smoothing price action over a customizable period.
Volatility Envelopes: Bollinger Bands adapt to dynamic price swings, showing overbought/oversold extremes and periods of contraction or expansion.
Behavioral Sentiment: A Greed vs. Fear heatmap combines RSI and MACD Histogram readings to visualize when markets are dominated by buying enthusiasm or selling pressure.
The combination is designed to help traders interpret market context more effectively than using any single component alone.
🛠️ How to Use the Indicator
Trajectory EMA:
Use the blue EMA line to assess overall trend direction.
Price closing above the EMA may indicate bullish momentum; closing below may indicate bearish bias.
Buy/Sell Signals:
Green circles appear when price crosses above the EMA (potential long entry).
Red circles appear when price crosses below the EMA (potential exit or short entry).
Bollinger Bands:
Monitor upper/lower bands for overbought and oversold price extremes.
Narrowing bands may signal upcoming volatility expansion.
Greed vs. Fear Heatmap:
Green histogram bars indicate bullish sentiment when RSI exceeds 60 and MACD Histogram is positive.
Red histogram bars indicate bearish sentiment when RSI is below 40 and MACD Histogram is negative.
Gray bars indicate neutral or mixed conditions.
Background Color Zones:
The chart background shifts to green when EMA slope is positive and red when negative, providing quick directional cues.
All inputs are adjustable in settings, including EMA length, Bollinger Band parameters, and oscillator configurations.
📊 Interpretation
Bullish Conditions:
Price above the Trajectory EMA, background green, and Greed heatmap active.
May signal trend continuation and increased buying pressure.
Bearish Conditions:
Price below the Trajectory EMA, background red, and Fear heatmap active.
May signal momentum breakdown or potential continuation to the downside.
Volatility Clues:
Wide Bollinger Bands = trending, volatile market.
Narrow Bollinger Bands = low volatility and possible breakout setup.
Signal Confirmation:
Consider combining signals (e.g., EMA crossover + Greed/Fear heatmap + Bollinger Band touch) for higher-confidence entries.
📝 Notes
The script does not repaint or use future data.
Suitable for multiple timeframes (intraday to daily).
May be combined with other confirmation tools or price action analysis.
⚠️ Disclaimer
This script is for educational and informational purposes only and does not constitute financial advice. Trading carries risk and past performance is not indicative of future results. Always perform your own due diligence before making trading decisions.
Momentum-Based Fair Value Gaps [BackQuant]Momentum-Based Fair Value Gaps
A precision tool that detects Fair Value Gaps and color-codes each zone by momentum, so you can quickly tell which imbalances matter, which are likely to fill, and which may power continuation.
What is a Fair Value Gap
A Fair Value Gap is a 3-candle price imbalance that forms when the middle candle expands fast enough that it leaves a void between candle 1 and candle 3.
Bullish FVG : low > high . This marks a bullish imbalance left beneath price.
Bearish FVG : high < low . This marks a bearish imbalance left above price.
These zones often act as magnets for mean reversion or as fuel for trend continuation when price respects the gap boundary and runs.
Why add momentum
Not all gaps are equal. This script measures momentum with RSI on your chosen source and paints each FVG with a momentum heatmap. Strong-momentum gaps are more likely to hold or propel continuation. Weak-momentum gaps are more likely to fill.
Core Features
Auto FVG Detection with size filters in percent of price.
Momentum Heatmap per gap using RSI with smoothing. Multiple palettes: Gradient, Discrete, Simple, and scientific schemes like Viridis, Plasma, Inferno, Magma, Cividis, Turbo, Jet, plus Red-Green and Blue-White-Red.
Bull and Bear Modes with independent toggles.
Extend Until Filled : keep drawing live to the right until price fully fills the gap.
Auto Remove Filled for a clean chart.
Optional Labels showing the smoothed RSI value stored at the gap’s birth.
RSI-based Filters : only accept bullish gaps when RSI is oversold and bearish gaps when RSI is overbought.
Performance Controls : cap how many FVGs to keep on chart.
Alerts : new bullish or bearish FVG, filled FVG, and extreme RSI FVGs.
How it works
Source for Momentum : choose Returns, Close, or Volume.
Returns computes percent change over a short lookback to focus on impulse quality.
RSI and Smoothing : RSI length and a small SMA smooth the signal to stabilize the color coding.
Gap Scan : each bar checks for a 3-candle bullish or bearish imbalance that also clears your minimum size filter in percent of price.
Heatmap Color : the gap is painted at creation with a color from your palette based on the smoothed RSI value, preserving the momentum signature that formed it.
Lifecycle : if Extend Unfilled is on, the zone projects forward until price fully trades through the far edge. If Auto Remove is on, a filled gap is deleted immediately.
How to use it
Scan for structure : turn on both bullish and bearish FVGs. Start with a moderate Min FVG Size percent to reduce noise. You will see stacked clusters in trends and scattered singletons in chop.
Read the colors : brighter or stronger palette values imply stronger momentum at gap formation. Weakly colored gaps are lower conviction.
Decide bias : bullish FVGs below price suggest demand footprints. Bearish FVGs above price suggest supply footprints. Use the heatmap and RSI value to rank importance.
Choose your playbook :
Mean reversion : target partial or full fills of opposing FVGs that were created on weak momentum or that sit against higher timeframe context.
Trend continuation : look for price to respect the near edge of a strong-momentum FVG, then break away in the direction of the original impulse.
Manage risk : in continuation ideas, invalidation often sits beyond the opposite edge of the active FVG. In reversion ideas, invalidation sits beyond the gap that should attract price.
Two trade playbooks
Continuation - Buy the hold of a bullish FVG
Context uptrend.
A bullish FVG prints with strong RSI color.
Price revisits the top of the gap, holds, and rotates up. Enter on hold or first higher low inside or just above the gap.
Invalidation: below the gap bottom. Targets: prior swing, measured move, or next LV area.
Reversion - Fade a weak bearish FVG toward fill
Context range or fading trend.
A bearish FVG prints with weak RSI color near a completed move.
Price fails to accelerate lower and rotates back into the gap.
Enter toward mid-gap with confirmation.
Invalidation: above gap top. Target: opposite edge for a full fill, or the gap midline for partials.
Key settings
Max FVG Display : memory cap to keep charts fast. Try 30 to 60 on intraday.
Min FVG Size % : sets a quality floor. Start near 0.20 to 0.50 on liquid markets.
RSI Length and Smooth : 14 and 3 are balanced. Increase length for higher timeframe stability.
RSI Source :
Returns : most sensitive to true momentum bursts
Close : traditional.
Volume : uses raw volume impulses to judge footprint strength.
Filter by RSI Extremes : tighten rules so only the most stretched gaps print as signals.
Heatmap Style and Palette : pick a palette with good contrast for your background. Gradient for continuous feel, Discrete for quick zoning, Simple for binary, Palette for scientific schemes.
Extend Unfilled - Auto Remove : choose live projection and cleanup behavior to match your workflow.
Reading the chart
Bullish zones sit beneath price. Respect and hold of the upper boundary suggests demand. Strong green or warm palette tones indicate impulse quality.
Bearish zones sit above price. Respect and hold of the lower boundary suggests supply. Strong red or cool palette tones indicate impulse quality.
Stacking : multiple same-direction gaps stacked in a trend create ladders. Ladders often act as stepping stones for continuation.
Overlapping : opposing gaps overlapping in a small region usually mark a battle zone. Expect chop until one side is absorbed.
Workflow tips
Map higher timeframe trend first. Use lower timeframe FVGs for entries aligned with the higher timeframe bias.
Increase Min FVG Size percent and RSI length for noisy symbols.
Use labels when learning to correlate the RSI numbers with your palette colors.
Combine with VWAP or moving averages for confluence at FVG edges.
If you see repeated fills and refills of the same zone, treat that area as fair value and avoid chasing.
Alerts included
New Bullish FVG
New Bearish FVG
Bullish FVG Filled
Bearish FVG Filled
Extreme Oversold FVG - bullish
Extreme Overbought FVG - bearish
Practical defaults
RSI Length 14, Smooth 3, Source Returns.
Min FVG Size 0.25 percent on liquid majors.
Heatmap Style Gradient, Palette Viridis or Turbo for contrast.
Extend Unfilled on, Auto Remove on for a clean live map.
Notes
This tool does not predict the future. It maps imbalances and momentum so you can frame trades with clearer context, cleaner invalidation, and better ranking of which gaps matter. Use it with risk control and in combination with your broader process.
Candle Opens by HAZED🎯 Candle Opens by HAZED - Multi-Timeframe Open Levels Indicator
📊 Overview
This powerful indicator displays multiple timeframe opening prices on your chart, providing crucial reference levels that institutional traders and algorithms frequently monitor. Track up to 7 different timeframe opens simultaneously, from 1-hour to yearly, with advanced visualization features including dynamic coloring, heatmap analysis, and real-time status tracking.
✨ Key Features
📈 Multi-Timeframe Support:
- 1H, 4H, Daily, Weekly, Monthly, Quarterly, and Yearly opens
- Each timeframe can be individually enabled/disabled
- Automatic visibility adjustment based on chart timeframe
🎨 Dynamic Visual System:
- Smart Color Coding: Lines automatically change color based on price position (green above, red below)
- Customizable Styling: Adjust line thickness, transparency, and colors
- Intelligent Line Positioning: Choose between equal-length or staggered lines for better visibility
- Enhanced Labels: Display timeframe only or include price with colored background
🌈 Advanced Heatmap:
- Background coloring shows overall market sentiment across all timeframes
- Gradient or solid color modes
- Instantly see when multiple timeframes align bullish or bearish
📊 Status Table Dashboard:
- Real-time overview of all active opens
- Shows current price position relative to each open
- Simplified view when all timeframes align
- Customizable position and font style
⚙️ Professional Tools:
- Alert system for new open levels
- Extended hours session support
- Price discovery mode for EOD/intraday discrepancies
- Left/right line extensions for enhanced visibility
💡 Trading Applications
Support & Resistance:
Opening prices act as natural support/resistance levels. Price often reacts at these levels, providing entry/exit opportunities.
Trend Confirmation:
When price is above multiple opens (especially higher timeframes), it confirms bullish momentum. The opposite indicates bearish pressure.
Mean Reversion:
Price tends to revert to significant opens, particularly daily and weekly levels. Use these as targets for counter-trend trades.
Breakout Trading:
Monitor when price breaks above/below clustered opens for potential continuation moves.
Risk Management:
Use opens as logical stop-loss levels or position sizing references based on distance from key opens.
🔧 Indicator Settings
Timeframes Section:
- Toggle each timeframe on/off
- Customize individual colors
Visual Style Section:
- Dynamic Colors: Auto-color based on price position
- Line Thickness: 1-4 pixels
- Transparency: 0-80%
- Extension Length: How far lines extend right
- Label Style: Plain or enhanced with price
Heatmap Section:
- Enable/disable background coloring
- Adjust transparency
- Choose gradient or solid zones
Status Table Section:
- Position on chart
- Font selection
Advanced Section:
- Enable alerts for new opens
- Price discovery mode
- Extended hours inclusion
]📈 Best Practices
1. Timeframe Selection:
- For intraday: Focus on 1H, 4H, and Daily
- For swing trading: Daily, Weekly, Monthly
- For position trading: Monthly, Quarterly, Yearly
2. Color Coding:
- Enable dynamic colors for instant sentiment reading
- Use heatmap for overall market bias
3. Confluence Zones:
- Pay special attention when multiple opens cluster
- These zones often produce stronger reactions
4. Alignment Signals:
- When all timeframes show same color = strong trend
- Mixed colors = potential consolidation or reversal zone
🎯 Pro Tips
- Volume Confirmation: Combine with volume indicators to confirm reactions at open levels
- Multiple Instruments: Compare opens across correlated assets for divergences
- News Events: Opens often act as magnets after major news releases
- Options Trading: Weekly and monthly opens align with options expiry levels
- Algorithmic Levels: Many algorithms use these opens for entries/exits
🔄 Updates in Version 8.3
- Added 1H and 4H timeframe support
- Enhanced dynamic color system
- Implemented heatmap visualization
- Added real-time status table
- Optimized performance for smoother operation
- Improved label styling options
- Better yearly timeframe detection
⚡ Performance Optimizations
This indicator uses advanced Pine Script v6 features for optimal performance:
- Efficient object reuse instead of recreation
- Smart calculation loops
- Minimal repainting
- Optimized for real-time updates
📝 Notes
- Works on all markets (stocks, forex, crypto, futures)
- Best on timeframes lower than the opens you're tracking
- Lines automatically hide when their timeframe is lower than chart timeframe
- Past opens are not displayed (indicator shows current opens only)
🙏 Credits & Support
Created by HAZED | Version 8.3
Optimized for TradingView Pine Script v6
For questions, suggestions, or bug reports, please comment below.
If you find this indicator useful, please consider leaving a like and a follow!
Remember: No indicator is perfect. Always use proper risk management and combine multiple confirmation signals in your trading decisions.
SMA Trend Spectrum [InvestorUnknown]The SMA Trend Spectrum indicator is designed to visually represent market trends and momentum by using a series of Simple Moving Averages (SMAs) to create a color-coded spectrum or heatmap. This tool helps traders identify the strength and direction of market trends across various time frames within one chart.
Functionality:
SMA Calculation: The indicator calculates multiple SMAs starting from a user-defined base period (Starting Period) and increasing by a specified increment (Period Increment). This creates a sequence of moving averages that span from short-term to long-term perspectives.
Trend Analysis: Each segment of the spectrum compares three SMAs to determine the market's trend strength: Bullish (color-coded green) when the current price is above all three SMAs. Neutral (color-coded purple) when the price is above some but not all SMAs. Bearish (color-coded red) when the price is below all three SMAs.
f_col(x1, x2, x3) =>
min = ta.sma(src, x1)
mid = ta.sma(src, x2)
max = ta.sma(src, x3)
c = src > min and src > mid and src > max ? bull : src > min or src > mid or src > max ? ncol : bear
Heatmap Visualization: The indicator plots these trends as a vertical spectrum where each row represents a different set of SMAs, forming a heatmap-like display. The color of each segment in the heatmap directly correlates with market conditions, providing an intuitive view of market sentiment.
Signal Smoothing: Users can choose to smooth the trend signal using either a Simple Moving Average (SMA), Exponential Moving Average (EMA), or leave it as raw data (Signal Smoothing). The length of smoothing can be adjusted (Smoothing Length). The signal is displayed in a scaled way to automatically adjust for the best visual experience, ensuring that the trend is clear and easily interpretable across different chart scales and time frames
Additional Features:
Plot Signal: Optionally plots a line representing the average trend across all calculated SMAs. This line helps in identifying the overall market direction based on the spectrum data.
Bar Coloring: Bars on the chart can be colored according to the average trend strength, providing a quick visual cue of market conditions.
Usage:
Trend Identification: Use the heatmap to quickly assess if the market is trending strongly in one direction or if it's in a consolidation phase.
Entry/Exit Points: Look for shifts in color patterns to anticipate potential trend changes or confirmations for entry or exit points.
Momentum Analysis: The gradient from bearish to bullish across the spectrum can be used to gauge momentum and potentially forecast future price movements.
Notes:
The effectiveness of this indicator can vary based on market conditions, asset volatility, and the chosen SMA periods and increments.
It's advisable to combine this tool with other technical indicators or fundamental analysis for more robust trading decisions.
Disclaimer: Past performance does not guarantee future results. Always use this indicator as part of a broader trading strategy.
Adaptive Linear Regression ChannelOverview
The Adaptive Linear Regression Channel Script is an advanced, multi-functional trading tool crafted to help traders pinpoint market trends, identify potential reversals, assess volatility, and establish dynamic levels for profit-taking and position exits. By incorporating key concepts such as linear regression , standard deviation , and other volatility measures like the ATR , the script offers a comprehensive view of market behavior beyond traditional deviation metrics.
This dynamic model continuously adapts to changing market conditions, adjusting in real-time to provide clear visualizations of trends, channels, and volatility levels. This adaptability makes the script invaluable for both trend-following and counter-trend strategies, giving traders the flexibility to respond effectively to different market environments.
Background
What is Linear Regression?
Definition : Linear regression is a statistical technique used to model the relationship between a dependent variable (target) and one or more independent variables (predictors).
In its simplest form (simple linear regression), the relationship between two variables is represented by a straight line (the regression line).
y = mx + b
where :
- y is the target variable (price)
- m is the slope
- x is the independent variable (time)
- b is the intercept
Slope of the Regression Line
Definition: The slope (m) measures the rate at which the dependent variable (y) changes as the independent variable (x) changes.
Interpretation:
- A positive slope indicates an uptrend.
- A negative slope indicates a downtrend.
Uses in Trading:
- Identifying the strength and direction of market trends.
- Assessing the momentum of price movements.
R-squared (Coefficient of Determination)
Definition: A measure of how well the regression line fits the data, ranging from 0 to 1.
Calculation :
R2 = 1− (SS tot/SS res)
where:
- SSres is the sum of squared residuals.
- SStot is the total sum of squares.
Interpretation:
- Higher R2 indicates a better fit, meaning the model explains a larger proportion of the variance in the data.
Uses in Trading:
- Higher R-squared values give traders confidence in trend-based signals.
- Low R-squared values may suggest that the market is more random or volatile.
Standard Deviation
Definition: Standard Deviation quantifies the dispersion of data points in a dataset relative to the mean. A low standard deviation indicates that data points tend to be close to the mean, while a high standard deviation indicates that the data points are spread out over a larger range of values.
Calculation
σ=√∑(xi−μ)2/N
Where
- σ is the standard deviation.
- ∑ is the summation symbol, indicating that the expression that follows should be summed over all data points.
- xi, this represents the i-th data point in the dataset.
- μ\mu, this represents the mean(average) of all the data points in the dataset.
- (xi−μ)2, this is the squared difference between each data point and the mean.
- N is the total number of data points in the dataset.
- **Interpretation**
- A higher standard deviation indicates greater volatility.
- Useful for identifying overbought/oversold conditions in markets.
Key Features
Dynamic Linear Regression Channels:
The script automatically generates adaptive regression channels that expand or contract based on the current market volatility. This real-time adjustment ensures that traders are always working with the most relevant data, making it easier to spot key support and resistance levels.
The channel width itself serves as an indicator of market volatility, expanding during periods of heightened uncertainty and contracting during more stable phases. Additionally, the channel width is trained on previous channel widths , allowing the script to adapt and provide a more accurate view of volatility trends of the asset. Traders can also customize the script to train on less historical data , enabling a more recent view of volatility , which is particularly useful in fast-moving or changing markets.
Dynamic Profits and Stops:
What is it?
Dynamic profit levels allow traders to adjust take-profit targets based on real-time market conditions. Unlike static levels, which remain fixed regardless of market changes, these adaptive levels leverage past volatility data to create more flexible profit-taking strategies.
How does it work?
The script determines these levels using previously stored deviation values. These deviations are categorized into quantiles (like Q1, Q2, Q3, etc.) to classify current market conditions. As new deviation data is recorded, the profit levels are adjusted dynamically to reflect changes in market volatility. This approach helps to refine profit targets, especially when using regression channels with standard deviation rather than traditional ATR bands.
Why is it valuable?
By utilizing adaptive profit levels, traders can optimize their exits based on the current volatility landscape. For instance, when volatility increases, the dynamic levels expand, allowing trades to capture larger price movements. Conversely, during low volatility, profit targets tighten to lock in gains sooner, reducing exposure to market reversals. This flexibility is especially beneficial when combined with adaptive regression channels that respond to changes in standard deviation.
Slope-Based Trend Analysis:
One of the core elements of this script is the slope of the regression line , which helps define the direction and strength of the trend. Positive slopes indicate bullish momentum, while negative slopes suggest bearish conditions. The slope's steepness gives traders insight into the market's momentum, allowing them to adjust their strategies based on the strength of the trend.
Additionally, the script uses the slope to create a color gradient , which visually represents the intensity of the market's momentum. The gradient peaks at one color to show the maximum bullish momentum experienced in the past, while another color represents the maximum bearish momentum experienced in the past. This color-coded visualization makes it easier for traders to quickly assess the market's strength and direction at a glance.
Volatility Heatmap:
The integrated heatmap provides an intuitive, color-coded visualization of market volatility. The heatmap highlights areas where price action is expanding or contracting, giving traders a clear view of where volatility is rising or falling. By mapping out deviations from the regression line, the heatmap makes it easier to spot periods of high volatility that could lead to major market moves or potential reversals.
Deviation Concepts:
The script tracks price deviations from the regression line when a new range is formed, providing valuable insights when the price significantly deviates from the expected trend. These deviations are key in identifying potential breakout points or trend shifts .
This helps traders understand when the market is overextended or when a pullback may be imminent, allowing them to make more informed trading decisions.
Adaptive Model Properties:
Unlike static indicators, this script adapts over time . As the market changes, it stores historical data related to channel widths , slope dynamics , and volatility levels , adjusting its analysis accordingly to stay relevant to current market conditions.
Traders have the ability to train the model on all available data or specify a set number of bars to focus on more recent market activity. This flexibility allows for more tailored analysis , ensuring that traders can work with data that best fits their trading style and time horizon.
This continuous learning approach ensures that traders always have the most up-to-date insight into the market's structure.
Table
The table displays key metrics in real time to provide deeper insights into market behavior:
1. Deviation & Slope : Shows the current deviation if set to standard deviation or atr if set to atr(values used to calculated the channel widths) and the trend slope, helping to gauge market volatility and trend direction.
2. Rate of Change : For both deviation/atr and slope, the table also calculates the rate of change of their rates—essentially capturing the acceleration or deceleration of trends and volatility. This helps identify shifts in market momentum early.
3. R-squared : Indicates the strength and reliability of the trend fit. A higher value means the regression line better explains the price movements.
4. Quantiles : Uses historical deviation data to categorize current market conditions into quartiles (e.g., Q1, Q2, Q3). This helps classify the market's current volatility level, allowing traders to adjust strategies dynamically.
By combining these metrics, the table offers a comprehensive, real-time snapshot of market conditions, enabling more informed and adaptive trading decisions.
Settings
Here’s a breakdown of the script's settings for easy reference:
Linear Regression Settings
Show Dynamic Levels :Toggle to display dynamic profit levels on the chart.
Deviation Type :Select the method for calculating deviation—options include ATR (Average True Range) or Standard Deviation.
Timeframe :Sets the specific timeframe for the regression analysis (default is the chart’s timeframe).
Period :Defines the number of bars used for calculating the regression line (e.g., 50 bars).
Deviation Multiplier :Multiplier used to adjust the width of the deviation channel around the regression line.
Rate of Change :Sets the period for calculating the rate of change of the slope (used for momentum analysis).
Max Bars Back :Limits the number of historical bars to analyze (0 means all available data).
Slope Lookback :Number of bars used to calculate the slope gradient for trend detection.
Slope Gradient Display :Toggle to enable gradient coloring based on slope direction.
Slope Gradient Colors :Set colors for positive and negative slopes, respectively.
Slope Fill :Adjusts the transparency of the slope gradient fill.
Volatility Gradient Display :Toggle to enable gradient coloring based on volatility levels.
Volatility Gradient Colors :Set colors for low and high volatility, respectively.
Volatility Fill :Adjusts the transparency of the volatility gradient fill.
Table Settings
Show Table :Toggle to display the metrics table on the chart.
Table Position :Choose where to position the table (e.g., top-right, middle-center, etc.).
Font Size :Set the size of the text in the table. Options include Tiny, Small, Normal, Large, and Huge.
Infinity Market Grid -AynetConcept
Imagine viewing the market as a dynamic grid where price, time, and momentum intersect to reveal infinite possibilities. This indicator leverages:
Grid-Based Market Flow: Visualizes price action as a grid with zones for:
Accumulation
Distribution
Breakout Expansion
Volatility Compression
Predictive Dynamic Layers:
Forecasts future price zones using historical volatility and momentum.
Tracks event probabilities like breakout, fakeout, and trend reversals.
Data Science Visuals:
Uses heatmap-style layers, moving waveforms, and price trajectory paths.
Interactive Alerts:
Real-time alerts for high-probability market events.
Marks critical zones for "buy," "sell," or "wait."
Key Features
Market Layers Grid:
Creates dynamic "boxes" around price using fractals and ATR-based volatility.
These boxes show potential future price zones and probabilities.
Volatility and Momentum Waves:
Overlay volatility oscillators and momentum bands for directional context.
Dynamic Heatmap Zones:
Colors the chart dynamically based on breakout probabilities and risk.
Price Path Prediction:
Tracks price trajectory as a moving "wave" across the grid.
How It Works
Grid Box Structure:
Upper and lower price levels are based on ATR (volatility) and plotted dynamically.
Dashed green/red lines show the grid for potential price expansion zones.
Heatmap Zones:
Colors the background based on probabilities:
Green: High breakout probability.
Blue: High consolidation probability.
Price Path Prediction:
Forecasts future price movements using momentum.
Plots these as a dynamic "wave" on the chart.
Momentum and Volatility Waves:
Shows the relationship between momentum and volatility as oscillating waves.
Helps identify when momentum exceeds volatility (potential breakouts).
Buy/Sell Signals:
Triggers when price approaches grid edges with strong momentum.
Provides alerts and visual markers.
Why Is It Revolutionary?
Grid and Wave Synergy:
Combines structural price zones (grid boxes) with real-time momentum and volatility waves.
Predictive Analytics:
Uses momentum-based forecasting to visualize what’s next, not just what’s happening.
Dynamic Heatmap:
Creates a living map of breakout/consolidation zones in real-time.
Scalable for Any Market:
Works seamlessly with forex, crypto, and stocks by adjusting the ATR multiplier and box length.
This indicator is not just a tool but a framework for understanding market dynamics at a deeper level. Let me know if you'd like to take it even further — for example, adding machine learning-inspired probability models or multi-timeframe analysis! 🚀
Multi-Mode Seasonality Map [BackQuant]Multi-Mode Seasonality Map
A fast, visual way to expose repeatable calendar patterns in returns, volatility, volume, and range across multiple granularities (Day of Week, Day of Month, Hour of Day, Week of Month). Built for idea generation, regime context, and execution timing.
What is “seasonality” in markets?
Seasonality refers to statistically repeatable patterns tied to the calendar or clock, rather than to price levels. Examples include specific weekdays tending to be stronger, certain hours showing higher realized volatility, or month-end flow boosting volumes. This tool measures those effects directly on your charted symbol.
Why seasonality matters
It’s orthogonal alpha: timing edges independent of price structure that can complement trend, mean reversion, or flow-based setups.
It frames expectations: when a session typically runs hot or cold, you size and pace risk accordingly.
It improves execution: entering during historically favorable windows, avoiding historically noisy windows.
It clarifies context: separating normal “calendar noise” from true anomaly helps avoid overreacting to routine moves.
How traders use seasonality in practice
Timing entries/exits : If Tuesday morning is historically weak for this asset, a mean-reversion buyer may wait for that drift to complete before entering.
Sizing & stops : If 13:00–15:00 shows elevated volatility, widen stops or reduce size to maintain constant risk.
Session playbooks : Build repeatable routines around the hours/days that consistently drive PnL.
Portfolio rotation : Compare seasonal edges across assets to schedule focus and deploy attention where the calendar favors you.
Why Day-of-Week (DOW) can be especially helpful
Flows cluster by weekday (ETF creations/redemptions, options hedging cadence, futures roll patterns, macro data releases), so DOW often encodes a stable micro-structure signal.
Desk behavior and liquidity provision differ by weekday, impacting realized range and slippage.
DOW is simple to operationalize: easy rules like “fade Monday afternoon chop” or “press Thursday trend extension” can be tested and enforced.
What this indicator does
Multi-mode heatmaps : Switch between Day of Week, Day of Month, Hour of Day, Week of Month .
Metric selection : Analyze Returns , Volatility ((high-low)/open), Volume (vs 20-bar average), or Range (vs 20-bar average).
Confidence intervals : Per cell, compute mean, standard deviation, and a z-based CI at your chosen confidence level.
Sample guards : Enforce a minimum sample size so thin data doesn’t mislead.
Readable map : Color palettes, value labels, sample size, and an optional legend for fast interpretation.
Scoreboard : Optional table highlights best/worst DOW and today’s seasonality with CI and a simple “edge” tag.
How it’s calculated (under the hood)
Per bar, compute the chosen metric (return, vol, volume %, or range %) over your lookback window.
Bucket that metric into the active calendar bin (e.g., Tuesday, the 15th, 10:00 hour, or Week-2 of month).
For each bin, accumulate sum , sum of squares , and count , then at render compute mean , std dev , and confidence interval .
Color scale normalizes to the observed min/max of eligible bins (those meeting the minimum sample size).
How to read the heatmap
Color : Greener/warmer typically implies higher mean value for the chosen metric; cooler implies lower.
Value label : The center number is the bin’s mean (e.g., average % return for Tuesdays).
Confidence bracket : Optional “ ” shows the CI for the mean, helping you gauge stability.
n = sample size : More samples = more reliability. Treat small-n bins with skepticism.
Suggested workflows
Pick the lens : Start with Analysis Type = Returns , Heatmap View = Day of Week , lookback ≈ 252 trading days . Note the best/worst weekdays and their CI width.
Sanity-check volatility : Switch to Volatility to see which bins carry the most realized range. Use that to plan stop width and trade pacing.
Check liquidity proxy : Flip to Volume , identify thin vs thick windows. Execute risk in thicker windows to reduce slippage.
Drill to intraday : Use Hour of Day to reveal opening bursts, lunchtime lulls, and closing ramps. Combine with your main strategy to schedule entries.
Calendar nuance : Inspect Week of Month and Day of Month for end-of-month, options-cycle, or data-release effects.
Codify rules : Translate stable edges into rules like “no fresh risk during bottom-quartile hours” or “scale entries during top-quartile hours.”
Parameter guidance
Analysis Period (Days) : 252 for a one-year view. Shorten (100–150) to emphasize the current regime; lengthen (500+) for long-memory effects.
Heatmap View : Start with DOW for robustness, then refine with Hour-of-Day for your execution window.
Confidence Level : 95% is standard; use 90% if you want wider coverage with fewer false “insufficient data” bins.
Min Sample Size : 10–20 helps filter noise. For Hour-of-Day on higher timeframes, consider lowering if your dataset is small.
Color Scheme : Choose a palette with good mid-tone contrast (e.g., Red-Green or Viridis) for quick thresholding.
Interpreting common patterns
Return-positive but low-vol bins : Favorable drift windows for passive adds or tight-stop trend continuation.
Return-flat but high-vol bins : Opportunity for mean reversion or breakout scalping, but manage risk accordingly.
High-volume bins : Better expected execution quality; schedule size here if slippage matters.
Wide CI : Edge is unstable or sample is thin; treat as exploratory until more data accumulates.
Best practices
Revalidate after regime shifts (new macro cycle, liquidity regime change, major exchange microstructure updates).
Use multiple lenses: DOW to find the day, then Hour-of-Day to refine the entry window.
Combine with your core setup signals; treat seasonality as a filter or weight, not a standalone trigger.
Test across assets/timeframes—edges are instrument-specific and may not transfer 1:1.
Limitations & notes
History-dependent: short histories or sparse intraday data reduce reliability.
Not causal: a hot Tuesday doesn’t guarantee future Tuesday strength; treat as probabilistic bias.
Aggregation bias: changing session hours or symbol migrations can distort older samples.
CI is z-approximate: good for fast triage, not a substitute for full hypothesis testing.
Quick setup
Use Returns + Day of Week + 252d to get a clean yearly map of weekday edge.
Flip to Hour of Day on intraday charts to schedule precise entries/exits.
Keep Show Values and Confidence Intervals on while you calibrate; hide later for a clean visual.
The Multi-Mode Seasonality Map helps you convert the calendar from an afterthought into a quantitative edge, surfacing when an asset tends to move, expand, or stay quiet—so you can plan, size, and execute with intent.
Cumulative Returns by Session [BackQuant]Cumulative Returns by Session
What this is
This tool breaks the trading day into three user-defined sessions and tracks how much each session contributes to return, volatility, and volume. It then aggregates results over a rolling window so you can see which session has been pulling its weight, how streaky each session has been, and how sessions relate to one another through a compact correlation heatmap.
We’ve also given the functionality for the user to use a simplified table, just by switching off all settings they are not interested in.
How it works
1) Session segmentation
You define APAC, EU, and US sessions with explicit hours and time zones. The script detects when each session starts and ends on every intraday bar and records its open, intraday high and low, close, and summed volume.
2) Per-session math
At each session end the script computes:
Return — either Percent: (Close−Open)÷Open×100(Close − Open) ÷ Open × 100(Close−Open)÷Open×100 or Points: (Close−Open)(Close − Open)(Close−Open), based on your selection.
Volatility — either Range: (High−Low)÷Open×100(High − Low) ÷ Open × 100(High−Low)÷Open×100 or ATR scaled by price: ATR÷Open×100ATR ÷ Open × 100ATR÷Open×100.
Volume — total volume transacted during that session.
3) Storage and lookback
Each day’s three session stats are stored as a row. You choose how many recent sessions to keep in memory. The script then:
Builds cumulative returns for APAC, EU, US across the lookback.
Computes averages, win rates, and a Sharpe-like ratio avgreturn÷avgvolatilityavg return ÷ avg volatilityavgreturn÷avgvolatility per session.
Tracks streaks of positive or negative sessions to show momentum.
Tracks drawdowns on cumulative returns to show worst runs from peak.
Computes rolling means over a short window for short-term drift.
4) Correlation heatmap
Using the stored arrays of session returns, the script calculates Pearson correlations between APAC–EU, APAC–US, and EU–US, and colors the matrix by strength and sign so you can spot coupling or decoupling at a glance.
What it plots
Three lines: cumulative return for APAC, EU, US over the chosen lookback.
Zero reference line for orientation.
A statistics table with cumulative %, average %, positive session rate, and optional columns for volatility, average volume, max drawdown, current streak, return-to-vol ratio, and rolling average.
A small correlation heatmap table showing APAC, EU, US cross-session correlations.
How to use it
Pick the asset — leave Custom Instrument empty to use the chart symbol, or point to another symbol for cross-asset studies.
Set your sessions and time zones — defaults approximate APAC, EU, and US hours, but you can align them to exchange times or your workflow.
Choose calculation modes — Percent vs Points for return, Range vs ATR for volatility. Points are convenient for futures and fixed-tick assets, Percent is comparable across symbols.
Decide the lookback — more sessions smooths lines and stats; fewer sessions makes the tool more reactive.
Toggle analytics — add volatility, volume, drawdown, streaks, Sharpe-like ratio, rolling averages, and the correlation table as needed.
Why session attribution helps
Different sessions are driven by different flows. Asia often sets the overnight tone, Europe adds liquidity and direction changes, and the US session can dominate range expansion. Separating contributions by session helps you:
Identify which session has been the main driver of net trend.
Measure whether volatility or volume is concentrated in a specific window.
See if one session’s gains are consistently given back in another.
Adapt tactics: fade during a mean-reverting session, press during a trending session.
Reading the tables
Cumulative % — sum of session returns over the lookback. The sign and slope tell you who is carrying the move.
Avg Return % and Positive Sessions % — direction and hit rate. A low average but high hit rate implies many small moves; the reverse implies occasional big swings.
Avg Volatility % — typical intrabars range for that session. Compare with Avg Return to judge efficiency.
Return/Vol Ratio — return per unit of volatility. Higher is better for stability.
Max Drawdown % — worst cumulative give-back within the lookback. A quick way to spot riskiness by session.
Current Streak — consecutive up or down sessions. Useful for mean-reversion or regime awareness.
Rolling Avg % — short-window drift indicator to catch recent turnarounds.
Correlation matrix — green clusters indicate sessions tending to move together; red indicates offsetting behavior.
Settings overview
Basic
Number of Sessions — how many recent days to include.
Custom Instrument — analyze another ticker while staying on your current chart.
Session Configuration and Times
Enable or hide APAC, EU, US rows.
Set hours per session and the specific time zone for each.
Calculation Methods
Return Calculation — Percent or Points.
Volatility Calculation — Range or ATR; ATR Length when applicable.
Advanced Analytics
Correlation, Drawdown, Momentum, Sharpe-like ratio, Rolling Statistics, Rolling Period.
Display Options and Colors
Show Statistics Table and its position.
Toggle columns for Volatility and Volume.
Pick individual colors for each session line and row accents.
Common applications
Session bias mapping — find which window tends to trend in your market and plan exposure accordingly.
Strategy scheduling — allocate attention or risk to the session with the best return-to-vol ratio.
News and macro awareness — see if correlation rises around central bank cycles or major data releases.
Cross-asset monitoring — set the Custom Instrument to a driver (index future, DXY, yields) to see if your symbol reacts in a particular session.
Notes
This indicator works on intraday charts, since sessions are defined within a day. If you change session clocks or time zones, give the script a few bars to accumulate fresh rows. Percent vs Points and Range vs ATR choices affect comparability across assets, so be consistent when comparing symbols.
Session context is one of the simplest ways to explain a messy tape. By separating the day into three windows and scoring each one on return, volatility, and consistency, this tool shows not just where price ended up but when and how it got there. Use the cumulative lines to spot the steady driver, read the table to judge quality and risk, and glance at the heatmap to learn whether the sessions are amplifying or canceling one another. Adjust the hours to your market and let the data tell you which session deserves your focus.
Flexi MA Heat ZonesOverview
Flexi MA Heat Zones is a powerful multi-timeframe visualization tool that helps traders easily identify trend strength, direction, and potential zones of confluence using multiple moving averages and dynamic heatmaps. The indicator plots up to three pairs of customizable moving averages, with color-coded heat zones to highlight bullish and bearish conditions at a glance.
Whether you're a trend follower, mean-reversion trader, or looking for visual confirmation zones, this indicator is designed to offer deep insights with high customizability.
⚙️ Key Features
🔄 Supports multiple MA types: Choose from EMA, SMA, WMA, VWMA to suit your strategy.
🎯 Six moving averages: Three MA pairs (MA1-MA2, MA3-MA4, MA5-MA6), each with independent lengths and colors.
🌈 Heatmap Zones: Dynamic fills between MA pairs, changing color based on bullish or bearish alignment.
👁️🗨️ Full customization: Enable/disable any MA pair and its heatmap zone from the settings.
🪞 Transparency controls: Adjust the visibility of heat zones for clarity or stylistic preference.
🎨 Color-coded for clarity: Bullish and bearish colors for each heat zone pair, fully user-configurable.
🧩 Efficient layout: Smart use of grouped inputs for easier configuration and visibility management.
📈 How to Use
Use the MA1–MA2 and MA3–MA4 zones for longer-term trend tracking and confluence analysis.
Use the faster MA5–MA6 zone for short-term micro-trend identification or scalping.
When a faster MA is above the slower one within a pair, the fill turns bullish (user-defined color).
When the faster MA is below the slower one, the fill turns bearish.
Combine with price action or other indicators for entry/exit confirmation.
🧠 Pro Tips
For trend-following strategies, consider using EMA or WMA types.
For mean-reversion or support/resistance zones, SMA and VWMA may offer better zone clarity.
Overlay with RSI, MACD, or custom entry signals for higher confidence setups.
Use different heatmap transparencies to visually separate overlapping MA zones.
Bubbles Volume [BigBeluga]The Bubbles Volume indicator is an innovative visualization tool designed to represent trading volume in a more intuitive and visually appealing manner. By displaying volume as bubbles of varying sizes and colors on the price chart, this indicator helps traders quickly identify significant volume levels and potential areas of interest.
Important Note:
For correct visual representation of indicator, layout it to front:
🔵 KEY FEATURES
● Volume Bubbles
Represents trading volume as bubbles on the price chart
Bubble size increases with higher volume levels
Color intensity changes based on volume significance
Provides an intuitive visual representation of volume distribution
● Heatmap Coloring
Optional feature to color bubbles based on volume intensity
Uses a color gradient from cool (low volume) to hot (high volume) colors
Helps quickly identify extremely high volume areas
● Significant Volume Levels
Option to display horizontal lines at significant volume levels
Shows volume amount as labels for highly significant levels
Helps identify potential support/resistance areas based on volume
Volume Levels:
Levels with HeatMap:
Levels without Volume Bubles:
● Normalized Volume Calculation
Uses normalized volume to account for overall market volume trends
Provides a more accurate representation of volume significance
🔵 HOW TO USE
● Volume Analysis
Larger bubbles indicate higher trading volume
Clusters of large bubbles may suggest areas of high interest or potential reversals
Use in conjunction with price action to identify potential breakouts or fakeouts
● Trend Confirmation
Strong trends often show increasing bubble sizes in the trend direction
Diminishing bubble sizes might indicate weakening trends
● Support and Resistance
Significant volume levels (displayed as lines) can act as potential support/resistance
Pay attention to price reactions at these levels for trading opportunities
● Divergences
Look for divergences between price action and bubble sizes
Price making new highs/lows with smaller bubbles might indicate weakening momentum
● Volatility Assessment
Periods with consistently large bubbles indicate high volatility
Can be used to adjust trading strategies or position sizing
🔵 CUSTOMIZATION
The Bubbles Volume indicator offers several customization options:
Toggle bubble display on/off
Adjust volume threshold for filtering low volume bubbles
Enable/disable heatmap coloring for enhanced visual analysis
Show/hide significant volume levels
Adjust the number of significant levels displayed
Customize colors to suit personal preferences
By fine-tuning these settings, traders can adapt the indicator to various market conditions and personal analysis preferences.
The Bubbles Volume indicator provides a unique and intuitive way to visualize trading volume directly on the price chart. This approach allows traders to quickly identify areas of significant trading activity and potential price levels of interest without the need for a separate volume sub-chart.
This tool can be particularly useful for traders focusing on volume analysis, breakout strategies, or those looking to confirm price action with volume. The visual nature of the bubbles makes it easy to spot volume patterns and anomalies at a glance, potentially leading to faster and more informed trading decisions.
As with all technical indicators, it's recommended to use the Bubbles Volume indicator in conjunction with other forms of analysis and within the context of a well-defined trading strategy. While this indicator provides valuable volume insights, it should be considered alongside other factors such as overall market trends, price patterns, and fundamental analysis when making trading decisions.
Activity and Volume Orderflow Profile [AlgoAlpha]🔍 Activity and Volume Orderflow Profile 📊
🚀 Unlock the power of market order flow analysis with the Activity and Volume Orderflow Profile indicator by AlgoAlpha . This versatile tool helps you visualize and understand the dynamics of buying and selling pressure within a specified lookback period. Perfect for traders who want to dig deeper into volume-based market insights!
Key Features:
📊 Profile Type Options : Choose between "Comparison" and "Net Order Flow" to analyze market activity based on your preferred method.
🔎 Adjustable Lookback Period : Customize the lookback period to fit your trading strategy.
🎨 Flexible Appearance Settings : Toggle the display of the profile, lookback period visualization, and heatmap to suit your preferences.
🖍 Color Customization : Set your preferred colors for up and down volumes.
🕹 High Activity Highlight : Use the minimum transparency setting to highlight areas of significant activity.
Quick Guide to Using the Activity and Volume Orderflow Profile
🛠 Add the Indicator: Add the indicator to your favorites. Customize settings like profile type, lookback period, and resolution to fit your trading style.
📊 Market Analysis: Use the profile to identify areas of high buying or selling pressure. In "Comparison" mode, look for significant volume differences; in "Net Order Flow" mode, focus on net volume changes. Additionally, you can use the activity heatmap to find key levels that can act as support and resistance as price is likely to react to the zones as indicated by the heatmap.
How it Works:
The indicator operates by first gathering data on high and low prices, as well as buy and sell volumes, over a user-defined lookback period. It then calculates the maximum and minimum prices during this period and divides this range into bins based on the chosen resolution. For each bin, it computes the total volume of buy and sell orders. In "Comparison" mode, it displays side-by-side boxes representing buy and sell volumes, while in "Net Order Flow" mode, it shows the net volume difference. The indicator visually presents these profiles on the chart with customizable colors, transparency levels, and the option to display a heatmap for enhanced volume activity insights.
Maximize your trading with the Activity and Volume Orderflow Profile from AlgoAlpha! 🚀✨
Order Flow: Structural Sniper [Profile + Signals]Overview
This script is a comprehensive tool designed to bridge the gap between Market Structure and Order Flow analysis. It aims to eliminate the subjectivity of static support and resistance lines by focusing on dynamic liquidity and the behavior of aggressive versus passive market participants.
Unlike traditional indicators that plot static data, the Structural Delta Map dynamically anchors its analysis to the start of the current trend (Pivots), providing a clear "X-Ray" view of how volume was distributed during the current price swing.
How it Works
The indicator combines three distinct technical concepts into a single system:
1. Market Structure (Pivots):
It uses a pivot detection algorithm to identify significant Swing Highs and Swing Lows. This determines the market bias and anchors the analysis to the origin of the movement.
2. Anchored VWAP (Fair Price):
It automatically calculates the Volume Weighted Average Price (VWAP) starting from the last confirmed pivot. This yellow line acts as the "spine" of the trend, serving as dynamic institutional support/resistance.
3. Delta Profile & Heatmap:
A Volume Profile is plotted on the left side, anchored to the pivot.
Split Delta: Instead of a single color, bars are split into Green (Buying Volume) and Red (Selling Volume) based on price action estimation.
Heatmap Logic: The opacity of the bars adjusts automatically. Bright/Solid bars represent High Volume Nodes (HVN), while transparent bars represent Low Volume Nodes (LVN) or liquidity voids.
How to Use (Strategy)
The indicator provides both visual context and specific entry signals:
1. Visual Context:
Profile: Look for reactions at bright, wide bars (High Volume Nodes). These act as magnets or barriers.
Yellow Line (VWAP): In an uptrend, look for buy opportunities when price retraces to this line. In a downtrend, look for shorts on the retest.
2. Aggression Signals (Triangle "AGR"):
Type: Trend Continuation / Pullback.
Logic: Triggers when price retraces to the structural value zone (near VWAP), rejects it with higher-than-average volume, and closes in the direction of the trend.
3. Absorption Signals (Cross "ABS"):
Type: Reversal / Trap.
Logic:
Bullish Absorption: Price makes a new local low with high volume (selling pressure), but the candle closes bullish (leaving a long bottom wick). Passive buyers absorbed the aggression.
Bearish Absorption: Price makes a new local high with high volume, but closes bearish. Passive sellers absorbed the buying pressure.
Settings
Pivot Sensitivity: Adjusts how the script detects trend changes.
Profile Resolution: Controls the number of rows in the histogram.
Signal Filters: Enable/Disable signals and adjust the Volume Multiplier threshold.
Technical Disclaimer
This indicator estimates "Delta" (Buy vs. Sell volume) based on OHLC price action and bar volume, as Pine Script does not grant access to historical tick-by-tick data. While this approximation is highly effective for identifying aggression and absorption, it differs slightly from Level 2 footprint data found on platforms like Sierra Chart. Accuracy depends on the volume data provided by your exchange.
Multi-Distribution Volume Profile (Zeiierman)█ Overview
Multi-Distribution Volume Profile (Zeiierman) is a flexible, structure-first volume profile tool that lets you reshape how volume is distributed across price, from classic uniform profiles to advanced statistical curves like Gaussian, Lognormal, Student-t, and more.
Instead of forcing every market into a single "one-size-fits-all" profile, this tool lets you model how volume is likely concentrated inside each bar (body vs wicks, midpoint, tails, center bias, right-skew, heavy tails, etc.) and then stacks that behavior across a whole lookback window to build a rich, multi-distribution map of traded activity.
On top of that, it overlays a dynamic Center Band (value area) and a fade/gradient model that can color each price row by volume, hits, recency, volatility, reversals, or even liquidity voids, turning a plain profile into a multi-dimensional context map.
Highlights
Choose from multiple Profile Build Modes , including uniform, body-only, wick-only, midpoint/close/open, center-weighted, and a suite of probability-style distributions (Gaussian, Lognormal, Weibull, Student-t, etc.)
Flexible anchor layout: draw the profile on Right/Left (horizontal) or Bottom/Top (vertical) to fit any chart layout
Value Area / Center Band computed from volume quantiles around the POC.
Gradient-based Fade Metrics: volume, price hits, freshness (time decay), volatility impact, dwell time, reversal density, compression, and liquidity voids
Separate bullish vs bearish volume at each price row for directional structure insights
█ How It Works
⚪ Profile Construction
The script scans a user-defined Bars Included window and finds the full high–low span of that zone. It then divides this range into a user-controlled number of Price Levels (rows).
For each historical bar within the window:
It measures the candle’s price range, body, and wicks.
It assigns volume to rows according to the selected Profile Build Mode, for example:
* Range Uniform – volume spread evenly across the full high–low range.
* Range Body Only / Range Wick Only – concentrate volume inside the body or wicks only.
* Midpoint / Close / Open Only – allocate volume entirely into one price row (pinpoint modeling).
HL2 / Body Center Weighted – center weights around the middle of the range/body.
Recent-Weighted Volume – amplify newer bars using exponential time decay.
Volume Squared (Hard) – aggressively boost bars with large volume.
Up Bars Only / Down Bars Only – filter volume to only bullish or bearish bars.
For more advanced shapes, the script uses continuous distributions across the bar’s span:
Linear, Triangular, Exponential to High
Cosine Centered, PERT
Gaussian, Lognormal, Cauchy, Laplace
Pareto, Weibull, Logistic, Gumbel
Gamma, Beta, Chi-Square, Student-t, F-Shape
Each distribution produces a weight for each row within the bar’s range, normalized so the total volume remains consistent, but the shape of where that volume lands changes.
⚪ POC & Center Band (Value Area)
Once all rows are accumulated:
The row with the highest total volume becomes the Point of Control (POC)
The script computes cumulative volume and finds the band that wraps a user-defined Center of Profile % (e.g., 68%) around the center of distribution.
This range is displayed as a central band, often treated like a value area where price has spent the most “effort” trading.
⚪ Gradient Fade Engine
Each row also gets a fade metric, chosen in Fade Metric:
Volume – opacity based on relative volume.
Price Hits – how frequently that row was touched.
Blended (Vol+Hits) – average of volume & hits.
Freshness – emphasizes recent activity, controlled by Decay.
Volatility Impact – rows that saw larger ranges contribute more.
Dwell Time – where price “camped” the longest.
Reversal Density – where direction changes cluster.
Compression – tight-range compression zones.
Liquidity Void – inverse of volume (thin liquidity zones).
When Apply Gradient is enabled, the row’s bullish/bearish colors are tinted from faint to strong based on this chosen metric, effectively turning the profile into a heatmap of your chosen structural property.
█ How to Use
⚪ Explore Different Distribution Assumptions
Switch between multiple Profile Build Modes to see how your assumptions about intrabar volume affect structure:
Use Range Uniform for classical profile reading.
Deploy Gaussian, Logistic, or Cosine shapes to emphasize central clustering.
Try Pareto, Lognormal, or F-Shape to focus on tail / extremal activity.
Use Recent-Weighted Volume to prioritize the most recent structural behavior.
This is especially useful for traders who want to test how different modeling assumptions change perceived value areas and levels of interest.
⚪ Identify Value, Acceptance & Rejection Zones
Use the POC and Center of Profile (%) band to distinguish:
High-acceptance zones – wide central band, thick rows, strong gradient → fair value areas
Rejection zones & tails – thin extremes, low dwell time, high volatility or reversal density
These regions can be used as:
Targets and origin zones for mean reversion
Context for breakout validation (leaving value)
Bias reference for intraday rotations or swing rotations
⚪ Read Directional Structure Within the Profile
Because each row is split into bullish vs bearish contributions, you can visually read:
Where buyers dominated a price region (large bullish slice)
Where sellers absorbed or defended (large bearish slice)
Combining this with Fade Metrics like Reversal Density, Dwell Time, or Freshness turns the profile into a structural order-flow map, without needing raw tick-by-tick volume data.
⚪ Use Fade Metrics for Contextual Heatmaps
Each Fade Metric can be used for a different analytical lens:
Volume / Blended – emphasize where volume and activity are concentrated.
Freshness – highlight the most recently active zones that still matter.
Volatility Impact & Compression – spot areas of explosive moves vs coiled ranges.
Reversal Density – locate micro turning points and battle zones.
Liquidity Void – visually pop out thin regions that may act as speedways or magnets.
█ Settings
Profile Build Mode – Selects how each bar’s volume is distributed across its price range (uniform, body/wick, midpoint/close/open, center-weighted, or statistical distribution families).
Bars Included – Number of bars used to build the profile from the current bar backward.
Price Levels – Vertical resolution of the profile: more levels = smoother but heavier.
Anchor Side – Where the profile is drawn on the chart: Right, Left, Bottom, or Top.
Offset (bars) – Horizontal offset from the last bar to the profile when using Right/Left modes.
Apply Gradient – Toggles the fade/heatmap coloring based on the selected metric.
Fade Metric – Chooses the property driving row opacity (Volume, Hits, Freshness, Volatility Impact, Dwell Time, Reversal Density, Compression, Liquidity Void).
Decay – Time-decay factor for Freshness (values close to 1 keep older activity relevant for longer).
Profile Thickness – Relative thickness of the profile along the time axis, as a % of the lookback window.
Center of Profile (%) – Volume percentage used to define the central band (value area) around the POC.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Obsidian Flux Matrix# Obsidian Flux Matrix | JackOfAllTrades
Made with my Senior Level AI Pine Script v6 coding bot for the community!
Narrative Overview
Obsidian Flux Matrix (OFM) is an open-source Pine Script v6 study that fuses social sentiment, higher timeframe trend bias, fair-value-gap detection, liquidity raids, VWAP gravitation, session profiling, and a diagnostic HUD. The layout keeps the obsidian palette so critical overlays stay readable without overwhelming a price chart.
Purpose & Scope
OFM focuses on actionable structure rather than marketing claims. It documents every driver that powers its confluence engine so reviewers understand what triggers each visual.
Core Analytical Pillars
1. Social Pulse Engine
Sentiment Webhook Feed: Accepts normalized scores (-1 to +1). Signals only arm when the EMA-smoothed value exceeds the `sentimentMin` input (0.35 by default).
Volume Confirmation: Requires local volume > 30-bar average × `volSpikeMult` (default 2.0) before sentiment flags.
EMA Cross Validation: Fast EMA 8 crossing above/below slow EMA 21 keeps momentum aligned with flow.
Momentum Alignment: Multi-timeframe momentum composite must agree (positive for longs, negative for shorts).
2. Peer Momentum Heatmap
Multi-Timeframe Blend: RSI + Stoch RSI fetched via request.security() on 1H/4H/1D by default.
Composite Scoring: Each timeframe votes +1/-1/0; totals are clamped between -3 and +3.
Intraday Readability: Configurable band thickness (1-5) so scalpers see context without losing space.
Dynamic Opacity: Stronger agreement boosts column opacity for quick bias checks.
3. Trend & Displacement Framework
Dual EMA Ribbon: Cyan/magenta ribbon highlights immediate posture.
HTF Bias: A higher-timeframe EMA (default 55 on 4H) sets macro direction.
Displacement Score: Body-to-ATR ratio (>1.4 default) detects impulses that seed FVGs or VWAP raids.
ATR Normalization: All thresholds float with volatility so the study adapts to assets and regimes.
4. Intelligent Fair Value Gap (FVG) System
Gap Detection: Three-candle logic (bullish: low > high ; bearish: high < low ) with ATR-sized minimums (0.15 × ATR default).
Overlap Prevention: Price-range checks stop redundant boxes.
Spacing Control: `fvgMinSpacing` (default 5) avoids stacking from the same impulse.
Storage Caps: Max three FVGs per side unless the user widens the limit.
Session Awareness: Kill zone filters keep taps focused on London/NY if desired.
Auto Cleanup: Boxes delete when price closes beyond their invalidation level.
5. VWAP Magnet + Liquidity Raid Engine
Session or Rolling VWAP: Toggle resets to match intraday or rolling preferences.
Equal High/Low Scanner: Looks back 20 bars by default for liquidity pools.
Displacement Filter: ATR multiplier ensures raids represent genuine liquidity sweeps.
Mean Reversion Focus: Signals fire when price displaces back toward VWAP following a raid.
6. Session Range Breakout System
Initial Balance Tracking: First N bars (15 default) define the session box.
Breakout Logic: Requires simultaneous liquidity spikes, nearby FVG activity, and supportive momentum.
Z-Score Volume Filter: >1.5σ by default to filter noisy moves.
7. Lifestyle Liquidity Scanner
Volume Z-Scores: 50-bar baseline highlights statistically significant spikes.
Smart Money Footprints: Bottom-of-chart squares color-code buy vs sell participation.
Panel Memory: HUD logs the last five raid timestamps, direction, and normalized size.
8. Risk Matrix & Diagnostic HUD
HUD Structure: Table in the top-right summarizes HTF bias, sentiment, momentum, range state, liquidity memory, and current risk references.
Signal Tags: Aggregates SPS, FVG, VWAP, Range, and Liquidity states into a compact string.
Risk Metrics: Swing-based stops (5-bar lookback) + ATR targets (1.5× default) keep risk transparent.
Signal Families & Alerts
Social Pulse (SPS): Volume-confirmed sentiment alignment; triangle markers with “SPS”.
Kill-Zone FVG: Session + HTF alignment + FVG tap; arrow markers plus SL/TP labels.
Local FVG: Captures local reversals when HTF bias has not flipped yet.
VWAP Raid: Equal-high/low raids that snap toward VWAP; “VWAP” label markers.
Range Breakout: Initial balance violations with liquidity and imbalance confirmation; circle markers.
Liquidity Spike: Z-score spikes ≥ threshold; square markers along the baseline.
Visual Design & Customization
Theme Palette: Primary background RGB (12,6,24). Accent shading RGB (26,10,48). Long accents RGB (88,174,255). Short accents RGB (219,109,255).
Stylized Candles: Optional overlay using theme colors.
Signal Toggles: Independently enable markers, heatmap, and diagnostics.
Label Spacing: Auto-spacing enforces ≥4-bar gaps to prevent text overlap.
Customization & Workflow Notes
Adjust ATR/FVG thresholds when volatility shifts.
Re-anchor sentiment to your webhook cadence; EMA smoothing (default 5) dampens noise.
Reposition the HUD by editing the `table.new` coordinates.
Use multiples of the chart timeframe for HTF requests to minimize load.
Session inputs accept exchange-local time; align them to your market.
Performance & Compliance
Pure Pine v6: Single-line statements, no `lookahead_on`.
Resource Safe: Arrays trimmed, boxes limited, `request.security` cached.
Repaint Awareness: Signals confirm on close; alerts mirror on-chart logic.
Runtime Safety: Arrays/loops guard against `na`.
Use Cases
Measure when social sentiment aligns with structure.
Plan ICT-style intraday rebalances around session-specific FVG taps.
Fade VWAP raids when displacement shows exhaustion.
Watch initial balance breaks backed by statistical volume.
Keep risk/target references anchored in ATR logic.
Signal Logic Snapshot
Social Pulse Long/Short: `sentimentEMA` gated by `sentimentMin`, `volSpike`, EMA 8/21 cross, and `momoComposite` sign agreement. Keeps hype tied to structural follow-through.
Kill-Zone FVG Long/Short: Requires session filter, HTF EMA bias alignment, and an active FVG tap (`bullFvgTap` / `bearFvgTap`). Labels include swing stops + ATR targets pulled from `swingLookback` and `liqTargetMultiple`.
Local FVG Long/Short: Uses `localBullish` / `localBearish` heuristics (EMA slope, displacement, sequential closes) to surface intraday reversals even when HTF bias has not flipped.
VWAP Raids: Detect equal-high/equal-low sweeps (`raidHigh`, `raidLow`) that revert toward `sessionVwap` or rolling VWAP when displacement exceeds `vwapAlertDisplace`.
Range Breakouts: Combine `rangeComplete`, breakout confirmation, liquidity spikes, and nearby FVG activity for statistically backed initial balance breaks.
Liquidity Spikes: Volume Z-score > `zScoreThreshold` logs direction, size, and timestamp for the HUD and optional review workflows.
Session Logic & VWAP Handling
Kill zone + NY session inputs use TradingView’s session strings; `f_inSession()` drives both visual shading and whether FVG taps are tradeable when `killZoneOnly` is true.
Session VWAP resets using cumulative price × volume sums that restart when the daily timestamp changes; rolling VWAP falls back to `ta.vwap(hlc3)` for instruments where daily resets are less relevant.
Initial balance box (`rangeBars` input) locks once complete, extends forward, and stays on chart to contextualize later liquidity raids or breakouts.
Parameter Reference
Trend: `emaFastLen`, `emaSlowLen`, `htfResolution`, `htfEmaLen`, `showEmaRibbon`, `showHtfBiasLine`.
Momentum: `tf1`, `tf2`, `tf3`, `rsiLen`, `stochLen`, `stochSmooth`, `heatmapHeight`.
Volume/Liquidity: `volLookback`, `volSpikeMult`, `zScoreLen`, `zScoreThreshold`, `equalLookback`.
VWAP & Sessions: `vwapMode`, `showVwapLine`, `vwapAlertDisplace`, `killSession`, `nySession`, `showSessionShade`, `rangeBars`.
FVG/Risk: `fvgMinTicks`, `fvgLookback`, `fvgMinSpacing`, `killZoneOnly`, `liqTargetMultiple`, `swingLookback`.
Visualization Toggles: `showSignalMarkers`, `showHeatmapBand`, `showInfoPanel`, `showStylizedCandles`.
Workflow Recipes
Kill-Zone Continuation: During the defined kill session, look for `killFvgLong` or `killFvgShort` arrows that line up with `sentimentValid` and positive `momoComposite`. Use the HUD’s risk readout to confirm SL/TP distances before entering.
VWAP Raid Fade: Outside kill zone, track `raidToVwapLong/Short`. Confirm the candle body exceeds the displacement multiplier, and price crosses back toward VWAP before considering reversions.
Range Break Monitor: After the initial balance locks, mark `rangeBreakLong/Short` circles only when the momentum band is >0 or <0 respectively and a fresh FVG box sits near price.
Liquidity Spike Review: When the HUD shows “Liquidity” timestamps, hover the plotted squares at chart bottom to see whether spikes were buy/sell oriented and if local FVGs formed immediately after.
Metadata
Author: officialjackofalltrades
Platform: TradingView (Pine Script v6)
Category: Sentiment + Liquidity Intelligence
Hope you Enjoy!
Auto-Adjusting Kalman Filter by TenozenNew year, new indicator! Auto-Adjusting Kalman Filter is an indicator designed to provide an adaptive approach to trend analysis. Using the Kalman Filter (a recursive algorithm used in signal processing), this algo dynamically adjusts to market conditions, offering traders a reliable way to identify trends and manage risk! In other words, it's a remaster of my previous indicator, Kalman Filter by Tenozen.
What's the difference with the previous indicator (Kalman Filter by Tenozen)?
The indicator adjusts its parameters (Q and R) in real-time using the Average True Range (ATR) as a measure of market volatility. This ensures the filter remains responsive during high-volatility periods and smooth during low-volatility conditions, optimizing its performance across different market environments.
The filter resets on a user-defined timeframe, aligning its calculations with dominant trends and reducing sensitivity to short-term noise. This helps maintain consistency with the broader market structure.
A confidence metric, derived from the deviation of price from the Kalman filter line (measured in ATR multiples), is visualized as a heatmap:
Green : Bullish confidence (higher values indicate stronger trends).
Red : Bearish confidence (higher values indicate stronger trends).
Gray : Neutral zone (low confidence, suggesting caution).
This provides a clear, objective measure of trend strength.
How it works?
The Kalman Filter estimates the "true" price by filtering out market noise. It operates in two steps, that is, prediction and update. Prediction is about projection the current state (price) forward. Update is about adjusting the prediction based on the latest price data. The filter's parameters (Q and R) are scaled using normalized ATR, ensuring adaptibility to changing market conditions. So it means that, Q (Process Noise) increases during high volatility, making the filter more responsive to price changes and R (Measurement Noise) increases during low volatility, smoothing out the filter to avoid overreacting to minor fluctuations. Also, the trend confidence is calculated based on the deviation of price from the Kalman filter line, measured in ATR multiples, this provides a quantifiable measure of trend strength, helping traders assess market conditions objectively.
How to use?
Use the Kalman Filter line to identify the prevailing trend direction. Trade in alignment with the filter's slope for higher-probability setups.
Look for pullbacks toward the Kalman Filter line during strong trends (high confidence zones)
Utilize the dynamic stop-loss and take-profit levels to manage risk and lock in profits
Confidence Heatmap provides an objective measure of market sentiment, helping traders avoid low-confidence (neutral) zones and focus on high-probability opportunities
Guess that's it! I hope this indicator helps! Let me know if you guys got some feedback! Ciao!
