Liquidity Sweep Filter [Magu]SMC The smart money concept in forex trading involves understanding the behavior of institutional players, such as banks and hedge funds, and analyzing supply and demand dynamics, order blocks, and price patterns.
SMC is often seen as a repackaged version of price action trading with a long history of producing positive results in various asset classes
Market liquidity is a fundamental concept in financial markets that significantly impacts trading strategies, asset pricing, and financial stability. The stock market is a prime example of a financial market where liquidity plays a crucial role in determining asset prices and trading strategies. Understanding market liquidity helps investors and traders make informed decisions, especially during times of market volatility. This article explores the key concepts, factors affecting liquidity, and strategies to navigate both liquid and illiquid markets
[i]price
Volume Cluster Heatmap [BackQuant]Volume Cluster Heatmap
A visualization tool that maps traded volume across price levels over a chosen lookback period. It highlights where the market builds balance through heavy participation and where it moves efficiently through low-volume zones. By combining a heatmap, volume profile, and high/low volume node detection, this indicator reveals structural areas of support, resistance, and liquidity that drive price behavior.
What Are Volume Clusters?
A volume cluster is a horizontal aggregation of traded volume at specific price levels, showing where market participants concentrated their buying and selling.
High Volume Nodes (HVN) : Price levels with significant trading activity; often act as support or resistance.
Low Volume Nodes (LVN) : Price levels with little trading activity; price moves quickly through these areas, reflecting low liquidity.
Volume clusters help identify key structural zones, reveal potential reversals, and gauge market efficiency by highlighting where the market is balanced versus areas of thin liquidity.
By creating heatmaps, profiles, and highlighting high and low volume nodes (HVNs and LVNs), it allows traders to see where the market builds balance and where it moves efficiently through thin liquidity zones.
Example: Bitcoin breaking away from the high-volume zone near 118k and moving cleanly through the low-volume pocket around 113k–115k, illustrating how markets seek efficiency:
Core Features
Visual Analysis Components:
Heatmap Display : Displays volume intensity as colored boxes, lines, or a combination for a dynamic view of market participation.
Volume Profile Overlay : Shows cumulative volume per price level along the right-hand side of the chart.
HVN & LVN Labels : Marks high and low volume nodes with color-coded lines and labels.
Customizable Colors & Transparency : Adjust high and low volume colors and minimum transparency for clear differentiation.
Session Reset & Timeframe Control : Dynamically resets clusters at the start of new sessions or chosen timeframes (intraday, daily, weekly).
Alerts
HVN / LVN Alerts : Notify when price reaches a significant high or low volume node.
High Volume Zone Alerts : Trigger when price enters the top X% of cumulative volume, signaling key areas of market interest.
How It Works
Each bar’s volume is distributed proportionally across the horizontal price levels it touches. Over the lookback period, this builds a cumulative volume profile, identifying price levels with the most and least trading activity. The highest cumulative volume levels become HVNs, while the lowest are LVNs. A side volume profile shows aggregated volume per level, and a heatmap overlay visually reinforces market structure.
Applications for Traders
Identify strong support and resistance at HVNs.
Detect areas of low liquidity where price may move quickly (LVNs).
Determine market balance zones where price may consolidate.
Filter noise: because volume clusters aggregate activity into levels, minor fluctuations and irrelevant micro-moves are removed, simplifying analysis and improving strategy development.
Combine with other indicators such as VWAP, Supertrend, or CVD for higher-probability entries and exits.
Use volume clusters to anticipate price reactions to breaking points in thin liquidity zones.
Advanced Display Options
Heatmap Styles : Boxes, lines, or both. Boxes provide a traditional heatmap, lines are better for high granularity data.
Line Mode Example : Simplified line visualization for easier reading at high level counts:
Profile Width & Offset : Adjust spacing and placement of the volume profile for clarity alongside price.
Transparency Control : Lower transparency for more opaque visualization of high-volume zones.
Best Practices for Usage
Reduce the number of levels when using line mode to avoid clutter.
Use HVN and LVN markers in conjunction with volume profiles to plan entries and exits.
Apply session resets to monitor intraday vs. multi-day volume accumulation.
Combine with other technical indicators to confirm high-probability trading signals.
Watch price interactions with LVNs for potential rapid movements and with HVNs for possible support/resistance or reversals.
Technical Notes
Each bar contributes volume proportionally to the price levels it spans, creating a dynamic and accurate representation of traded interest.
Volume profiles are scaled and offset for visual clarity alongside live price.
Alerts are fully integrated for HVN/LVN interaction and high-volume zone entries.
Optimized to handle large lookback windows and numerous price levels efficiently without performance degradation.
This indicator is ideal for understanding market structure, detecting key liquidity areas, and filtering out noise to model price more accurately in high-frequency or algorithmic strategies.
Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
ATH Levels v4# ATH Levels v4
A powerful indicator for tracking All-Time Highs (ATH) and setting customizable price levels based on percentage drops from the ATH. Perfect for cryptocurrency trading, DCA strategies, and risk management.
## Overview
ATH Levels v4 helps traders visualize key support levels calculated as percentage drops from the All-Time High within a configurable lookback period. The indicator also tracks the All-Time Low (ATL) since the last ATH, providing a complete picture of price range dynamics.
## Key Features
### Configurable Percentage Levels
- Define up to 8 custom price levels as percentage drops from ATH
- No longer limited to fixed 10% intervals
- Each level can be set anywhere from 0% to 100% drop
- Default levels: 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%
### ATL Tracking (NEW in v4)
- Automatically tracks the All-Time Low since the last ATH was reached
- Displays ATL price and percentage drop from ATH
- Resets when a new ATH is detected
- Can be toggled on/off
### Portfolio Management
- Allocate pot size percentages to each level
- Visualize dollar amounts for each level based on your total pot size
- Plan your DCA (Dollar Cost Averaging) strategy
- Only displays levels with allocated pot percentages
### Flexible Display Options
- Show/hide level lines
- Hide ATH level for zooming into lower levels
- Configurable lookback period (default 365 days)
- Adjustable right margin positioning for labels
- Color-coded labels with transparency gradient
## How to Use
### Basic Setup
1. Add the indicator to your chart
2. Set your total pot size in dollars
3. Configure the percentage drops for each level (where you want to buy/accumulate)
4. Allocate pot size percentages to each level
### Example DCA Strategy
```
Total Pot Size: $10,000
Level 3 (-30%): 10% pot = $1,000
Level 4 (-40%): 20% pot = $2,000
Level 5 (-50%): 25% pot = $2,500
Level 6 (-60%): 30% pot = $3,000
Level 7 (-70%): 10% pot = $1,000
Level 8 (-80%): 5% pot = $500
```
## Settings
### Display Options
- **Show level lines**: Toggle horizontal lines on/off
- **Hide ATH level**: Hide the ATH label for cleaner charts
- **Show ATL since last ATH**: Display/hide the All-Time Low indicator
- **Days to Lookback**: Period for calculating ATH (default: 365)
- **Margin from last bar**: Spacing between chart and labels (default: 10)
### Level Configuration
- **Level 1-8 % drop from ATH**: Set custom percentage drops (0-100%)
- **Level 1-8 pot %**: Allocate your portfolio percentage to each level (0-100%)
**Note**: Levels only display if they have a pot percentage allocated (>0%)
### Pot Size
- **Pot size**: Total amount in dollars available for the strategy
## Version History
### V4 (October 2025)
- Upgraded to PineScript v6
- Configurable percentage drops from ATH (no longer hardcoded)
- ATL tracking and display since last ATH
- Updated syntax and functions for v6 compatibility
### V3 (May 2020)
- Added option to hide ATH level for better chart zoom
### V2
- Hide/show level lines
- Configurable lookback period
- Configurable right margin
- Only shows levels with pot size % set
### V1
- Initial release with 8 fixed levels
## Use Cases
### Cryptocurrency Trading
- Plan accumulation zones during bear markets
- Set alerts at key percentage drops from ATH
- Track historical ATH and ATL ranges
### Risk Management
- Visualize potential support zones
- Plan position sizing at different levels
- Monitor distance from ATH in real-time
### DCA Strategies
- Automate dollar-cost averaging planning
- Allocate budget across multiple price levels
- Track execution of your DCA plan
## Technical Details
- **Version**: PineScript v6
- **Type**: Indicator
- **Overlay**: Yes
- **Default Timeframe**: Works on all timeframes
- **Calculations**: Based on closing prices within lookback period
## Credits
Original concept inspired by daytask. Enhanced and maintained by SilvesterScorpion.com
## License
This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
---
**Tip**: For best results, use on higher timeframes (4H, Daily, Weekly) to identify major support zones. Combine with volume analysis and other indicators for confirmation.
Volume Sampled Supertrend [BackQuant]Volume Sampled Supertrend
A Supertrend that runs on a volume sampled price series instead of fixed time. New synthetic bars are only created after sufficient traded activity, which filters out low participation noise and makes the trend much easier to read and model.
Original Script Link
This indicator is built on top of my volume sampling engine. See the base implementation here:
Why Volume Sampling
Traditional charts print a bar every N minutes regardless of how active the tape is. During quiet periods you accumulate many small, low information bars that add noise and whipsaws to downstream signals.
Volume sampling replaces the clock with participation. A new synthetic bar is created only when a pre-set amount of volume accumulates (or, in Dollar Bars mode, when pricevolume reaches a dollar threshold). The result is a non-uniform time series that stretches in busy regimes and compresses in quiet regimes. This naturally:
filters dead time by skipping low volume chop;
standardizes the information content per bar, improving comparability across regimes;
stabilizes volatility estimates used inside banded indicators;
gives trend and breakout logic cleaner state transitions with fewer micro flips.
What this tool does
It builds a synthetic OHLCV stream from volume based buckets and then applies a Supertrend to that synthetic price. You are effectively running Supertrend on a participation clock rather than a wall clock.
Core Features
Sampling Engine - Choose Volume buckets or Dollar Bars . Thresholds can be dynamic from a rolling mean or median, or fixed by the user.
Synthetic Candles - Plots the volume sampled OHLC candles so you can visually compare against regular time candles.
Supertrend on Synthetic Price - ATR bands and direction are computed on the sampled series, not on time bars.
Adaptive Coloring - Candle colors can reflect side, intensity by volume, or a neutral scheme.
Research Panels - Table shows total samples, current bucket fill, threshold, bars-per-sample, and synthetic return stats.
Alerts - Long and Short triggers on Supertrend direction flips for the synthetic series.
How it works
Sampling
Pick Sampling Method = Volume or Dollar Bars.
Set the dynamic threshold via Rolling Lookback and Filter (Mean or Median), or enable Use Fixed and type a constant.
The script accumulates volume (or pricevolume) each time bar. When the bucket reaches the threshold, it finalizes one or more synthetic candles and resets accumulation.
Each synthetic candle stores its own OHLCV and is appended to the synthetic series used for all downstream logic.
Supertrend on the sampled stream
Choose Supertrend Source (Open, High, Low, Close, HLC3, HL2, OHLC4, HLCC4) derived from the synthetic candle.
Compute ATR over the synthetic series with ATR Period , then form upperBand = src + factorATR and lowerBand = src - factorATR .
Apply classic trailing band and direction rules to produce Supertrend and trend state.
Because bars only come when there is sufficient participation, band touches and flips tend to align with meaningful pushes, not idle prints.
Reading the display
Synthetic Volume Bars - The non-uniform candles that represent equal information buckets. Expect more candles during active sessions and fewer during lulls.
Volume Sampled Supertrend - The main line. Green when Trend is 1, red when Trend is -1.
Markers - Small dots appear when a new synthetic sample is created, useful for aligning activity cycles.
Time Bars Overlay (optional) - Plot regular time candles to compare how the synthetic stream compresses quiet chop.
Settings you will use most
Data Settings
Sampling Method - Volume or Dollar Bars.
Rolling Lookback and Filter - Controls the dynamic threshold. Median is robust to outliers, Mean is smoother.
Use Fixed and Fixed Threshold - Force a constant bucket size for consistent sampling across regimes.
Max Stored Samples - Ring buffer limit for performance.
Indicator Settings
SMA over last N samples - A moving average computed on the synthetic close series. Can be hidden for a cleaner layout.
Supertrend Source - Price field from the synthetic candle.
ATR Period and Factor - Standard Supertrend controls applied on the synthetic series.
Visuals and UI
Show Synthetic Bars - Turn synthetic candles on or off.
Candle Color Mode - Green/Red, Volume Intensity, Neutral, or Adaptive.
Mark new samples - Puts a dot when a bucket closes.
Show Time Bars - Overlay regular candles for comparison.
Paint candles according to Trend - Colors chart candles using current synthetic Supertrend direction.
Line Width , Colors , and Stats Table toggles.
Some workflow notes:
Trend Following
Set Sampling Method = Volume, Filter = Median, and a reasonable Rolling Lookback so busy regimes produce more samples.
Trade in the direction of the Volume Sampled Supertrend. Because flips require real participation, you tend to avoid micro whipsaws seen on time bars.
Use the synthetic SMA as a bias rail and trailing reference for partials or re-entries.
Breakout and Continuation
Watch for rapid clustering of new sample markers and a clean flip of the synthetic Supertrend.
The compression of quiet time and expansion in busy bursts often makes breakouts more legible than on uniform time charts.
Mean Reversion
In instruments that oscillate, faded moves against the synthetic Supertrend are easier to time when the bucket cadence slows and Supertrend flattens.
Combine with the synthetic SMA and return statistics in the table for sizing and expectation setting.
Stats table (top right)
Method and Total Samples - Sampling regime and current synthetic history length.
Current Vol or Dollar and Threshold - Live bucket fill versus the trigger.
Bars in Bucket and Avg Bars per Sample - How much time data each synthetic bar tends to compress.
Avg Return and Return StdDev - Simple research metrics over synthetic close-to-close changes.
Why this reduces noise
Time based bars treat a 5 minute print with 1 percent of average participation the same as one with 300 percent. Volume sampling equalizes bar information content. By advancing the bar only when sufficient activity occurs, you skip low quality intervals that add variance but little signal. For banded systems like Supertrend, this often means fewer false flips and cleaner runs.
Notes and tips
Use Dollar Bars on assets where nominal price varies widely over time or across symbols.
Median filter can resist single burst outliers when setting dynamic thresholds.
If you need a stable research baseline, set Use Fixed and keep the threshold constant across tests.
Enable Show Time Bars occasionally to sanity check what the synthetic stream is compressing or stretching.
Link again for reference
Original Volume Based Sampling engine:
Bottom line
When you let participation set the clock, your Supertrend reacts to meaningful flow instead of idle prints. The result is a cleaner state machine, fewer micro whipsaws, and a trend read that respects when the market is actually trading.
Volume x Close in CroresThis indicator provides a clear visualization of the monetary volume activity for each candle by calculating the product of trading volume and closing price and converting it into crores for easier readability.
Cumulative Volume Delta Profile and Heatmap [BackQuant]Cumulative Volume Delta Profile and Heatmap
A multi-view CVD workstation that measures buying vs selling pressure, renders a price-aligned CVD profile with Point of Control, paints an optional heatmap of delta intensity, and detects classical CVD divergences using pivot logic. Built for reading who is in control, where participation clustered, and when effort is failing to produce result.
What is CVD
Cumulative Volume Delta accumulates the difference between aggressive buys and aggressive sells over time. When CVD rises, buyers are lifting the offer more than sellers are hitting the bid. When CVD falls, the opposite is true. Plotting CVD alongside price helps you judge whether price moves are supported by real participation or are running on fumes.
Core Features
Visual Analysis Components
CVD Columns - Plot of cumulative delta, colored by side, for quick read of participation bias.
CVD Profile - Price-aligned histogram of CVD accumulation using user-set bins. Shows where net initiative clustered.
Split Buy and Sell CVD - Optional two-sided profile that separates positive and negative CVD into distinct wings.
POC - Point of Control - The price level with the highest absolute CVD accumulation, labeled and line-marked.
Heatmap - Semi-transparent blocks behind price that encode CVD intensity across the last N bars.
Divergence Engine - Pivot-based detection of Bearish and Bullish CVD divergences with optional lines and labels.
Stats Panel - Top level metrics: Total CVD, Buy and Sell totals with percentages, Delta Ratio, and current POC price.
How it works
Delta source and sampling
You select an Anchor Timeframe that defines the higher time aggregation for reading the trend of CVD.
The script pulls lower timeframe volume delta and aggregates it to the anchor window. You can let it auto-select the lower timeframe or force a custom one.
CVD is then accumulated bar by bar to form a running total. This plot shows the direction and persistence of initiative.
Profile construction
The recent price range is split into Profile Granularity bins.
As price traverses a bin, the current delta contribution is added to that bin.
If Split Buy and Sell CVD is enabled, positive CVD goes to the right wing and negative CVD to the left wing.
Widths are scaled by each side’s maximum so you can compare distribution shape at a glance.
The Point of Control is the bin with the highest absolute CVD. This marks where initiative concentrated the most.
Heatmap
For each bin, the script computes intensity as absolute CVD relative to the maximum bin value.
Color is derived from the side in control in that bin and shaded by intensity.
Heatmap Length sets how far back the panels extend, highlighting recurring participation zones.
Divergence model
You define pivot sensitivity with Pivot Left and Right .
Bearish divergence triggers when price confirms a higher high while CVD fails to make a higher high within a configurable Delta Tolerance .
Bullish divergence triggers when price confirms a lower low while CVD fails to make a lower low.
On trigger, optional link lines and labels are drawn at the pivots for immediate context.
Key Settings
Delta Source
Anchor Timeframe - Higher TF for the CVD narrative.
Custom Lower TF and Lower Timeframe - Force the sampling TF if desired.
Pivot Logic
Pivot Left and Right - Bars to each side for swing confirmation.
Delta Tolerance - Small allowance to avoid near-miss false positives.
CVD Profile
Show CVD Profile - Toggle profile rendering.
Split Buy and Sell CVD - Two-sided profile for clearer side attribution.
Show Heatmap - Project intensity panels behind price.
Show POC and POC Color - Mark the dominant CVD node.
Profile Granularity - Number of bins across the visible price range.
Profile Offset and Profile Width - Position and scale the profile.
Profile Position - Right, Left, or Current bar alignment.
Visuals
Bullish Div Color and Bearish Div Color - Colors for divergence artifacts.
Show Divergence Lines and Labels - Visualize pivots and annotations.
Plot CVD - Column plot of total CVD.
Show Statistics and Position - Toggle and place the summary table.
Reading the display
CVD columns
Rising CVD confirms buyers are in control. Falling CVD confirms sellers.
Flat or choppy CVD during wide price moves hints at passive or exhausted participation.
CVD profile wings
Thick right wing near a price zone implies heavy buy initiative accumulated there.
Thick left wing implies heavy sell initiative.
POC marks the strongest initiative node. Expect reactions on first touch and rotations around this level when the tape is balanced.
Heatmap
Brighter blocks indicate stronger historical net initiative at that price.
Stacked bright bands form CVD high volume nodes. These often behave like magnets or shelves for future trade.
Divergences
Bearish - Price prints a higher high while CVD fails to do so. Effort is not producing result. Potential fade or pause.
Bullish - Price prints a lower low while CVD fails to do so. Capitulation lacks initiative. Potential bounce or reversal.
Stats panel
Total CVD - Net initiative over the window.
Buy and Sell volume with percentages - Side composition.
Delta Ratio - Buy over Sell. Values above 1 favor buyers, below 1 favor sellers.
POC Price - Current control node for plan and risk.
Workflows
Trend following
Choose an Anchor Timeframe that matches your holding period.
Trade in the direction of CVD slope while price holds above a bullish POC or below a bearish POC.
Use pullbacks to CVD nodes on your profile as entry locations.
Trend weakens when price makes new highs but CVD stalls, or new lows while CVD recovers.
Mean reversion
Look for divergences at or near prior CVD nodes, especially the POC.
Fade tests into thick wings when the side that dominated there now fails to push CVD further.
Target rotations back toward the POC or the opposite wing edge.
Liquidity and execution map
Treat strong wings and heatmap bands as probable passive interest zones.
Expect pauses, partial fills, or flips at these shelves.
Stops make sense beyond the far edge of the active wing supporting your idea.
Alerts included
CVD Bearish Divergence and CVD Bullish Divergence.
Price Cross Above POC and Price Cross Below POC.
Extreme Buy Imbalance and Extreme Sell Imbalance from Delta Ratio.
CVD Turn Bullish and CVD Turn Bearish when net CVD crosses zero.
Price Near POC proximity alert.
Best practices
Use a higher Anchor Timeframe to stabilize the CVD story and a sensible Profile Granularity so wings are readable without clutter.
Keep Split mode on when you want to separate initiative attribution. Turn it off when you prefer a single net profile.
Tune Pivot Left and Right by instrument to avoid overfitting. Larger values find swing divergences. Smaller values find micro fades.
If volume is thin or synthetic for the symbol, CVD will be less reliable. The script will warn if volume is zero.
Trading applications
Context - Confirm or question breakouts with CVD slope.
Location - Build entries at CVD nodes and POC.
Timing - Use divergence and POC crosses for triggers.
Risk - Place stops beyond the opposite wing or outside the POC shelf.
Important notes and limits
This is a price and volume based study. It does not access off-book or venue-level order flow.
CVD profiles are built from the data available on your chart and the chosen lower timeframe sampling.
Like all volume tools, readings can distort during roll periods, holidays, or feed anomalies. Validate on your instrument.
Technical notes
Delta is aggregated from a lower timeframe into an Anchor Timeframe narrative.
Profile bins update in real time. Splitting by side scales each wing independently so both are readable in the same panel.
Divergences are confirmed using standard pivot definitions with user-set tolerances.
All profile drawing uses fixed X offsets so panels and POC do not swim when you scroll.
Quick start
Anchor Timeframe = Daily for intraday context.
Split Buy and Sell CVD = On.
Profile Granularity = 100 to 200, Profile Position = Right, Width to taste.
Pivot Left and Right around 8 to 12 to start, then adapt.
Turn on Heatmap for a fast map of interest bands.
Bottom line
CVD tells you who is doing the lifting. The profile shows where they did it. Divergences tell you when effort stops paying. Put them together and you get a clear read on control, location, and timing for both trend and mean reversion.
Stop Loss and TargetsEnter your purchase price, SL% and up to 3x TP%s. Automatically plots them on your chart to enable quicker set up of alerts.
VWAP Deviation Oscillator [BackQuant]VWAP Deviation Oscillator
Introduction
The VWAP Deviation Oscillator turns VWAP context into a clean, tradeable oscillator that works across assets and sessions. It adapts to your workflow with four VWAP regimes plus two rolling modes, and three deviation metrics: Percent, Absolute, and Z-Score. Colored zones, optional standard deviation rails, and flexible plot styles make it fast to read for both trend following and mean reversion.
What it does
This tool measures how far price is from a chosen VWAP and expresses that gap as an oscillator. You can view the deviation as raw price units, percent, or standardized Z-Score. The plot can be a histogram or a line with optional fills and sigma bands, so you can quickly spot polarity shifts, overbought and oversold conditions, and strength of extension.
VWAP modes track a session VWAP that resets (4H, Daily, Weekly) or a rolling VWAP that updates continuously over a fixed number of bars or days.
Deviation modes let you choose the lens: Percent, Absolute, or Z-Score. Each highlights different aspects of stretch and mean pressure.
Visual encoding uses a 10-zone color palette to grade the magnitude of deviation on both sides of zero.
Volatility guards compute mode-specific sigma so thresholds are stable even when volatility compresses.
Why this works
VWAP is a high signal anchor used by institutions to gauge fair participation. Deviations around VWAP cluster in regimes: mild oscillations within a band, decisive pushes that signal imbalance, and standardized extremes that often precede either continuation or snapback. Expressing that distance as a single time series adds clarity: bias is the oscillator’s sign, risk context is its magnitude, and regime is the way it behaves around sigma lines.
How to use it
Trend following
Favor the side of the zero line. Bullish when the oscillator is above zero and making higher swing highs. Bearish when below zero and making lower swing lows. Use +1 sigma and +2 sigma in your mode as strength tiers. Pullbacks that hold above zero in uptrends, or below zero in downtrends, are often continuation entries.
Mean reversion
Fade stretched readings when structure supports it. Look for tests of +2 sigma to +3 sigma that fail to progress and roll back toward zero, or the mirror on the downside. Z-Score mode is best when you want standardized gates across assets. Percent mode is intuitive for intraday scalps where a given percent stretch tends to mean revert.
Session playbook
Use Daily or Weekly VWAP for intraday or swing context. Rolling modes help when the asset lacks clean session boundaries or when you want a continuous anchor that adapts to liquidity shifts.
Key settings
VWAP computation
VWAP Mode = 4 Hours, Daily, Weekly, Rolling (Bars), Rolling (Days). Session modes reset the VWAP when a new session begins. Rolling modes compute VWAP over a fixed trailing window.
Rolling (Lookback: Bars) controls the trailing bar count when using Rolling (Bars).
Rolling (Lookback: Days) converts days to bars at runtime and uses that trailing span.
Use Close instead of HLC3 switches the price reference. HLC3 is smoother. Close makes the anchor track settlement more tightly.
Deviation measurement
Deviation Mode
Percent : 100 * (Price / VWAP - 1). Good for uniform scaling across instruments.
Absolute : Price - VWAP. Good when price units themselves matter.
Z-Score : Standardizes the absolute residual by its own mean and standard deviation over Z/Std Window . Ideal for cross-asset comparability and regime studies.
Z/Std Window sets the mean and standard deviation window for Z-Score mode.
Volatility controls
Percent Mode Volatility Lookback estimates sigma for percent deviations.
Absolute Mode Volatility Lookback estimates sigma for absolute deviations.
Minimum Sigma Guard (pct pts) prevents the percent sigma from collapsing to near zero in extremely quiet markets.
Visualization
Plot Type = Histogram or Line. Histogram emphasizes impulse and polarity changes. Line emphasizes trend waves and divergences.
Positive Color / Negative Color define the palette for line mode. Histogram uses a 10-bucket gradient automatically.
Show Standard Deviations plots symmetric rails at ±1, ±2, ±3 sigma in the current mode’s units.
Fill Line Oscillator and Fill Opacity add a soft bias band around zero for line mode.
Line Width affects both the oscillator and the sigma rails.
Reading the zones
The oscillator’s color and height map deviation to nine graded buckets on each side of zero, with deeper greens above and deeper reds below. In Percent and Absolute modes, those buckets are scaled by their mode-specific sigma. In Z-Score mode the bucket edges are fixed at 0.5, 1.0, 2.0, and 2.8.
0 to +1 sigma weak positive bias, usually rotational.
+1 to +2 sigma constructive impulse. Pullbacks that hold above zero often continue.
+2 to +3 sigma strong expansion. Watch for either trend continuation or exhaustion tells.
Beyond +3 sigma statistical extreme. Requires structure to avoid fading too soon.
Mirror logic applies on the negative side.
Suggested workflows
Trend continuation checklist
Pick a session VWAP that matches your timeframe, for example Daily for intraday or Weekly for position trades.
Wait for the oscillator to hold the correct side of zero and for a sequence of higher swing lows in the oscillator (uptrend) or lower swing highs (downtrend).
Buy pullbacks that stabilize between zero and +1 sigma in an uptrend. Sell rallies that stabilize between zero and -1 sigma in a downtrend.
Use the next sigma band or a prior price swing as your target reference.
Mean reversion checklist
Switch to Z-Score mode for standardized thresholds.
Identify tests of ±2 sigma to ±3 sigma that fail to extend while price meets support or resistance.
Enter on a polarity change through the prior histogram bar or a small hook in line mode.
Fade back to zero or to the opposite inner band, then reassess.
Notes on the three modes
Percent is easy to reason about when you care about proportional stretch. It is well suited to intraday and multi-asset dashboards.
Absolute tracks cash distance from VWAP. This is useful when instruments have tight ticks and you plan risk in price units.
Z-Score standardizes the residual and is best for quant studies, cross-asset comparisons, and threshold research that must be scale invariant.
What the alerts can tell you
Polarity changes at zero can mark the start or end of a leg.
Crosses of ±1 sigma identify overbought or oversold in the current mode’s units.
Zone changes signal an upgrade or downgrade in deviation strength.
Troubleshooting and edge cases
If your instrument has long flat periods, keep Minimum Sigma Guard above zero in Percent mode so the rails do not vanish.
In Rolling modes, very short windows will respond quickly but can whip around. Session modes smooth this by resetting at well known boundaries.
If Z-Score looks erratic, increase Z/Std Window to stabilize the estimate of mean and sigma for the residual.
Final thoughts
VWAP is the anchor. The deviation oscillator is the narrative. By separating bias, magnitude, and regime into a simple stream you can execute faster and review cleaner. Pick the VWAP mode that matches your horizon, choose the deviation lens that matches your risk framework, and let the color graded zones guide your decisions.
Current Price (Customizable) by DRtradeCurrent Price Line & Dynamic Label (Fully Customizable)
The ultimate tool for clear, real-time price visualization.
This powerful, lightweight indicator draws a clean horizontal line at the current market price, updating instantly with every price tick. Unlike other current price line scripts, this tool ensures you always see where the price is right now and provides full control over every visual element.
Key Features:
- Real-Time Tracking: The line moves dynamically with price ticks within the current candle, eliminating lag and providing true current market price awareness.
- Line Extension Control: Choose to extend: Left, Right, or Both. Helpful for scalpers and options traders
- Visual Customizations: Color, Style, Size, Width, etc.
- Label Positioning: Left of Candle, Above Candle, or Right of Candle
All customization options are available in the indicator's settings menu.
Ping me with feature reqeusts.
Volume Based Sampling [BackQuant]Volume Based Sampling
What this does
This indicator converts the usual time-based stream of candles into an event-based stream of “synthetic” bars that are created only when enough trading activity has occurred . You choose the activity definition:
Volume bars : create a new synthetic bar whenever the cumulative number of shares/contracts traded reaches a threshold.
Dollar bars : create a new synthetic bar whenever the cumulative traded dollar value (price × volume) reaches a threshold.
The script then keeps an internal ledger of these synthetic opens, highs, lows, closes, and volumes, and can display them as candles, plot a moving average calculated over the synthetic closes, mark each time a new sample is formed, and optionally overlay the native time-bars for comparison.
Why event-based sampling matters
Markets do not release information on a clock: activity clusters during news, opens/closes, and liquidity shocks. Event-based bars normalize for that heteroskedastic arrival of information: during active periods you get more bars (finer resolution); during quiet periods you get fewer bars (coarser resolution). Research shows this can reduce microstructure pathologies and produce series that are closer to i.i.d. and more suitable for statistical modeling and ML. In particular:
Volume and dollar bars are a common event-time alternative to time bars in quantitative research and are discussed extensively in Advances in Financial Machine Learning (AFML). These bars aim to homogenize information flow by sampling on traded size or value rather than elapsed seconds.
The Volume Clock perspective models market activity in “volume time,” showing that many intraday phenomena (volatility, liquidity shocks) are better explained when time is measured by traded volume instead of seconds.
Related market microstructure work on flow toxicity and liquidity highlights that the risk dealers face is tied to information intensity of order flow, again arguing for activity-based clocks.
How the indicator works (plain English)
Choose your bucket type
Volume : accumulate volume until it meets a threshold.
Dollar Bars : accumulate close × volume until it meets a dollar threshold.
Pick the threshold rule
Dynamic threshold : by default, the script computes a rolling statistic (mean or median) of recent activity to set the next bucket size. This adapts bar size to changing conditions (e.g., busier sessions produce more frequent synthetic bars).
Fixed threshold : optionally override with a constant target (e.g., exactly 100,000 contracts per synthetic bar, or $5,000,000 per dollar bar).
Build the synthetic bar
While a bucket fills, the script tracks:
o_s: first price of the bucket (synthetic open)
h_s: running maximum price (synthetic high)
l_s: running minimum price (synthetic low)
c_s: last price seen (synthetic close)
v_s: cumulative native volume inside the bucket
d_samples: number of native bars consumed to complete the bucket (a proxy for “how fast” the threshold filled)
Emit a new sample
Once the bucket meets/exceeds the threshold, a new synthetic bar is finalized and stored. If overflow occurs (e.g., a single native bar pushes you past the threshold by a lot), the code will emit multiple synthetic samples to account for the extra activity.
Maintain a rolling history efficiently
A ring buffer can overwrite the oldest samples when you hit your Max Stored Samples cap, keeping memory usage stable.
Compute synthetic-space statistics
The script computes an SMA over the last N synthetic closes and basic descriptors like average bars per synthetic sample, mean and standard deviation of synthetic returns, and more. These are all in event time , not clock time.
Inputs and options you will actually use
Data Settings
Sampling Method : Volume or Dollar Bars.
Rolling Lookback : window used to estimate the dynamic threshold from recent activity.
Filter : Mean or Median for the dynamic threshold. Median is more robust to spikes.
Use Fixed? / Fixed Threshold : override dynamic sizing with a constant target.
Max Stored Samples : cap on synthetic history to keep performance snappy.
Use Ring Buffer : turn on to recycle storage when at capacity.
Indicator Settings
SMA over last N samples : moving average in synthetic space . Because its index is sample count, not minutes, it adapts naturally: more updates in busy regimes, fewer in quiet regimes.
Visuals
Show Synthetic Bars : plot the synthetic OHLC candles.
Candle Color Mode :
Green/Red: directional close vs open
Volume Intensity: opacity scales with synthetic size
Neutral: single color
Adaptive: graded by how large the bucket was relative to threshold
Mark new samples : drop a small marker whenever a new synthetic bar prints.
Comparison & Research
Show Time Bars : overlay the native time-based candles to visually compare how the two sampling schemes differ.
How to read it, step by step
Turn on “Synthetic Bars” and optionally overlay “Time Bars.” You will see that during high-activity bursts, synthetic bars print much faster than time bars.
Watch the synthetic SMA . Crosses in synthetic space can be more meaningful because each update represents a roughly comparable amount of traded information.
Use the “Avg Bars per Sample” in the info table as a regime signal. Falling average bars per sample means activity is clustering, often coincident with higher realized volatility.
Try Dollar Bars when price varies a lot but share count does not; they normalize by dollar risk taken in each sample. Volume Bars are ideal when share count is a better proxy for information flow in your instrument.
Quant finance background and citations
Event time vs. clock time : Easley, López de Prado, and O’Hara advocate measuring intraday phenomena on a volume clock to better align sampling with information arrival. This framing helps explain volatility bursts and liquidity droughts and motivates volume-based bars.
Flow toxicity and dealer risk : The same authors show how adverse selection risk changes with the intensity and informativeness of order flow, further supporting activity-based clocks for modeling and risk management.
AFML framework : In Advances in Financial Machine Learning , event-driven bars such as volume, dollar, and imbalance bars are presented as superior sampling units for many ML tasks, yielding more stationary features and fewer microstructure distortions than fixed time bars. ( Alpaca )
Practical use cases
1) Regime-aware moving averages
The synthetic SMA in event time is not fooled by quiet periods: if nothing of consequence trades, it barely updates. This can make trend filters less sensitive to calendar drift and more sensitive to true participation.
2) Breakout logic on “equal-information” samples
The script exposes simple alerts such as breakout above/below the synthetic SMA . Because each bar approximates a constant amount of activity, breakouts are conditioned on comparable informational mass, not arbitrary time buckets.
3) Volatility-adaptive backtests
If you use synthetic bars as your base data stream, most signal rules become self-paced : entry and exit opportunities accelerate in fast markets and slow down in quiet regimes, which often improves the realism of slippage and fill modeling in research pipelines (pair this indicator with strategy code downstream).
4) Regime diagnostics
Avg Bars per Sample trending down: activity is dense; expect larger realized ranges.
Return StdDev (synthetic) rising: noise or trend acceleration in event time; re-tune risk.
Interpreting the info panel
Method : your sampling choice and current threshold.
Total Samples : how many synthetic bars have been formed.
Current Vol/Dollar : how much of the next bucket is already filled.
Bars in Bucket : native bars consumed so far in the current bucket.
Avg Bars/Sample : lower means higher trading intensity.
Avg Return / Return StdDev : return stats computed over synthetic closes .
Research directions you can build from here
Imbalance and run bars
Extend beyond pure volume or dollar thresholds to imbalance bars that trigger on directional order flow imbalance (e.g., buy volume minus sell volume), as discussed in the AFML ecosystem. These often further homogenize distributional properties used in ML. alpaca.markets
Volume-time indicators
Re-compute classical indicators (RSI, MACD, Bollinger) on the synthetic stream. The premise is that signals are updated by traded information , not seconds, which may stabilize indicator behavior in heteroskedastic regimes.
Liquidity and toxicity overlays
Combine synthetic bars with proxies of flow toxicity to anticipate spread widening or volatility clustering. For instance, tag synthetic bars that surpass multiples of the threshold and test whether subsequent realized volatility is elevated.
Dollar-risk parity sampling for portfolios
Use dollar bars to align samples across assets by notional risk, enabling cleaner cross-asset features and comparability in multi-asset models (e.g., correlation studies, regime clustering). AFML discusses the benefits of event-driven sampling for cross-sectional ML feature engineering.
Microstructure feature set
Compute duration in native bars per synthetic sample , range per sample , and volume multiple of threshold as inputs to state classifiers or regime HMMs . These features are inherently activity-aware and often predictive of short-horizon volatility and trend persistence per the event-time literature. ( Alpaca )
Tips for clean usage
Start with dynamic thresholds using Median over a sensible lookback to avoid outlier distortion, then move to Fixed thresholds when you know your instrument’s typical activity scale.
Compare time bars vs synthetic bars side by side to develop intuition for how your market “breathes” in activity time.
Keep Max Stored Samples reasonable for performance; the ring buffer avoids memory creep while preserving a rolling window of research-grade data.
VWAP Daily/Weekly/Monthly - Automatic AnchoredExplanation:
This script plots Volume-Weighted Average Price (VWAP) lines that are automatically anchored to the beginning of key timeframes — daily, weekly, and monthly. VWAP is a widely used trading indicator that shows the average price of an asset weighted by trading volume, making it useful for identifying fair value and institutional trading levels.
The “automatic anchored” feature means that you don’t have to manually select starting points. Instead, the script automatically resets the VWAP at the start of each day, week, or month, depending on the chosen setting. This ensures the VWAP always reflects the true average price for that period, providing traders with a consistent reference for support, resistance, and trend direction across multiple timeframes.
Notice:
On the chart, you may notice visible “jumps” in the VWAP lines. These are intentional. Each jump marks the reset point at the start of a new day, week, or month, depending on the selected setting. This design keeps the VWAP history from the previous period intact, allowing you to clearly see how price interacted with VWAP in past sessions.
By keeping these historical resets, you can easily compare short-term (daily) VWAP behavior against longer-term levels like weekly and monthly VWAP. This provides valuable context, helping you spot when price respects or diverges from fair value across different timeframes.
In short:
Daily VWAP resets at the start of each trading day.
Weekly VWAP resets at the beginning of each trading week.
Monthly VWAP resets at the start of each month.
This makes it easy to analyze how price interacts with VWAP levels across different time horizons without manual adjustments.
Volume Percentile Supertrend [BackQuant]Volume Percentile Supertrend
A volatility and participation aware Supertrend that automatically widens or tightens its bands based on where current volume sits inside its recent distribution. The goal is simple: fewer whipsaws when activity surges, faster reaction when the tape is quiet.
What it does
Calculates a standard Supertrend framework from an ATR on a volume weighted price source.
Measures current volume against its recent percentile and converts that context into a dynamic ATR multiplier.
Widens bands when volume is unusually high to reduce chop. Tightens bands when volume is unusually low to catch turns earlier.
Paints candles, draws the active Supertrend line and optional bands, and prints clear Long and Short signal markers.
Why volume percentile
Fixed ATR multipliers assume all bars are equal. They are not. When participation spikes, price swings expand and a static band gets sliced.
Percentiles place the current bar inside a recent distribution. If volume is in the top slice, the Supertrend allows more room. If volume is in the bottom slice, it expects smaller noise and tightens.
This keeps the same playbook usable across busy sessions and sleepy ones without constant manual retuning.
How it works
Volume distribution - A rolling window computes the Pth percentile of volume. Above that is flagged as high volume. A lower reference percentile marks quiet bars.
Dynamic multiplier - Start from a Base Multiplier. If bar is high volume, scale it up by a function of volume-to-average and a Sensitivity knob. If bar is low volume, scale it down. Smooth the result with an EMA to avoid jitter.
VWMA source - The price input for bands is a short volume weighted moving average of close. Heavy prints matter more.
ATR envelope - Compute ATR on your length. UpperBasic = VWMA + Multiplier x ATR. LowerBasic = VWMA - Multiplier x ATR.
Trailing logic - The final lines trail price so they only move in a direction that preserves Supertrend behavior. This prevents sudden flips from transient pokes.
Direction and signals - Direction flips when price crosses through the relevant trailing line. SupertrendLong and SupertrendShort mark those flips. The plotted Supertrend is the active trailing side.
Inputs and what they change
Volume Lookback - Window for percentile and average. Larger window = stabler percentile, smaller = snappier.
Volume Percentile Level - Threshold that defines high volume. Example 70 means top 30 percent of recent bars are treated as high activity.
Volume Sensitivity - Gain from volume ratio to the dynamic multiplier. Higher = bands expand more when volume spikes.
VWMA Source Length - Smoothing of the volume weighted price source for the bands.
ATR Length - Standard ATR window. Larger = slower, smaller = quicker.
Base Multiplier - Core band width before volume adjustment. Think of this as your neutral volatility setting.
Multiplier Smoothing - EMA on the dynamic multiplier. Reduces back and forth changes when volume oscillates around the threshold.
Show Supertrend on chart - Toggles the active line.
Show Upper Lower Bands - Draws both sides even when inactive. Good for context.
Paint candles according to Trend - Colors bars by trend direction.
Show Long and Short Signals - Prints 𝕃 and 𝕊 markers at flips.
Colors - Choose your long and short palette.
Reading the plot
Supertrend line - Thick line that hugs price from above in downtrends and from below in uptrends. Its distance breathes with volume.
Bands - Optional upper and lower rails. Useful to see the inactive side and judge how wide the envelope is right now.
Signals - 𝕃 prints when the trend flips long. 𝕊 prints when the trend flips short.
Candle colors - Quick bias read at a glance when painting is enabled.
Typical workflows
Trend following - Use 𝕃 flips to initiate longs and ride while bars remain colored long and price respects the lower trailing line. Mirror for shorts with 𝕊 and the upper trailing line. During high volume phases the line will give more room, which helps stay in the move.
Pullback adds - In an established trend, shallow tags toward the active line after a high volume expansion can be add points. The dynamic envelope adjusts to the session so your add distance is not fixed to a stale volatility regime.
Mean reversion filter - In quiet tape the multiplier contracts and flips come earlier. If you prefer fading, watch for quick toggles around the bands when volume percentile remains low. In high volume, avoid fading into the widened line unless you have other strong reasons.
Notes on behavior
High volume bar: the percentile gate opens, volRatio > 1 powers up the multiplier through the Sensitivity lever, bands widen, fewer false flips.
Low volume bar: multiplier contracts, bands tighten, flips can happen earlier which is useful when you want to catch regime changes in quiet conditions.
Smoothing matters: both the price source (VWMA) and the multiplier are smoothed to keep structure readable while still adapting.
Quick checklist
If you see frequent chop and today feels busy: check that volume is above your percentile. Wider bands are expected. Consider letting the trend prove itself against the expanded line before acting.
If everything feels slow and you want earlier entries: percentile likely marks low volume, so bands tighten and 𝕃 or 𝕊 can appear sooner.
If you want more or fewer flips overall: adjust Base Multiplier first. If you want more reaction specifically tied to volume surges: raise Volume Sensitivity. If the envelope breathes too fast: raise Multiplier Smoothing.
What the signals mean
SupertrendLong - Direction changed from non-long to long. 𝕃 marker prints. The active line switches to support below price.
SupertrendShort - Direction changed from non-short to short. 𝕊 marker prints. The active line switches to resistance above price.
Trend color - Bars painted long or short help validate context for entries and management.
Summary
Volume Percentile Supertrend adapts the classic Supertrend to the day you are trading. Volume percentile sets the mood, sensitivity translates it into dynamic band width, and smoothing keeps it clean. The result is a single plot that aims to stay conservative when the tape is loud and act decisively when it is quiet, without you having to constantly retune settings.
Quarterly EarningsThis Pine script shows quarterly EPS, Sales, and P/E (TTM-based) in a styled table.
J. YOUNG INDICATOR (2)QUICK REFERENCE to help with a PRICE FOR OPTIONS and or B/H entry MEDIAN PRICE of the MONTHLY/QUARTERLY aVWAPS to get a more accurate price point
Pairs Trading Scanner [BackQuant]Pairs Trading Scanner
What it is
This scanner analyzes the relationship between your chart symbol and a chosen pair symbol in real time. It builds a normalized “spread” between them, tracks how tightly they move together (correlation), converts the spread into a Z-Score (how far from typical it is), and then prints clear LONG / SHORT / EXIT prompts plus an at-a-glance dashboard with the numbers that matter.
Why pairs at all?
Markets co-move. When two assets are statistically related, their relationship (the spread) tends to oscillate around a mean.
Pairs trading doesn’t require calling overall market direction you trade the relative mispricing between two instruments.
This scanner gives you a robust, visual way to find those dislocations, size their significance, and structure the trade.
How it works (plain English)
Step 1 Pick a partner: Select the Pair Symbol to compare against your chart symbol. The tool fetches synchronized prices for both.
Step 2 Build a spread: Choose a Spread Method that defines “relative value” (e.g., Log Spread, Price Ratio, Return Difference, Price Difference). Each lens highlights a different flavor of divergence.
Step 3 Validate relationship: A rolling Correlation checks if the pair is moving together enough to be tradable. If correlation is weak, the scanner stands down.
Step 4 Standardize & score: The spread is normalized (mean & variability over a lookback) to form a Z-Score . Large absolute Z means “stretched,” small means “near fair.”
Step 5 Signals: When the Z-Score crosses user-defined thresholds with sufficient correlation , entries print:
LONG = long chart symbol / short pair symbol,
SHORT = short chart symbol / long pair symbol,
EXIT = mean reversion into the exit zone or correlation failure.
Core concepts (the three pillars)
Spread Method Your definition of “distance” between the two series.
Guidance:
Log Spread: Focuses on proportional differences; robust when prices live on different scales.
Price Ratio: Classic relative value; good when you care about “X per Y.”
Return Difference: Emphasizes recent performance gaps; nimble for momentum-to-mean plays.
Price Difference: Straight subtraction; intuitive for similar-scale assets (e.g., two ETFs).
Correlation A rolling score of co-movement. The scanner requires it to be above your Min Correlation before acting, so you’re not trading random divergence.
Z-Score “How abnormal is today’s spread?” Positive = chart richer than pair; negative = cheaper. Thresholds define entries/exits with transparent, statistical context.
What you’ll see on the chart
Correlation plot (blue line) with a dashed Min Correlation guide. Above the line = green zone for signals; below = hands off.
Z-Score plot (white line) with colored, dashed Entry bands and dotted Exit bands. Zero line for mean.
Normalized spread (yellow) for a quick “shape read” of recent divergence swings.
Signal markers :
LONG (green label) when Z < –Entry and corr OK,
SHORT (red label) when Z > +Entry and corr OK,
EXIT (gray label) when Z returns inside the Exit band or correlation drops below the floor.
Background tint for active state (faint green for long-spread stance, faint red for short-spread stance).
The two built-in dashboards
Statistics Table (top-right)
Pair Symbol Your chosen partner.
Correlation Live value vs. your minimum.
Z-Score How stretched the spread is now.
Current / Pair Prices Real-time anchors.
Signal State NEUTRAL / LONG / SHORT.
Price Ratio Context for ratio-style setups.
Analysis Table (bottom-right)
Avg Correlation Typical co-movement level over your window.
Max |Z| The recent extremes of dislocation.
Spread Volatility How “lively” the spread has been.
Trade Signal A human-readable prompt (e.g., “LONG A / SHORT B” or “NO TRADE” / “LOW CORRELATION”).
Risk Level LOW / MEDIUM / HIGH based on current stretch (absolute Z).
Signals logic (plain English)
Entry (LONG): The spread is unusually negative (chart cheaper vs pair) and correlation is healthy. Expect mean reversion upward in the spread: long chart, short pair.
Entry (SHORT): The spread is unusually positive (chart richer vs pair) and correlation is healthy. Expect mean reversion downward in the spread: short chart, long pair.
Exit: The spread relaxes back toward normal (inside your exit band), or correlation deteriorates (relationship no longer trusted).
A quick, repeatable workflow
1) Choose your pair in context (same sector/theme or known macro link). Think: “Do these two plausibly co-move?”
2) Pick a spread lens that matches your narrative (ratio for relative value, returns for short-term performance gaps, etc.).
3) Confirm correlation is above your floor no corr, no trade.
4) Wait for a stretch (Z beyond Entry band) and a printed LONG / SHORT .
5) Manage to the mean (EXIT band) or correlation failure; let the scanners’ state/labels keep you honest.
Settings that matter (and why)
Spread Method Defines the “mispricing” you care about.
Correlation Period Longer = steadier regime read, shorter = snappier to regime change.
Z-Score Period The window that defines “normal” for the spread; it sets the yardstick.
Use Percentage Returns Normalizes series when using return-based logic; keep on for mixed-scale assets.
Entry / Exit Thresholds Set your stretch and your target reversion zone. Wider entries = rarer but stronger signals.
Minimum Correlation The gatekeeper. Raising it favors quality over quantity.
Choosing pairs (practical cheat sheet)
Same family: two index ETFs, two oil-linked names, two gold miners, two L1 tokens.
Hedge & proxy: stock vs. sector ETF, BTC vs. BTC index, WTI vs. energy ETF.
Cross-venue or cross-listing: instruments that are functionally the same exposure but price differently intraday.
Reading the cues like a pro
Divergence shape: The yellow normalized spread helps you see rhythm fast spike and snap-back versus slow grind.
Corr-first discipline: Don’t fight the “Min Correlation” line. Good pairs trading starts with a relationship you can trust.
Exit humility: When Z re-centers, let the EXIT do its job. The edge is the journey to the mean, not overstaying it.
Frequently asked (quick answers)
“Long/Short means what exactly?”
LONG = long the chart symbol and short the pair symbol.
SHORT = short the chart symbol and long the pair symbol.
“Do I need same price scales?” No. The spread methods normalize in different ways; choose the one that fits your use case (log/ratio are great for mixed scales).
“What if correlation falls mid-trade?” The scanner will neutralize the state and print EXIT . Relationship first; trade second.
Field notes & patterns
Snap-back days: After a one-sided session, return-difference spreads often flag cleaner intraday mean reversions.
Macro rotations: Ratio spreads shine during sector re-weights (e.g., value vs. growth ETFs); look for steady corr + elevated |Z|.
Event bleed-through: If one symbol reacts to news and its partner lags, Z often flags a high-quality, short-horizon re-centering.
Display controls at a glance
Show Statistics Table Live state & key numbers, top-right.
Show Analysis Table Context/risk read, bottom-right.
Show Correlation / Spread / Z-Score Toggle the sub-charts you want visible.
Show Entry/Exit Signals Turn markers on/off as needed.
Coloring Adjust Long/Short/Neutral and correlation line colors to match your theme.
Alerts (ready to route to your workflow)
Pairs Long Entry Z falls through the long threshold with correlation above minimum.
Pairs Short Entry Z rises through the short threshold with correlation above minimum.
Pairs Trade Exit Z returns to neutral or the relationship fails your correlation floor.
Correlation Breakdown Rolling correlation crosses your minimum; relationship caution.
Final notes
The scanner is designed to keep you systematic: require relationship (correlation), quantify dislocation (Z-Score), act when stretched, stand down when it normalizes or the relationship degrades. It’s a full, visual loop for relative-value trading that stays out of your way when it should and gets loud only when the numbers line up.
Price Level Highlighter [ldlwtrades]This indicator is a minimalist and highly effective tool designed for traders who incorporate institutional concepts into their analysis. It automates the identification of key psychological price levels and adds a unique, dynamic layer of information to help you focus on the most relevant area of the market. Inspired by core principles of market structure and liquidity, it serves as a powerful visual guide for anticipating potential support and resistance.
The core idea is simple: specific price points, particularly those ending in round numbers or common increments, often act as magnets or barriers for price. While many indicators simply plot static lines, this tool goes further by intelligently highlighting the single most significant level in real-time. This dynamic feature allows you to quickly pinpoint where the market is currently engaged, offering a clear reference point for your trading decisions. It reduces chart clutter and enhances your focus on the immediate price action.
Features
Customizable Price Range: Easily define a specific Start Price and End Price to focus the indicator on the most relevant area of your chart, preventing unnecessary clutter.
Adjustable Increment: Change the interval of the lines to suit your trading style, from high-frequency increments (e.g., 10 points) for scalping to wider intervals (e.g., 50 or 100 points) for swing trading.
Intelligent Highlighting: A key feature that automatically identifies and highlights the single horizontal line closest to the current market price with a distinct color and thickness. This gives you an immediate visual cue for the most relevant price level.
Highly Customizabile: Adjust the line color, style, and width for both the main lines and the highlighted line to fit your personal chart aesthetic.
Usage
Apply the indicator to your chart.
In the settings, input your desired price range (Start Price and End Price) to match the market you are trading.
Set the Price Increment to your preferred density.
Monitor the chart for the highlighted line. This is your active price level and a key area of interest.
Combine this tool with other confirmation signals (e.g., order blocks, fair value gaps, liquidity pools) to build higher-probability trade setups.
Best Practices
Pairing: This tool is effective across all markets, including stocks, forex, indices, and crypto. It is particularly useful for volatile markets where price moves rapidly between psychological levels.
Mindful Analysis: Use the highlighted level as a reference point for your analysis, not as a standalone signal. A break above or below this level can signify a shift in market control.
Backtesting: Always backtest the indicator on your preferred market and timeframe to understand how it performs under different conditions.
Trend Compass (Manual)## Trend Compass (Manual) - A Discretionary Trader's Dashboard
### Summary
Trend Compass is a simple yet powerful dashboard designed for discretionary traders who want a constant, visual reminder of their market analysis directly on their chart. Instead of relying on automated indicators, this tool gives you **full manual control** to define the market state across different timeframes or conditions.
It helps you stay aligned with your higher-level analysis (e.g., HTF bias, current market structure) and avoid making impulsive decisions that go against your plan.
### Key Features
- **Fully Manual Control:** You decide the trend. No lagging indicators, no confusing signals. Just your own analysis, displayed clearly.
- **Multiple Market States:** Define each row as an `Uptrend`, `Downtrend`, `Pullback`, or `Neutral` market.
- **Customizable Rows:** Display up to 8 rows. You can label each one however you like (e.g., "D1", "H4", "Market Structure", "Liquidity Bias").
- **Flexible Panel:** Change all colors, text sizes, and place the panel in any of the 9 positions on your chart.
- **Clean & Minimalist:** Designed to provide essential information at a glance without cluttering your chart.
### How to Use
1. **Add to Chart:** Add the indicator to your chart.
2. **Open Settings:** Go into the indicator settings.
3. **Configure Rows:**
- In the "Rows (Manual Control)" section, set the "Number of rows" you want to display.
- For each row, give it a custom **Label** (e.g., "m15").
- Select its current state from the dropdown menu (`Uptrend`, `Downtrend`, etc.).
- To remove a row, simply set its state to `Hidden`.
4. **Customize Style:**
- In the "Panel & Visual Style" section, adjust colors, text sizes, and the panel's position to match your chart's theme.
This tool is perfect for price action traders, ICT/SMC traders, or anyone who values a clean chart and a disciplined approach to their analysis.
Dynamic Stop Loss Optimizer [BackQuant]Dynamic Stop Loss Optimizer
Overview
Stop placement decides expectancy. This tool gives you three professional-grade, adaptive stop engines, ATR, Volatility, and Hybrid. So your exits scale with current conditions instead of guessing fixed ticks. It trails intelligently, redraws as the market evolves, and annotates the chart with clean labels/lines and a compact stats table. Pick the engine that fits the trade, or switch on the fly.
What it does
Calculates three adaptive stops in real time (ATR-based, Volatility-based, and Hybrid) and keeps them trailed as price makes progress.
Shows exactly where your risk lives with on-chart levels, color-coded markers (long/short), and precise “Risk %” labels at the current bar.
Surfaces context you actually use - current ATR, daily volatility, selected method, and the live stop level—in a tidy, movable table.
Fires alerts on stop hits so you can automate exits or journal outcomes without staring at the screen.
Why it matters
Adaptive risk control: Stops expand in fast tape and tighten in quiet tape. You’re not punished for volatility; you’re aligned with it.
Consistency across assets: The same playbook works whether you’re trading indexes, FX, crypto, or equities, because the engine normalizes to each symbol’s behavior.
Cleaner decision-making: One chart shows your entry idea and its invalidation in the same breath. If price trespasses, you know it instantly.
The three methods (choose your engine)
1) ATR Based “Structure-aware” distance
This classic approach keys off Average True Range to set a stop just beyond typical bar-to-bar excursion. It adapts smoothly to changing ranges and respects swing structure.
Use when: you want a steady, intuitive buffer that tracks trend legs without hugging price.
See it in action:
2) Volatility Based “Behavior-aware” distance
This engine derives stop distance from current return volatility (annualized, then scaled back down to the session). It reacts to regime shifts quickly and normalizes risk across symbols with very different prices.
Use when: you want the stop to breathe with realized volatility and respond faster to heat-ups/cool-downs.
See it in action:
3) Hybrid “Best of both worlds”
The Hybrid blends the ATR and Volatility distances into one consensus level, then trails it intelligently. You get the structural common sense of ATR and the regime sensitivity of Vol.
Use when: you want robust, all-weather behavior without micromanaging inputs.
See it in action:
How it trails
Longs: The stop ratchets up with favorable movement and holds its ground on shallow pullbacks. If price closes back into the risk zone, the level refreshes to the newest valid distance.
Shorts: Mirror logic ratchets down with trend, resists noise, and refreshes if price reclaims the zone.
Hybrid trailing: Uses the blended distance and the same “no give-backs” principle to keep gains protected as structure builds.
Reading the chart
Markers: Circles = ATR stops, Crosses = Vol stops, Diamonds = Hybrid. Colors indicate long (red level under price) vs short (green level above price).
Lines: The latest active stop is extended with a dashed line so you can see it at a glance.
Labels: “Long SL / Short SL” shows the exact price and current risk % from the last close no math required.
Table: ATR value, Daily Vol %, your chosen Method, the Current SL, and Risk %—all in one compact block that you can pin top-left/right/center.
Quick workflow
Define the idea: Long or Short, and which engine fits the tape (ATR, Vol, or Hybrid).
Place and trail: Let the optimizer print the level; trail automatically as the move develops.
Manage outcomes: If the line is tagged, you’re out clean. If it holds, you’ve contained heat while giving the trade room to work.
Inputs you’ll actually touch
Calculation Settings
ATR Length / Multiplier: Controls the “structural” cushion.
Volatility Length / Multiplier: Controls the “behavioral” cushion.
Trading Days: 252 or 365 to keep the volatility math aligned with the asset’s trading calendar.
Stop Loss Method
ATR Based | Volatility Based | Hybrid : Switch engines instantly to fit the trade.
Position Type
Long | Short | Both : Show only what you need for the current strategy.
Visual Settings
Show ATR / Vol / Hybrid Stops: Toggle families on/off.
Show Labels: Print price + Risk % at the live stop.
Table Position: Park the metrics where you like.
Coloring
Long/Short/Hybrid colors: Set a palette that matches your theme and stands out on your background.
Practical patterns to watch
Trend-pullback continuation: The stop ratchets behind higher lows (long) or lower highs (short). If price tests the level and rejects, that’s your risk-defined continuation cue.
Break-and-run: After a clean break, the Hybrid will usually sit slightly wider than pure Vol, use it to avoid getting shaken on the first retest.
Range compression: When the ATR and Vol distances converge, the table will show small Risk %. That’s your green light to size up with the same dollar risk, or keep it conservative if you expect expansion.
Alerts
Long Stop Loss Hit : Notifies when price crosses below the live long stop.
Short Stop Loss Hit : Notifies when price crosses above the live short stop.
Why this feels “set-and-serious”
You get a single look that answers three questions in real time: “Where’s my line in the sand?”, “How much heat am I taking right now?”, and “Is this distance appropriate for current conditions?” With ATR, Vol, and Hybrid in one tool, you can run the exact same playbook across symbols and regimes while keeping your chart clean and your risk explicit.
PolyFilter [BackQuant]PolyFilter
A flexible, low-lag trend filter with three smoothing engines—optimized for clean bias, fewer whipsaws, and clear alerting.
What it does
PolyFilter draws a single “intelligent” baseline that adapts to price while suppressing noise. You choose the engine— Fractional MA , Ehlers 2-Pole Super Smoother , or a Multi-Kernel blend . The line can color itself by slope (trend) or by position vs price (above/below), and you get four ready-made alerts for flips and crosses.
What it plots
PolyFilter line — your smoothed trend baseline (width set by “Line Width”).
Optional candle & background coloring — choose: color by trend slope or by whether price is above/below the filter.
Signal markers — Arrows with L/S when the slope flips or when price crosses the line (if you enable shapes/alerts).
How the three engines differ
Fractional MA (experimental) — A power-law weighting of past bars (heavier focus on the most recent samples without throwing away history). The Adaptation Speed acts like the “fraction” exponent (default 0.618). Lower values lean more on recent bars; higher values spread weight further back.
Ehlers 2-Pole Super Smoother — Classic low-lag IIR smoother that aggressively reduces high-frequency noise while preserving turns. Great default when you want a steady, responsive baseline with minimal parameter fuss.
Multi-Kernel — A 70/30 blend of a Gaussian window and an exponential kernel. The Gaussian contributes smooth structure; the exponential adds a hint of responsiveness. Useful for assets that oscillate but still trend.
Reading the colors
Trend mode (default) — Line & candles turn green while the filter is rising (signal > signal ) and red while it’s falling.
Above/Below mode — Line & candles reflect price’s position relative to the filter: green when price > filter, red when price < filter. This is handy if you treat the filter like a dynamic “fair value” or bias line.
Inputs you’ll actually use
Calculation Settings
Price Source — Default HLC/3. Switch to Close for stricter trend, or HLC3/HL2 to soften single-print spikes.
Filter Length — Window/period for all engines. Shorter = snappier turns; longer = smoother line.
Adaptation Speed — Only affects Fractional MA . Lower it for faster, more local weighting; raise it for smoother, more global weighting.
Filter Type — Pick one of: Fractional MA, Ehlers 2-Pole, Multi-Kernel.
UI & Plotting
Color based off… — Choose Trend (slope) or > or < Close (position vs price).
Long/Short Colors — Customize bull/bear hues to your theme.
Show Filter Line / Paint candles / Color background — Visual toggles for the line, bars, and backdrop.
Line Width — Make the filter stand out (2–3 works well on most charts).
Signals & Alerts
PolyFilter Trend Up — Slope flips upward (the filter crosses above its prior value). Good for early continuation entries or stop-tightening on shorts.
PolyFilter Trend Down — Slope flips downward. Often used to scale out longs or rotate bias.
PolyFilter Above Price — The filter line crosses up through price (filter > price). This can confirm that mean has “caught up” after a pullback.
PolyFilter Below Price — The filter line crosses down through price (filter < price). Useful to confirm momentum loss on bounces.
Quick starts (suggested presets)
Intraday (5–15m, crypto or indices) — Ehlers 2-Pole, Length 55–80. Trend coloring ON, candle paint ON. Look for pullbacks to a rising filter; avoid fading a falling one.
Swing (1H–4H) — Multi-Kernel, Length 80–120. Background color OFF (cleaner), candle paint ON. Add a higher-TF confirmation (e.g., 4H filter rising when you trade 1H).
Range-prone FX — Fractional MA, Length 70–100, Adaptation ~0.55–0.70. Consider Above/Below mode to trade mean reversion to the line with a strict risk cap.
How to use it in practice
Bias line — Trade in the direction of the filter slope; stand aside when it flattens and color chops back and forth.
Dynamic support/resistance — Treat the line as a moving value area. In trends, entries often appear on shallow tags of the line with structure confluence.
Regime switch — When the filter flips and holds color for several bars, tighten stops on the opposing side and look for first pullback in the new color.
Stacking filters — Many users run PolyFilter on the active chart and a slower instance (longer length) on a higher timeframe as a “macro bias” guardrail.
Tuning tips
If you see too many flips, lengthen the filter or switch to Multi-Kernel.
If turns feel late, shorten the filter or try Ehlers 2-Pole for lower lag.
On thin or very noisy symbols, prefer HLC3 as the source and longer lengths.
Performance note: very large lengths increase computation time for the Multi-Kernel and Fractional engines. Start moderate and scale up only if needed.
Summary
PolyFilter gives you a single, trustworthy baseline that you can read at a glance—either as a pure trend line (slope coloring) or as a dynamic “above/below fair value” reference. Pick the engine that matches your market’s personality, set a sensible length, and let the color and alerts guide bias, entries on pullbacks, and risk on reversals.
Kalman Adjusted Average True Range [BackQuant]Kalman Adjusted Average True Range
A volatility-aware trend baseline that fuses a Kalman price estimate with ATR “rails” to create a smooth, adaptive guide for entries, exits, and trailing risk.
Built on my original Kalman
This indicator is based on my original Kalman Price Filter:
That core smoother is used here to estimate the “true” price path, then blended with ATR to control step size and react proportionally to market noise.
What it plots
Kalman ATR Line the main baseline that turns up/down with the filtered trend.
Optional Moving Average of the Kalman ATR a secondary line for confluence (SMA/Hull/EMA/WMA/DEMA/RMA/LINREG/ALMA).
Candle Coloring (optional) paint bars by the baseline’s current direction.
Why combine Kalman + ATR?
Kalman reduces measurement noise and produces a stable path without the lag of heavy MAs.
ATR rails scale the baseline’s step to current volatility, so it’s calm in chop and more responsive in expansion.
The result is a single, intelligible line you can trade around: slope-up = constructive; slope-down = caution.
How it works (plain English)
Each bar, the Kalman filter updates an internal state (tunable via Process Noise , Measurement Noise , and Filter Order ) to estimate the underlying price.
An ATR band (Period × Factor) defines the allowed per-bar adjustment. The baseline cannot “jump” beyond those rails in one step.
A direction flip is detected when the baseline’s slope changes sign (upturn/downturn), and alerts are provided for both.
Typical uses
Trend confirmation Trade in the baseline’s direction; avoid fading a firmly rising/falling line.
Pullback timing Look for entries when price mean-reverts toward a rising baseline (or exits on tags of a falling one).
Trailing risk Use the baseline as a dynamic guide; many traders set stops a small buffer beyond it (e.g., a fraction of ATR).
Confluence Enable the MA overlay of the Kalman ATR; alignment (baseline above its MA and rising) supports continuation.
Inputs & what they do
Calculation
Kalman Price Source which price the filter tracks (Close by default).
Process Noise how quickly the filter can adapt. Higher = more responsive (but choppier).
Measurement Noise how much you distrust raw price. Higher = smoother (but slower to turn).
Filter Order (N) depth of the internal state array. Higher = slightly steadier behavior.
Kalman ATR
Period ATR lookback. Shorter = snappier; longer = steadier.
Factor scales the allowed step per bar. Larger factors permit faster drift; smaller factors clamp movement.
Confluence (optional)
MA Type & Period compute an MA on the Kalman ATR line , not on price.
Sigma (ALMA) if ALMA is selected, this input controls the curve’s shape. (Ignored for other MA types.)
Visuals
Plot Kalman ATR toggle the main line.
Paint Candles color bars by up/down slope.
Colors choose long/short hues.
Signals & alerts
Trend Up baseline turns upward (slope crosses above 0).
Alert: “Kalman ATR Trend Up”
Trend Down baseline turns downward (slope crosses below 0).
Alert: “Kalman ATR Trend Down”
These are state flips , not “price crossovers,” so you avoid many one-bar head-fakes.
How to start (fast presets)
Swing (daily/4H) ATR Period 7–14, Factor 0.5–0.8, Process Noise 0.02–0.05, Measurement Noise 2–4, N = 3–5.
Intraday (5–15m) ATR Period 5–7, Factor 0.6–1.0, Process Noise 0.05–0.10, Measurement Noise 2–3, N = 3–5.
Slow assets / FX raise Measurement Noise or ATR Period for calmer lines; drop Factor if the baseline feels too jumpy.
Reading the line
Rising & curving upward momentum building; consider long bias until a clear downturn.
Flat & choppy regime uncertainty; many traders stand aside or tighten risk.
Falling & accelerating distribution lower; short bias until a clean upturn.
Practical playbook
Continuation entries After a Trend Up alert, wait for a minor pullback toward the baseline; enter on evidence the line keeps rising.
Exit/reduce If long and the baseline flattens then turns down, trim or exit; reverse logic for shorts.
Filters Add a higher-timeframe check (e.g., only take longs when the daily Kalman ATR is rising).
Stops Place stops just beyond the baseline (e.g., baseline − x% ATR for longs) to avoid “tag & reverse” noise.
Notes
This is a guide to state and momentum, not a guarantee. Combine with your process (structure, volume, time-of-day) for decisions.
Settings are asset/timeframe dependent; start with the presets and nudge Process/Measurement Noise until the baseline “feels right” for your market.
Summary
Kalman ATR takes the noise-reduction of a Kalman price estimate and couples it with volatility-scaled movement to produce a clean, adaptive baseline. If you liked the original Kalman Price Filter (), this is its trend-trading cousin purpose-built for cleaner state flips, intuitive trailing, and confluence with your existing
PE Rating by The Noiseless TraderPE Rating by The Noiseless Trader
This script analyzes a symbol’s Price-to-Earnings (P/E) ratio, using Diluted EPS (TTM) fundamentals directly from TradingView.
The script calculates the Price-to-Earnings ratio (P/E) using Diluted EPS (TTM) fundamentals. It then identifies:
PE High → the highest valuation point over a 3-year historical range.
PE Low → the lowest valuation point over a 3-year historical range.
PE Median → the midpoint between the two extremes, offering a fair-value benchmark.
PE (Int) → an additional intermediate low to track more recent undervaluation points. This is calculated based on lowest valuation point over a 1-year historical range
These levels are plotted directly on the chart as horizontal references, with markers showing the exact bars/dates when the extremes occurred. Candles corresponding to those days are also highlighted for context.
Bars corresponding to these extremes are highlighted (red = PE High, green = PE Low).
How it helps
Provides a historical valuation framework that complements technical analysis. We look for long opportunity or base formation near the PE Low and be cautious when stocks tends to trade near High PE.
We do not short the stock at High PE infact be cautious with long trades.
Helps identify whether current price action is happening near overvalued or undervalued zones.
Adds a long-term perspective to support swing trading and investing decisions. If a stock is coming from Low PE to Median PE and along with that if we get entry based on Classical strategies like Darvas Box, or HH-HL based on Dow Theory.
Offers a simple visual map of how far the market has moved from “cheap” to “expensive.”
This tool is best suited for long-term investors and swing traders who want to merge fundamentals with technical setups.
This indicator is designed as an educational tool to illustrate how valuation metrics (like earnings multiples) can be viewed alongside price action, helping traders connect fundamental context with technical execution in real market conditions.
Quantile Regression Bands [BackQuant]Quantile Regression Bands
Tail-aware trend channeling built from quantiles of real errors, not just standard deviations.
What it does
This indicator fits a simple linear trend over a rolling lookback and then measures how price has actually deviated from that trend during the window. It then places two pairs of bands at user-chosen quantiles of those deviations (inner and outer). Because bands are based on empirical quantiles rather than a symmetric standard deviation, they adapt to skewed and fat-tailed behaviour and often hug price better in trending or asymmetric markets.
Why “quantile” bands instead of Bollinger-style bands?
Bollinger Bands assume a (roughly) symmetric spread around the mean; quantiles don’t—upper and lower bands can sit at different distances if the error distribution is skewed.
Quantiles are robust to outliers; a single shock won’t inflate the bands for many bars.
You can choose tails precisely (e.g., 1%/99% or 5%/95%) to match your risk appetite.
How it works (intuitive)
Center line — a rolling linear regression approximates the local trend.
Residuals — for each bar in the lookback, the indicator looks at the gap between actual price and where the line “expected” price to be.
Quantiles — those gaps are sorted; you select which percentiles become your inner/outer offsets.
Bands — the chosen quantile offsets are added to the current end of the regression line to draw parallel support/resistance rails.
Smoothing — a light EMA can be applied to reduce jitter in the line and bands.
What you see
Center (linear regression) line (optional).
Inner quantile bands (e.g., 25th/75th) with optional translucent fill.
Outer quantile bands (e.g., 1st/99th) with a multi-step gradient to visualise “tail zones.”
Optional bar coloring: bars trend-colored by whether price is rising above or falling below the center line.
Alerts when price crosses the outer bands (upper or lower).
How to read it
Trend & drift — the slope of the center line is your local trend. Persistent closes on the same side of the center line indicate directional drift.
Pullbacks — tags of the inner band often mark routine pullbacks within trend. Reaction back to the center line can be used for continuation entries/partials.
Tails & squeezes — outer-band touches highlight statistically rare excursions for the chosen window. Frequent outer-band activity can signal regime change or volatility expansion.
Asymmetry — if the upper band sits much further from the center than the lower (or vice versa), recent behaviour has been skewed. Trade management can be adjusted accordingly (e.g., wider take-profit upslope than downslope).
A simple trend interpretation can be derived from the bar colouring
Good use-cases
Volatility-aware mean reversion — fade moves into outer bands back toward the center when trend is flat.
Trend participation — buy pullbacks to the inner band above a rising center; flip logic for shorts below a falling center.
Risk framing — set dynamic stops/targets at quantile rails so position sizing respects recent tail behaviour rather than fixed ticks.
Inputs (quick guide)
Source — price input used for the fit (default: close).
Lookback Length — bars in the regression window and residual sample. Longer = smoother, slower bands; shorter = tighter, more reactive.
Inner/Outer Quantiles (τ) — choose your “typical” vs “tail” levels (e.g., 0.25/0.75 inner, 0.01/0.99 outer).
Show toggles — independently toggle center line, inner bands, outer bands, and their fills.
Colors & transparency — customize band and fill appearance; gradient shading highlights the tail zone.
Band Smoothing Length — small EMA on lines to reduce stair-step artefacts without meaningfully changing levels.
Bar Coloring — optional trend tint from the center line’s momentum.
Practical settings
Swing trading — Length 75–150; inner τ = 0.25/0.75, outer τ = 0.05/0.95.
Intraday — Length 50–100 for liquid futures/FX; consider 0.20/0.80 inner and 0.02/0.98 outer in high-vol assets.
Crypto — Because of fat tails, try slightly wider outers (0.01/0.99) and keep smoothing at 2–4 to tame weekend jumps.
Signal ideas
Continuation — in an uptrend, look for pullback into the lower inner band with a close back above the center as a timing cue.
Exhaustion probe — in ranges, first touch of an outer band followed by a rejection candle back inside the inner band often precedes mean-reversion swings.
Regime shift — repeated closes beyond an outer band or a sharp re-tilt in the center line can mark a new trend phase; adjust tactics (stop-following along the opposite inner band).
Alerts included
“Price Crosses Upper Outer Band” — potential overextension or breakout risk.
“Price Crosses Lower Outer Band” — potential capitulation or breakdown risk.
Notes
The fit and quantiles are computed on a fixed rolling window and do not repaint; bands update as the window moves forward.
Quantiles are based on the recent distribution; if conditions change abruptly, expect band widths and skew to adapt over the next few bars.
Parameter choices directly shape behaviour: longer windows favour stability, tighter inner quantiles increase touch frequency, and extreme outer quantiles highlight only the rarest moves.
Final thought
Quantile bands answer a simple question: “How unusual is this move given the current trend and the way price has been missing it lately?” By scoring that question with real, distribution-aware limits rather than one-size-fits-all volatility you get cleaner pullback zones in trends, more honest “extreme” tags in ranges, and a framework for risk that matches the market’s recent personality.
