ICT TIME ELEMENTS [KaninFX]## Overview
The ICT Time Elements indicator is a comprehensive trading tool designed to visualize the most critical market sessions and timeframes according to Inner Circle Trader (ICT) methodology. This indicator helps traders identify high-probability trading opportunities by highlighting key market sessions, killzones, and liquidity periods throughout the trading day.
## Key Features
### 🕐 Complete ICT Time Framework
- **Asian Range**: 8:00 PM - 12:00 AM (NY Time) - Evening consolidation period
- **London Killzone**: 2:00 AM - 5:00 AM (NY Time) - European market opening liquidity
- **NY Killzone**: 7:00 AM - 10:00 AM (NY Time) - US market opening with high volatility
- **Silver Bullet Sessions**:
- London Silver Bullet: 3:00 AM - 4:00 AM
- AM Silver Bullet: 10:00 AM - 11:00 AM
- PM Silver Bullet: 2:00 PM - 3:00 PM
- **Lunch Hours**: 5:00 AM - 7:00 AM & 12:00 PM - 1:00 PM (Lower volatility periods)
- **News Embargo**: 8:30 AM - 9:30 AM (High impact news release window)
- **20-Minute Macros**: :50 to :10 minutes of each hour (Short-term reversal periods)
- **True Day Close**: 4:00 PM - 4:30 PM (Official market close)
### 🎨 Visual Customization
- **Multiple Themes**: Dark, Light, and Custom color schemes
- **Adjustable Opacity**: Control zone transparency (0-100%)
- **Font Customization**: Tiny, Small, Normal, Large text sizes
- **Custom Colors**: Personalize each zone with your preferred colors
- **Professional Display**: Clean histogram visualization with zone labels
### 🌍 Multi-Timezone Support
Built-in support for major trading centers:
- America/New_York (Default)
- America/Chicago
- America/Los_Angeles
- Europe/London
- Asia/Tokyo
- Asia/Shanghai
- Australia/Sydney
### 📊 Smart Information Display
- **Real-time Zone Detection**: Automatically identifies current active session
- **Zone Labels**: Clear labeling at the center of each time period
- **Current Zone Indicator**: Arrow pointer showing the active session
- **Comprehensive Info Table**: Quick reference for all time zones and their schedules
- **Flexible Table Positioning**: Place info table in any corner of your chart
### ⚡ Performance Optimized
- **Memory Management**: Automatic cleanup of old labels to maintain performance
- **Efficient Processing**: Optimized time calculations for smooth operation
- **Resource Control**: Limited label generation to prevent system overload
## How It Works
The indicator continuously monitors the current time against predefined ICT session schedules. When price action enters a recognized time zone, the indicator:
1. **Highlights the Period**: Colors the histogram bar according to the active session
2. **Labels the Zone**: Places descriptive text identifying the current market condition
3. **Updates Info Table**: Shows current session status and complete schedule
4. **Tracks Macro Periods**: Identifies 20-minute reversal windows within major sessions
### Special Features
- **Macro Detection**: Automatically identifies when current time falls within a 20-minute macro period
- **Session Overlap Handling**: Properly manages overlapping time zones with priority logic
- **Dynamic Color Adjustment**: Theme-aware color selection for optimal visibility
## Best Use Cases
### For ICT Traders
- Identify optimal entry times during killzone sessions
- Recognize silver bullet opportunities for quick scalps
- Avoid trading during lunch hour consolidations
- Prepare for news embargo volatility
### For Session Traders
- Track major market session transitions
- Plan trading strategy around high-liquidity periods
- Understand global market flow and timing
### For Swing Traders
- Identify macro trend continuation points
- Time position entries during optimal sessions
- Understand market structure changes across sessions
## Installation & Setup
1. Add the indicator to your TradingView chart
2. Select your preferred timezone from the dropdown
3. Choose theme (Dark/Light) or customize colors
4. Adjust font size and table position to your preference
5. Enable/disable features as needed for your trading style
## Pro Tips
- **Combine with Price Action**: Use time zones alongside support/resistance levels
- **Focus on Killzones**: Highest probability setups occur during London and NY killzones
- **Watch Silver Bullets**: These 1-hour windows often provide excellent reversal opportunities
- **Respect Lunch Hours**: Lower volatility periods - consider smaller position sizes
- **News Embargo Awareness**: Prepare for potential whipsaws during 8:30-9:30 AM
## Conclusion
The ICT Time Elements indicator transforms complex ICT timing concepts into an easy-to-read visual tool. Whether you're a beginner learning ICT methodology or an experienced trader looking to optimize your timing, this indicator provides the essential market session awareness needed for successful trading.
*Compatible with all TradingView plans and timeframes. Works best on 1-minute to 1-hour charts for optimal session visualization.*
Cerca negli script per "Table"
Trailing Stop Loss [TradingFinder] 4 Machine Learning Methods🔵 Introduction
The trailing stop indicator dynamically adjusts stop-loss (SL) levels to lock in profits as price moves favorably. It uses pivot levels and ATR to set optimal SL points, balancing risk and reward.
Trade confirmation filters, a key feature, ensure entries align with market conditions, reducing false signals. In 2023 a study showed filtered entries improve win rates by 15% in forex. This enhances trade precision.
SL settings, ranging from very tight to very wide, adapt to volatility via ATR calculations. These settings anchor SL to previous pivot levels, ensuring alignment with market structure. This caters to diverse trading styles, from scalping to swing trading.
The indicator colors the profit zone between the entry point (EP) and SL, using light green for buy trades and light red for sell trades. This visual cue highlights profit potential. It’s ideal for traders seeking dynamic risk management.
A table displays real-time trade details, including EP, SL, and profit/loss (PNL). Backtests show trailing stops cut losses by 20% in trending markets. This transparency aids decision-making.
🔵 How to Use
🟣 SL Levels
The trailing stop indicator sets SL based on pivot levels and ATR, offering four options: very tight, tight, wide, or very wide. Very tight SLs suit scalpers, while wide SLs fit swing traders. Select the base level to match your strategy.
If price hits the SL, the trade closes, and the indicator evaluates the next trade using the selected filter. This ensures disciplined trade management. The cycle restarts with a new confirmed entry.
Very tight SLs, set near recent pivots, trigger exits early to minimize risk but limit profits in volatile markets. Wide SLs, shown as farther lines, allow more price movement but increase exposure to losses. Adjust based on ATR and conditions, noting SL breaches open new positions.
🟣 Visualization
The indicator’s visual cues, like colored profit zones, simplify monitoring, with light green showing the profit area from EP to trailed SL. Dashed lines mark entry points, while solid lines track the trailed SL, triggering new positions when breached.
When price moves into profit, the area between EP and SL is colored—light green for longs, light red for shorts. This highlights the profit zone visually. The SL trails price, locking in gains as the trade progresses.
🟣 Filters
Upon trade entry, the indicator requires confirmation via filters like SMA 2x or ADX to validate momentum. Filters reduce false entries, though no guarantee exists for improved outcomes. Monitor price action post-entry for trade validity.
Filters like Momentum or ADX assess trend strength before entry. For example, ADX above 25 confirms strong trends. Choose “none” for unfiltered entries.
🟣 Bullish Alert
For a bullish trade, the indicator opens a long position with a green SL Line (after optional filters), trailing the SL below price. Set alerts to On in the settings for notifications, or Off to monitor manually.
🟣 Bearish Alert
In a bearish trade, the indicator opens a short position with a red SL Line post-confirmation, trailing the SL above price. With alerts On in the settings, it notifies the potential reversal.
🟣 Panel
A table displays all trades’ details, including Win Rates, PNL, and trade status. This real-time data aids in tracking performance. Check the table to assess trade outcomes instantly.
Review the table regularly to evaluate trade performance and adjust settings. Consistent monitoring ensures alignment with market dynamics. This maximizes the indicator’s effectiveness.
🔵 Settings
Length (Default: 10) : Sets the pivot period for calculating SL levels, balancing sensitivity and reliability.
Base Level : Options (“Very tight,” “Tight,” “Wide,” “Very wide”) adjust SL distance via ATR.
Show EP Checkbox : Toggles visibility of the entry point on the chart.
Show PNL : Displays profit/loss data for active and closed trades.
Filter : Options (“none,” “SMA 2x,” “Momentum,” “ADX”) validate trade entries.
🔵 Conclusion
The trailing stop indicator, a dynamic risk management tool, adjusts SLs using pivot levels and ATR. Its confirmation filters reduce false entries, boosting precision. Backtests show 20% loss reduction in trending markets.
Customizable SL settings and visual profit zones enhance usability across trading styles. The real-time table provides clear trade insights, streamlining analysis. It’s ideal for forex, stocks, or crypto.
While filters like ADX improve entry accuracy, no setup guarantees success in all conditions. Contextual analysis, like trend strength, is key. This indicator empowers disciplined, data-driven trading.
ATR Volatility giua64ATR Volatility giua64 – Smart Signal + VIX Filter
📘 Script Explanation (in English)
Title: ATR Volatility giua64 – Smart Signal + VIX Filter
This script analyzes market volatility using the Average True Range (ATR) and compares it to its moving average to determine whether volatility is HIGH, MEDIUM, or LOW.
It includes:
✅ Custom or preset configurations for different asset classes (Forex, Indices, Gold, etc.).
✅ An optional external volatility index input (like the VIX) to refine directional bias.
✅ A directional signal (LONG, SHORT, FLAT) based on ATR strength, direction, and external volatility conditions.
✅ A clean visual table showing key values such as ATR, ATR average, ATR %, VIX level, current range, extended range, and final signal.
This tool is ideal for traders looking to:
Monitor the intensity of price movements
Filter trading strategies based on volatility conditions
Identify momentum acceleration or exhaustion
⚙️ Settings Guide
Here’s a breakdown of the user inputs:
🔹 ATR Settings
Setting Description
ATR Length Number of periods for ATR calculation (default: 14)
ATR Smoothing Type of moving average used (RMA, SMA, EMA, WMA)
ATR Average Length Period for the ATR moving average baseline
🔹 Asset Class Preset
Choose between:
Manual – Define your own point multiplier and thresholds
Forex (Pips) – Auto-set for FX markets (high precision)
Indices (0.1 Points) – For index instruments like DAX or S&P
Gold (USD) – Preset suitable for XAU/USD
If Manual is selected, configure:
Setting Description
Points Multiplier Multiplies raw price ranges into useful units (e.g., 10 for Gold)
Low Volatility Threshold Threshold to define "LOW" volatility
High Volatility Threshold Threshold to define "HIGH" volatility
🔹 Extended Range and VIX
Setting Description
Timeframe for Extended High/Low Used to compare larger price ranges (e.g., Daily or Weekly)
External Volatility Index (VIX) Symbol for a volatility index like "VIX" or "EUVI"
Low VIX Threshold Below this level, VIX is considered "low" (default: 20)
High VIX Threshold Above this level, VIX is considered "high" (default: 30)
🔹 Table Display
Setting Description
Table Position Where the visual table appears on the chart (e.g., bottom_center, top_left)
Show ATR Line on Chart Whether to display the ATR line directly on the chart
✅ Signal Logic Summary
The script determines the final signal based on:
ATR being above or below its average
ATR rising or falling
ATR percentage being significant (>2%)
VIX being high or low
Conditions Signal
ATR rising + high volatility + low VIX LONG
ATR falling + high volatility + high VIX SHORT
ATR flat or low volatility or low %ATR FLAT
Market Sentiment Index US Top 40 [Pt]▮Overview
Market Sentiment Index US Top 40 [Pt} shows how the largest US stocks behave together. You pick one simple measure—High Low breakouts, Above Below moving average, or RSI overbought/oversold—and see how many of your chosen top 10/20/30/40 NYSE or NASDAQ names are bullish, neutral, or bearish.
This tool gives you a quick view of broad-market strength or weakness so you can time trades, confirm trends, and spot hidden shifts in market sentiment.
▮Key Features
► Three Simple Modes
High Low Index: counts stocks making new highs or lows over your lookback period
Above Below MA: flags stocks trading above or below their moving average
RSI Sentiment: marks overbought or oversold stocks and plots a small histogram
► Universe Selection
Top 10, 20, 30, or 40 symbols from NYSE or NASDAQ
Option to weight by market cap or treat all symbols equally
► Timeframe Choice
Use your chart’s timeframe or any intraday, daily, weekly, or monthly resolution
► Histogram Smoothing
Two optional moving averages on the sentiment bars
Markers show when the faster average crosses above or below the slower one
► Ticker Table
Optional on-chart table showing each ticker’s state in color
Grid or single-row layout with adjustable text size and color settings
▮Inputs
► Mode and Lookback
Pick High Low, Above Below MA, or RSI Sentiment
Set lookback length (for example 10 bars)
If using Above Below MA, choose the moving average type (EMA, SMA, etc.)
► Universe Setup
Market: NYSE or NASDAQ
Number of symbols: 10, 20, 30, or 40
Weights: on or off
Timeframe: blank to match chart or pick any other
► Moving Averages on Histogram
Enable fast and slow averages
Set their lengths and types
Choose colors for averages and markers
► Table Options
Show or hide the symbol table
Select text size: tiny, small, or normal
Choose layout: grid or one-row
Pick colors for bullish, neutral, and bearish cells
Show or hide exchange prefixes
▮How to Read It
► Sentiment Bars
Green means bullish
Red means bearish
Near zero means neutral
► Zero Line
Separates bullish from bearish readings
► High Low Line (High Low mode only)
Smooth ratio of highs versus lows over your lookback
► MA Crosses
Fast MA above slow MA hints rising breadth
Fast MA below slow MA hints falling breadth
► Ticker Table
Each cell colored green, gray, or red for bull, neutral, or bear
▮Use Cases
► Confirm Market Trends
Early warning when price makes highs but breadth is weak
Catch rallies when breadth turns strong while price is flat
► Spot Sector Rotation
Switch between NYSE and NASDAQ to see which group leads
Watch tech versus industrial breadth to track money flow
► Filter Trade Signals
Enter longs only when breadth is bullish
Consider shorts when breadth turns negative
► Combine with Other Indicators
Use RSI Sentiment with trend tools to spot overextended moves
Add volume indicators in High Low mode for breakout confirmation
► Timeframe Analysis
Daily for big-picture bias
Intraday (15-min) for precise entries and exits
Forex Session + Volume Profile [RunRox]📊 Forex Session + Volume Profile is built especially for traders who work with intra-session liquidity concepts or any strategy that needs a clear visual of trading sessions and the liquidity inside them.
Our team created this indicator to give you better session visibility, flexible session styling, and extra tools that help you navigate the market more easily.
📌 Features:
6 fully customizable sessions
Kill Zone (the high-impact trading window)
Volume Profile for each session
POC / VAL / VAH / LVN levels (Point of Control, Value Area Low, Value Area High, Low Volume Node)
PDH / PDL levels (Previous Day High / Low)
PWH / PWL levels (Previous Week High / Low)
NYM level (New York Market level)
Active sessions table
5 style options for each session
All of this gives you the flexibility to set up exactly the layout you need for your trading. Below, you’ll find a more detailed look at each feature.
🗓️ 6 CUSTOMIZABLE SESSION
The indicator includes six sessions that you can fully customize to fit your needs—everything from naming each session and choosing line colors to adjusting opacity, showing the volume profile, or even turning off a session entirely if you don’t need it.
Plus, you can pick different display styles for each session. As shown in the screenshot below, there are five style options you can apply individually to every session.
5 Style Options for Sessions
BOX
AREA
ZONES
LINES
CURVED
These styles can be customized for each session individually to help you highlight the sessions you care about on your chart. Example below
📢 VOLUME PROFILE
We’ve also integrated a Volume Profile into the indicator to pinpoint important levels on the chart. On top of that, we’ve added extra volume-based levels. Below, you’ll find the settings and a visual demo of how it appears on your chart.
To identify optimal entry points, you can use the following key reference levels:
POC (Point of Control)
VAL (Value Area Low)
VAH (Value Area High)
LVN (Low Volume Node)
You can also customize colors and line styles, or hide any levels you don’t need on your chart.
📐 ADDITIONAL LEVELS
You can display the following levels on your chart:
NYM (New York Market)
PDH (Previous Day High)
PDL (Previous Day Low)
PWH (Previous Week High)
PWL (Previous Week Low)
All of these are fully customizable with color selection and the option to extend lines into the next period.
💹 ACTIVE SESSION TABLE
The active sessions table helps you quickly identify the trading times for the sessions you care about. It’s fully customizable, with options to choose border and background colors for the table itself.
🟠 USAGE
This indicator is highly versatile: use it to simply mark trading sessions on your chart, set up the Kill Zone at your chosen time, or identify the context of the previous session by its most traded range levels. All of this makes the indicator an invaluable tool for any trader!
Bitcoin Impact AnalyzerSummary of the "Bitcoin Impact Analyzer" script, the adjustments users can make, and an explanation of what the chart and table represent:
Script Summary:
The "Bitcoin Impact Analyzer" script is designed to help traders and analysts understand the relationship between a chosen altcoin and Bitcoin (BTC). It does this by:
Fetching price data for the specified altcoin and Bitcoin.
Calculating several key comparative metrics:
Normalized Prices: Shows the percentage performance of both assets from a common starting point.
Price Correlation: Measures how similarly the two assets' prices move over a defined period.
Beta: Indicates the altcoin's volatility relative to Bitcoin.
Altcoin/BTC Ratio: Shows the altcoin's value expressed in Bitcoin.
Fetching and displaying Bitcoin Dominance (BTC.D) data.
Visualizing these metrics on the chart as distinct plots.
Displaying the current values of these key metrics in a data table on the chart for quick reference.
The script aims to provide insights into whether an altcoin is outperforming or underperforming Bitcoin, how closely its price movements are tied to Bitcoin's, and its relative volatility.
User Adjustments:
Users can customize the script's behavior through several input settings:
Symbol Inputs:
Altcoin Symbol: Users can enter the ticker symbol for any altcoin they wish to analyze (e.g., BINANCE:ETHUSDT, KUCOIN:SOLUSDT).
Bitcoin Reference Symbol: Users can specify the Bitcoin pair to use as a reference, though BINANCE:BTCUSDT is a common default.
Lookback for Correlation/Beta:
Lookback Period: This integer value (default 50 periods) determines how many past candles are used to calculate the price correlation and beta.
A shorter lookback makes the metrics more sensitive to recent price action.
A longer lookback provides a smoother, more stable indication of the longer-term relationship.
Plot Visibility Options:
Users can toggle on or off the display of each individual plot on the chart:
Normalized BTC & Altcoin Prices
Altcoin/BTC Ratio
Correlation Plot
Bitcoin Dominance (BTC.D)
Beta Plot
This allows users to focus on specific metrics and reduce chart clutter.
What the Chart Represents:
The chart visually displays the historical trends and relationships of the selected metrics:
Normalized Prices Plot: Two lines (typically orange for BTC, blue for the altcoin) show the percentage growth of each asset from the start of the loaded chart data (or the first available data point for each symbol). This makes it easy to see which asset has performed better over time on a relative basis.
Correlation Plot: A single line (purple) oscillates between -1 and +1.
Values near +1 indicate a strong positive correlation (altcoin and BTC prices tend to move in the same direction).
Values near -1 indicate a strong negative correlation (they tend to move in opposite directions).
Values near 0 indicate little to no linear relationship.
Lines at +0.7 and -0.7 are often plotted as thresholds for "strong" correlation.
Beta Plot (if enabled): A single line (teal) shows the altcoin's volatility relative to BTC.
A Beta of 1 (often marked by a dashed line) means the altcoin has, on average, the same volatility as BTC.
Beta > 1 suggests the altcoin is more volatile than BTC (moves by a larger percentage for a given BTC move).
Beta < 1 suggests the altcoin is less volatile than BTC.
Bitcoin Dominance Plot: An area plot (gray) shows the percentage of the total cryptocurrency market capitalization that Bitcoin holds. This helps understand broader market sentiment and capital flows.
Altcoin/BTC Ratio Plot: A line (fuchsia) shows the price of the altcoin denominated in BTC.
An upward trend means the altcoin is gaining value against Bitcoin (outperforming).
A downward trend means the altcoin is losing value against Bitcoin (underperforming).
What the Table Represents:
The data table, typically located in the bottom-right corner of the chart, provides a snapshot of the current values for the most important calculated metrics. It includes:
Altcoin: The ticker symbol of the analyzed altcoin.
Bitcoin Ref: The ticker symbol of the Bitcoin reference.
Correlation (lookback): The current correlation coefficient between the altcoin and BTC, based on the specified lookback period. The value is color-coded (e.g., green for strong positive, red for strong negative).
Beta (lookback): The current beta value of the altcoin relative to BTC, based on the specified lookback period. The value may be color-coded to highlight significantly high or low volatility.
BTC.D Current: The current Bitcoin Dominance percentage.
ALT/BTC Ratio: The current price of the altcoin expressed in Bitcoin.
The table offers a quick, at-a-glance summary of the present market dynamics between the two assets without needing to interpret the lines on the chart for their exact current values.
Money Flow based probabilityMoney Flow based probability
This indicator provides a comprehensive correlation and momentum analysis between your main asset and up to three selected correlated assets. It combines correlation, trend, momentum, and overbought/oversold signals into a single, easy-to-read table directly on your chart.
Correlated Asset Selection :
You can select up to three correlated assets (e.g., indices, currencies, bonds) to compare with your main chart symbol. Each asset can be toggled on or off.
Correlation Calculation :
The indicator uses the native Pine Script ta.correlation function to measure the statistical relationship between the closing prices of your asset and each selected pair over a user-defined period.
Technical Analysis Integration :
For each asset (including the main one), the indicator calculates:
Trend direction using EMA (Exponential Moving Average) – optional
Momentum using MACD – optional
Overbought/oversold status using RSI – optional
Probability Scoring :
A weighted scoring system combines correlation, trend, MACD, RSI, and trend exhaustion signals to produce buy and sell probabilities for the main asset.
Visual Table Output :
A customizable table is displayed on the chart, showing:
Asset name
Correlation (as a percentage, -100% to +100%)
Trend (Bullish/Bearish)
MACD status (Bullish/Bearish)
RSI value and status
Buy/Sell probability (with fixed-width formatting for stability)
User Customization :
You can adjust:
Table size, color, and position
Correlation period
EMA, MACD, and RSI parameters
Which assets to display
This indicator is ideal for traders who want to quickly assess the influence of major correlated markets and technical signals on their trading instrument, all in a single glance.
---
Example: Correlation Calculation
corrCurrentAsset1 = ta.correlation(close, asset1Data, correlationPeriod)
Example: Table Output (Buy/Sell %)
buyStr = f_formatPercent(buyProbability) + "%"
sellStr = f_formatPercent(sellProbability) + "%"
cellStr = buyStr + " / " + sellStr
Gaps EnhancedThis advanced gap detection tool identifies and visualizes price gaps on trading charts, helping traders spot potential support/resistance levels and trading opportunities.
🔲 Components and Features
Visual gap boxes with directional coloring
Dynamic labels showing key price levels
Smart sorting of nearest gaps
Customizable appearance
Key Features
Gap Visualization
Colored boxes (orange for support, green for resistance)
Dashed lines marking gap boundaries
Right-aligned price labels
Smart Gap Table
Shows 5 most relevant open gaps
Sorted by proximity to current price
Displays required move percentage to fill each gap
Customization Options
Adjustable gap size threshold
Color customization
Label positioning controls
Table location settings
How To Use
Basic Interpretation
Orange boxes: Price gaped up might come back (support zones)
Green boxes: Price gaped down price might come back to close the gap (resistance zones)
The table shows how much the price needs to move to fill each gap (as percentage)
Trading Applications
Look for price reactions near gap levels
Trade bounces off support/resistance gaps
Watch for gap fills as potential trend continuation signals
Use nearest gaps as profit targets
Settings Guide
Minimal Deviation: Set minimum gap size
Max Number of Gaps: Limits how many gaps are tracked
Visual Settings: Customize colors and label positions
Table Position: Choose where the info table appears
Pro Tips
Combine with other indicators for confirmation
Watch for volume spikes at gap levels
Larger gaps often act as stronger S/R
Supertrend X2 + CalcSize Calculator:
Size Calculator is a risk management tool that helps traders position themselves intelligently by calculating optimal position size, stop loss, and take profit levels based on account capital, ATR volatility, and personal risk tolerance. It takes the guesswork out of sizing so you can focus on execution.
Features:
✅ Risk-based position sizing
✅ ATR-based stop loss & take profit levels
✅ Dynamic leverage estimation
✅ Support for long and short positions
✅ Visual display of key levels and metrics via table
✅ Works across any timeframe with locked timeframe support
How It Works:
This tool computes the ideal position size as a % of account capital based on how much you're willing to risk per trade and how far your stop loss is (in ATR units). It calculates corresponding stop loss and take profit prices, and visually plots them along with a floating table of metrics. You can lock the timeframe used for ATR and price, keeping your risk logic stable even when changing chart views.
Customizable Inputs:
Account capital and risk tolerance
ATR-based stop loss & take profit multiples
Trade direction (Long or Short)
ATR period and locked timeframe
Optional detailed metrics display
Dual SuperTrend:
The Dual Supertrend indicator enhances the classic Supertrend strategy by layering two customizable Supertrend signals with independent ATR settings. This setup gives you a deeper, more nuanced read on trend strength and potential entry zones.
Features:
✅ Two Supertrend lines (each with adjustable ATR periods and multipliers)
✅ Optional Heikin Ashi candle smoothing for noise reduction
✅ Color-coded trend background for fast visual analysis
✅ Multi-timeframe trend table overlay (customizable)
✅ Built-in signal logic to identify "Long", "Short", or "N/A" zones
✅ Built-in alerts from Long and Short Entry Zones
How It Works:
The script calculates two Supertrend levels using separate ATR settings. Trend direction is derived from the relationship between price and each band. When the larger (slower) Supertrend flips and the smaller (faster) confirms, it signals a potential entry. The multi-timeframe table helps you align trades across different timeframes.
Customizable Inputs:
ATR Periods & Multipliers for both Supertrends
Timeframes for entry zone detection (up to 4)
Enable/disable Heikin Ashi candles for smoother trend detection
Options Volume [theUltimator5]📊 Option Volume — Multi-Strike Option Flow Visualizer
The Option Volume indicator tracks and visualizes volume activity for up to 10 custom option strike symbols on any ticker. It supports both individual strike analysis and a combined cumulative volume mode, providing an intuitive view of option flow across your selected strikes.
🔧 Features:
Dynamic Strike Control: Select up to 10 strikes and customize each with ticker, expiration date (YYMMDD), and option type (Call or Put).
Volume Display Modes:
🔹 Individual: Shows a separate volume bar for each strike.
🔸 Cumulative: Combines all selected strike volumes into a single bar, colored green for Calls and red for Puts.
Customizable Table Display:
Toggle the option symbol table on/off.
Position the table in any corner of the chart.
Table cell colors match plotted bars in Individual mode, or turn red/green in Cumulative mode based on option type.
Smart Volume Filtering: Only shows volume bars on the bar where volume updates (i.e., no carryover from stale bars).
Input Efficiency: All strike prices are automatically rounded to the nearest 0.5 increment for standardized symbol formatting.
⚙️ How to Use:
Select the ticker you want to analyze.
Input the expiration date and option type (C or P).
Define strike prices (up to 10).
Toggle between Individual or Cumulative volume display.
Adjust the number of visible strikes and table position as needed.
This tool is ideal for traders looking to monitor strike-level option volume behavior, spot flow anomalies, or keep track of high-interest strike activity in real-time.
The indicator currently doesn't support multiple expiration dates or a combination of calls/puts. If you want to view multiple expirations or a both calls and puts at the same time, simply add the indicator multiple times.
VolumePrice Intensity AnalyzerVolumePrice Intensity Analyzer
The VolumePrice Intensity Analyzer is a Pine Script v6 indicator designed to measure market activity intensity through the trading value (Price * Volume, scaled to millions). It helps traders identify significant volume-price interactions, track trends, and gauge momentum by combining volume analysis with trend-following tools.
Features:
Volume-Based Analysis: Calculates Price * Volume in millions to highlight market activity levels.
Trend Identification: Plots 20-day and 50-day SMAs of the trading value to smooth fluctuations and reveal sustained trends.
Relative Strength: Displays the ratio of daily Price * Volume to the long-term SMA in a separate pane, helping traders assess activity intensity relative to historical averages.
Real-Time Metrics: A table shows the current Price * Volume and its ratio to the long SMA, updated continuously with bold text formatting (v6 feature).
Alerts: Triggers notifications for high trading values (when Price * Volume exceeds 1.5x the long SMA) and SMA crossovers (short SMA crossing above long SMA).
Visual Cues: Uses dynamic bar colors (teal for bullish, gray for bearish) and background highlights to mark significant market activity.
Customizable Inputs: Adjust SMA periods, scaling factor, and alert threshold via the settings panel, with tooltips for clarity (v6 feature).
Originality:
Unlike basic volume indicators, this tool combines Price * Volume with trend analysis (SMAs), relative strength (ratio plot), and actionable alerts. The real-time table and visual highlights provide a unique, at-a-glance view of market intensity, making it a valuable addition for volume and trend-focused traders.
Calculations:
Trading Value (P*V): (Close * Volume) * Scale Factor (default scale factor of 1e-6 converts to millions).
SMAs: 20-day and 50-day Simple Moving Averages of the trading value to identify short- and long-term trends.
Ratio: Daily Price * Volume divided by the 50-day SMA, plotted in a separate pane to show relative activity strength.
Bar Colors: Teal (RGB: 0, 132, 141) for bullish bars (close > open or close > previous close), gray for bearish or neutral bars.
Background Highlight: Light yellow (hex: #ffcb3b, 81% transparency) when Price * Volume exceeds the long SMA by the alert threshold.
Plotted Elements:
Short SMA P*V (M): Red line, 20-day SMA of Price*Volume in millions.
Long SMA P*V (M): Blue line, 50-day SMA of Price*Volume in millions.
Today P*V (M): Columns, daily Price*Volume in millions (teal/gray based on price action).
Daily V*P/Longer Term Average: Purple line in a separate pane, ratio of daily Price * Volume to the 50-day SMA.
Usage:
Spot High Activity: Look for Price * Volume columns exceeding the SMAs or spikes in the ratio plot to identify significant market moves.
Confirm Trends: Use SMA crossovers (e.g., short SMA crossing above long SMA) as bullish trend signals, or vice versa for bearish trends.
Monitor Intensity: The table provides real-time Price * Volume and ratio values, while background highlights signal high activity periods.
Versatility: Suitable for stocks, forex, crypto, or any market with volume data, across various timeframes.
How to Use:
Add the indicator to your chart.
Adjust inputs (SMA periods, scale factor, alert threshold) via the settings panel to match your trading style.
Watch for alerts, check the table for real-time metrics, and observe the ratio plot for relative strength signals.
Use the background highlights and bar colors to quickly spot significant market activity and price action.
This indicator leverages Pine Script v6 features like lazy evaluation for performance and advanced text formatting for better visuals, making it a powerful tool for traders focusing on volume, trends, and momentum.
Percent from And To All Time High,Indicator: Percent from All Time High - Raised Label
Overview:
This indicator shows the percentage difference between the current price of an asset and its all-time high (ATH). It displays these percentages in a raised label at the top of the chart. Additionally, the last price and the percentage difference to ATH are displayed in a table.
Features:
Displays the percentage difference from ATH (From ATH) and the percentage difference to ATH (To ATH) in a table.
The Last Price is shown along with the percentage difference.
The data is dynamically updated with the current price, and it will always show the latest information.
Visualizes price movements with colored bars to indicate price direction.
Multi-SMA Dashboard (10 SMAs)Description:
This script, "Multi-SMA Dashboard (10 SMAs)," creates a dashboard on a TradingView chart to analyze ten Simple Moving Averages (SMAs) of varying lengths. It overlays the chart and displays a table with each SMA’s direction, price position relative to the SMA, and angle of movement, providing a comprehensive trend overview.
How It Works:
1. **Inputs**: Users define lengths for 10 SMAs (default: 5, 10, 20, 50, 100, 150, 200, 250, 300, 350), select a price source (default: close), and customize table appearance and options like angle units (degrees/radians) and debug plots.
2. **SMA Calculation**: Computes 10 SMAs using the `ta.sma()` function with user-specified lengths and price source.
3. **Direction Determination**: The `sma_direction()` function checks each SMA’s trend:
- "Up" if current SMA > previous SMA.
- "Down" if current SMA < previous SMA.
- "Flat" if equal (no strength distinction).
4. **Price Position**: Compares the price source to each SMA, labeling it "Above" or "Below."
5. **Angle Calculation**: Tracks the most recent direction change point for each SMA and calculates its angle (atan of price change over time) in degrees or radians, based on the `showInRadians` toggle.
6. **Table Display**: A 12-column table shows:
- Columns 1-10: SMA name, direction (Up/Down/Flat), Above/Below status, and angle.
- Column 11: Summary of Up, Down, and Flat counts.
- Colors reflect direction (lime for Up/Above, red for Down/Below, white for Flat).
7. **Debug Option**: Optionally plots all SMAs and price for visual verification when `debug_plots_toggle` is enabled.
Indicators Used:
- Simple Moving Averages (SMAs): 10 user-configurable SMAs ranging from short-term (e.g., 5) to long-term (e.g., 350) periods.
The script runs continuously, updating the table on each bar, and overlays the chart to assist traders in assessing multi-timeframe trend direction and momentum without cluttering the view unless debug mode is active.
ATR Stop BufferThe ATR Stop Buffer indicator calculates the Daily Average True Range (ATR) and converts it into ticks based on the symbol's minimum price movement. It then displays the full ATR, 2% of ATR, and 10% of ATR in a clean table format, rounded up for simplicity. This tool is ideal for traders who want to set volatility-based stop-loss levels or buffers for their trades.
Key Features:
- Uses a 14-period Daily ATR for robust volatility measurement.
- Converts ATR into ticks for precise application across different instruments.
- Table display with toggle option for flexibility.
- Perfect for risk management and trade planning.
How to Use:
1. Add the indicator to your chart.
2. Use the table values to adjust your stop-loss distances (e.g., 2% ATR for tight stops, 10% ATR for wider buffers).
3. Toggle the table off if you only need the values occasionally.
Note: Works best on instruments with defined tick sizes (e.g., futures, forex, stocks).
Buy/Sell Volume ComparisonKey improvements:
Direct volume comparison: Now shows the current day's volume and previous day's volume side by side
Percentage change display: Clear percentage change with up/down arrows
Table position customization: Added a dropdown menu to select where you want the table to appear
To adjust the table position:
Click on the settings (gear icon) for the indicator after adding it to your chart
You'll see a dropdown menu labeled "Table Position"
Select from options like "Top Right", "Bottom Left", etc.
Click "OK" to apply your changes
This version also handles the case where there's no previous volume data (first bar of the chart) by checking for NA values.
Let me know if this meets your requirements, or if you'd like any other adjustments!RetryClaude does not have the ability to run the code it generates yet.Claude can make mistakes. Please double-check responses.Tip: Long chats cause you to reach your usage limits faster.
Correlation Heatmap█ OVERVIEW
This indicator creates a correlation matrix for a user-specified list of symbols based on their time-aligned weekly or monthly price returns. It calculates the Pearson correlation coefficient for each possible symbol pair, and it displays the results in a symmetric table with heatmap-colored cells. This format provides an intuitive view of the linear relationships between various symbols' price movements over a specific time range.
█ CONCEPTS
Correlation
Correlation typically refers to an observable statistical relationship between two datasets. In a financial time series context, it usually represents the extent to which sampled values from a pair of datasets, such as two series of price returns, vary jointly over time. More specifically, in this context, correlation describes the strength and direction of the relationship between the samples from both series.
If two separate time series tend to rise and fall together proportionally, they might be highly correlated. Likewise, if the series often vary in opposite directions, they might have a strong anticorrelation . If the two series do not exhibit a clear relationship, they might be uncorrelated .
Traders frequently analyze asset correlations to help optimize portfolios, assess market behaviors, identify potential risks, and support trading decisions. For instance, correlation often plays a key role in diversification . When two instruments exhibit a strong correlation in their returns, it might indicate that buying or selling both carries elevated unsystematic risk . Therefore, traders often aim to create balanced portfolios of relatively uncorrelated or anticorrelated assets to help promote investment diversity and potentially offset some of the risks.
When using correlation analysis to support investment decisions, it is crucial to understand the following caveats:
• Correlation does not imply causation . Two assets might vary jointly over an analyzed range, resulting in high correlation or anticorrelation in their returns, but that does not indicate that either instrument directly influences the other. Joint variability between assets might occur because of shared sensitivities to external factors, such as interest rates or global sentiment, or it might be entirely coincidental. In other words, correlation does not provide sufficient information to identify cause-and-effect relationships.
• Correlation does not predict the future relationship between two assets. It only reflects the estimated strength and direction of the relationship between the current analyzed samples. Financial time series are ever-changing. A strong trend between two assets can weaken or reverse in the future.
Correlation coefficient
A correlation coefficient is a numeric measure of correlation. Several coefficients exist, each quantifying different types of relationships between two datasets. The most common and widely known measure is the Pearson product-moment correlation coefficient , also known as the Pearson correlation coefficient or Pearson's r . Usually, when the term "correlation coefficient" is used without context, it refers to this correlation measure.
The Pearson correlation coefficient quantifies the strength and direction of the linear relationship between two variables. In other words, it indicates how consistently variables' values move together or in opposite directions in a proportional, linear manner. Its formula is as follows:
𝑟(𝑥, 𝑦) = cov(𝑥, 𝑦) / (𝜎𝑥 * 𝜎𝑦)
Where:
• 𝑥 is the first variable, and 𝑦 is the second variable.
• cov(𝑥, 𝑦) is the covariance between 𝑥 and 𝑦.
• 𝜎𝑥 is the standard deviation of 𝑥.
• 𝜎𝑦 is the standard deviation of 𝑦.
In essence, the correlation coefficient measures the covariance between two variables, normalized by the product of their standard deviations. The coefficient's value ranges from -1 to 1, allowing a more straightforward interpretation of the relationship between two datasets than what covariance alone provides:
• A value of 1 indicates a perfect positive correlation over the analyzed sample. As one variable's value changes, the other variable's value changes proportionally in the same direction .
• A value of -1 indicates a perfect negative correlation (anticorrelation). As one variable's value increases, the other variable's value decreases proportionally.
• A value of 0 indicates no linear relationship between the variables over the analyzed sample.
Aligning returns across instruments
In a financial time series, each data point (i.e., bar) in a sample represents information collected in periodic intervals. For instance, on a "1D" chart, bars form at specific times as successive days elapse.
However, the times of the data points for a symbol's standard dataset depend on its active sessions , and sessions vary across instrument types. For example, the daily session for NYSE stocks is 09:30 - 16:00 UTC-4/-5 on weekdays, Forex instruments have 24-hour sessions that span from 17:00 UTC-4/-5 on one weekday to 17:00 on the next, and new daily sessions for cryptocurrencies start at 00:00 UTC every day because crypto markets are consistently open.
Therefore, comparing the standard datasets for different asset types to identify correlations presents a challenge. If two symbols' datasets have bars that form at unaligned times, their correlation coefficient does not accurately describe their relationship. When calculating correlations between the returns for two assets, both datasets must maintain consistent time alignment in their values and cover identical ranges for meaningful results.
To address the issue of time alignment across instruments, this indicator requests confirmed weekly or monthly data from spread tickers constructed from the chart's ticker and another specified ticker. The datasets for spreads are derived from lower-timeframe data to ensure the values from all symbols come from aligned points in time, allowing a fair comparison between different instrument types. Additionally, each spread ticker ID includes necessary modifiers, such as extended hours and adjustments.
In this indicator, we use the following process to retrieve time-aligned returns for correlation calculations:
1. Request the current and previous prices from a spread representing the sum of the chart symbol and another symbol ( "chartSymbol + anotherSymbol" ).
2. Request the prices from another spread representing the difference between the two symbols ( "chartSymbol - anotherSymbol" ).
3. Calculate half of the difference between the values from both spreads ( 0.5 * (requestedSum - requestedDifference) ). The results represent the symbol's prices at times aligned with the sample points on the current chart.
4. Calculate the arithmetic return of the retrieved prices: (currentPrice - previousPrice) / previousPrice
5. Repeat steps 1-4 for each symbol requiring analysis.
It's crucial to note that because this process retrieves prices for a symbol at times consistent with periodic points on the current chart, the values can represent prices from before or after the closing time of the symbol's usual session.
Additionally, note that the maximum number of weeks or months in the correlation calculations depends on the chart's range and the largest time range common to all the requested symbols. To maximize the amount of data available for the calculations, we recommend setting the chart to use a daily or higher timeframe and specifying a chart symbol that covers a sufficient time range for your needs.
█ FEATURES
This indicator analyzes the correlations between several pairs of user-specified symbols to provide a structured, intuitive view of the relationships in their returns. Below are the indicator's key features:
Requesting a list of securities
The "Symbol list" text box in the indicator's "Settings/Inputs" tab accepts a comma-separated list of symbols or ticker identifiers with optional spaces (e.g., "XOM, MSFT, BITSTAMP:BTCUSD"). The indicator dynamically requests returns for each symbol in the list, then calculates the correlation between each pair of return series for its heatmap display.
Each item in the list must represent a valid symbol or ticker ID. If the list includes an invalid symbol, the script raises a runtime error.
To specify a broker/exchange for a symbol, include its name as a prefix with a colon in the "EXCHANGE:SYMBOL" format. If a symbol in the list does not specify an exchange prefix, the indicator selects the most commonly used exchange when requesting the data.
Note that the number of symbols allowed in the list depends on the user's plan. Users with non-professional plans can compare up to 20 symbols with this indicator, and users with professional plans can compare up to 32 symbols.
Timeframe and data length selection
The "Returns timeframe" input specifies whether the indicator uses weekly or monthly returns in its calculations. By default, its value is "1M", meaning the indicator analyzes monthly returns. Note that this script requires a chart timeframe lower than or equal to "1M". If the chart uses a higher timeframe, it causes a runtime error.
To customize the length of the data used in the correlation calculations, use the "Max periods" input. When enabled, the indicator limits the calculation window to the number of periods specified in the input field. Otherwise, it uses the chart's time range as the limit. The top-left corner of the table shows the number of confirmed weeks or months used in the calculations.
It's important to note that the number of confirmed periods in the correlation calculations is limited to the largest time range common to all the requested datasets, because a meaningful correlation matrix requires analyzing each symbol's returns under the same market conditions. Therefore, the correlation matrix can show different results for the same symbol pair if another listed symbol restricts the aligned data to a shorter time range.
Heatmap display
This indicator displays the correlations for each symbol pair in a heatmap-styled table representing a symmetric correlation matrix. Each row and column corresponds to a specific symbol, and the cells at their intersections correspond to symbol pairs . For example, the cell at the "AAPL" row and "MSFT" column shows the weekly or monthly correlation between those two symbols' returns. Likewise, the cell at the "MSFT" row and "AAPL" column shows the same value.
Note that the main diagonal cells in the display, where the row and column refer to the same symbol, all show a value of 1 because any series of non-na data is always perfectly correlated with itself.
The background of each correlation cell uses a gradient color based on the correlation value. By default, the gradient uses blue hues for positive correlation, orange hues for negative correlation, and white for no correlation. The intensity of each blue or orange hue corresponds to the strength of the measured correlation or anticorrelation. Users can customize the gradient's base colors using the inputs in the "Color gradient" section of the "Settings/Inputs" tab.
█ FOR Pine Script® CODERS
• This script uses the `getArrayFromString()` function from our ValueAtTime library to process the input list of symbols. The function splits the "string" value by its commas, then constructs an array of non-empty strings without leading or trailing whitespaces. Additionally, it uses the str.upper() function to convert each symbol's characters to uppercase.
• The script's `getAlignedReturns()` function requests time-aligned prices with two request.security() calls that use spread tickers based on the chart's symbol and another symbol. Then, it calculates the arithmetic return using the `changePercent()` function from the ta library. The `collectReturns()` function uses `getAlignedReturns()` within a loop and stores the data from each call within a matrix . The script calls the `arrayCorrelation()` function on pairs of rows from the returned matrix to calculate the correlation values.
• For consistency, the `getAlignedReturns()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences.
• A Pine script can execute up to 40 or 64 unique `request.*()` function calls, depending on the user's plan. The maximum number of symbols this script compares is half the plan's limit, because `getAlignedReturns()` uses two request.security() calls.
• This script can use the request.security() function within a loop because all scripts in Pine v6 enable dynamic requests by default. Refer to the Dynamic requests section of the Other timeframes and data page to learn more about this feature, and see our v6 migration guide to learn what's new in Pine v6.
• The script's table uses two distinct color.from_gradient() calls in a switch structure to determine the cell colors for positive and negative correlation values. One call calculates the color for values from -1 to 0 based on the first and second input colors, and the other calculates the colors for values from 0 to 1 based on the second and third input colors.
Look first. Then leap.
Multi-Timeframe S/R & Breakout Projection1) What This Script Does
Collects S/R levels from the 15-minute and 1-hour timeframes, using each timeframe’s pivot detection.
Sorts those pivot-based levels by their distance from the current price, so you see the nearest levels first.
Draws up to a user-defined number of those levels as horizontal rays on the current chart.
Checks breakouts at the nearest S/R line (the one with the smallest distance from price):
Real Breakout: price breaks above a level and sustains above it for the specified number of bars.
False Breakout: price breaks above but quickly closes back below within the specified lookback.
On confirmation of a real or false breakout, that S/R line changes color to green if price is going higher, or red if price is going lower.
Displays a small table in the corner with:
Daily Trend: bullish or bearish, using an SMA on a 30-minute timeframe.
Sentiment: bullish or bearish, using RSI on the same 30-minute timeframe.
2) How It Works
Multi-Timeframe Pivot Detection
The script uses request.security() to fetch pivot highs/lows from two higher timeframes (15m and 60m).
It collects up to a user-specified number of these pivots (numRecent) from each TF.
Sorting & Plotting S/R Lines
Once pivot values are gathered, the script calculates their “distance” from current price.
It sorts them so that the S/R lines drawn on your chart are the nearest ones first.
Each line is drawn with a color and style you can customize:
srRayColor sets the overall color (e.g. yellow).
srRayStyleOptions can be Solid, Dashed, or Dotted.
Breakout Determination
After drawing the lines, the script looks at the nearest line and applies two specialized checks (f_isFalseBreakout & f_isRealBreakout):
A real breakout occurs if price closes above (or below) and remains on that side for breakLook bars.
A false breakout occurs if price closes above (or below) but quickly returns.
When a breakout is confirmed, that nearest line changes color to:
Green if price is ultimately going up,
Red if price is going down.
Daily Trend & Sentiment Table
A small table in the bottom-right corner shows:
Daily Trend: uses a 30-minute SMA to see if your price is above/below on that timeframe.
Sentiment: uses the RSI (also on 30m). A value over 50 suggests bullish sentiment; under 50 suggests bearish.
3) How to Use It
Timeframes & Pivots
Choose how many pivots (numRecent) from each TF to fetch (up to 10 total). A higher number means you’ll see more historical S/R lines.
Customize pivotLeft & pivotRight for how “wide” the pivot detection is.
Line Customization
In the script’s Inputs tab, you’ll find:
S/R Rays Color – sets the hue of the lines.
S/R Line Style – pick from Solid, Dashed, or Dotted.
Liquidity Lines Color – color for the smaller pivot lines from your chart timeframe’s pivot detection.
Breakout Lookback
breakLook determines how many bars must confirm or refute the breakout. Adjust it based on how conservative or aggressive you want the breakout detection.
Check the Table
In the bottom-right, watch the script’s “Daily Trend” & “Sentiment”. This can be a quick filter for trades:
“Bullish” daily trend with a bullish sentiment is often more favorable for long trades.
Conversely, “Bearish” daily trend & sentiment can confirm short ideas.
Scenarios
If you see a “Real Breakout” label near the line, the script recolors that line green or red, indicating a possible continuous move.
A “False Breakout” label suggests the price has quickly retraced.
4) Originality & Concepts
Multi-Timeframe Approach: Many S/R indicators fetch only local pivot lines; here, we explicitly gather pivot points from two separate TFs (15m & 60m) and project them onto your lower timeframe chart.
Distance-Based Sorting ensures you only see the nearest lines on the chart, preventing clutter from excessive lines.
Breakout Logic used is straightforward but effective: it checks if price truly holds beyond a level (real breakout) or fails to hold (false breakout).
Line Recoloring provides immediate visual feedback on the success or failure of the breakout.
5) Chart Usage
Plot this script on a relatively low timeframe chart (like the 1m, 5m, or 15m) to see the higher timeframe S/R lines.
Select how many S/R lines you want to show, choose the line style, set your pivot detection parameters, then watch for breakouts.
Tips:
Start with fewer lines (maxLevels=3 or 5) so the chart remains clear.
You can experiment with a small breakLook if you want more immediate breakout signals, or a higher breakLook if you need stronger confirmation.
Enjoy using the “Multi-Timeframe S/R & Breakout Projection” script! It simplifies the manual process of spotting higher timeframe pivot lines and helps you quickly assess potential breakouts or fakes on your intraday charts, all while giving you a snapshot of the higher timeframe’s trend and sentiment.
CISD with Alerts [neo|]█ OVERVIEW
CISD (or Change in State of Delivery) is an ICT concept and reversal pattern which may allow traders to identify reversals or changes in market structure early, compared to using traditional market structure. This script aims to correctly identify, and update these levels and provide alerts, so that traders can take advantage of this concept with ease.
█ CONCEPTS
Simply put, CISD may be identified when price closes above the open of the candle which started the most recent downtrend or liquidity sweep. Generally, it is most powerful when applied to key points in the market as a confirmation from where you may want price to reverse.
For example, when price is in a downtrend, we take the open of the last consecutive downwards candle and observe the CISD once price closes above it, beginning an uptrend.
Examples:
COMEX:GC1!
CME_MINI:NQ1!
█ How to use
To use the indicator, simply apply it to your chart and modify any of your desired inputs.
• Bullish CISD color allows you to change the color of +CISD levels.
• Bearish CISD color allows you to change the color of -CISD levels.
• Line width allows you to modify the width of +-CISD lines.
• Line extension bars allows you to change how far ahead CISD levels are drawn (by default it is 5).
• Keep old CISD levels will allow you to preserve all past CISD levels if you would like to observe the logic.
• Enable stat table will let you add a table on your chart which will tell you the current CISD trend, as well as your ticker and timeframe.
• Table position allows you to customize where the table will appear on your chart.
Zig Zag Trend Metrics“ Zig Zag Trend Metrics ” is a highly versatile indicator, built on the classic Zig Zag concept and thoughtfully designed for technical traders seeking a deeper, more structured view of market dynamics. This tool identifies significant swing highs and lows, classifies them, and annotates each with key metrics, offering a precise snapshot of each movement. It enhances visual analysis by drawing connecting lines that outline the flow of market structure, making trend progression and reversals instantly recognizable. Beyond visual mapping, it features a compact, real-time statistics table that calculates the average price and time deltas for both bullish and bearish swings, giving traders deep insights into trend momentum and rhythm. With extensive customization options, this indicator adapts seamlessly to vast trading styles or chart setups, empowering traders to spot patterns, evaluate trend strength, and make more confident, data-backed decisions.
❖ FEATURES
✦ Automatic Swing Detection
At its core, this indicator automatically identifies swing highs and lows based on a customizable lookback period (default: 10 bars).
✦ Labeling Swing Points
Each swing is visualized with a label that includes:
Swing Classification : “HH” (Higher High), “LH” (Lower High), “LL” (Lower Low), or “HL” (Higher Low).
Price Difference : Displayed in percentage or absolute value from the previous opposite swing.
Time Difference : The number of bars since the previous swing of the opposite type.
These labels offer traders clear, immediate insight into price movements and structural changes.
✦ Visual Lines
The indicator draws three types of lines:
Bullish Lines: Connect recent swing lows to new swing highs, indicating uptrends.
Bearish Lines: Connect recent swing highs to new swing lows, indicating downtrends.
Range Lines: Connect consecutive highs or lows to outline price channels.
Each line type can be color-coded and customized for visibility.
✦ Statistics Table
An on-screen metrics table provides a live summary of trends. Script uses Relative Averaging to smooth price and time changes. This prevents outliers from distorting the data and provides a more reliable sense of typical swing behavior.
Uptrend Metrics: Shows average price and time differences from recent bullish swings.
Downtrend Metrics: Shows the same for bearish swings.
🛠️ Customization Options
Ability to tailor the indicator to suit their strategy and aesthetic preferences:
Swing Period: Adjust sensitivity to short- or long-term swings.
Color Settings: Customize line and label colors.
Label Display: Choose between absolute or percentage price differences.
Table Settings: Modify size, location, or visibility.
This makes the indicator highly flexible and useful across various timeframes and assets.
Multi-MA Strategy Analyzer with BacktestMulti-MA Strategy Analyzer with Backtest
This TradingView Pine Script indicator is designed to analyze multiple moving averages (SMA or EMA) dynamically and identify the most profitable one based on historical performance.
Features
Dynamic MA Range:
Specify a minLength, maxLength, and step size.
Automatically calculates up to 20 MAs.
Custom MA Calculation:
Uses custom SMA and EMA implementations to support dynamic length values.
Buy/Sell Logic:
Buy when price crosses above a MA.
Sell when price crosses below.
Supports both long and short trades.
Performance Tracking:
Tracks PnL, number of trades, win rate, average profit, and drawdown.
Maintains individual stats for each MA.
Best MA Detection:
Automatically highlights the best-performing MA.
Optional showBestOnly toggle to focus only on the best line and its stats.
Visualization:
Up to 20 plot() calls (static) for MAs.
Green highlight for the best MA.
Color-coded result table and chart.
Table View
When showBestOnly = false, the table displays all MAs with stats.
When showBestOnly = true, the table displays only the best MA with a summary row.
Includes:
Best MA length
Total PnL
Number of trades
Win rate
Avg PnL per trade
Max Drawdown
Configuration
minLength (default: 10)
maxLength (default: 200)
step (default: 10)
useEMA: Toggle between EMA and SMA
showBestOnly: Focus on best-performing MA only
Notes
MA plotting is static, limited to 20 total.
Table supports highlighting and is optimized for performance.
Script is structured to run efficiently using arrays and simple int where required.
Potential Extensions
Add visual buy/sell arrows
Export stats to CSV
Strategy tester conversion
Custom date range filtering for backtesting
Author: Muhammad Wasim
Version: 1.0
UM Futures Dashboard with Moving Average DirectionUM Futures Dashboard with Moving Average Direction
Description :
This futures dashboard gives you quick glance of all “major” futures prices and percentage changes. The text color and trends are based on your configured moving average type and length. The dashboard will display LONG in green text when the configure MA is trending higher and SHORT in red when the configured MA is trending lower. The dashboard also includes the VIX futures roll yield and VIX futures status of Contango or Backwardation.
I have included the indicator twice on the sample chart to illustrate different table settings. I also included an 8 period WMA overlay on the price chart since this is the default of the dashboard. (The Moving Average color change is another one of my indicators titled “UM EMA SMA WMA HMA with Directional Color Change”)
Defaults and Configuration :
The default MA type is the Weighted Moving Average, (WMA) with a daily setting of 8. Choices include WMA, SMA, and EMA. The table location defaults to the upper right corner in landscape mode. It can also be set to “flip” to portrait mode. I have added the table to the chart twice to illustrate the table orientations.
Table location, orientation, timeframe, moving average type and length are user-configurable. The configured dashboard timeframe is independent of the chart timeframe. Percentage changes and Moving Averages are based on the configured dashboard timeframe.
Alerts :
Alerts can be configured on the directional change of the dashboard moving average. For example, if the daily 8 period weighted moving average begins trending higher it will turn from red to green. This color change would fire a LONG alert. A color trend change of the weighted moving average from green to red would fire a SHORT alert. Alerts are disabled by default but can be set for any or all of the futures contracts included.
Suggested Uses :
If you follow or trade futures, add this dashboard indicator to your chart layout. Configure your favorite moving average. Use this to quickly see where all the major futures are trading. This saved me from thumbing through the CNBC app on my phone.
One thing I do is to “stretch” moving average to a smaller timeframe. For example, if you like the 8 period WMA on the daily, try the 192 WMA on the hourly. ( The daily 8 period WMA is roughly a 192 WMA on an hourly chart) This can smooth out some of the violent price action and give better entries/exits.
Setup a FUTURES indicator template. I do this with the dashboard and couple other of my favorite indicators.
Suggested Settings :
Daily charts: 8 WMA
Multi-Anchored Linear Regression Channels [TANHEF]█ Overview:
The 'Multi-Anchored Linear Regression Channels ' plots multiple dynamic regression channels (or bands) with unique selectable calculation types for both regression and deviation. It leverages a variety of techniques, customizable anchor sources to determine regression lengths, and user-defined criteria to highlight potential opportunities.
Before getting started, it's worth exploring all sections, but make sure to review the Setup & Configuration section in particular. It covers key parameters like anchor type, regression length, bias, and signal criteria—essential for aligning the tool with your trading strategy.
█ Key Features:
⯁ Multi-Regression Capability:
Plot up to three distinct regression channels and/or bands simultaneously, each with customizable anchor types to define their length.
⯁ Regression & Deviation Methods:
Regressions Types:
Standard: Uses ordinary least squares to compute a simple linear trend by averaging the data and deriving a slope and endpoints over the lookback period.
Ridge: Introduces L2 regularization to stabilize the slope by penalizing large coefficients, which helps mitigate multicollinearity in the data.
Lasso: Uses L1 regularization through soft-thresholding to shrink less important coefficients, yielding a simpler model that highlights key trends.
Elastic Net: Combines L1 and L2 penalties to balance coefficient shrinkage and selection, producing a robust weighted slope that handles redundant predictors.
Huber: Implements the Huber loss with iteratively reweighted least squares (IRLS) and EMA-style weights to reduce the impact of outliers while estimating the slope.
Least Absolute Deviations (LAD): Reduces absolute errors using iteratively reweighted least squares (IRLS), yielding a slope less sensitive to outliers than squared-error methods.
Bayesian Linear: Merges prior beliefs with weighted data through Bayesian updating, balancing the prior slope with data evidence to derive a probabilistic trend.
Deviation Types:
Regressive Linear (Reverse): In reverse order (recent to oldest), compute weighted squared differences between the data and a line defined by a starting value and slope.
Progressive Linear (Forward): In forward order (oldest to recent), compute weighted squared differences between the data and a line defined by a starting value and slope.
Balanced Linear: In forward order (oldest to newest), compute regression, then pair to source data in reverse order (newest to oldest) to compute weighted squared differences.
Mean Absolute: Compute weighted absolute differences between each data point and its regression line value, then aggregate them to yield an average deviation.
Median Absolute: Determine the weighted median of the absolute differences between each data point and its regression line value to capture the central tendency of deviations.
Percent: Compute deviation as a percentage of a base value by multiplying that base by the specified percentage, yielding symmetric positive and negative deviations.
Fitted: Compare a regression line with high and low series values by computing weighted differences to determine the maximum upward and downward deviations.
Average True Range: Iteratively compute the weighted average of absolute differences between the data and its regression line to yield an ATR-style deviation measure.
Bias:
Bias: Applies EMA or inverse-EMA style weighting to both Regression and/or Deviation, emphasizing either recent or older data.
⯁ Customizable Regression Length via Anchors:
Anchor Types:
Fixed: Length.
Bar-Based: Bar Highest/Lowest, Volume Highest/Lowest, Spread Highest/Lowest.
Correlation: R Zero, R Highest, R Lowest, R Absolute.
Slope: Slope Zero, Slope Highest, Slope Lowest, Slope Absolute.
Indicator-Based: Indicators Highest/Lowest (ADX, ATR, BBW, CCI, MACD, RSI, Stoch).
Time-Based: Time (Day, Week, Month, Quarter, Year, Decade, Custom).
Session-Based: Session (Tokyo, London, New York, Sydney, Custom).
Event-Based: Earnings, Dividends, Splits.
External: Input Source Highest/Lowest.
Length Selection:
Maximum: The highest allowed regression length (also fixed value of “Length” anchor).
Minimum: The shortest allowed length, ensuring enough bars for a valid regression.
Step: The sampling interval (e.g., 1 checks every bar, 2 checks every other bar, etc.). Increasing the step reduces the loading time, most applicable to “Slope” and “R” anchors.
Adaptive lookback:
Adaptive Lookback: Enable to display regression regardless of too few historical bars.
⯁ Selecting Bias:
Bias applies separately to regression and deviation.
Positive values emphasize recent data (EMA-style), negative invert, and near-zero maintains balance. (e.g., a length 100, bias +1 gives the newest price ~7× more weight than the oldest).
It's best to apply bias to both (regression and deviation) or just the deviation. Biasing only regression may distort deviation visually, while biasing both keeps their relationship intuitive. Using bias only for deviation scales it without altering regression, offering unique analysis.
⯁ Scale Awareness:
Supports linear and logarithmic price scaling, the regression and deviations adjust accordingly.
⯁ Signal Generation & Alerts:
Customizable entry/exit signals and alerts, detailed in the dedicated section below.
⯁ Visual Enhancements & Real-World Examples:
Optional on-chart table display summarizing regression input criteria (display type, anchor type, source, regression type, regression bias, deviation type, deviation bias, deviation multiplier) and key calculated metrics (regression length, slope, Pearson’s R, percentage position within deviations, etc.) for quick reference.
█ Understanding R (Pearson Correlation Coefficient):
Pearson’s R gauges data alignment to a straight-line trend within the regression length:
Range: R varies between –1 and +1.
R = +1 → Perfect positive correlation (strong uptrend).
R = 0 → No linear relationship detected.
R = –1 → Perfect negative correlation (strong downtrend).
This script uses Pearson’s R as an anchor, adjusting regression length to target specific R traits. Strong R (±1) follows the regression channel, while weak R (0) shows inconsistency.
█ Understanding the Slope:
The slope is the direction and rate at which the regression line rises or falls per bar:
Positive Slope (>0): Uptrend – Steeper means faster increase.
Negative Slope (<0): Downtrend – Steeper means sharper drop.
Zero or Near-Zero Slope: Sideways – Indicating range-bound conditions.
This script uses highest and lowest slope as an anchor, where extremes highlight strong moves and trend lines, while values near zero indicate sideways action and possible support/resistance.
█ Setup & Configuration:
Whether you’re new to this script or want to quickly adjust all critical parameters, the panel below shows the main settings available. You can customize everything from the anchor type and maximum length to the bias, signal conditions, and more.
Scale (select Log Scale for logarithmic, otherwise linear scale).
Display (regression channel and/or bands).
Anchor (how regression length is determined).
Length (control bars analyzed):
• Max – Upper limit.
• Min – Prevents regression from becoming too short.
• Step – Controls scanning precision; increasing Step reduces load time.
Regression:
• Type – Calculation method.
• Bias – EMA-style emphasis (>0=new bars weighted more; <0=old bars weighted more).
Deviation:
• Type – Calculation method.
• Bias – EMA-style emphasis (>0=new bars weighted more; <0=old bars weighted more).
• Multiplier - Adjusts Upper and Lower Deviation.
Signal Criteria:
• % (Price vs Deviation) – (0% = lower deviation, 50% = regression, 100% = upper deviation).
• R – (0 = no correlation, ±1 = perfect correlation; >0 = +slope, <0 = -slope).
Table (analyze table of input settings, calculated results, and signal criteria).
Adaptive Lookback (display regression while too few historical bars).
Multiple Regressions (steps 2 to 7 apply to #1, #2, and #3 regressions).
█ Signal Generation & Alerts:
The script offers customizable entry and exit signals with flexible criteria and visual cues (background color, dots, or triangles). Alerts can also be triggered for these opportunities.
Percent Direction Criteria:
(0% = lower deviation, 50% = regression line, 100% = upper deviation)
Above %: Triggers if price is above a specified percent of the deviation channel.
Below %: Triggers if price is below a specified percent of the deviation channel.
(Blank): Ignores the percent‐based condition.
Pearson's R (Correlation) Direction Criteria:
(0 = no correlation, ±1 = perfect correlation; >0 = positive slope, <0 = negative slope)
Above R / Below R: Compares the correlation to a threshold.
Above│R│ / Below│R│: Uses absolute correlation to focus on strength, ignoring direction.
Zero to R: Checks if R is in the 0-to-threshold range.
(Blank): Ignores correlation-based conditions.
█ User Tips & Best Practices:
Choose an anchor type that suits your strategy, “Bar Highest/Lowest” automatically spots commonly used regression zones, while “│R│ Highest” targets strong linear trends.
Consider enabling or disabling the Adaptive Lookback feature to ensure you always have a plotted regression if your chart doesn’t meet the maximum-length requirement.
Use a small Step size (1) unless relying on R-correlation or slope-based anchors as the are time-consuming to calculate. Larger steps speed up calculations but reduce precision.
Fine-tune settings such as lookback periods, regression bias, and deviation multipliers, or trend strength. Small adjustments can significantly affect how channels and signals behave.
To reduce loading time , show only channels (not bands) and disable signals, this limits calculations to the last bar and supports more extreme criteria.
Use the table display to monitor anchor type, calculated length, slope, R value, and percent location at a glance—especially if you have multiple regressions visible simultaneously.
█ Conclusion:
With its blend of advanced regression techniques, flexible deviation options, and a wide range of anchor types, this indicator offers a highly adaptable linear regression channeling system. Whether you're anchoring to time, price extremes, correlation, slope, or external events, the tool can be shaped to fit a variety of strategies. Combined with customizable signals and alerts, it may help highlight areas of confluence and support a more structured approach to identifying potential opportunities.
StatPivot- Dynamic Range Analyzer - indicator [PresentTrading]Hello everyone! In the following few open scripts, I would like to share various statistical tools that benefit trading. For this time, it is a powerful indicator called StatPivot- Dynamic Range Analyzer that brings a whole new dimension to your technical analysis toolkit.
This tool goes beyond traditional pivot point analysis by providing comprehensive statistical insights about price movements, helping you identify high-probability trading opportunities based on historical data patterns rather than subjective interpretations. Whether you're a day trader, swing trader, or position trader, StatPivot's real-time percentile rankings give you a statistical edge in understanding exactly where current price action stands within historical contexts.
Welcome to share your opinions! Looking forward to sharing the next tool soon!
█ Introduction and How it is Different
StatPivot is an advanced technical analysis tool that revolutionizes retracement analysis. Unlike traditional pivot indicators that only show static support/resistance levels, StatPivot delivers dynamic statistical insights based on historical pivot patterns.
Its key innovation is real-time percentile calculation - while conventional tools require new pivot formations before updating (often too late for trading decisions), StatPivot continuously analyzes where current price stands within historical retracement distributions.
Furthermore, StatPivot provides comprehensive statistical metrics including mean, median, standard deviation, and percentile distributions of price movements, giving traders a probabilistic edge by revealing which price levels represent statistically significant zones for potential reversals or continuations. By transforming raw price data into statistical insights, StatPivot helps traders move beyond subjective price analysis to evidence-based decision making.
█ Strategy, How it Works: Detailed Explanation
🔶 Pivot Point Detection and Analysis
The core of StatPivot's functionality begins with identifying significant pivot points in the price structure. Using the parameters left and right, the indicator locates pivot highs and lows by examining a specified number of bars to the left and right of each potential pivot point:
Copyp_low = ta.pivotlow(low, left, right)
p_high = ta.pivothigh(high, left, right)
For a point to qualify as a pivot low, it must have left higher lows to its left and right higher lows to its right. Similarly, a pivot high must have left lower highs to its left and right lower highs to its right. This approach ensures that only significant turning points are recognized.
🔶 Percentage Change Calculation
Once pivot points are identified, StatPivot calculates the percentage changes between consecutive pivot points:
For drops (when a pivot low is lower than the previous pivot low):
CopydropPercent = (previous_pivot_low - current_pivot_low) / previous_pivot_low * 100
For rises (when a pivot high is higher than the previous pivot high):
CopyrisePercent = (current_pivot_high - previous_pivot_high) / previous_pivot_high * 100
These calculations quantify the magnitude of each market swing, allowing for statistical analysis of historical price movements.
🔶 Statistical Distribution Analysis
StatPivot computes comprehensive statistics on the historical distribution of drops and rises:
Average (Mean): The arithmetic mean of all recorded percentage changes
CopyavgDrop = array.avg(dropValues)
Median: The middle value when all percentage changes are arranged in order
CopymedianDrop = array.median(dropValues)
Standard Deviation: Measures the dispersion of percentage changes from the average
CopystdDevDrop = array.stdev(dropValues)
Percentiles (25th, 75th): Values below which 25% and 75% of observations fall
Copyq1 = array.get(sorted, math.floor(cnt * 0.25))
q3 = array.get(sorted, math.floor(cnt * 0.75))
VaR95: The maximum expected percentage drop with 95% confidence
Copyvar95D = array.get(sortedD, math.floor(nD * 0.95))
Coefficient of Variation (CV): Measures relative variability
CopycvD = stdDevDrop / avgDrop
These statistics provide a comprehensive view of market behavior, enabling traders to understand the typical ranges and extreme moves.
🔶 Real-time Percentile Ranking
StatPivot's most innovative feature is its real-time percentile calculation. For each current price, it calculates:
The percentage drop from the latest pivot high:
CopycurrentDropPct = (latestPivotHigh - close) / latestPivotHigh * 100
The percentage rise from the latest pivot low:
CopycurrentRisePct = (close - latestPivotLow) / latestPivotLow * 100
The percentile ranks of these values within the historical distribution:
CopyrealtimeDropRank = (count of historical drops <= currentDropPct) / total drops * 100
This calculation reveals exactly where the current price movement stands in relation to all historical movements, providing crucial context for decision-making.
🔶 Cluster Analysis
To identify the most common retracement zones, StatPivot performs a cluster analysis by dividing the range of historical drops into five equal intervals:
CopyrangeSize = maxVal - minVal
For each interval boundary:
Copyboundaries = minVal + rangeSize * i / 5
By counting the number of observations in each interval, the indicator identifies the most frequently occurring retracement zones, which often serve as significant support or resistance areas.
🔶 Expected Price Targets
Using the statistical data, StatPivot calculates expected price targets:
CopytargetBuyPrice = close * (1 - avgDrop / 100)
targetSellPrice = close * (1 + avgRise / 100)
These targets represent statistically probable price levels for potential entries and exits based on the average historical behavior of the market.
█ Trade Direction
StatPivot functions as an analytical tool rather than a direct trading signal generator, providing statistical insights that can be applied to various trading strategies. However, the data it generates can be interpreted for different trade directions:
For Long Trades:
Entry considerations: Look for price drops that reach the 70-80th percentile range in the historical distribution, suggesting a statistically significant retracement
Target setting: Use the Expected Sell price or consider the average rise percentage as a reasonable target
Risk management: Set stop losses below recent pivot lows or at a distance related to the statistical volatility (standard deviation)
For Short Trades:
Entry considerations: Look for price rises that reach the 70-80th percentile range, indicating an unusual extension
Target setting: Use the Expected Buy price or average drop percentage as a target
Risk management: Set stop losses above recent pivot highs or based on statistical measures of volatility
For Range Trading:
Use the most common drop and rise clusters to identify probable reversal zones
Trade bounces between these statistically significant levels
For Trend Following:
Confirm trend strength by analyzing consecutive higher pivot lows (uptrend) or lower pivot highs (downtrend)
Use lower percentile retracements (20-30th percentile) as entry opportunities in established trends
█ Usage
StatPivot offers multiple ways to integrate its statistical insights into your trading workflow:
Statistical Table Analysis: Review the comprehensive statistics displayed in the data table to understand the market's behavior. Pay particular attention to:
Average drop and rise percentages to set reasonable expectations
Standard deviation to gauge volatility
VaR95 for risk assessment
Real-time Percentile Monitoring: Watch the real-time percentile display to see where the current price movement stands within the historical distribution. This can help identify:
Extreme movements (90th+ percentile) that might indicate reversal opportunities
Typical retracements (40-60th percentile) that might continue further
Shallow pullbacks (10-30th percentile) that might represent continuation opportunities in trends
Support and Resistance Identification: Utilize the plotted pivot points as key support and resistance levels, especially when they align with statistically significant percentile ranges.
Target Price Setting: Use the expected buy and sell prices calculated from historical averages as initial targets for your trades.
Risk Management: Apply the statistical measurements like standard deviation and VaR95 to set appropriate stop loss levels that account for the market's historical volatility.
Pattern Recognition: Over time, learn to recognize when certain percentile levels consistently lead to reversals or continuations in your specific market, and develop personalized strategies based on these observations.
█ Default Settings
The default settings of StatPivot have been carefully calibrated to provide reliable statistical analysis across a variety of markets and timeframes, but understanding their effects allows for optimal customization:
Left Bars (30) and Right Bars (30): These parameters determine how pivot points are identified. With both set to 30 by default:
A pivot low must be the lowest point among 30 bars to its left and 30 bars to its right
A pivot high must be the highest point among 30 bars to its left and 30 bars to its right
Effect on performance: Larger values create fewer but more significant pivot points, reducing noise but potentially missing important market structures. Smaller values generate more pivot points, capturing more nuanced movements but potentially including noise.
Table Position (Top Right): Determines where the statistical data table appears on the chart.
Effect on performance: No impact on analytical performance, purely a visual preference.
Show Distribution Histogram (False): Controls whether the distribution histogram of drop percentages is displayed.
Effect on performance: Enabling this provides visual insight into the distribution of retracements but can clutter the chart.
Show Real-time Percentile (True): Toggles the display of real-time percentile rankings.
Effect on performance: A critical setting that enables the dynamic analysis of current price movements. Disabling this removes one of the key advantages of the indicator.
Real-time Percentile Display Mode (Label): Chooses between label display or indicator line for percentile rankings.
Effect on performance: Labels provide precise information at the current price point, while indicator lines show the evolution of percentile rankings over time.
Advanced Considerations for Settings Optimization:
Timeframe Adjustment: Higher timeframes generally benefit from larger Left/Right values to identify truly significant pivots, while lower timeframes may require smaller values to capture shorter-term swings.
Volatility-Based Tuning: In highly volatile markets, consider increasing the Left/Right values to filter out noise. In less volatile conditions, lower values can help identify more potential entry and exit points.
Market-Specific Optimization: Different markets (forex, stocks, commodities) display different retracement patterns. Monitor the statistics table to see if your market typically shows larger or smaller retracements than the current settings are optimized for.
Trading Style Alignment: Adjust the settings to match your trading timeframe. Day traders might prefer settings that identify shorter-term pivots (smaller Left/Right values), while swing traders benefit from more significant pivots (larger Left/Right values).
By understanding how these settings affect the analysis and customizing them to your specific market and trading style, you can maximize the effectiveness of StatPivot as a powerful statistical tool for identifying high-probability trading opportunities.
