DMI Percentile MTF📈 DMI Percentile MTF – Custom Technical Indicator
This indicator is an enhanced version of the classic Directional Movement Index (DMI), converting +DI, -DI, and ADX values into dynamic percentiles ranging from 0% to 100%, making it easier to interpret the strength and direction of a trend.
⚙️ Key Features:
Percentile Normalization: Calculates where current values stand within a historical range (default: 100 bars), providing clearer overbought/oversold context.
+DI (green): Indicates bullish directional strength.
-DI (orange): Indicates bearish directional strength.
ADX (fuchsia): Measures overall trend strength (rising = strong trend, falling = flat market).
20% / 80% reference lines: Help identify weak or strong conditions.
Multi-Timeframe (MTF) Support: Analyze a higher timeframe trend (e.g., daily) while viewing a lower timeframe chart (e.g., 1h).
📊 How to Read It:
+DI > -DI → bullish trend dominance.
-DI > +DI → bearish trend dominance.
ADX rising → strengthening trend (regardless of direction).
ADX falling → sideways or consolidating market.
Values above 80% → historically high / strong conditions.
Values below 20% → historically low / weak conditions or potential breakout setup.
Indicators and strategies
Market Structure: BoS & CHoCH (Math by Thomas)📌 Description:
Market Structure: BoS & CHoCH (Math by Thomas) is a clean and reliable market structure tool designed to visually mark Swing Highs, Swing Lows, and classify each one as HH (Higher High), LH (Lower High), LL (Lower Low), or HL (Higher Low) based on price action. It also detects and labels Break of Structure (BoS) and Change of Character (CHoCH) to help identify potential continuation or reversal in trend.
🛠️ How to Use:
Add the indicator to your chart (works on any timeframe and asset).
Adjust the "Swing Sensitivity" input to fine-tune how many bars the script uses to detect a swing high/low. A higher number smooths out noise.
The script will automatically:
Mark every confirmed swing high or low with a solid line.
Label the swing as HH, LH, HL, or LL depending on its relative position.
Show BoS (trend continuation) or CHoCH (trend reversal) labels with the current trend direction.
Toggle labels or lines on or off with the corresponding checkboxes in settings.
🔍 Tip:
Use this indicator alongside other tools like volume or RSI for more confident entries. A CHoCH followed by two BoS in the same direction often signals a strong trend reversal.
Volume Intelligence Suite (VIS) v2📊 Volume Intelligence Suite – Smart Volume, Smart Trading
The Volume Intelligence Suite is a powerful, all-in-one TradingView indicator designed to give traders deeper insight into market activity by visualizing volume behavior with price action context. Whether you're a scalper, day trader, or swing trader, this tool helps uncover hidden momentum, institutional activity, and potential reversals with precision.
🔍 Key Features:
Dynamic Volume Zones – Highlights high and low volume areas to spot accumulation/distribution ranges.
Volume Spikes Detector – Automatically marks abnormal volume bars signaling potential breakout or trap setups.
Smart Delta Highlighting – Compares bullish vs bearish volume in real time to reveal buyer/seller strength shifts.
Session-Based Volume Profiling – Breaks volume into key trading sessions (e.g., London, New York) for clearer context.
Volume Heatmap Overlay – Optional heatmap to show intensity and velocity of volume flow per candle.
Custom Alerts – Built-in alerts for volume surges, divergences, and exhaustion signals.
Optimized for Kill Zone Analysis – Pairs perfectly with ICT-style session strategies and Waqar Asim’s trading methods.
🧠 Why Use Volume Intelligence?
Most traders overlook the story behind each candle. Volume Intelligence Suite helps you "see the why behind the move" — exposing key areas of interest where smart money may be active. Instead of reacting late, this tool puts you in position to anticipate.
Use it to:
Validate breakouts
Detect fakeouts and liquidity grabs
Confirm bias during kill zones
Analyze volume divergence with price swings
⚙️ Fully Customizable:
From volume thresholds to visual styles and session timings, everything is user-adjustable to fit your market, timeframe, and strategy.
✅ Best For:
ICT/Smart Money Concepts (SMC) traders
Breakout & reversal traders
Kill zone session scalpers
Institutional footprint followers
Volume towers by GSK-VIZAG-AP-INDIAVolume Towers by GSK-VIZAG-AP-INDIA
Overview :
This Pine Script visualizes volume activity and provides insights into market sentiment through the display of buying and selling volume, alongside moving averages. It highlights high and low volume candles, enabling traders to make informed decisions based on volume anomalies. The script is designed to identify key volume conditions, such as below-average volume, high-volume candles, and their relationship to price movement.
Script Details:
The script calculates a Simple Moving Average (SMA) of the volume over a user-defined period and categorizes volume into several states:
Below Average Volume: Volume is below the moving average.
High Volume: Volume exceeds the moving average by a multiplier (configurable by the user).
Low Volume: Volume that doesn’t qualify as either high or below average.
Additionally, the script distinguishes between buying volume (when the close is higher than the open) and selling volume (when the close is lower than the open). This categorization is color-coded for better visualization:
Green: Below average buying volume.
Red: Below average selling volume.
Blue: High-volume buying.
Purple: High-volume selling.
Black: Low volume.
The Volume Moving Average (SMA) is plotted as a reference line, helping users identify trends in volume over time.
Features & Customization:
Customizable Inputs:
Volume MA Length: The period for calculating the volume moving average (default is 20).
High Volume Multiplier: A multiplier for defining high volume conditions (default is 2.0).
Color-Coded Volume Histograms:
Different colors are used for buying and selling volume, as well as high and low-volume candles, for quick visual analysis.
Alerts:
Alerts can be set for the following conditions:
Below-average buying volume.
Below-average selling volume.
High-volume conditions.
How It Works:
Volume Moving Average (SMA) is calculated using the user-defined period (length), and it acts as the baseline for categorizing volume.
Volume Conditions:
Below Average Volume: Identifies candles with volume below the SMA.
High Volume: Identifies candles where volume exceeds the SMA by the set multiplier (highVolumeMultiplier).
Low Volume: When volume is neither high nor below average.
Buying and Selling Volume:
The script identifies buying and selling volume based on the closing price relative to the opening price:
Buying Volume: When the close is greater than the open.
Selling Volume: When the close is less than the open.
Volume histograms are then plotted using the respective colors for quick visualization of volume trends.
User Interface & Settings:
Inputs:
Volume MA Length: Adjust the period for the volume moving average.
High Volume Multiplier: Define the multiplier for high volume conditions.
Plots:
Buying Volume: Green bars indicate buying volume.
Selling Volume: Red bars indicate selling volume.
High Volume: Blue or purple bars for high-volume candles.
Low Volume: Black bars for low-volume candles.
Volume Moving Average Line: Displays the moving average line for reference.
Source Code / Authorship:
Author: prowelltraders
Disclaimer:
This script is intended for educational purposes only. While it visualizes important volume data, users are encouraged to perform their own research and testing before applying this script for trading decisions. No guarantees are made regarding the effectiveness of this script for real-world trading.
Contact & Support:
For questions, support, or feedback, please reach out to the author directly through TradingView (prowelltraders).
Signature:
GSK-VIZAG-AP-INDIA
ConeCastConeCast is a forward-looking projection indicator that visualizes a future price range (or "cone") based on recent trend momentum and adaptive volatility. Unlike lagging bands or reactive channels, this tool plots a predictive zone 3–50 bars ahead, allowing traders to anticipate potential price behavior rather than merely react to it.
How It Works
The core of ConeCast is a dynamic trend-slope engine derived from a Linear Regression line fitted over a user-defined lookback window. The slope of this trend is projected forward, and the cone’s width adapts based on real-time market volatility. In calm markets, the cone is narrow and focused. In volatile regimes, it expands proportionally, using an ATR-based % of price to scale.
Key Features
📈 Predictive Cone Zone: Visualizes a forward range using trend slope × volatility width.
🔄 Auto-Adaptive Volatility Scaling: Expands or contracts based on market quiet/chaotic states.
📊 Regime Detection: Identifies Bull, Bear, or Neutral states using a tunable slope threshold.
🧭 Multi-Timeframe Compatible: Slope and volatility can be calculated from higher timeframes.
🔔 Smart Alerts: Detects price entering the cone, and signals trend regime changes in real time.
🖼️ Clean Visual Output: Optionally includes outer cones, trend-trail marker, and dashboard label.
How to Use It
Use on 15m–4H charts for best forward visibility.
Look for price entering the cone as a potential trend continuation setup.
Monitor regime changes and volatility expansion to filter choppy market zones.
Tune the slope sensitivity and ATR multiplier to match your symbol's behavior.
Use outer cones to anticipate aggressive swings and wick traps.
What Makes It Unique
ConeCast doesn’t follow price — it predicts a possible future price envelope using trend + volatility math, without relying on lagging indicators or repainting logic. It's a hybrid of regression-based forecasting and dynamic risk zoning, designed for swing traders, scalpers, and algo developers alike.
Limitations
ConeCast projects based on current trend and volatility — it does not "know" future price. Like all projection tools, accuracy depends on trend persistence and market conditions. Use this in combination with confirmation signals and risk management.
Color Coded Volume IndicatorColor Coded Volume Indicator
Overview
Splits each bar’s total volume into estimated buy-side vs. sell-side components and displays them as stacked two-tone columns (red = sell, green = buy). Axis labels and tooltips use “K”/“M” formatting.
Features
Stacked Two-Tone Columns
Red Base : estimated sell volume (50% opacity)
Green Top : remaining buy volume (50% opacity)
Automatic K/M Formatting via format=format.volume
Zero Baseline for clean reference at zero
Positive-Only Bars (no negatives)
How It Works
True-Range Guard
Skips bars where high == low to avoid divide-by-zero.
Volume Split
BuyVol = Volume × (Close − Low) / (High − Low)
SellVol = Volume × (High − Close) / (High − Low)
Both series clamped ≥ 0.
Layered Plot
Draw semi-transparent green at full height, then overlay red sell portion.
Usage
Open TradingView’s Pine Editor
Paste in the full script
Click “Save & Add to Chart”
In the Publish dialog, title it “Color Coded Volume Indicator” and paste this description.
Interpretation
Green-dominant bars → strong buying pressure
Red-dominant bars → strong selling pressure
Equal halves → balanced activity
Price-Confirmed Hull Moving AverageThis is a modified HULL moving average that adds some enhancements providing visual clues as to a change in trend direction. The user can add slight modifications to the abruptness of trend change indications, which are clearly seen by the color change of the hull line itself. The user can also choose to have the background color change for easier visual indication that the hull line has changed slope direction. In addition, the user can either have both the line and the background visuals on, or turn one or the other (or both) off.
The purpose of this HULL moving average is to provide easy identification of trend direction within the scope of the moving average values provided in settings.
DEMA HMA Z-score OscillatorThis custom oscillator combines the power of the Hull Moving Average (HMA) with the Z-Score to identify momentum shifts and potential trend reversals. The Z-Score measures how far the current HMA is from its historical mean, helping to spot overbought or oversold conditions.
Uptrend: Long signals are generated when the Z-Score crosses above the defined Long Threshold.
Downtrend: Short signals are triggered when the Z-Score drops below the Short Threshold.
Visuals: The Z-Score is plotted along with background color changes and fills to clearly indicate trend strength. Green fills highlight uptrends, while pink fills indicate downtrends.
Alerts: Alerts are available for both long and short conditions based on Z-Score crossovers.
Customizable Inputs:
HMA Length
Smoothing Length (for DEMA)
Z-Score Length
Long and Short Thresholds
This indicator is ideal for detecting momentum shifts, confirming trend strength, and helping to time entry/exit points in your trading strategy.
Reintegration OPR zone 9h30📝 Indicator Description (for TradingView):
Name: Reintegration OPR Zone – 9:30 AM EST (UTC-4)
Purpose:
This indicator is designed for US indices like NAS100, US30, or SPX500. It helps identify potential false breakouts or retests by tracking when the price re-enters the Opening Price Range (OPR) after an initial breakout.
🔍 How it works:
At 9:30 AM New York time (UTC-4), the script captures the high and low of the first 15-minute candle (which is key for the US session open).
It then draws a horizontal box (rectangle) from the high to the low of that candle.
The box extends horizontally for 7 hours (28 candles on a 15-minute chart).
The script tracks if price:
Breaks above or below the OPR zone
Then re-enters the zone (a potential "fakeout" or "retest" signal)
No label or text is displayed on the chart (you requested it to be hidden).
🕒 Timeframe:
Designed for the 15-minute chart (M15)
Assumes New York session open at 9:30 AM EST (UTC-4)
Market Manipulation Index (MMI)The Composite Manipulation Index (CMI) is a structural integrity tool that quantifies how chaotic or orderly current market conditions are, with the aim of detecting potentially manipulated or unstable environments. It blends two distinct mathematical models that assess price behavior in terms of both structural rhythm and predictability.
1. Sine-Fit Deviation Model:
This component assumes that ideal, low-manipulation price behavior resembles a smooth oscillation, such as a sine wave. It generates a synthetic sine wave using a user-defined period and compares it to actual price movement over an adaptive window. The error between the real price and this synthetic wave—normalized by price variance—forms the Sine-Based Manipulation Index. A high error indicates deviation from natural rhythm, suggesting structural disorder.
2. Predictability-Based Model:
The second component estimates how well current price can be predicted using recent price lags. A two-variable rolling linear regression is computed between the current price and two lagged inputs (close and close ). If the predicted price diverges from the actual price, this error—also normalized by price variance—reflects unpredictability. High prediction error implies a more manipulated or erratic environment.
3. Adaptive Mechanism:
Both components are calculated using an adaptive smoothing window based on the Average True Range (ATR). This allows the indicator to respond proportionally to market volatility. During high volatility, the analysis window expands to avoid over-sensitivity; during calm periods, it contracts for better responsiveness.
4. Composite Output:
The two normalized metrics are averaged to form the final CMI value, which is then optionally smoothed further. The output is scaled between 0 and 1:
0 indicates a highly structured, orderly market.
1 indicates complete structural breakdown or randomness.
Suggested Interpretation:
CMI < 0.3: Market is clean and structured. Trend-following or breakout strategies may perform better.
CMI > 0.7: Market is structurally unstable. Choppy price action, fakeouts, or manipulative behavior may dominate.
CMI 0.3–0.7: Transitional zone. Caution or reduced risk may be warranted.
This indicator is designed to serve as a contextual filter, helping traders assess whether current market conditions are conducive to structured strategies, or if discretion and defense are more appropriate.
ICT Macro and Daye QT ShiftEST Vertical Lines - Auto DST Adjustment
Overview
This indicator draws customizable vertical lines at specific Eastern Time (EST/EDT) points throughout the trading day, automatically adjusting for daylight savings time. Designed for precision trading on 1-minute and 5-minute charts, it highlights key intraday moments when price action tends to accelerate.
Features
- **18 pre-configured NY session times** (09:50-15:45 ET)
- **Auto timezone conversion** - Always shows correct EST/EDT regardless of your local timezone
- **3 line styles** - Choose between solid/dashed/dotted lines
- **Clean labeling** - Optional time markers above each line
- **1m/5m optimized** - Perfect for scalpers and day traders
- **Visual alerts** - "TOUCH" labels when price interacts with lines
Inputs
| Parameter | Description | Default |
|-----------|-------------|---------|
| Line Times | Comma-separated HH:MM times | 09:50,10:10,...15:45 |
| Line Color | Line color | Black |
| Line Width | 1-5px thickness | 2 |
| Line Style | Solid/Dashed/Dotted | Solid |
| Show Labels | Display time markers | true |
How To Use
1. Apply to 1m or 5m charts
2. Lines appear automatically at specified EST times
3. Watch for price reactions at these key levels
4. Customize styles via indicator settings
Ideal For
- NY open/London close traders
- Earnings/News traders
- Breakout traders
- Market open/close strategies
Updates
v1.1 - Added line style customization
v1.0 - Initial release
ORB Advanced Cloud Indicator & FIB's by TenAMTraderSummary: ORB Advanced Cloud Indicator with Alerts and Fibonacci Retracement Targets by TenAMTrader
This TradingView script is an advanced version of the Opening Range Breakout (ORB) indicator, enhanced with visual clouds and Fibonacci retracement/extension levels. It is designed to help traders identify key price levels and track price movements relative to those levels throughout the trading day. The script includes alert functionalities to notify traders when price crosses key levels and when Fibonacci levels are reached, which can serve as potential entry and exit targets.
Key Features:
Primary and Secondary Range Calculation:
The indicator calculates the primary range (defined by a start and end time) and optionally, a secondary range.
The primary range includes the highest and lowest prices during the designated time period, as well as the midpoint of this range.
The secondary range (if enabled) tracks another price range during a second time period, with its own high, low, and midpoint.
Visual Clouds:
The script draws colored clouds between the high, midpoint, and low of the opening range.
The upper cloud spans between the Opening High and Midpoint, while the lower cloud spans between the Midpoint and Opening Low.
Similarly, a second set of clouds can be drawn for the secondary range (if enabled).
Fibonacci Levels:
The script calculates Fibonacci retracement and extension levels based on the primary range (the difference between the Opening High and Opening Low).
Fibonacci levels can be used as entry and exit targets in a trading strategy, as these levels often act as potential support/resistance zones.
Fibonacci levels include standard values like -0.236, -0.382, -0.618, and positive extensions like 1.236, 1.618, etc.
Customizable Alerts:
Alerts can be set to trigger when:
The price crosses above the Opening High.
The price crosses below the Opening Low.
The price crosses the Opening Midpoint.
These alerts can help traders act quickly on important price movements relative to the opening range.
Customization Options:
The indicator allows users to adjust the time settings for both the primary and secondary ranges.
Custom colors can be set for the lines, clouds, and Fibonacci levels.
The visibility of each line and cloud can be toggled on or off, giving users flexibility in how the chart is displayed.
Fibonacci Levels Overview:
The script includes several Fibonacci retracement and extension levels:
Negative Retracements (e.g., -0.236, -0.382, -0.50, -0.618, etc.) are plotted below the Opening Low, and can act as potential support levels in a downtrend.
Positive Extensions (e.g., 1.236, 1.382, 1.618, 2.0, etc.) are plotted above the Opening High, and can act as potential resistance levels in an uptrend.
Fib levels can be used as entry and exit targets to capitalize on price reversals or breakouts.
Safety Warning:
This script is for educational and informational purposes only and is not intended as financial advice. While it provides valuable technical information about price ranges and Fibonacci levels, trading always involves risk. Users are encouraged to:
Paper trade or use a demo account before applying this indicator with real capital.
Use proper risk management strategies, including stop-loss orders, to protect against unexpected market movements.
Understand that no trading strategy, indicator, or tool can guarantee profits, and losses can occur.
Important: The creator, TenAMTrader, and TradingView are not responsible for any financial losses resulting from the use of this script. Always trade responsibly, and ensure you fully understand the risks involved in any trading strategy.
Ticker DataThis script mostly for Pine coders but may be useful for regular users too.
I often find myself needing quick access to certain information about a ticker — like its full ticker name, mintick, last bar index and so on. Usually, I write a few lines of code just to display this info and check it.
Today I got tired of doing that manually, so I created a small script that shows the most essential data in one place. I also added a few extra fields that might be useful or interesting to regular users.
Description for regular users (from Pine Script Reference Manual)
tickerid - full ticker name
description - description for the current symbol
industry - the industry of the symbol. Example: "Internet Software/Services", "Packaged software", "Integrated Oil", "Motor Vehicles", etc.
country - the two-letter code of the country where the symbol is traded
sector - the sector of the symbol. Example: "Electronic Technology", "Technology services", "Energy Minerals", "Consumer Durables", etc.
session - session type (regular or extended)
timezone - timezone of the exchange of the chart
type - the type of market the symbol belongs to. Example: "stock", "fund", "index", "forex", "futures", "spread", "economic", "fundamental", "crypto".
volumetype - volume type of the current symbol.
mincontract - the smallest amount of the current symbol that can be traded
mintick - min tick value for the current symbol (the smallest increment between a symbol's price movements)
pointvalue - point value for the current symbol
pricescale - a whole number used to calculate mintick (usually (when minmove is 1), it shows the resolution — how many decimal places the price has. For example, a pricescale 100 means the price will have two decimal places - 1 / 100 = 0.01)
bar index - last bar index (if add 1 (because indexes starts from 0) it will shows how many bars available to you on the chart)
If you need some more information at table feel free to leave a comment.
X HL RangeOverview:
The X Range indicator is a multi-timeframe visualization tool designed to display the high and low price ranges of previous candles from higher timeframes (HTFs) directly on a lower timeframe chart. It helps traders identify significant price zones and potential support/resistance levels by visually representing the price range of up to three previous candles for each selected timeframe.
Key Features:
Multi-Timeframe Support: The indicator supports three configurable higher timeframes (default: 60 min, 15 min, 5 min) which can be independently toggled on or off.
Custom Candle Range Display: For each enabled timeframe, users can choose to display the range of the most recent 1, 2, or 3 completed candles.
Dynamic Box Drawing: Price ranges are highlighted using rectangular boxes that extend across the chart to show where the highs and lows of each selected HTF candle occurred.
Custom Styling: Each timeframe's boxes can be individually styled with user-defined background and border colors to suit visual preferences or chart themes.
Efficient Redrawing: Boxes update in real-time as new higher timeframe candles complete, and previous boxes are removed to prevent chart clutter.
Use Case:
This indicator is particularly useful for intraday traders who want to align entries and exits with higher timeframe levels. By visualizing previous HTF ranges on a lower timeframe chart, traders gain contextual awareness of where price is likely to react or consolidate, aiding in decision-making for breakouts, reversals, or trend continuation setups.
Opening Range Breakout Cloud Indicator by TenAMTraderOpening Range Breakout Cloud Indicator – by TenAMTrader
This indicator visually maps out the Opening Range of the trading day — the price high and low between a configurable start and end time (default: 9:30 AM–10:00 AM EST). It helps traders identify breakout levels, key intraday zones, and price behavior relative to the early range.
🔹 What It Shows:
Opening High, Low, and Midpoint lines for each day.
Clouds between the midpoint and high/low for visual clarity.
Optional Second Range (e.g., 9:30–9:45 AM) for more aggressive early signals.
Historical Ranges are preserved, allowing you to view previous days' levels on the chart.
Custom Alerts when price crosses the Opening High, Low, or Midpoint.
Full customization: colors, range times, and display toggles.
🔔 Use It For:
Spotting breakouts or rejections at key levels.
Finding early support/resistance zones.
Planning trades using intraday structure.
⚠️ Use this tool as part of a broader trading strategy. No indicator guarantees results — always trade at your own discretion.
X OHLdesigned to plot significant levels—closed higher timeframe High, Low, Open, and an Equilibrium (EQ) level and current Open—on the current chart based on user-defined higher timeframes (HTFs). It helps traders visualize HTF price levels on lower timeframes for confluence, context, or decision-making.
Key Functional Components:
Configurable Inputs:
Four Timeframes: Customizable (default: 1H, 4H, D, W).
Visibility Toggles for:
Previous High (pHigh)
Previous Low (pLow)
EQ (midpoint between high and low)
Current Open
Previous Open
How It Works:
For each selected timeframe:
retrieves OHL Data
Previous high/low (high , low )
Current and previous open
EQ is calculated as midpoint: (high + low) / 2
Draws Horizontal Lines:
Lines are drawn from the candle where the HTF bar opens and extended until timeframe switch. Lines extends a few bars beyond current to assist in visualization
Labels:
On the most recent bar, each level is labeled with a description (pHigh 1H, EQ 6H, etc.).
Labels are customizable (size, color, background).
Anchoring:
Lines and labels are redrawn on the start of each new HTF bar to ensure accuracy and relevance.
[blackcat] L3 Twin Range Filter ProOVERVIEW
The L3 Twin Range Filter Pro indicator enhances trading strategies by filtering out market noise through a sophisticated dual-range approach. Unlike previous versions, this script not only provides clear visual indications of buy/sell signals but also incorporates a dynamic trend range filter line. By averaging two smoothed exponential moving averages—one fast and one slow—the indicator generates upper and lower range boundaries that adapt to changing market conditions. Traders can easily spot buy/sell opportunities when the closing price crosses these boundaries, supported by configurable alerts for real-time notifications.
FEATURES
Dual-Range Calculation: Combines fast and slow moving averages to create adaptive range boundaries.
Customizable Parameters:
Periods: Adjustable lengths for fast (default 9 bars) and slow (default 34 bars) moving averages.
Multipliers: Coefficients to modify the distance of the trailing lines from the price.
Dynamic Trend Range Filter Line: Visually displays buy/sell signals directly on the chart.
Trailing Stop Loss Logic: Automatically follows price movements to act as a trailing stop loss indicator.
Trade Signals: Clearly indicates buy/sell points with labeled signals.
Alerts: Configurable notifications for buy/sell signals to keep traders informed.
Visual Enhancements: Colored fills and dynamic boundary lines for easy interpretation.
HOW TO USE
Add the L3 Twin Range Filter Pro indicator to your TradingView chart.
Customize the input parameters:
Price Source: Choose the desired price source (e.g., Close).
Show Trade Signals: Toggle on/off for displaying buy/sell labels.
Fast Period: Set the period for the fast moving average (default 9 bars).
Slow Period: Set the period for the slow moving average (default 34 bars).
Fast Range Multiplier: Adjust the multiplier for the fast moving average.
Slow Range Multiplier: Adjust the multiplier for the slow moving average.
Monitor the plotted trend range filter and dynamic boundaries on the chart.
Identify buy/sell signals based on the crossing of price and range boundaries.
Configure alerts for real-time notifications when signals are triggered.
TRADE LOGIC
BUY Signal: Triggered when the price is higher than or equal to the upper range level. The indicator line will trail just below the price, acting as a trailing stop loss.
SELL Signal: Triggered when the price is lower than or equal to the lower range level. The indicator line will trail just above the price, serving as a trailing stop loss.
LIMITATIONS
The performance of this indicator relies on the selected periods and multipliers.
Market volatility can impact the accuracy of the signals.
Always complement this indicator with other analytical tools for robust decision-making.
NOTES
Experiment with different parameter settings to optimize the indicator for various market conditions.
Thoroughly backtest the indicator using historical data to ensure its compatibility with your trading strategy.
THANKS
A big thank you to Colin McKee for his foundational work on the Twin Range Filter! Your contributions have paved the way for enhanced trading tools. 🙏📈🔍
Heikin Ashi Colored Regular OHLC CandlesHeikin Ashi Colored Regular OHLC Candles
In the world of trading, Heikin Ashi candles are a popular tool for smoothing out price action and identifying trends more clearly. However, Heikin Ashi candles do not reflect the actual open, high, low, and close prices of a market. They are calculated values that change the chart’s structure. This can make it harder to see precise price levels or use standard price-based tools effectively.
To get the best of both worlds, we can apply the color logic of Heikin Ashi candles to regular OHLC candles. This means we keep the true market data, but show the trend visually in the same smooth way Heikin Ashi candles do.
Why use this approach
Heikin Ashi color logic filters out noise and helps provide a clearer view of the current trend direction. Since we are still plotting real OHLC candles, we do not lose important price information such as actual highs, lows, or closing prices. This method offers a hybrid view that combines the accuracy of real price levels with the visual benefits of Heikin Ashi trend coloring. It also helps maintain visual consistency for traders who are used to Heikin Ashi signals but want to see real price action.
Advantages for scalping
Scalping requires fast decisions. Even small price noise can lead to hesitation or bad entries. Coloring regular candles based on Heikin Ashi direction helps reduce that noise and makes short-term trends easier to read. It allows for faster confirmation of momentum without switching away from real prices. Since the candles are not modified, scalpers can still place tight stop-losses and targets based on actual price structure. This approach also avoids clutter, keeping the chart clean and focused.
How it works
We calculate the Heikin Ashi values in the background. If the Heikin Ashi close is higher than the Heikin Ashi open, the trend is considered bullish and the candle is colored green. If the close is lower than the open, it is bearish and the candle is red. If they are equal, the candle is gray or neutral. We then use these colors to paint the real OHLC candles, which are unchanged in shape or position.
Test OHLCV LibraryThis indicator, "Test OHLCV Library," serves as a practical example of how to use the OHLCVData library to fetch historical candle data from a specific timeframe (like 4H) in a way that is largely impervious to the chart's currently selected time frame.
Here's a breakdown of its purpose and how it addresses request.security limitations:
Indicator Purpose:
The main goal of this indicator is to demonstrate and verify that the OHLCVData library can reliably provide confirmed historical OHLCV data for a user-specified timeframe (e.g., 4H), and that a collection of these data points (the last 10 completed candles) remains consistent even when the user switches the chart's time frame (e.g., from 5-second to Daily).
It does this by:
Importing the OHLCVData library.
Using the library's getTimeframeData function on every bar of the chart.
Checking the isTargetBarClosed flag returned by the library to identify the exact moment a candle in the target timeframe (e.g., 4H) has closed.
When isTargetBarClosed is true, it captures the confirmed OHLCV data provided by the library for that moment and stores it in a persistent var array.
It maintains a list of the last 10 captured historical 4H candle opens in this array.
It displays these last 10 confirmed opens in a table.
It uses the isAdjustedToChartTF flag from the library to show a warning if the chart's time frame is higher than the target timeframe, indicating that the data fetched by request.security is being aligned to that higher resolution.
Circumventing request.security Limitations:
The primary limitation of request.security that this setup addresses is the challenge of getting a consistent, non-repainting collection of historical data points from a different timeframe when the chart's time frame is changed.
The Problem: Standard request.security calls, while capable of fetching data from other timeframes, align that data to the bars of the current chart. When you switch the chart's time frame, the set of chart bars changes, and the way the requested data aligns to these new bars changes. If you simply collected data on every chart bar where request.security returned a non-na value, the resulting collection would differ depending on the chart's resolution. Furthermore, using request.security without lookahead=barmerge.lookahead_off or an offset ( ) can lead to repainting on historical bars, where values change as the script recalculates.
How the Library/Indicator Setup Helps:
Confirmed Data: The OHLCVData library uses lookahead=barmerge.lookahead_off and, more importantly, provides the isTargetBarClosed flag. This flag is calculated using a reliable method (checking for a change in the target timeframe's time series) that accurately identifies the precise chart bar corresponding to the completion of a candle in the target timeframe (e.g., a 4H candle), regardless of the chart's time frame.
Precise Capture: The indicator only captures and stores the OHLCV data into its var array when this isTargetBarClosed flag is true. This means it's capturing the confirmed, finalized data for the target timeframe candle at the exact moment it closes.
Persistent Storage: The var array in the indicator persists its contents across the bars of the chart's history. As the script runs through the historical bars, it selectively adds confirmed 4H candle data points to this array only when the trigger is met.
Impervious Collection: Because the array is populated based on the completion of the target timeframe candles (detected reliably by the library) rather than simply collecting data on every chart bar, the final contents of the array (the list of the last 10 confirmed 4H opens) will be the same regardless of the chart's time frame. The table then displays this static collection.
In essence, this setup doesn't change how request.security fundamentally works or aligns data to the chart's bars. Instead, it uses the capabilities of request.security (fetching data from another timeframe) and Pine Script's execution model (bar-by-bar processing, var persistence) in a specific way, guided by the library's logic, to build a historical collection of data points that represent the target timeframe's candles and are independent of the chart's display resolution.
S&P 500 Top 25 - EPS AnalysisEarnings Surprise Analysis Framework for S&P 500 Components: A Technical Implementation
The "S&P 500 Top 25 - EPS Analysis" indicator represents a sophisticated technical implementation designed to analyze earnings surprises among major market constituents. Earnings surprises, defined as the deviation between actual reported earnings per share (EPS) and analyst estimates, have been consistently documented as significant market-moving events with substantial implications for price discovery and asset valuation (Ball and Brown, 1968; Livnat and Mendenhall, 2006). This implementation provides a comprehensive framework for quantifying and visualizing these deviations across multiple timeframes.
The methodology employs a parameterized approach that allows for dynamic analysis of up to 25 top market capitalization components of the S&P 500 index. As noted by Bartov et al. (2002), large-cap stocks typically demonstrate different earnings response coefficients compared to their smaller counterparts, justifying the focus on market leaders.
The technical infrastructure leverages the TradingView Pine Script language (version 6) to construct a real-time analytical framework that processes both actual and estimated EPS data through the platform's request.earnings() function, consistent with approaches described by Pine (2022) in financial indicator development documentation.
At its core, the indicator calculates three primary metrics: actual EPS, estimated EPS, and earnings surprise (both absolute and percentage values). This calculation methodology aligns with standardized approaches in financial literature (Skinner and Sloan, 2002; Ke and Yu, 2006), where percentage surprise is computed as: (Actual EPS - Estimated EPS) / |Estimated EPS| × 100. The implementation rigorously handles potential division-by-zero scenarios and missing data points through conditional logic gates, ensuring robust performance across varying market conditions.
The visual representation system employs a multi-layered approach consistent with best practices in financial data visualization (Few, 2009; Tufte, 2001).
The indicator presents time-series plots of the four key metrics (actual EPS, estimated EPS, absolute surprise, and percentage surprise) with customizable color-coding that defaults to industry-standard conventions: green for actual figures, blue for estimates, red for absolute surprises, and orange for percentage deviations. As demonstrated by Padilla et al. (2018), appropriate color mapping significantly enhances the interpretability of financial data visualizations, particularly for identifying anomalies and trends.
The implementation includes an advanced background coloring system that highlights periods of significant earnings surprises (exceeding ±3%), a threshold identified by Kinney et al. (2002) as statistically significant for market reactions.
Additionally, the indicator features a dynamic information panel displaying current values, historical maximums and minimums, and sample counts, providing important context for statistical validity assessment.
From an architectural perspective, the implementation employs a modular design that separates data acquisition, processing, and visualization components. This separation of concerns facilitates maintenance and extensibility, aligning with software engineering best practices for financial applications (Johnson et al., 2020).
The indicator processes individual ticker data independently before aggregating results, mitigating potential issues with missing or irregular data reports.
Applications of this indicator extend beyond merely observational analysis. As demonstrated by Chan et al. (1996) and more recently by Chordia and Shivakumar (2006), earnings surprises can be successfully incorporated into systematic trading strategies. The indicator's ability to track surprise percentages across multiple companies simultaneously provides a foundation for sector-wide analysis and potentially improves portfolio management during earnings seasons, when market volatility typically increases (Patell and Wolfson, 1984).
References:
Ball, R., & Brown, P. (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research, 6(2), 159-178.
Bartov, E., Givoly, D., & Hayn, C. (2002). The rewards to meeting or beating earnings expectations. Journal of Accounting and Economics, 33(2), 173-204.
Bernard, V. L., & Thomas, J. K. (1989). Post-earnings-announcement drift: Delayed price response or risk premium? Journal of Accounting Research, 27, 1-36.
Chan, L. K., Jegadeesh, N., & Lakonishok, J. (1996). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Chordia, T., & Shivakumar, L. (2006). Earnings and price momentum. Journal of Financial Economics, 80(3), 627-656.
Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Analytics Press.
Gu, S., Kelly, B., & Xiu, D. (2020). Empirical asset pricing via machine learning. The Review of Financial Studies, 33(5), 2223-2273.
Johnson, J. A., Scharfstein, B. S., & Cook, R. G. (2020). Financial software development: Best practices and architectures. Wiley Finance.
Ke, B., & Yu, Y. (2006). The effect of issuing biased earnings forecasts on analysts' access to management and survival. Journal of Accounting Research, 44(5), 965-999.
Kinney, W., Burgstahler, D., & Martin, R. (2002). Earnings surprise "materiality" as measured by stock returns. Journal of Accounting Research, 40(5), 1297-1329.
Livnat, J., & Mendenhall, R. R. (2006). Comparing the post-earnings announcement drift for surprises calculated from analyst and time series forecasts. Journal of Accounting Research, 44(1), 177-205.
Padilla, L., Kay, M., & Hullman, J. (2018). Uncertainty visualization. Handbook of Human-Computer Interaction.
Patell, J. M., & Wolfson, M. A. (1984). The intraday speed of adjustment of stock prices to earnings and dividend announcements. Journal of Financial Economics, 13(2), 223-252.
Skinner, D. J., & Sloan, R. G. (2002). Earnings surprises, growth expectations, and stock returns or don't let an earnings torpedo sink your portfolio. Review of Accounting Studies, 7(2-3), 289-312.
Tufte, E. R. (2001). The visual display of quantitative information (Vol. 2). Graphics Press.
Climax Detector (Buy & Sell)This indicator identifies potential Buying Climax (BC) and Selling Climax (SC) events based on volume spikes relative to historical averages.
• Buying Climax (BC):
• Detected when a green candle forms with volume significantly higher than the average (default: 2×).
• Often signals the end of an uptrend or distribution phase.
• Selling Climax (SC):
• Detected when a red candle forms with very high volume (default: 2× average).
• Often occurs at the end of a downtrend, suggesting panic selling and potential accumulation.
How it works:
• Calculates a moving average of volume over a user-defined period (default: 20 candles)
• Flags a climax when current volume exceeds the defined multiplier (default: 2.0×)
• Marks:
• BC with an orange triangle above the bar
• SC with a fuchsia triangle below the bar
Customizable Settings:
• Volume spike sensitivity
• Lookback period for average volume
Use Cases:
• Spot possible trend exhaustion
• Confirm Wyckoff phases
• Combine with support/resistance for reversal entries
Disclaimer: This tool is designed to assist in identifying high-probability exhaustion zones but should be used alongside other confirmations or strategies.
FVG [TakingProphets]🧠 Purpose
This indicator is built for traders applying Inner Circle Trader (ICT) methodology. It detects and manages Fair Value Gaps (FVGs) — price imbalances that often act as future reaction zones. It also highlights New Day Opening Gaps (NDOGs) and New Week Opening Gaps (NWOGs) that frequently play a role in early-session price behavior.
📚 What is a Fair Value Gap?
A Fair Value Gap forms when price moves rapidly, skipping over a portion of the chart between three candles — typically between the high of the first candle and the low of the third. These zones are considered inefficient, meaning institutions may return to them later to:
-Rebalance unfilled orders
-Enter or scale into positions
-Engineer liquidity with minimal slippage
In ICT methodology, FVGs are seen as both entry zones and targets, depending on market structure and context.
⚙️ How It Works
-This script automatically identifies and manages valid FVGs using the following logic:
-Bullish FVGs: When the low of the current candle is above the high from two candles ago
-Bearish FVGs: When the high of the current candle is below the body of two candles ago
-Minimum Gap Filter: Gaps must be larger than 0.05% of price
-Combine Consecutive Gaps (optional): Merges adjacent gaps of the same type
-Consequent Encroachment Line (optional): Plots the midpoint of each gap
-NDOG/NWOG Tracking: Labels gaps created during the 5–6 PM session transition
-Automatic Invalidation: Gaps are removed once price closes beyond their boundary
🎯 Practical Use
-Use unmitigated FVGs as potential entry points or targets
-Monitor NDOG and NWOG for context around daily or weekly opens
-Apply the midpoint (encroachment) line for precise execution decisions
-Let the script handle cleanup — only active, relevant zones remain visible
🎨 Customization
-Control colors for bullish, bearish, and opening gaps
-Toggle FVG borders and midpoint lines
-Enable or disable combining of consecutive gaps
-Fully automated zone management, no manual intervention required
✅ Summary
This tool offers a clear, rules-based approach to identifying price inefficiencies rooted in ICT methodology. Whether used for intraday or swing trading, it helps traders stay focused on valid, active Fair Value Gaps while filtering out noise and maintaining chart clarity.
Weekly Moving Averages (MAs) to Intraday ChartThis indicator overlays key weekly timeframe moving averages onto your intraday chart, allowing you to visualize important long-term support and resistance levels while trading shorter timeframes. The indicator includes:
330-period Simple Moving Average (white): Ultra long-term trend indicator
200-period Simple Moving Average (fuchsia): Major long-term trend indicator often watched by institutional traders
100-period Simple Moving Average (purple): Medium-to-long term trend indicator
50-period Exponential Moving Average (blue): Medium-term trend indicator, more responsive to recent price action
21-period Exponential Moving Average (teal): Short-to-medium term trend indicator
9-period Exponential Moving Average (aqua): Short-term trend indicator, highly responsive to recent price movements
This multi-timeframe approach helps identify significant support/resistance zones that might not be visible on your current timeframe. When price interacts with these weekly moving averages during intraday trading, it often signals important areas where institutional orders may be placed.
The indicator uses color-coding with increasing line thickness to help you quickly distinguish between different moving averages. Consider areas where multiple MAs cluster together as particularly strong support/resistance zones.
Perfect for day traders and swing traders who want to maintain awareness of the bigger picture while focusing on shorter-term price action.
Hull Moving Average with Cloud📈 Hull Moving Average with Cloud – Adaptive Trend Visualization
This indicator combines the power of the Hull Moving Average (HMA) with a visual signal line and trend cloud, giving traders a clearer view of market direction, momentum shifts, and potential reversals.
🔍 Key Features:
Dynamic HMA Length (optional): Adjusts the HMA period based on ATR volatility, allowing the moving average to adapt to changing market conditions.
Custom Smoothing Options: Smooth the main HMA with your choice of SMA, EMA, or WMA for a tailored trend line.
Signal Line (Orange HMA): A shorter-period Hull MA that acts as a trigger line for crossovers and trend changes.
Color-Coded Trend Cloud:
🟩 Green Cloud: Bullish – main HMA is above the signal HMA.
🟥 Red Cloud: Bearish – main HMA is below the signal HMA.
Real-Time Trend Coloring: Both lines dynamically change color based on slope (green for rising, red/purple for falling).
Offset Capability: Shift the HMA forward to visualize trend development and potential future direction.
✅ Use Cases:
Identify trend direction with cloud coloration.
Spot early reversals through HMA crossover signals.
Filter trades with volatility-aware moving average responsiveness.
