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.
Penunjuk dan strategi
Reverse Keltner Channel StrategyReverse Keltner Channel Strategy
Overview
The Reverse Keltner Channel Strategy is a mean-reversion trading system that capitalizes on price movements between Keltner Channels. Unlike traditional Keltner Channel strategies that trade breakouts, this system takes the contrarian approach by entering positions when price returns to the channel after overextending.
Strategy Logic
Long Entry Conditions:
Price crosses above the lower Keltner Channel from below
This signals a potential reversal after an oversold condition
Position is entered at market price upon signal confirmation
Long Exit Conditions:
Take Profit: Price reaches the upper Keltner Channel
Stop Loss: Placed at half the channel width below entry price
Short Entry Conditions:
Price crosses below the upper Keltner Channel from above
This signals a potential reversal after an overbought condition
Position is entered at market price upon signal confirmation
Short Exit Conditions:
Take Profit: Price reaches the lower Keltner Channel
Stop Loss: Placed at half the channel width above entry price
Key Features
Mean Reversion Approach: Takes advantage of price tendency to return to mean after extreme moves
Adaptive Stop Loss: Stop loss dynamically adjusts based on market volatility via ATR
Visual Signals: Entry points clearly marked with directional triangles
Fully Customizable: All parameters can be adjusted to fit various market conditions
Customizable Parameters
Keltner EMA Length: Controls the responsiveness of the channel (default: 20)
ATR Multiplier: Determines channel width/sensitivity (default: 2.0)
ATR Length: Affects volatility calculation period (default: 10)
Stop Loss Factor: Adjusts risk management aggressiveness (default: 0.5)
Best Used On
This strategy performs well on:
Currency pairs with defined ranging behavior
Commodities that show cyclical price movements
Higher timeframes (4H, Daily) for more reliable signals
Markets with moderate volatility
Risk Management
The built-in stop loss mechanism automatically adjusts to market conditions by calculating position risk relative to the current channel width. This approach ensures that risk remains proportional to potential reward across varying market conditions.
Notes for Optimization
Consider adjusting the EMA length and ATR multiplier based on the specific asset and timeframe:
Lower values increase sensitivity and generate more signals
Higher values produce fewer but potentially more reliable signals
As with any trading strategy, thorough backtesting is recommended before live implementation.
Past performance is not indicative of future results. Always practice sound risk management.
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.
Fibonacci + TP/SL Strategy [Backtest]✅ Key Features Added and Adjusted:
Fibonacci Retracement Levels:
Automatically calculated based on the last 100 bars' high/low
Plotted levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%
Extension targets: 161.8%, 261.8%, 423.6%
Buy/Sell Signal Logic:
Buy: Price is between 78.6% and 38.2% levels
Sell: Price is between 61.8% and 23.6% levels
Both depend on a can_trade time filter to avoid overtrading
ATR-based Stop-Loss:
Stop-loss dynamically adapts to market volatility:
SL = Entry - ATR * 1.5 (long)
SL = Entry + ATR * 1.5 (short)
Fixed Take-Profit:
Configurable via input: default is 4%
Can be changed in TradingView UI
Golden/Death Cross Indicator (Visual Only):
EMA 50 crossing EMA 200 plotted on chart:
Golden Cross = Buy signal (green triangle)
Death Cross = Sell signal (red triangle)
Weekly Profit Cap:
Prevents new trades if weekly profit exceeds 15%
Resets at the start of every week
Visual Elements:
All Fibonacci levels are plotted
Buy/Sell signals are labeled on the chart (BUY, SELL)
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.
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.
MA Crossover with Adaptive Trend Strength📘 MA Crossover with Adaptive Trend Strength —
📌 Overview
This TradingView indicator plots two moving averages (Fast & Slow) with user-selected types (T3, EMA, SMA, HMA), visual crossovers, and dynamically calculates an adaptive trend strength score using Z-scores of multiple features. Optional higher timeframe (HTF) confirmation is supported. A color-filled region between the MAs visually indicates momentum direction.
⚙️ Inputs & Controls
📈 Moving Average Settings
Fast MA Length: Length of the fast-moving average (default: 9).
Slow MA Length: Length of the slow-moving average (default: 21).
MA Type: Type of moving average used (T3, EMA, SMA, HMA).
Source: Input data source (default: close).
T3 Volume Factor: Only used when T3 is selected, controls smoothing (range: 0–1).
🎨 Visual Controls
Bullish Fill Color: Fill color when Fast MA is above Slow MA.
Bearish Fill Color: Fill color when Fast MA is below Slow MA.
Show Gradient Fill: Enable or disable the colored area between Fast & Slow MAs.
Trend Label Position: Choose where the trend strength label appears (top or bottom).
Label Update Interval: Number of bars between label updates (reduces clutter).
⏱ Multi-Timeframe Support
Higher Timeframe: Timeframe used for confirmation (default: 60 min).
Use HTF Confirmation: Enables filtering of trend score by higher timeframe trend direction.
📊 Lookback Configuration
Auto Lookback Based on Timeframe: Dynamically adapts scoring lookback period per chart timeframe.
Manual Lookback: Manual fallback lookback length when auto is off.
🧮 MA Calculation Options
T3 MA: Custom T3 function with exponential moving averages and volume factor.
EMA/SMA: Built-in Pine functions (ta.ema, ta.sma).
HMA: Hull Moving Average using WMA calculations.
📉 Trend Strength Calculation
🧠 Z-Score Inputs
Distance between MAs (zDist)
Slope of the Fast MA (zSlope)
Volume (zVol)
ATR (zATR)
📏 Choppiness & Adaptive Weighting
A Choppiness Index (based on ATR & price range) reduces score impact in sideways markets.
Dynamically adjusts Z-score weights:
W1: Distance
W2: Slope
W3: Volume
W4: ATR
🔁 HTF Confirmation
Optionally multiplies the trend score by the direction of the higher timeframe trend to filter noise.
🟩 Plot & Visual Elements
📊 MA Lines
Plots Fast and Slow MA lines in colors based on selected MA type.
🌈 Gradient Fill
Fills the area between Fast and Slow MAs with opacity proportional to their difference.
Colors based on bullish/bearish condition.
🏷️ Trend Strength Label
Updates every n bars (Label Update Interval).
Shows:
Trend Classification: Weak, Moderate, Strong
Numerical Score
Label position (top or bottom) is configurable.
🔔 Crossover Signals
Bullish Crossover ("B"): Fast MA crosses above Slow MA.
Bearish Crossover ("S"): Fast MA crosses below Slow MA.
Labels are plotted at crossover points.
Old labels are removed after a threshold (100) to reduce chart clutter.
📋 Score Summary Table
A table showing:
Max Score within the lookback period
Min Score
HTF Confirmation Status (ON / OFF)
Updates on the same user-defined interval as the trend label.
🚨 Alerts
Condition Description
Bullish MA Cross Fast MA crosses above Slow MA
Bearish MA Cross Fast MA crosses below Slow MA
These are provided via alertcondition() for use in alert creation.
📌 Customization Tips
Turn off the gradient fill for a cleaner chart.
Use HTF confirmation to reduce false positives in ranging markets.
Adjust label update frequency to prevent visual clutter on faster timeframes.
Use T3 MA with volume factor for smoother signals in volatile markets.
Central Bank Assets YoY % with StdDev BandsCentral Bank Assets YoY % with StdDev Bands - Indicator Documentation
Overview
This indicator tracks the year-over-year (YoY) percentage change in combined central bank assets using a custom formula. It displays the annual growth rate along with statistical bands showing when the growth is significantly above or below historical norms.
Formula Components
The indicator is based on a custom symbol combining multiple central bank balance sheets:
Federal Reserve balance sheet (FRED)
Bank of Japan assets converted to USD (FX_IDC*FRED)
European Central Bank assets converted to USD (FX_IDC*FRED)
Subtracting Fed reverse repo operations (FRED)
Subtracting Treasury General Account (FRED)
Calculations
Year-over-Year Percentage Change: Calculates the percentage change between the current value and the value from exactly one year ago (252 trading days).
Formula: ((current - year_ago) / year_ago) * 100
Statistical Measures:
Mean (Average): The 252-day simple moving average of the YoY percentage changes
Standard Deviation: The 252-day standard deviation of YoY percentage changes
Display Components
The indicator displays:
Main Line: YoY percentage change (green when positive, red when negative)
Zero Line: Reference line at 0% (gray dashed)
Mean Line: Average YoY change over the past 252 days (blue)
Standard Deviation Bands: Shows +/- 1 standard deviation from the mean
Upper band (+1 StdDev): Green, line with breaks style
Lower band (-1 StdDev): Red, line with breaks style
Interpretation
Values above zero indicate YoY growth in central bank assets
Values below zero indicate YoY contraction
Values above the +1 StdDev line indicate unusually strong growth
Values below the -1 StdDev line indicate unusually severe contraction
Crossing above/below the mean line can signal shifts in central bank policy trends
Usage
This indicator is useful for:
Monitoring global central bank liquidity trends
Identifying unusual periods of balance sheet expansion/contraction
Analyzing correlations between central bank activity and market performance
Anticipating potential market impacts from changes in central bank policy
The 252-day lookback period (approximately one trading year) provides a balance between statistical stability and responsiveness to changing trends in central bank behavior.
RSI-EMA-Crossing with Donchian-Stop-LossThe Donchian RSI Indicator is a visual tool that combines momentum and trend analysis to identify high-quality long opportunities based on RSI crossovers, price action, and Donchian channel dynamics.
How It Works
Momentum Signal: A bullish RSI crossover is detected when the RSI crosses above its moving average.
Trend Filter: A signal is only valid if the crossover occurs while the price is above its moving average – filtering out entries against the prevailing trend.
Signal Candle: The high of the crossover candle is stored.
Entry Trigger: A valid signal occurs when a later candle closes above that signal high.
Stop-Loss (Visual Only)
The lower band of the Donchian Channel acts as a visual reference for a dynamic stop-loss level.
Features
Customizable RSI, Donchian Channel, and moving average lengths
Selectable MA types: SMA, EMA, WMA, VWMA, HMA
Signal candle highlighted (yellow background)
Entry points labeled on the chart
Price MA and Donchian Channel plotted
Trend filter improves signal quality by confirming upward bias
Use Case
Designed for swing and position traders
Optimized for use on daily or 4H charts
Volume Peak RectangleOutlines the 'Latest' Highest Volume Bar. Typically High Volume bars create very good support and resistance levels. This is a draw off the Opening Range Breakout theory, with the idea that high volume candles create very good upper and lower levels of liquidity zones.
QuantumTrend SwiftEdgeQuantumTrend SwiftEdge - A Trend-Following Indicator for TradingView
Overview:
QuantumTrend SwiftEdge is a visually engaging and customizable trend-following indicator that combines the power of Supertrend, Keltner Channels, and a 100-period EMA to generate precise buy and sell signals. Designed to help traders identify trends and breakouts, this indicator offers a unique blend of technical tools with a modern gradient color effect, making it both functional and visually appealing.
What It Does:
This indicator identifies trend directions and potential entry/exit points:
- Supertrend determines the overall trend direction, showing a green line below the price during uptrends and a red line above the price during downtrends. The line only appears when the price is close to it, indicating an active trend.
- Keltner Channels highlight volatility and breakouts, with the upper and lower bands dynamically adjusting to market conditions.
- A 100-period EMA provides a longer-term trend perspective, helping to filter out noise.
- Buy and sell signals are generated when specific conditions align across these indicators, ensuring robust trade setups.
How It Works:
The indicator uses three components to generate signals:
1. **Supertrend**: Calculates trend direction using the Average True Range (ATR) and a multiplier. It switches between uptrend (green) and downtrend (red) based on price movements relative to the Supertrend line.
2. **Keltner Channels**: Consists of an EMA (default 20 periods) with upper and lower bands based on ATR. A breakout above the upper band signals potential buying opportunities, while a breakout below the lower band signals potential selling opportunities.
3. **100-period EMA**: Acts as a trend filter, ensuring signals align with the broader market direction.
**Buy Signal**:
- Price is above the 100-period EMA (bullish market).
- Price breaks above the Keltner Channel upper band (indicating a breakout).
- Supertrend switches to an uptrend (trend changes from down to up).
**Sell Signal**:
- Price is below the 100-period EMA (bearish market).
- Price breaks below the Keltner Channel lower band (indicating a breakout).
- Supertrend switches to a downtrend (trend changes from up to down).
Visual Features:
- **Gradient Colors**: Supertrend lines and Keltner Channels use a smooth gradient color transition between green (uptrend) and red (downtrend), reflecting the trend's strength. The gradient is based on a smoothed trend value, creating a visually appealing effect.
- **Keltner Channel Fill**: The area between the upper and lower Keltner Channels is filled with a transparent gradient, enhancing the trend visualization.
- **Dynamic Supertrend Visibility**: Supertrend lines only appear when the price is close to the line (within an ATR-based threshold), indicating an active trend.
How to Use:
1. Add the "QuantumTrend SwiftEdge" indicator to your chart in TradingView.
2. Customize the settings:
- **Signal Sensitivity (1=Low, 5=High)**: Default is 3. Lower values (e.g., 1) make signals less frequent by using wider parameters, while higher values (e.g., 5) make signals more frequent by tightening parameters.
- **Use Manual Settings**: If enabled, you can manually adjust all parameters (ATR Period, ATR Multiplier, Keltner Channel Length, Keltner Channel Multiplier, Keltner ATR Length, EMA Length) to fine-tune the indicator.
- **Change ATR Calculation Method**: Toggle between standard ATR calculation and a simple moving average of true range.
- **Show Buy/Sell Signals**: Toggle to show or hide buy (green "Buy" label) and sell (red "Sell" label) signals.
- **Highlighter On/Off**: Toggle to show or hide the gradient fill between the price and Supertrend line when the line is visible.
3. Interpret the signals:
- A green "Buy" label below the price indicates a potential buying opportunity.
- A red "Sell" label above the price indicates a potential selling opportunity.
- Use the Keltner Channel gradient fill and Supertrend lines to confirm the trend direction and strength.
Why This Combination?
- **Supertrend** provides a robust trend-following mechanism, ensuring signals align with the market direction.
- **Keltner Channels** add a volatility component, identifying breakouts that often precede significant price movements.
- **100-period EMA** filters out noise, ensuring signals are generated in the context of the broader trend.
Together, these indicators create a balanced approach: Supertrend and EMA confirm the trend, while Keltner Channels pinpoint actionable entry and exit points. The gradient visuals and dynamic visibility make it easier to focus on active trends.
Originality:
QuantumTrend SwiftEdge stands out with its unique features:
- Gradient color transitions for a modern, dynamic look.
- A filled gradient between Keltner Channels, visually emphasizing the trend.
- Supertrend lines that only appear when the price is close, reducing clutter and focusing on active trends.
- Flexible settings with both sensitivity-based and manual adjustments for maximum customization.
Default Settings:
The default sensitivity is set to 3, providing a balanced approach for most markets and timeframes (e.g., 5-minute charts for crypto like BTC/USD). This setting uses moderate parameters (ATR Period=10, ATR Multiplier=3.0, Keltner Channel Length=20, Keltner Channel Multiplier=1.5, Keltner ATR Length=10, EMA Length=100). Users can adjust the sensitivity or switch to manual settings for more control.
Important Notes:
- This indicator is a tool to assist in identifying trends and potential entry/exit points. It does not guarantee profits and should be used in conjunction with other analysis and risk management practices.
- The signals are based on historical price data and do not predict future performance. Always test the indicator on a demo account before using it in live trading.
- The gradient effect is purely visual and does not affect the signal logic.
Advanced Donchian ChannelsJust an indicator I got ChatGPT to cook up for my own use, sharing it in case anyone else finds it useful. I have included a screenshot of my own settings as well for reference.
This indicator enhances the classic Donchian Channel with powerful contextual features to support modern breakout and volatility-based trading strategies.
🔹 Core Features:
Donchian Bands: Plots the highest high and lowest low over a configurable lookback period.
Dynamic Fill Shading:
- Color-coded based on the slope of the midline (Basis): Default settings are Green for uptrend, Red for downtrend, Silver for flat, Gray for narrow volatility.
- All fill colors are fully customizable.
Volatility Filter:
- Detects when the channel width is narrow using either a fixed value or a percentage of price.
- Optionally shades only during low-volatility (compression) periods.
Customizable Style:
- Adjustable opacity, offsets, and color settings to suit your charting style.
🛠 Use Cases:
- Spot potential breakout setups after periods of low volatility.
- Identify trend direction via basis slope shading.
- Combine with momentum or volume tools for high-probability entries.
HexworksSharedUtilitiesLibrary "HexworksSharedUtilities"
Shared global utilities that can be used for
- creating bounded queues from primitives
- checking visibility of objects having Bounds on both (x, y) axes
- checking if a line is too long
method offer(history, value)
Namespace types: FloatHistory
Parameters:
history (FloatHistory)
value (simple float)
method offer(history, value)
Namespace types: IntHistory
Parameters:
history (IntHistory)
value (simple int)
method offer(history, value)
Namespace types: StringHistory
Parameters:
history (StringHistory)
value (simple string)
method offer(history, value)
Namespace types: BoolHistory
Parameters:
history (BoolHistory)
value (simple bool)
method toString(point)
Namespace types: chart.point
Parameters:
point (chart.point)
method toString(num)
Namespace types: simple float, input float, const float
Parameters:
num (simple float)
method toString(num)
Namespace types: simple int, input int, const int
Parameters:
num (simple int)
method toString(value)
Namespace types: simple bool, input bool, const bool
Parameters:
value (simple bool)
method toString(l)
Namespace types: series line
Parameters:
l (line)
method isLineTooLong(fromPoint, toPoint)
Namespace types: chart.point
Parameters:
fromPoint (chart.point)
toPoint (chart.point)
method isTooLong(l)
Namespace types: series line
Parameters:
l (line)
createVisibilityChecker()
method update(v)
Namespace types: VisibilityChecker
Parameters:
v (VisibilityChecker)
method canDraw(v)
Namespace types: VisibilityChecker
Parameters:
v (VisibilityChecker)
method isVisible(v, b)
Namespace types: VisibilityChecker
Parameters:
v (VisibilityChecker)
b (Bounds)
FloatHistory
Fields:
history (array)
maxLength (series int)
IntHistory
Fields:
history (array)
maxLength (series int)
StringHistory
Fields:
history (array)
maxLength (series int)
BoolHistory
Fields:
history (array)
maxLength (series int)
Bounds
Fields:
startIdx (series int)
endIdx (series int)
highValue (series float)
lowValue (series float)
VisibilityChecker
Fields:
leftVisibleBarIdx (series int)
rightVisibleBarIdx (series int)
maxDrawDistance (series int)
updatedAt (series int)
visibleHighest (series float)
visibleLowest (series float)
Volume Sentiment Pro (NTY88)Volume Sentiment Edge: Smart Volume & RSI Trading System
Description:
Unlock the power of volume-driven market psychology combined with precision RSI analysis! This professional-grade indicator identifies high-probability trading opportunities through:
🔥 Key Features
1. Smart Volume Spike Detection
Auto-detects abnormal volume activity with adaptive threshold
Clear spike labels & multi-timeframe confirmation
RSI-Powered Sentiment Analysis
Real-time Bullish/Bearish signals based on RSI extremes
Combined volume-RSI scoring system (Strong Bull/Bear alerts)
2. Professional Dashboard
Instant sentiment status table (bottom-right)
Color-coded momentum strength visualization
Customizable themes for all chart styles
3. Institutional-Grade Tools
HTF (Daily/Weekly) volume confirmation
EMA trend-filtered momentum signals
Spike-to-Threshold ratio monitoring
4. Trade-Ready Alerts
Pre-configured "Bullish Setup" (Spike + Oversold RSI)
"Bearish Setup" (Spike + Overbought RSI)
Why Traders Love This:
✅ Real-Time Visual Alerts - SPIKE markers above bars + table updates
✅ Adaptive Thresholds - Self-adjusting to market volatility
✅ Multi-Timeframe Verification - Avoid false signals with HTF confirmation
✅ Customizable UI - 10+ color settings for perfect chart integration
Usage Scenarios:
Day Traders: Catch volume surges during key sessions
Swing Traders: Confirm reversals with RSI extremes
All Markets: Works equally well on stocks, forex & crypto
Confirmation Tool: Combine with your existing strategy
Sample Setup:
"Enter long when:
5. RED SPIKE label appears
Table shows 'Oversold RSI'
Momentum status turns 'Bullish'
Volume exceeds daily average (Confirmed)"
📈 Try Risk-Free Today!
Perfect for traders who want:
Clean, non-repainting signals
Institutional-level volume analysis
Professional visual feedback
Customizable trading rules
⚠️ Important: Works best on 15m-4h timeframes. Combine with price action for maximum effectiveness.
📜 Legal Disclaimer
By using this indicator, you agree to the following terms:
Not Financial Advice
This tool provides technical analysis only. It does NOT constitute investment advice, financial guidance, or solicitation to trade.
High Risk Warning
Trading financial instruments carries substantial risk. Past performance ≠ future results. Never risk capital you cannot afford to lose.
No Guarantees
Signals are based on historical data and mathematical models. Market conditions may change rapidly, rendering previous patterns ineffective.
User Responsibility
You alone bear 100% responsibility for trading decisions. We expressly disclaim liability for any profit/loss resulting from this tool's use.
Professional Consultation
Always consult a licensed financial advisor before taking positions. This tool should NEVER be used as sole decision-making criteria.
Educational Purpose
This indicator is provided "as is" for informational/educational use only. No representation is made about its accuracy or completeness.
Third-Party Data
We do not verify exchange data accuracy. Use signals at your own discretion after independent verification.
TrendScopeTrendScope is a custom-built, multi-factor trading tool designed to identify high-probability market entries and exits using a combination of trend structure, volume dynamics, and momentum behavior. Unlike traditional oscillators, it does not rely on bounded cyclical formulas but instead analyzes real-time price-volume relationships and trend integrity.
🔍 Key Features
EMA Confluence Analysis: Detects trend strength and alignment across EMAs from 5 to 800 periods.
Volume Spike Detection: Flags significant increases in trading volume following periods of stagnation—useful for breakout confirmation.
Order Flow Momentum: Measures buying vs. selling pressure based on volume-weighted price action, signaling directional conviction.
Reversal Alerts: Identifies divergences between price and momentum (e.g., volume-based net flow), warning of potential trend shifts.
Clean Visual Markers: BUY/SELL labels, directional volume spikes, and a trend strength table for clarity in execution.
⏱️ Best Used On
Timeframes: 4H, 8H, 12H, 1D (Daily)
Style: Swing trading, trend trading, and momentum-based entries
Markets: Crypto, Forex, Commodities, and Indices (works well on liquid assets with healthy volume)
This indicator is especially useful for traders who want directional confirmation during trending conditions and a visual edge for spotting volume-driven breakouts or early-stage reversals.
I made this for my own benefit since I didn't really find any non-paid options out there that work in a similar fashion and I wanted to keep it simple and was inspired by Delorean Trading Indicators.
Disclaimer: Just wanna throw this out there...please never use this as a standalone indicator and combine it with your own analysis to detect market behaviour and structure! Don't rely on any indicators to form your own pov of probable market moves. You have been warned.
Volume Cluster Support & ResistanceVolume Cluster Support & Resistance
This indicator identifies potential Support and Resistance (S/R) levels on the chart using Volume-Based Point of Control (POC) Clustering. It offers extensive customization for calculation parameters, display styles, and visualization options, including S/R zones, color gradients, and historical reaction markers.
How It Works
Volume Based S/R:
Scans the specified Clustering Lookback period for "High Volume Bars", defined as bars where volume exceeds the average volume (over Volume Lookback Period) multiplied by the High Volume Threshold Multiplier.
Calculates the Point of Control (POC) for each high-volume bar using hl2.
Clusters these high-volume bar POCs: POCs within a proximity defined by Cluster Proximity (ATR) (Average True Range multiplier) are grouped together.
Filters these clusters, requiring a Min Bars in Cluster to form a valid S/R zone.
(Image showing the indicator being used on the Bitcoin 5min chart)
The center price of valid clusters determines the S/R level. Clusters above the current price become potential Resistance, and those below become potential Support.
Calculates the offset based on the most recent bar included in the cluster.
Level Selection & Display:
The indicator identifies multiple potential S/R levels.
It then selects and displays the top Number of S/R Levels to Display support levels below the current price and resistance levels above the current price.
(Image showing the indicator on the GBP/USD 5min chart)
ATR Usage:
The Average True Range (ta.atr(14)) is used in two key areas:
Determining the proximity threshold for grouping POCs in the 'Volume Based' clustering (clusterProximityAtr).
Calculating the width of the S/R zones when 'Use Zone Visualization' is enabled (zoneAtrMultiplier).
Key Features & Components
Dual Calculation Methods: Choose between Pivot-based S/R or Volume-based POC clustering.
Volume Confirmation: Pivots require volume confirmation; Volume method directly analyzes high-volume bars.
POC Clustering: Groups high-volume areas to identify significant price zones.
Configurable Lookbacks: Adjust periods for volume averaging, pivot detection, and clustering analysis.
Dynamic S/R Display: Shows a configurable number of the most relevant S/R levels relative to the current price.
Optional Zone Visualization: Display levels as filled zones with configurable width (ATR-based), fill transparency, and border transparency. Includes a dashed center line.
Optional Historical Reactions: Mark past price interactions (lows bouncing off support zones, highs rejecting from resistance zones) directly on the chart (Warning: Can significantly impact performance).
Customizable Styling: Control line style (Solid, Dashed, Dotted), width, color (separate for Support & Resistance), and horizontal extension (None, Left, Right, Both).
Price Labels: Toggle visibility of price labels next to each S/R level/zone.
Visual Elements Explained
S/R Lines/Zones: Plotted lines or filled zones representing calculated support and resistance levels. Color-coded for Support (default green) and Resistance (default magenta).
Line/Zone Borders: Appearance controlled by Style settings (Style, Width, Extension). Can have a gradient color effect based on age if enabled.
Zone Fills: Semi-transparent fills for zones (if enabled), with configurable transparency. Fill color matches the border color (including gradient effect if enabled).
Zone Center Line: A thin, dashed line indicating the exact calculated S/R price within a zone.
Price Labels: Text labels showing the exact price of the S/R level.
Historical Reactions: Small dot markers appearing on historical bars where price potentially reacted to a displayed zone (only if Show Historical Reactions is enabled).
Configuration Options
Users can adjust the following parameters in the indicator settings:
Calculation Method: Select "Pivot Based" or "Volume Based".
Volume Zone Settings (Volume Based): Threshold multiplier, clustering lookback, cluster proximity (ATR), minimum bars per cluster.
Display Options: Toggle S/R visibility, price tags, set the number of levels to show.
Volume Settings: Volume lookback period, volume multiplier (for Pivot confirmation).
Style Settings: Line style, width, extension, support/resistance text and line colors, enable gradient coloring, set gradient start/end colors.
Zone Visualization: Enable/disable zones, set zone width (ATR multiplier), fill and border transparency, enable/disable historical reaction markers (performance warning).
Interpretation Notes
This indicator identifies potential areas of support and resistance based on historical price action and volume analysis. These levels are not guaranteed reversal points.
The 'Volume Based' method focuses on areas where significant trading activity occurred, while the 'Pivot Based' method focuses on price turning points confirmed by volume.
Use the displayed levels in conjunction with other technical analysis tools, price action patterns, and risk management strategies.
Be mindful of the performance impact when enabling Show Historical Reactions, especially on longer timeframes or with large lookback periods. The default setting is false for optimal performance.
The max_bars_back setting is optimized for performance; increasing it significantly may slow down chart loading.
Risk Disclaimer
Trading involves significant risk. This indicator is provided for analytical and educational purposes only and does not constitute financial advice or a trading recommendation. Past performance is not indicative of future results. Always use sound risk management practices and never trade with capital you cannot afford to lose.
