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[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. 🙏📈🔍
Pine Script® indicator
by blackcat1402
support band level 2📉 Support Band Level 2 – Support Zone and resistance zones only for Bitcoin. Overview: Support Band Level 2 is a support band designed for long-term traders, providing a reliable support range based on a combination of SMA and EMA calculated on a fixed higher timeframe (default: 1W) 🧠 What Makes It Unique: This band highlights the strongest support in a Bitcoin's bull market. Unlike traditional SMA and EMA indicators, which can be confusing when multiple levels break or hold, the band clearly shows when support is holding or being broken. By using this band, you can avoid the uncertainty that comes from analyzing individual moving averages. besides more than just code this indicator has a strategy and a extensive backtesting behind it. 🛠️ How to Use: Apply it to any chart timeframe — the band will remain synchronized with the fixed higher timeframe (e.g., 1W). Use the white band to identify long-term support levels and invalidation points. Support is often tested multiple times, and after holding, we usually see a continuation of the pump. However, if 2 weekly candles close below the white band, this indicates a bearish trend. ⚠️ Disclaimer: This indicator does not provide buy/sell signals or predictions. It serves as a visual reference tool to assist in technical analysis by marking key support zones. Always use proper risk management strategies when making trading decisions. Why Choose Support Band Level 2? Support Band Level 2 provides a clear and reliable indication of market trends, making it an essential tool for long-term traders. The indicator helps you easily identify when the market is in a bullish or bearish phase: Bullish when the price is above the white band. Bearish when the price is below the white band. Additionally, this indicator can also complement your day trading strategy. By combining it with your existing tools, you can follow a simple yet effective strategy: Go long only when the price is above the white band. Go short only when the price is below the white band. Proven Performance: Based on 10 years of backtesting using Bitcoin data, this indicator has shown strong reliability in identifying critical support and resistance levels. It’s an invaluable tool for both long-term planning and short-term strategies, helping you make more informed trading decisions with ease. Why Choose Support Band Level 2? While many indicators can look visually impressive, the key focus of Support Band Level 2 is its practicality, simplicity and performance. I prioritize creating tools that work effectively in real market conditions, ensuring that you get in most cases good trading signals. This indicator is designed to provide actionable insights, not just aesthetics. the strenght of this indicator is its backtesting. this is not a financial advice
Pine Script® indicator
by sam_180x
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.
Pine Script® indicator
by LuxmiAI
G10 FX Basket ComparisonDescription: This indicator shows how individual FX major currencies (including CNY) have performed relative to each other. It calculates each currency's performance against a "Trade Weighted" basket of other major currencies. I created this because I couldn't find it, and I wanted an easy way to see currency behaviour and flows. Purpose: It lets you see the relative strength and weakness of each currency, similar to how the DXY measures USD strength, but for all the major currencies. Each basket and currency weights are based on Trade Weighted values from literature/economics. This way you can maybe decide which crosses / pairs to trade. Can helps you visualise how events (economic, news or otherwise) affect currency flows. Features: Relative Performance: Focuses on how a currency's value has changed over time, rather than its absolute level. Normalization: Adjusts currency values to a starting date, making it easy to compare their performance. Adjustable Start Date: You can set the anchor date to choose the starting point for calculating relative performance. Customizable Weights: The indicator allows you to use custom weights for each currency basket should you wish.
Pine Script® indicator
by Things
1
TradeNeon - Level of InterestLevel of Interest (LOI) is part of the TradeNeon Software Portfolio – built for professional futures traders. LOI highlights key price zones of institutional interest based on proprietary models and displays them directly on your chart. It helps you cut through market noise, improve timing, and focus on what truly matters: structure, context, and key decision points. Use LOI to navigate markets with clarity and confidence. Level of Interest – See what matters. Use the daily, professional market analyses to your advantage. Our experts with years of experience identify precise price areas of institutional interest. Maximize your trading potential and use these high-quality trading locations for your individual strategies. tradeneon-academy.com/level-of-interest/
Pine Script® indicator
by l4am
Envelope//@version=5 indicator("FX 5分足 EMA+MACD+RSI 手法アラート", overlay=true) // === EMA設定 === ema20 = ta.ema(close, 20) ema50 = ta.ema(close, 50) ema100 = ta.ema(close, 100) plot(ema20, color=color.yellow, title="EMA 20") plot(ema50, color=color.orange, title="EMA 50") plot(ema100, color=color.red, title="EMA 100") // === MACD設定 === = ta.macd(close, 12, 26, 9) macdBuy = ta.crossover(macdLine, signalLine) macdSell = ta.crossunder(macdLine, signalLine) // === RSI設定 === rsi = ta.rsi(close, 14) // === ロング条件 === longCondition = ema20 > ema50 and ema50 > ema100 and close >= ema20 and macdBuy and rsi > 50 and rsi < 70 plotshape(longCondition, location=location.belowbar, color=color.green, style=shape.labelup, text="Buy", title="Buy Signal") // === ショート条件 === shortCondition = ema20 < ema50 and ema50 < ema100 and close <= ema20 and macdSell and rsi < 50 and rsi > 30 plotshape(shortCondition, location=location.abovebar, color=color.red, style=shape.labeldown, text="Sell", title="Sell Signal") // === アラート設定 === alertcondition(longCondition, title="Buy Alert", message="Buy Signal: EMA + MACD + RSI conditions met") alertcondition(shortCondition, title="Sell Alert", message="Sell Signal: EMA + MACD + RSI conditions met")
Pine Script® indicator
by tosimasa
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.
Pine Script® indicator
by viorel8
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.
Pine Script® indicator
by EdgeTools
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.
Pine Script® indicator
by peacefulFerret86228
6 Exponential Moving Averages 2 SMA6 EMA Trend Indicator This indicator plots 6 Exponential Moving Averages (EMAs) with customizable periods to help traders visually analyze short-, medium-, and long-term trend alignments. Ideal for identifying trend strength, pullback zones, and dynamic support/resistance. Features: • 6 fully adjustable EMA inputs • Clear color-coded visualization • Works on all timeframes • Effective for trend trading and scalping Use it to confirm trend direction, spot EMA crossovers, or align multiple EMAs for high-probability entries.
Pine Script® indicator
by yashdarji
All‑MA Crossover + analyzer + risk Management [quantotc]🔍 Overview All‑MA Trend Analyzer + Risk Management is a full-featured, multi-purpose trend and crossover system that lets you compare 8 different moving average types, visualize their alignment across timeframes, and apply robust risk management strategies — all in one powerful tool. 🧠 What Makes This Indicator Unique? 🔄 8 Moving Average Types — Easily switch between SMA, EMA, WMA, VWMA, HMA, RMA, SMMA, and TMA. 🟢 Signal Clarity — Buy/Sell labels appear on fast/slow MA crossovers. 📊 Dual Analysis Tables Top-right: Multi-timeframe crossover trends (15m, 1h, 4h, Daily) Bottom-right: MA type trends on current timeframe (Bull/Bear) ⚙️ Risk Management Supports fixed SL/TP or trailing stop-loss Works in % or Points Visual SL/TP/TSL exit labels with separate alerts 🎯 How to Use Select your desired MA Type (e.g., TMA, VWMA, etc.) Adjust Fast/Slow Lengths depending on your strategy Enable Long/Short entries as needed Choose SL/TP Mode: Points or Percentage Enable Trailing Stop for dynamic protection Each feature is grouped and labeled with tooltips in the settings panel for clarity. 🖼 Visual Aids A TMA Bull signal Table-based trend analysis Buy label clarity Sell label clarity Exit label on Take Profit Exit label on Stop Loss Trailing Stop Loss Exit 🚨 Alerts Included BUY / SELL TAKE PROFIT STOPLOSS TRAILING STOPLOSS Each is customizable in the settings. 👤 Developer Info Developer: quantotc Website: quantotc.com YouTube:https://youtube.com/@quantotc Tags: multi timeframe, crossover, risk management, all MA, trailing stop, bullish bearish, trend table, strategy builder ⚠️ Disclaimer This script is for educational purposes only. No guarantee of profitability. Always backtest and use proper risk management.
Pine Script® indicator
by quantotc