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DEGA RMA | QuantEdgeB🧠 Introducing DEGA RMA (DGR ) by QuantEdgeB 🛠️ Overview DEGA RMA (DGR) is a precision-engineered trend-following system that merges DEMA, Gaussian kernel smoothing, and ATR-based envelopes into a single, seamless overlay indicator. Its mission: to filter out market noise while accurately capturing directional bias using a layered volatility-sensitive trend core. DGR excels at identifying valid breakouts, sustained momentum conditions, and trend-defining price behavior without falling into the trap of frequent signal reversals. 🔍 How It Works 1️⃣ Double Exponential Moving Average (DEMA) The system begins by applying a DEMA to the selected price source. DEMA responds faster than a traditional EMA, making it ideal for capturing transitions in momentum. 2️⃣ Gaussian Filtering A custom Gaussian kernel is used to smooth the DEMA signal. The Gaussian function applies symmetrical weights, centered around the most recent bar, effectively softening sharp price oscillations while preserving the underlying trend structure. 3️⃣ Recursive Moving Average (RMA) Core The filtered Gaussian output is then processed through an RMA to generate a stable dynamic baseline. This baseline becomes the foundation for the final trend logic. 4️⃣ ATR-Scaled Breakout Zones Upper and lower trend envelopes are calculated using a custom ATR filter built on DEMA-smoothed volatility. • ✅ Long Signal when price closes above the upper envelope • ❌ Short Signal when price closes below the lower envelope • ➖ Neutral when inside the band (no signal noise) ✨ Key Features 🔹 Multi-Layer Trend Model DEMA → Gaussian → RMA creates a signal structure that is both responsive and robust. 🔹 Volatility-Aware Entry System Adaptive ATR bands adjust in real-time, expanding during high volatility and contracting during calm periods. 🔹 Noise-Reducing Gaussian Kernel Sigma-adjustable kernel ensures signal smoothness without introducing excessive lag. 🔹 Clean Visual System Candle coloring and band fills make trend state easy to read and act on at a glance. ⚙️ Custom Settings • DEMA Source – Input source for trend core (default: close) • DEMA Length – Length for initial smoothing (default: 30) • Gaussian Filter Length – Determines smoothing depth (default: 4) • Gaussian Sigma – Sharpness of Gaussian curve (default: 2.0) • RMA Length – Core baseline smoothing (default: 12) • ATR Length – Volatility detection period (default: 40) • ATR Mult Up/Down – Controls the upper/lower threshold range for signals (default: 1.7) 📌 How to Use 1️⃣ Trend-Following Mode • Go Long when price closes above the upper ATR band • Go Short when price closes below the lower ATR band • Remain neutral otherwise 2️⃣ Breakout Confirmation Tool DGR’s ATR-based zone logic helps validate price breakouts and filter out false signals that occur inside compressed ranges. 3️⃣ Volatility Monitoring Watch the ATR envelope width — a narrowing band often precedes expansion and potential directional shifts. 📌 Conclusion DEGA RMA (DGR) is a thoughtfully constructed trend-following framework that goes beyond basic moving averages. Its Gaussian smoothing, adaptive ATR thresholds, and layered filtering logic provide a versatile solution for traders looking for cleaner signals, less noise, and real-time trend awareness. Whether you're trading crypto, forex, or equities — DGR adapts to volatility while keeping your chart clean and actionable. 🔹 Summary • ✅ Advanced Smoothing → DEMA + Gaussian + RMA = ultra-smooth trend core • ✅ Volatility-Adjusted Zones → ATR envelope scaling removes whipsaws • ✅ Fully Customizable → Tailor to any asset or timeframe • ✅ Quant-Inspired Structure → Built for clarity, consistency, and confidence 📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets. 📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Penunjuk Pine Script®
oleh QuantEdgeB
2
Gaussian Smooth Trend | QuantEdgeB🧠 Introducing Gaussian Smooth Trend (GST) by QuantEdgeB 🛠️ Overview Gaussian Smooth Trend (GST) is an advanced volatility-filtered trend-following system that blends multiple smoothing techniques into a single directional bias tool. It is purpose-built to reduce noise, isolate meaningful price shifts, and deliver early trend detection while dynamically adapting to market volatility. GST leverages the Gaussian filter as its core engine, wrapped in a layered framework of DEMA smoothing, SMMA signal tracking, and standard deviation-based breakout thresholds, producing a powerful toolset for trend confirmation and momentum-based decision-making. 🔍 How It Works 1️⃣ DEMA Smoothing Engine The indicator begins by calculating a Double Exponential Moving Average (DEMA), which provides a responsive and noise-resistant base input for subsequent filtering. 2️⃣ Gaussian Filter A custom Gaussian kernel is applied to the DEMA signal, allowing the system to detect smooth momentum shifts while filtering out short-term volatility. This is especially powerful during low-volume or sideways markets where traditional MAs struggle. 3️⃣ SMMA Layer with Z-Filtering The filtered Gaussian signal is then passed through a custom Smoothed Moving Average (SMMA). A standard deviation envelope is constructed around this SMMA, dynamically expanding/contracting based on market volatility. 4️⃣ Signal Generation • ✅ Long Signal: Price closes above Upper SD Band • ❌ Short Signal: Price closes below Lower SD Band • ➖ No trade: Price stays within the band → market indecision ✨ Key Features 🔹 Multi-Stage Trend Detection Combines DEMA → Gaussian Kernel → SMMA → SD Bands for robust signal integrity across market conditions. 🔹 Gaussian Adaptive Filtering Applies a tunable sigma parameter for the Gaussian kernel, enabling you to fine-tune smoothness vs. responsiveness. 🔹 Volatility-Aware Trend Zones Price must close outside of dynamic SD envelopes to trigger signals — reducing whipsaws and increasing signal quality. 🔹 Dynamic Color-Coded Visualization Candle coloring and band fills reflect live trend state, making the chart intuitive and fast to read. ⚙️ Custom Settings • DEMA Source: Price stream used for smoothing (default: close) • DEMA Length: Period for initial exponential smoothing (default: 7) • Gaussian Length / Sigma: Controls smoothing strength of kernel filter • SMMA Length: Final smoothing layer (default: 12) • SD Length: Lookback period for standard deviation filtering (default: 30) • SD Mult Up / Down: Adjusts distance of upper/lower breakout zones (default: 2.5 / 1.8) • Color Modes: Six distinct color palettes (e.g., Strategy, Warm, Cool) • Signal Labels: Toggle on/off entry markers ("𝓛𝓸𝓷𝓰", "𝓢𝓱𝓸𝓻𝓽") 📌 Trading Applications ✅ Trend-Following → Enter on confirmed breakouts from Gaussian-smoothed volatility zones ✅ Breakout Validation → Use SD bands to avoid false breakouts during chop ✅ Volatility Compression Monitoring → Narrowing bands often precede large directional moves ✅ Overlay-Based Confirmation → Can complement other QuantEdgeB indicators like K-DMI, BMD, or Z-SMMA 📌 Conclusion Gaussian Smooth Trend (GST) delivers a precision-built trend model tailored for modern traders who demand both clarity and control. The layered signal architecture, combined with volatility awareness and Gaussian signal enhancement, ensures accurate entries, clean visualizations, and actionable trend structure — all in real-time. 🔹 Summary Highlights 1️⃣ Multi-stage Smoothing — DEMA → Gaussian → SMMA for deep signal integrity 2️⃣ Volatility-Aware Filtering — SD bands prevent false entries 3️⃣ Visual Trend Mapping — Gradient fills + candle coloring for clean charts 4️⃣ Highly Customizable — Adapt to your timeframe, style, and volatility 📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets. 📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Penunjuk Pine Script®
oleh QuantEdgeB
Kernel Weighted DMI | QuantEdgeB📊 Introducing Kernel Weighted DMI (K-DMI) by QuantEdgeB 🛠️ Overview K-DMI is a next-gen momentum indicator that combines the traditional Directional Movement Index (DMI) with advanced kernel smoothing techniques to produce a highly adaptive, noise-resistant trend signal. Unlike standard DMI that can be overly reactive or choppy in consolidation phases, K-DMI applies kernel-weighted filtering (Linear, Exponential, or Gaussian) to stabilize directional movement readings and extract a more reliable momentum signal. ✨ Key Features 🔹 Kernel Smoothing Engine Smooths DMI using your choice of kernel (Linear, Exponential, Gaussian) for flexible noise reduction and clarity. 🔹 Dynamic Trend Signal Generates real-time long/short trend bias based on signal crossing upper or lower thresholds (defaults: ±1). 🔹 Visual Encoding Includes directional gradient fills, candle coloring, and momentum-based overlays for instant signal comprehension. 🔹 Multi-Mode Plotting Optional moving average overlays visualize structure and compression/expansion within price action. 📐 How It Works 1️⃣ Directional Movement Index (DMI) Calculates the traditional +DI and -DI differential to derive directional bias. 2️⃣ Kernel-Based Smoothing Applies a custom-weighted average across historical DMI values using one of three smoothing methods: • Linear → Simple tapering weights • Exponential → Decay curve for recent emphasis • Gaussian → Bell-shaped weight for centered precision 3️⃣ Signal Generation • ✅ Long → Signal > Long Threshold (default: +1) • ❌ Short → Signal < Short Threshold (default: -1) Additional overlays signal potential compression zones or trend resumption using gradient and line fills. ⚙️ Custom Settings • DMI Length: Default = 7 • Kernel Type: Options → Linear, Exponential, Gaussian (Def:Linear) • Kernel Length: Default = 25 • Long Threshold: Default = 1 • Short Threshold: Default = -1 • Color Mode: Strategy, Solar, Warm, Cool, Classic, Magic • Show Labels: Optional entry signal labels (Long/Short) • Enable Extra Plots: Toggle MA overlays and dynamic bands 👥 Who Is It For? ✅ Trend Traders → Identify sustained directional bias with smoother signal lines ✅ Quant Analysts → Leverage advanced smoothing models to enhance data clarity ✅ Discretionary Swing Traders → Visualize clean breakouts or fades within choppy zones ✅ MA Compression Traders → Use overlay MAs to detect expansion opportunities 📌 Conclusion Kernel Weighted DMI is the evolution of classic momentum tracking—merging traditional DMI logic with adaptable kernel filters. It provides a refined lens for trend detection, while optional visual overlays support price structure analysis. 🔹 Key Takeaways: 1️⃣ Smoothed and stabilized DMI for reliable trend signal generation 2️⃣ Optional Gaussian/exponential weighting for adaptive responsiveness 3️⃣ Custom gradient fills, dynamic MAs, and candle coloring to support visual clarity 📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets. 📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Penunjuk Pine Script®
oleh QuantEdgeB
Normalized DEMA Oscillator SD| QuantEdgeB📊 Introducing Normalized DEMA Oscillator SD (NDOSD) by QuantEdgeB 🛠️ Overview Normalized DEMA Oscillator SD (NDOSD) is a powerful trend and momentum indicator that blends DEMA-based smoothing with a standard deviation-based normalization engine. The result is an oscillator that adapts to volatility, filters noise, and highlights both trend continuations and reversal zones with exceptional clarity. It normalizes price momentum within an adaptive SD envelope, allowing comparisons across assets and market conditions. Whether you're a trend trader or mean-reverter, NDOSD provides the insight needed for smarter decision-making. ✨ Key Features 🔹 DEMA-Powered Momentum Core Utilizes a Double EMA (DEMA) for smoother trend detection with reduced lag. 🔹 Normalized SD Bands Price momentum is standardized using a dynamic 2× standard deviation range—enabling consistent interpretation across assets and timeframes. 🔹 Overbought/Oversold Detection Includes clear OB/OS zones with shaded thresholds to identify potential reversals or trend exhaustion areas. 🔹 Visual Trend Feedback Color-coded oscillator zones, candle coloring, and optional signal labels help traders immediately see trend direction and strength. 📐 How It Works 1️⃣ DEMA Calculation The core of NDOSD is a smoothed price line using a Double EMA, designed to reduce false signals in choppy markets. 2️⃣ Normalization with SD The DEMA is normalized within a volatility range using a 2x SD calculation, producing a bounded oscillator from 0–100. This transforms the raw signal into a structured format, allowing for OB/OS detection and trend entry clarity. 3️⃣ Signal Generation • ✅ Long Signal → Oscillator crosses above the long threshold (default: 55) and price holds above the lower SD boundary. • ❌ Short Signal → Oscillator drops below short threshold (default: 45), often within upper SD boundary context. 4️⃣ OB/OS Thresholds • Overbought Zone: Above 100 → Caution / Consider profit-taking. • Oversold Zone: Below 0 → Watch for accumulation setups. ⚙️ Custom Settings • Calculation Source: Default = close • DEMA Period: Default = 30 • Base SMA Period: Default = 20 • Long Threshold: Default = 55 • Short Threshold: Default = 45 • Color Mode: Choose from Strategy, Solar, Warm, Cool, Classic, or Magic • Signal Labels Toggle: Show/hide Long/Short markers on chart 👥 Ideal For ✅ Trend Followers – Identify breakout continuation zones using oscillator thrust and SD structure ✅ Swing Traders – Catch mid-trend entries or mean reversion setups at OB/OS extremes ✅ Quant/Systemic Traders – Normalize signals for algorithmic integration across assets ✅ Multi-Timeframe Analysts – Easily compare trend health using standardized oscillator ranges 📌 Conclusion Normalized DEMA Oscillator SD is a sleek and adaptive momentum toolkit that helps traders distinguish true momentum from false noise. With its fusion of DEMA smoothing and SD normalization, it works equally well in trending and range-bound conditions. 🔹 Key Takeaways: 1️⃣ Smoother momentum tracking using DEMA 2️⃣ Cross-asset consistency via SD-based normalization 3️⃣ Versatile for both trend confirmation and reversal identification 📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets. 📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading. Let me know if you want a strategy script or publish-ready layout for TradingView next!
Penunjuk Pine Script®
oleh QuantEdgeB
2
TTM Squeeze Momentum MTF [Cometreon]TTM Squeeze Momentum MTF combines the core logic of both the Squeeze Momentum by LazyBear and the TTM Squeeze by John Carter into a single, unified indicator. It offers a complete system to analyze the phase, direction, and strength of market movements. Unlike the original versions, this indicator allows you to choose how to calculate the trend, select from 15 different types of moving averages, customize every parameter, and adapt the visual style to your trading preferences. If you are looking for a powerful, flexible and highly configurable tool, this is the perfect choice for you. 🔷 New Features and Improvements 🟩 Unified System: Trend Detection + Visual Style You can decide which logic to use for the trend via the "Show TTM Squeeze Trend" input: ✅ Enabled → Trend calculated using TTM Squeeze ❌ Disabled → Trend based on Squeeze Momentum You can also customize the visual style of the indicator: ✅ Enable "Show Histogram" for a visual mode using Histogram, Area, or Column ❌ Disable it to display the classic LazyBear-style line Everything updates automatically and dynamically based on your selection. 🟩 Full Customization Every base parameter of the original indicator is now fully configurable: lengths, sources, moving average types, and more. You can finally adapt the squeeze logic to your strategy — not the other way around. 🟩 Multi-MA Engine Choose from 15 different Moving Averages for each part of the calculation: SMA (Simple Moving Average) EMA (Exponential Moving Average) WMA (Weighted Moving Average) RMA (Smoothed Moving Average) HMA (Hull Moving Average) JMA (Jurik Moving Average) DEMA (Double Exponential Moving Average) TEMA (Triple Exponential Moving Average) LSMA (Least Squares Moving Average) VWMA (Volume-Weighted Moving Average) SMMA (Smoothed Moving Average) KAMA (Kaufman’s Adaptive Moving Average) ALMA (Arnaud Legoux Moving Average) FRAMA (Fractal Adaptive Moving Average) VIDYA (Variable Index Dynamic Average) 🟩 Dynamic Signal Line Apply a moving average to the momentum for real-time cross signals, with full control over its length and type. 🟩 Multi-Timeframe & Multi-Ticker Support You're no longer limited to the chart's current timeframe or ticker. Apply the squeeze to any symbol or timeframe without repainting. 🔷 Technical Details and Customizable Inputs This indicator offers a fully modular structure with configurable parameters for every component: 1️⃣ Squeeze Momentum Settings – Choose the source, length, and type of moving average used to calculate the base momentum. 2️⃣ Trend Mode Selector – Toggle "Show TTM Squeeze Trend" to select the trend logic displayed on the chart: ✅ Enabled – Shows the trend based on TTM Squeeze (Bollinger Bands inside/outside Keltner Channel) ❌ Disabled – Displays the trend based on Squeeze Momentum logic 🔁 The moving average type for the Keltner Channel is handled automatically, so you don't need to select it manually, even if the custom input is disabled. 3️⃣ Signal Line – Toggle the Signal Line on the Squeeze Momentum. Select its length and MA type to generate visual cross signals. 4️⃣ Bollinger Bands – Configure the length, multiplier, source, and MA type used in the bands. 5️⃣ Keltner Channel – Adjust the length, multiplier, source, and MA type. You can also enable or disable the True Range option. 6️⃣ Advanced MA Parameters – Customize the parameters for advanced MAs (JMA, ALMA, FRAMA, VIDYA), including Phase, Power, Offset, Sigma, and Shift values. 7️⃣ Ticker & Input Source – Select the ticker and manage inputs for alternative chart types like Renko, Kagi, Line Break, and Point & Figure. 8️⃣ Style Settings – Choose how the squeeze is displayed: Enable "Show Histogram" for Histogram, Area, or Column style Disable it to show the classic LazyBear-style line Use Reverse Color to invert line colors Toggle Show Label to highlight Signal Line cross signals Customize trend colors to suit your preferences 9️⃣ Multi-Timeframe Options - Timeframe – Use the squeeze on higher timeframes for stronger confirmation 🔟 Wait for Timeframe Closes - ✅ Enabled – Prevents multiple signals within the same candle ❌ Disabled – Displays the indicator smoothly without delay 🔧 Default Settings Reference To replicate the default settings of the original indicators as they appear when first applied to the chart, use the following configurations: 🟩 TTM Squeeze (John Carter Style) Squeeze Length: 20 MA Type: SMA Show TTM Squeeze Trend: Enabled Bollinger Bands Length: 20 Multiplier: 2.0 MA Type: SMA Keltner Channel Length: 20 Multiplier: 1.0 Use True Range: ON MA Type: EMA Style Show Histogram: Enabled Reverse Color: Enabled 🟩 Squeeze Momentum (LazyBear Style) Squeeze Length: 10 MA Type: SMA Show TTM Squeeze Trend: Disabled Bollinger Bands Length: 20 Multiplier: 1.5 MA Type: SMA Keltner Channel Length: 10 Multiplier: 1.5 Use True Range: ON MA Type: SMA Style Show Histogram: Disabled Reverse Color: Disabled ⚠️ These values are intended as a starting point. The Cometreon indicator lets you fully customize every input to fit your trading style. 🔷 How to Use Squeeze Momentum Pro 🔍 Identifying Trends Squeeze Momentum Pro supports two different methods for identifying the trend visually, each based on a distinct logic: Squeeze Momentum Trend (LazyBear-style): Displays 3 states based on the position of the Bollinger Bands relative to the Keltner Channel: 🔵 Blue = No Squeeze (BB outside KC and KC outside BB) ⚪️ White = Squeeze Active (BB fully inside KC) ⚫️ Gray = Neutral state (none of the above) TTM Squeeze Trend (John Carter-style): Calculates the difference in width between the Bollinger Bands and the Keltner Channel: 🟩 Green = BB width is greater than KC → potential expansion phase 🟥 Red = BB are tighter than KC → possible compression or pre-breakout 📈 Interpreting Signals Depending on the active configuration, the indicator can provide various signals, including: Trend color → Reflects the current compression/expansion state (based on selected mode) Momentum value (above or below 0) → May indicate directional pressure Signal Line cross → Can highlight momentum shifts Color change in the momentum → May suggest a potential trend reversal 🛠 Integration with Other Tools Squeeze Momentum Pro works well alongside other indicators to strengthen market context: ✅ Volume Profile / OBV – Helps confirm accumulation or distribution during squeezes ✅ RSI – Useful to detect divergence between momentum and price ✅ Moving Averages – Ideal for defining primary trend direction and filtering signals ☄️ If you find this indicator useful, leave a Boost to support its development! Every piece of feedback helps improve the tool and deliver an even better trading experience. 🔥 Share your ideas or feature requests in the comments!
Penunjuk Pine Script®
oleh Cometreon
Z-Score Normalized VIX StrategyThis strategy leverages the concept of the Z-score applied to multiple VIX-based volatility indices, specifically designed to capture market reversals based on the normalization of volatility. The strategy takes advantage of VIX-related indicators to measure extreme levels of market fear or greed and adjusts its position accordingly. 1. Overview of the Z-Score Methodology The Z-score is a statistical measure that describes the position of a value relative to the mean of a distribution in terms of standard deviations. In this strategy, the Z-score is calculated for various volatility indices to assess how far their values are from their historical averages, thus normalizing volatility levels. The Z-score is calculated as follows: Z = \frac{X - \mu}{\sigma} Where: • X is the current value of the volatility index. • \mu is the mean of the index over a specified period. • \sigma is the standard deviation of the index over the same period. This measure tells us how many standard deviations the current value of the index is away from its average, indicating whether the market is experiencing unusually high or low volatility (fear or calm). 2. VIX Indices Used in the Strategy The strategy utilizes four commonly referenced volatility indices: • VIX (CBOE Volatility Index): Measures the market’s expectations of 30-day volatility based on S&P 500 options. • VIX3M (3-Month VIX): Reflects expectations of volatility over the next three months. • VIX9D (9-Day VIX): Reflects shorter-term volatility expectations. • VVIX (VIX of VIX): Measures the volatility of the VIX itself, indicating the level of uncertainty in the volatility index. These indices provide a comprehensive view of the current volatility landscape across different time horizons. 3. Strategy Logic The strategy follows a long entry condition and an exit condition based on the combined Z-score of the selected volatility indices: • Long Entry Condition: The strategy enters a long position when the combined Z-score of the selected VIX indices falls below a user-defined threshold, indicating an abnormally low level of volatility (suggesting a potential market bottom and a bullish reversal). The threshold is set as a negative value (e.g., -1), where a more negative Z-score implies greater deviation below the mean. • Exit Condition: The strategy exits the long position when the combined Z-score exceeds the threshold (i.e., when the market volatility increases above the threshold, indicating a shift in market sentiment and reduced likelihood of continued upward momentum). 4. User Inputs • Z-Score Lookback Period: The user can adjust the lookback period for calculating the Z-score (e.g., 6 periods). • Z-Score Threshold: A customizable threshold value to define when the market has reached an extreme volatility level, triggering entries and exits. The strategy also allows users to select which VIX indices to use, with checkboxes to enable or disable each index in the calculation of the combined Z-score. 5. Trade Execution Parameters • Initial Capital: The strategy assumes an initial capital of $20,000. • Pyramiding: The strategy does not allow pyramiding (multiple positions in the same direction). • Commission and Slippage: The commission is set at $0.05 per contract, and slippage is set at 1 tick. 6. Statistical Basis of the Z-Score Approach The Z-score methodology is a standard technique in statistics and finance, commonly used in risk management and for identifying outliers or unusual events. According to Dumas, Fleming, and Whaley (1998), volatility indices like the VIX serve as a useful proxy for market sentiment, particularly during periods of high uncertainty. By calculating the Z-score, we normalize volatility and quantify the degree to which the current volatility deviates from historical norms, allowing for systematic entry and exit based on these deviations. 7. Implications of the Strategy This strategy aims to exploit market conditions where volatility has deviated significantly from its historical mean. When the Z-score falls below the threshold, it suggests that the market has become excessively calm, potentially indicating an overreaction to past market events. Entering long positions under such conditions could capture market reversals as fear subsides and volatility normalizes. Conversely, when the Z-score rises above the threshold, it signals increased volatility, which could be indicative of a bearish shift in the market, prompting an exit from the position. By applying this Z-score normalized approach, the strategy seeks to achieve more consistent entry and exit points by reducing reliance on subjective interpretation of market conditions. 8. Scientific Sources • Dumas, B., Fleming, J., & Whaley, R. (1998). “Implied Volatility Functions: Empirical Tests”. The Journal of Finance, 53(6), 2059-2106. This paper discusses the use of volatility indices and their empirical behavior, providing context for volatility-based strategies. • Black, F., & Scholes, M. (1973). “The Pricing of Options and Corporate Liabilities”. Journal of Political Economy, 81(3), 637-654. The original Black-Scholes model, which forms the basis for many volatility-related strategies.
Strategi Pine Script®
oleh EdgeTools
Median RSI SD| QuantEdgeB📈 Introducing Median RSI SD by QuantEdgeB 🛠️ Overview Median RSI SD is a hybrid momentum tool that fuses two powerful techniques: Median Price Filtering and RSI-based Momentum. The result? A cleaner, more responsive oscillator designed to reduce noise and increase clarity in trend detection and potential reversals. By applying the RSI not to raw price but to the percentile-based median, the indicator adapts better to real structural shifts in the market while filtering out temporary price spikes. ✨ Key Features 🔹 Smoothed RSI Momentum Utilizes a percentile-based median as input to RSI, reducing volatility and enhancing signal reliability. 🔹 Volatility-Weighted SD Zones Automatically detects overbought/oversold extremes using ±1 standard deviation bands on the median, adapting to current market volatility. 🔹 Trend Signal Overlay A directional trend signal (Long / Short / Neutral) is derived from the RSI crossing custom thresholds, combined with position relative to SD bands. 🔹 Visual Labeling System Optional in-chart labels for Long / Short signals and fully color-customizable theme modes. 📊 How It Works 1️⃣ Median RSI Calculation Instead of using the close price directly, the script first computes a smoothed median via percentile ranking. RSI is then applied to this filtered stream, improving reactivity without overfitting to short-term noise. 2️⃣ Standard Deviation Filtering Upper and lower SD bands are calculated around the median to identify extreme conditions. A position near the upper SD while RSI is below the short threshold triggers bearish bias. The reverse applies for longs. 3️⃣ Signal Generation • ✅ Long Signal → RSI crosses above the Long Threshold (default: 65) and price holds above lower SD. • ❌ Short Signal → RSI crosses below the Short Threshold (default: 45), typically within upper SD range. 4️⃣ Contextual Highlighting Zone fills on the chart and RSI subgraph indicate Overbought (>75) and Oversold (<25) conditions for added clarity. ⚙️ Custom Settings • RSI Length → Default: 21 • Median Length → Default: 10 • Long Threshold → Default: 65 • Short Threshold → Default: 45 • Color Mode → Choose from Strategy, Solar, Warm, Cool, Classic, Magic • Signal Labels Toggle → Optional in-chart long/short labels 👥 Who Should Use It? ✅ Swing & Momentum Traders → Filter entries based on confirmed directional RSI setups. ✅ Range-Bound Traders → Use SD thresholds to spot fakeouts or exhaustion zones. ✅ Intraday Strategists → Enhanced signal clarity makes it usable even on lower timeframes. ✅ System Builders → Combine this signal with price action or confluence layers for smarter rules. 📌 Conclusion Median RSI SD by QuantEdgeB is more than just a modified oscillator—it's a robust momentum confirmation framework designed for modern volatility. By replacing noisy price feeds with a statistically stable input and layering RSI + SD logic, this tool provides high-clarity signals without sacrificing responsiveness. 🔹 Key Takeaways: 1️⃣ Median-filtered RSI eliminates noise without lag 2️⃣ Standard deviation bands identify exhaustion zones 3️⃣ Reliable for both trend continuation and mean-reversion strategies 📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets. 📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Penunjuk Pine Script®
oleh QuantEdgeB
Linear % ST | QuantEdgeB🚀 Introducing Linear Percentile SuperTrend (Linear % ST) by QuantEdgeB 🛠️ Overview Linear % SuperTrend (Linear % ST) by QuantEdgeB is a hybrid trend-following indicator that combines Linear Regression, Percentile Filters, and Volatility-Based SuperTrend Logic into one dynamic tool. This system is designed to identify trend shifts early while filtering out noise during choppy market conditions. By utilizing percentile-based median smoothing and customized ATR multipliers, this tool captures both breakout momentum and pullback opportunities with precision. ✨ Key Features 🔹 Percentile-Based Median Filtering Removes outliers and normalizes price movement for cleaner trend detection using the 50th percentile (median) of recent price action. 🔹 Linear Regression Smoothing A smoothed baseline is computed with Linear Regression to detect the underlying trend while minimizing lag. 🔹 SuperTrend Structure with Adaptive Bands The indicator implements an enhanced SuperTrend engine with custom ATR bands that adapt to trend direction. Bands tighten or loosen based on volatility and trend strength. 🔹 Dynamic Long/Short Conditions Long and short signals are derived from the relationship between price and the SuperTrend threshold zones, clearly showing trend direction with optional "Long"/"Short" labels on the chart. 🔹 Multiple Visual Themes Select from 6 built-in color palettes including Strategy, Solar, Warm, Cool, Classic, and Magic to match your personal style or strategy layout. 📊 How It Works 1️⃣ Percentile Filtering The source price (default: close) is filtered using a nearest-rank 50th percentile over a custom lookback. This normalizes data to reflect the central tendency and removes noisy extremes. 2️⃣ Linear Regression Trend Base A Linear Regression Moving Average (LSMA) is applied to the filtered median, forming the core trend line. This dynamic trendline provides a low-lag yet smooth view of market direction. 3️⃣ SuperTrend Engine ATR is applied with custom multipliers (different for long and short) to create dynamic bands. The bands react to price movement and only shift direction after confirmation, preventing false flips. 4️⃣ Trend Signal Logic • When price stays above the dynamic lower band → Bullish trend • When price breaks below the upper band → Bearish trend • Trend direction remains stable until violated by price. ⚙️ Custom Settings • Percentile Length → Lookback for percentile smoothing (default: 35) • LSMA Length → Determines the base trend via linear regression (default: 24) • ATR Length → ATR period used in dynamic bands (default: 14) • Long Multiplier → ATR multiplier for bullish thresholds (default: 0.8) • Short Multiplier → ATR multiplier for bearish thresholds (default: 1.9) ✅ How to Use 1️⃣ Trend-Following Strategy ✔️ Go Long when price breaks above the lower ATR band, initiating an upward trend ✔️ Go Short when price falls below the upper ATR band, confirming bearish conditions ✔️ Remain in trend direction until the SuperTrend flips 2️⃣ Visual Confirmation ✔️ Use bar coloring and the dynamic bands to stay aligned with trend direction ✔️ Optional Long/Short labels highlight key signal flips 👥 Who Should Use Linear % ST? ✅ Swing & Position Traders → To ride trends confidently ✅ Trend Followers → As a primary directional filter ✅ Breakout Traders → For clean signal generation post-range break ✅ Quant/Systematic Traders → Integrate clean trend logic into algorithmic setups 📌 Conclusion Linear % ST by QuantEdgeB blends percentile smoothing with linear regression and volatility bands to deliver a powerful, adaptive trend-following engine. Whether you're a discretionary trader seeking cleaner entries or a systems-based trader building logic for automation, Linear % ST offers clarity, adaptability, and precision in trend detection. 🔹 Key Takeaways: 1️⃣ Percentile + Regression = Noise-Reduced Core Trend 2️⃣ ATR-Based SuperTrend = Reliable Breakout Confirmation 3️⃣ Flexible Parameters + Color Modes = Custom Fit for Any Strategy 📈 Use it to spot emerging trends, filter false signals, and stay confidently aligned with market momentum. 📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets. 📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Penunjuk Pine Script®
oleh QuantEdgeB
Quantile DEMA Trend | QuantEdgeB🚀 Introducing Quantile DEMA Trend (QDT) by QuantEdgeB 🛠️ Overview Quantile DEMA Trend (QDT) is an advanced trend-following and momentum detection indicator designed to capture price trends with superior accuracy. Combining DEMA (Double Exponential Moving Average) with SuperTrend and Quantile Filtering, QDT identifies strong trends while maintaining the ability to adapt to various market conditions. Unlike traditional trend indicators, QDT uses percentile filtering to adjust for volatility and provides dynamic thresholds, ensuring consistent signal performance across different assets and timeframes. ✨ Key Features 🔹 Trend Following with Adaptive Sensitivity The DEMA component ensures quicker responses to price changes while reducing lag, offering a real-time reflection of market momentum. 🔹 Volatility-Adjusted Filtering The SuperTrend logic incorporates quantile percentile filters and ATR (Average True Range) multipliers, allowing QDT to adapt to fluctuating market volatility. 🔹 Clear Signal Generation QDT generates clear Long and Short signals using percentile thresholds, effectively identifying trend changes and market reversals. 🔹 Customizable Visual & Signal Settings With multiple color modes and customizable settings, you can easily align the QDT indicator with your trading strategy, whether you're focused on trend-following or volatility adjustments. 📊 How It Works 1️⃣ DEMA Calculation DEMA is used to reduce lag compared to traditional moving averages. It is calculated by applying a Double Exponential Moving Average to price data. This smoother trend-following mechanism ensures responsiveness to market movements without introducing excessive noise. 2️⃣ SuperTrend with Percentile Filtering The SuperTrend component adapts the trend-following signal by incorporating quantile percentile filters. It identifies dynamic support and resistance levels based on historical price data: • Upper Band: Calculated using the 75th percentile + ATR (adjusted with multiplier) • Lower Band: Calculated using the 25th percentile - ATR (adjusted with multiplier) These dynamic bands adjust to market conditions, filtering out noise while identifying the true direction. 3️⃣ Signal Generation • Long Signal: Triggered when price crosses below the SuperTrend Lower Band • Short Signal: Triggered when price crosses above the SuperTrend Upper Band The indicator provides signals with corresponding trend direction based on these crossovers. 👁 Visual & Custom Features • 🎨 Multiple Color Modes: Choose from "Strategy", "Solar", "Warm", "Cool", "Classic", and "Magic" color palettes to match your charting style. • 🏷️ Long/Short Signal Labels: Optional labels for visual cueing when a long or short trend is triggered. • 📉 Bar Color Customization: Bar colors dynamically adjust based on trend direction to visually distinguish the market bias. 👥 Who Should Use QDT? ✅ Trend Followers: Use QDT as a dynamic tool to confirm trends and capture profits in trending markets. ✅ Swing Traders: Use QDT to time entries based on confirmed breakouts or breakdowns. ✅ Volatility Traders: Identify market exhaustion or expansion points, especially during volatile periods. ✅ Systematic & Quant Traders: Integrate QDT into algorithmic strategies to enhance market detection with adaptive filtering. ⚙️ Customization & Default Settings - DEMA Length(30): Controls the lookback period for DEMA calculation - Percentile Length(10): Sets the lookback period for percentile filtering - ATR Length(14): Defines the length for calculating ATR (used in SuperTrend) - ATR Multiplier(1.2 ): Multiplier for ATR in SuperTrend calculation - SuperTrend Length(30):Defines the length for SuperTrend calculations 📌 How to Use QDT in Trading 1️⃣ Trend-Following Strategy ✔ Enter Long positions when QDT signals a bullish breakout (price crosses below the SuperTrend lower band). ✔ Enter Short positions when QDT signals a bearish breakdown (price crosses above the SuperTrend upper band). ✔ Hold positions as long as QDT continues to provide the same direction. 2️⃣ Reversal Strategy ✔ Take profits when price reaches extreme levels (upper or lower percentile zones) that may indicate trend exhaustion or reversion. 3️⃣ Volatility-Driven Entries ✔ Use the percentile filtering to enter positions based on mean-reversion logic or breakout setups in volatile markets. 🧠 Why It Works QDT combines the DEMA’s quick response to price changes with SuperTrend's volatility-adjusted thresholds, ensuring a responsive and adaptive indicator. The use of percentile filters and ATR multipliers helps adjust to varying market conditions, making QDT suitable for both trending and range-bound environments. 🔹 Conclusion The Quantile DEMA Trend (QDT) by QuantEdgeB is a powerful, adaptive trend-following and momentum detection system. By integrating DEMA, SuperTrend, and quantile percentile filtering, it provides accurate and timely signals while adjusting to market volatility. Whether you are a trend follower or volatility trader, QDT offers a robust solution to identify high-probability entry and exit points. 🔹 Key Takeaways: 1️⃣ Trend Confirmation – Uses DEMA and SuperTrend for dynamic trend detection 2️⃣ Volatility Filtering – Adjusts to varying market conditions using percentile logic 3️⃣ Clear Signal Generation – Easy-to-read signals and visual cues for strategy implementation 📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets. 📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Penunjuk Pine Script®
oleh QuantEdgeB
Z-Score Normalized Volatility IndicesVolatility is one of the most important measures in financial markets, reflecting the extent of variation in asset prices over time. It is commonly viewed as a risk indicator, with higher volatility signifying greater uncertainty and potential for price swings, which can affect investment decisions. Understanding volatility and its dynamics is crucial for risk management and forecasting in both traditional and alternative asset classes. Z-Score Normalization in Volatility Analysis The Z-score is a statistical tool that quantifies how many standard deviations a given data point is from the mean of the dataset. It is calculated as: Z = \frac{X - \mu}{\sigma} Where X is the value of the data point, \mu is the mean of the dataset, and \sigma is the standard deviation of the dataset. In the context of volatility indices, the Z-score allows for the normalization of these values, enabling their comparison regardless of the original scale. This is particularly useful when analyzing volatility across multiple assets or asset classes. This script utilizes the Z-score to normalize various volatility indices: 1. VIX (CBOE Volatility Index): A widely used indicator that measures the implied volatility of S&P 500 options. It is considered a barometer of market fear and uncertainty (Whaley, 2000). 2. VIX3M: Represents the 3-month implied volatility of the S&P 500 options, providing insight into medium-term volatility expectations. 3. VIX9D: The implied volatility for a 9-day S&P 500 options contract, which reflects short-term volatility expectations. 4. VVIX: The volatility of the VIX itself, which measures the uncertainty in the expectations of future volatility. 5. VXN: The Nasdaq-100 volatility index, representing implied volatility in the Nasdaq-100 options. 6. RVX: The Russell 2000 volatility index, tracking the implied volatility of options on the Russell 2000 Index. 7. VXD: Volatility for the Dow Jones Industrial Average. 8. MOVE: The implied volatility index for U.S. Treasury bonds, offering insight into expectations for interest rate volatility. 9. BVIX: Volatility of Bitcoin options, a useful indicator for understanding the risk in the cryptocurrency market. 10. GVZ: Volatility index for gold futures, reflecting the risk perception of gold prices. 11. OVX: Measures implied volatility for crude oil futures. Volatility Clustering and Z-Score The concept of volatility clustering—where high volatility tends to be followed by more high volatility—is well documented in financial literature. This phenomenon is fundamental in volatility modeling and highlights the persistence of periods of heightened market uncertainty (Bollerslev, 1986). Moreover, studies by Andersen et al. (2012) explore how implied volatility indices, like the VIX, serve as predictors for future realized volatility, underlining the relationship between expected volatility and actual market behavior. The Z-score normalization process helps in making volatility data comparable across different asset classes, enabling more effective decision-making in volatility-based strategies. Applications in Trading and Risk Management By using Z-score normalization, traders can more easily assess deviations from the mean in volatility, helping to identify periods when volatility is unusually high or low. This can be used to adjust risk exposure or to implement volatility-based trading strategies, such as mean reversion strategies. Research suggests that volatility mean-reversion is a reliable pattern that can be exploited for profit (Christensen & Prabhala, 1998). References: • Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2012). Realized volatility and correlation dynamics: A long-run approach. Journal of Financial Economics, 104(3), 385-406. • Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327. • Christensen, B. J., & Prabhala, N. R. (1998). The relation between implied and realized volatility. Journal of Financial Economics, 50(2), 125-150. • Whaley, R. E. (2000). Derivatives on market volatility and the VIX index. Journal of Derivatives, 8(1), 71-84.
Penunjuk Pine Script®
oleh EdgeTools
Reversal Trading Bot Strategy[BullByte]Overview : The indicator Reversal Trading Bot Strategy is crafted to capture potential market reversal points by combining momentum, volatility, and trend alignment filters. It uses a blend of technical indicators to identify both bullish and bearish reversal setups, ensuring that multiple market conditions are met before entering a trade. Core Components : Technical Indicators Used : RSI (Relative Strength Index) : Purpose : Detects divergence conditions by comparing recent lows/highs in price with the RSI. Parameter : Length of 8. Bollinger Bands (BB) : Purpose : Measures volatility and identifies price levels that are statistically extreme. Parameter : Length of 20 and a 2-standard deviation multiplier. ADX (Average Directional Index) & DMI (Directional Movement Index) : Purpose : Quantifies the strength of the trend. The ADX threshold is set at 20, and additional filters check for the alignment of the directional indicators (DI+ and DI–). ATR (Average True Range) : Purpose : Provides a volatility measure used to set stop levels and determine risk through trailing stops. Volume SMA (Simple Moving Average of Volume ): Purpose : Helps confirm strength by comparing the current volume against a 20-period average, with an optional filter to ensure volume is at least twice the SMA. User-Defined Toggle Filters : Volume Filter : Confirms that the volume is above average (or twice the SMA) before taking trades. ADX Trend Alignment Filter : Checks that the ADX’s directional indicators support the trade direction. BB Close Confirmation : Optionally refines the entry by requiring price to be beyond the upper or lower Bollinger Band rather than just above or below. RSI Divergence Exit : Allows the script to close positions if RSI divergence is detected. BB Mean Reversion Exit : Closes positions if the price reverts to the Bollinger Bands’ middle line. Risk/Reward Filter : Ensures that the potential reward is at least twice the risk by comparing the distance to the Bollinger Band with the ATR. Candle Movement Filter : Optional filter to require a minimum percentage move in the candle to confirm momentum. ADX Trend Exit : Closes positions if the ADX falls below the threshold and the directional indicators reverse. Entry Conditions : Bullish Entry : RSI Divergence : Checks if the current close is lower than a previous low while the RSI is above the previous low, suggesting bullish divergence. Bollinger Confirmation : Requires that the price is above the lower (or upper if confirmation is toggled) Bollinger Band. Volume & Trend Filters : Combines volume condition, ADX strength, and an optional candle momentum condition. Risk/Reward Check : Validates that the trade meets a favorable risk-to-reward ratio. Bearish Entry : Uses a mirror logic of the bullish entry by checking for bearish divergence, ensuring the price is below the appropriate Bollinger level, and confirming volume, trend strength, candle pattern, and risk/reward criteria. Trade Execution and Exit Strateg y: Trade Execution : Upon meeting the entry conditions, the strategy initiates a long or short position. Stop Loss & Trailing Stops : A stop-loss is dynamically set using the ATR value, and trailing stops are implemented as a percentage of the close price. Exit Conditions : Additional exit filters can trigger early closures based on RSI divergence, mean reversion (via the middle Bollinger Band), or a weakening trend as signaled by ADX falling below its threshold. This multi-layered exit strategy is designed to lock in gains or minimize losses if the market begins to reverse unexpectedly. How the Strategy Works in Different Market Conditions : Trending Markets : The ADX filter ensures that trades are only taken when the trend is strong. When the market is trending, the directional movement indicators help confirm the momentum, making the reversal signal more reliable. Ranging Markets : In choppy markets, the Bollinger Bands expand and contract, while the RSI divergence can highlight potential turning points. The optional filters can be adjusted to avoid false signals in low-volume or low-volatility conditions. Volatility Management : With ATR-based stop-losses and a risk/reward filter, the strategy adapts to current market volatility, ensuring that risk is managed consistently. Recommendation on using this Strategy with a Trading Bot : This strategy is well-suited for high-frequency trading (HFT) due to its ability to quickly identify reversal setups and execute trades dynamically with automated stop-loss and trailing exits. By integrating this script with a TradingView webhook-based bot or an API-driven execution system, traders can automate trade entries and exits in real-time, reducing manual execution delays and capitalizing on fast market movements. Disclaimer : This script is provided for educational and informational purposes only. It is not intended as investment advice. Trading involves significant risk, and you should always conduct your own research and analysis before making any trading decisions. The author is not responsible for any losses incurred while using this script.
Strategi Pine Script®
oleh BullByte
2
Range Filter with MACD, RSI & Volume📌 Enhanced Range Filter with Multi-Indicator Confirmation This Pine Script indicator improves trend-following and trade signal accuracy by combining a Range Filter with MACD, RSI, Volume, and ATR confirmations. It is designed to help traders identify strong trends and breakout opportunities while filtering out noise. 📈 How It Works 1️⃣ Trend Detection (Range Filter) • The Range Filter smooths price action and identifies trends by filtering out minor fluctuations. • The indicator creates dynamic support and resistance bands: • High Target Band (Resistance) • Low Target Band (Support) • Color Coding: • White = Uptrend 📈 • Blue = Downtrend 📉 • Light Blue = Neutral ⚖️ 2️⃣ Multi-Indicator Trade Confirmation To avoid false signals, the script only generates Buy/Sell signals when multiple indicators agree: ✅ MACD: Checks if MACD Line is above or below the Signal Line for momentum confirmation. ✅ RSI: Ensures RSI is above 50 for long trades and below 50 for short trades. ✅ Volume: Requires a volume spike above the 20-period moving average for stronger signals. ✅ ATR (Volatility Check): Ensures ATR is higher than its 50-period SMA, signaling strong market movement. 💡 Only when all conditions align, a Buy or Sell signal is generated! 📊 How to Use It 1. Trend Analysis: • When price is above the Range Filter (white line) → Uptrend • When price is below the Range Filter (blue line) → Downtrend 2. Trade Signals: • Buy Signal 🟢 appears when: • Price breaks above the Range Filter • MACD is bullish • RSI > 50 • High volume and strong volatility • Sell Signal 🔴 appears when: • Price breaks below the Range Filter • MACD is bearish • RSI < 50 • High volume and strong volatility 3. Alerts 🔔: • The script includes built-in alerts to notify traders when a Buy or Sell signal is triggered. 🎯 Best for Traders Who: ✔️ Want to identify strong trends early ✔️ Need extra confirmation to avoid false signals ✔️ Trade breakouts with high volume & momentum ✔️ Prefer visual trend coloring to track market direction 🚀 Try it out and refine your entries with multi-indicator validation!
Penunjuk Pine Script®
oleh hipplan
Chonky ATR Levels 2.0Show ATR based high/low projections. Choose a custom ATR calculation in the indicator's settings. The default is a 20day RMA based ATR. ----------How projections are calculated---------- To project the ATR High, the ATR value is added to the low of the current candle that matches the ATR's timeframe. To project the ATR Low, the ATR value is subtracted from the high of the current candle that matches the ATR's timeframe. Example: If a 20day RMA ATR is used: - the ATR High will be the current day's low + the ATR value. - the ATR Low will be the current day's high - the ATR value. *However*, if the price action exceeds either ATR projection, the opposite ATR level will be fixed to the extreme of the period. See the AUDUSD screenshot above for an example. The ATR Low was exceeded, so the ATR High projection is capped at the high of day. If the ATR High is exceeded, the ATR Low would be capped at the low of day.
Penunjuk Pine Script®
oleh Chonky_
Rachas ATR AssistHey Traders! This indicator is a simple, it uses Average True Range (ATR) data from the daily chart and the current timeframe to estimate potential range and volatility. This indicator compares the daily ATR to the current daily wick range (from low to high), helping you gauge how much "room" might be left for price movement within the day. Alongside that, it shows the ATR over the last 14 candles and 5 candles on your current chart for intraday volatility awareness—ideal for setting stops, targets, or position sizing. Gauge Daily Potential Movement: The "Day Range Difference" cell shows how much of the expected daily range (based on ATR) is still unfilled. If the market has moved less than the average, there's still potential for expansion. If it's close to or above the ATR, expect a slowdown or reversal. Position Sizing & Stop Losses: Use the 14-period ATR and 5-period ATR on your current timeframe to understand recent volatility. This helps in choosing logical stop loss levels and adjusting position sizes based on market conditions. Volatility Awareness: Knowing the average daily range and how much of it has been used lets you avoid entering trades too late in the move or placing stops in overly tight spots. Table Position & Font: You can adjust the table location (top/bottom left/right) and font size to best fit your chart layout.
Penunjuk Pine Script®
oleh Racha23
ATR Momentum HistogramATR Momentum Histogram is a simple yet powerful tool that combines price action, ATR volatility, and trend filters to visualize market momentum. 🔍 Key Features: ATR Histogram Bars: Plots the Average True Range (ATR) as a histogram to highlight volatility expansion or contraction. Momentum Filter: Compares current price and ATR with values from N bars ago to determine bullish or bearish momentum. EMA Trend Filter: A 9-period EMA helps identify the prevailing trend and filters signals accordingly. Color-Coded Bars: 🟢 Green: Strong bullish momentum (price and ATR rising above EMA) 🔴 Red: Strong bearish momentum (price and ATR falling below EMA) 🟢/🔴 Faded Bars: Weaker trend continuation with less conviction 📈 How to Use: Use this indicator to confirm trend strength, identify high-momentum breakout conditions, or avoid low-volatility chop zones. Works well as a secondary confirmation tool in trend-following or breakout strategies.
Penunjuk Pine Script®
oleh Spacefunk01
ADR DSRI 6ADR tool, this is a 5 day ADR that plots on the chart. Code is adapted from ADR tool by as well as user JorgeSilvestrini's ADR tool. Code is OPEN SOURCE, and thus, presented AS IS. If you would like to change it, you are welcome to do so - yourself. Thank you. I will update this indicator as i can, as it is a workhorse of my own trading toolkit. The next update will include alerts. Plots todays ADR as total pips above high 100% line Plots the pips achieved so far below low 100% line. Plots table that shows what todays ADR is as a % basis. Statistically, you don't want to get into trades when the ADR is above 80% as its less likely to follow through. Therefore, anything above 80% achieved for the day will change the table colour to RED as a visual warning. Plots additional table called "DSRI". This counter counts the days since we last hit 100% of the 5 day ADR. As this counter moves up, and the days since hitting 100% of the range, it tells you the market is consolidating and to expect an expansion. DSRI stands for "Days since raptor incident" aka 100% range hit, and the correct phrasing to check on a markets health with a friend would be to say "How many raptors are we at?". And if they reply anything above a 3, you know range expansion (aka a raptor attack) is imminent, and you should be on alert, and interested.
Penunjuk Pine Script®
oleh BryceWH
Smart Dynamic Levels [ATR-Based]Smart Dynamic Levels Automated Support & Resistance Levels Based on Market Volatility Overview: This advanced indicator automatically plots dynamic support and resistance levels based on the Average True Range (ATR), creating meaningful price zones that adapt to changing market conditions. Unlike static round-number levels, these volatility-adjusted zones provide more relevant technical reference points. Key Features: Volatility-Responsive: Levels automatically adjust based on the asset's ATR Smart Visualization: Color gradient shows strength of each level (darker = stronger) Bullish (green) levels below price, bearish (red) levels above Customizable Settings: Adjust ATR length (14-period default) Modify level sensitivity with ATR multiplier (1.5x default) Choose number of levels to display (5 above/below default) Toggle labels and line extensions How It Works: Calculates the asset's true volatility using ATR Rounds to significant price intervals based on current volatility Plots equidistant levels above and below current price Colors levels based on their position relative to price Automatically updates as market conditions change Recommended Use: Day Trading: Identify intraday support/resistance zones Swing Trading: Spot potential reversal areas Breakout Trading: Watch for moves beyond key levels Works on all markets: Stocks, Forex, Crypto, Futures Settings Guide: ATR Length: Higher values for smoother levels (14-20) Multiplier: Increase for wider levels (1.5-3x) Levels Count: More levels for higher timeframes (3-10) Pro Tips: Combine with trend analysis - levels are more significant when aligned with trend Watch for price reactions at these levels for confirmation Use wider levels (higher multiplier) for volatile assets
Penunjuk Pine Script®
oleh PIXEL_BLADE
5
Rolling ATR Momentum Rolling ATR Momentum Indicator – User Manual --- 🔍 Overview The Rolling ATR Momentum Indicator is a simple yet powerful tool designed to detect shifts in market volatility. It compares the current Average True Range (ATR) with the ATR from a previous point in time to measure how market volatility is changing. This indicator is especially useful for: - Spotting the beginning or fading of a momentum phase - Filtering out low-volatility market conditions - Enhancing timing for entries and exits in trending or breakout trades --- 📊 Key Components ✅ ATR Delta (Rolling) - Definition: `ATR Delta = Current ATR - Past ATR` - Inputs: - ATR Period (default: 14): The base ATR calculation window - Lookback Period (default: 5): How many bars ago to compare ATR - Interpretation: - Positive ATR Delta (Green Line): Market volatility is increasing - Negative ATR Delta (Red Line): Market volatility is decreasing 📈 Zero Line - A horizontal baseline at zero helps you easily see when ATR momentum shifts from negative to positive (or vice versa). 🟩/🟥 Background Color - Green Background: ATR Delta is positive (rising volatility) - Red Background: ATR Delta is negative (falling volatility) 🔵 Optional: ATR Reference Lines - You can optionally display raw Current ATR and Past ATR by changing their visibility settings. --- ✅ How to Use It Entry Timing (Futures/Options) - Use ATR Delta as a filter: - Only take trades when ATR Delta is positive → confirms momentum is building - Avoid trades when ATR Delta is negative → market might be slow, sideways, or losing steam Breakout Anticipation - A rising ATR Delta after a tight range or consolidation can suggest that a breakout is underway Stop-loss Strategy - Use high ATR periods for wider stops (to avoid noise) - Use low ATR periods for tighter stops or skip trading --- 🧠 Pro Tips - This indicator doesn’t predict direction—combine with trend or price structure tools (like EMA, PPMA, candlesticks) - Works best in trending or breakout environments - Add it to multi-timeframe layouts to see volatility buildup on higher timeframes --- ⚙️ Settings | Parameter | Description | |----------|-------------| | ATR Period | Length of the ATR calculation (default 14) | | Lookback Period | How many bars back to compare ATR values | --- 🧭 Best For: - Index futures (Nifty, BankNifty) - Option buyers needing volatility confirmation - Intraday & swing traders looking to trade momentum setups --- Use the Rolling ATR Momentum indicator as your volatility radar—simple, clean, and highly effective for staying on the right side of market energy. End of Manual
Penunjuk Pine Script®
oleh abgaur01
Rolling ATR Momentum - EnhancedATR Rolling Momentum Indicator – User Manual --- 🔍 Overview The ATR Rolling Momentum Indicator is a dynamic volatility tool built on the Average True Range (ATR). It not only tracks increasing or decreasing momentum but also provides early warnings and confirmation signals for potential breakout moves. It’s especially powerful for futures and options traders looking to align with expanding price action. --- 📊 Core Components ✅ ATR Delta (Rolling ATR) - Definition: Difference between current ATR and past ATR (user-defined lookback). - Use: Tells whether volatility is expanding (positive delta) or contracting (negative delta). - Visual: Green line for rising momentum, red for declining. 🟣 ATR Delta Slope - Definition: Measures acceleration in momentum. - Use: Helps identify early signs of breakout buildup. - Visual: Purple line. Watch for slope turning up from below. 🟡 Volatility Squeeze (Yellow Dot) - Definition: Current ATR is significantly lower than its 20-period average. - Use: Indicates the market is coiling—possible breakout ahead. 🔼 Momentum Start (Green Triangle) - Definition: ATR Delta slope turns from negative to positive. - Use: Early warning to prepare for volatility expansion. 🔷 Breakout Confirmation (Blue Label Up) - Definition: ATR Delta exceeds its high of the last 10 candles. - Use: Confirms volatility breakout—trade opportunity if direction aligns. 🟩/🟥 Background Color - Green Background: Momentum rising (positive ATR delta) - Red Background: Momentum falling (negative ATR delta) - Yellow Tint: Active squeeze zone --- ✅ How to Use It (Futures/Options Focus) Step-by-Step: 1. Squeeze Detected (Yellow Dot) → Stay alert. Market is coiling. 2. Green Triangle Appears → Momentum is starting to rise. 3. Background Turns Green → Confirmed rising momentum. 4. Blue Label Appears → Confirmed breakout (enter trade if trend aligns). Directional Bias: - Use your main chart setup (price action, EMAs, trendlines, etc.) to decide direction (Call or Put, Long or Short). - ATR Momentum only tells you how strong the move is—not which way. --- ⚙️ Inputs & Settings - ATR Period: Default 14 (core volatility measure) - Rolling Lookback: Used to calculate delta (default 5) - Slope Length: Used to measure acceleration (default 3) - Squeeze Factor: Default 0.8 — lower = more sensitive squeeze detection - Breakout Lookback: Checks ATR delta against last X bars (default 10) --- 🧠 Pro Tips - Works great when paired with EMA stacks, price structure, or breakout patterns. - Avoid taking trades based only on squeeze or momentum—combine with chart confirmation. - If background turns red after a breakout, it may be losing momentum—book partials or tighten stops. --- 🧭 Ideal For: - Nifty/BankNifty Futures - Option directional trades (call/put buying) - Index scalping and momentum swing setups --- Use this tool as your volatility compass—it won't tell you where to go, but it'll tell you when the wind is strong enough to move fast. End of Manual
Penunjuk Pine Script®
oleh abgaur01
Smart Mean Reversion DashboardThis indicator is designed to help traders identify potential mean reversion opportunities using a combination of Bollinger Bands, RSI, and deviation from the moving average. It provides a clean, visually appealing dashboard that displays key metrics and signals in real-time. How to Read and Use: Deviation from Mean: Displays the percentage deviation of the current price from the moving average. A high positive or negative deviation may indicate overextension and a potential mean reversion opportunity. Bollinger Band Status: Indicates whether the price is inside or outside the Bollinger Bands. "Outside Upper" suggests overbought conditions, while "Outside Lower" suggests oversold conditions. RSI Status: Shows whether the RSI is in overbought (>70), oversold (<30), or neutral conditions. Overbought and oversold levels can confirm potential reversal zones. Signal: BUY: Triggered when the price is outside the lower Bollinger Band and RSI is in the oversold zone. SELL: Triggered when the price is outside the upper Bollinger Band and RSI is in the overbought zone. WAIT: No clear signal; wait for better conditions. Important Notes: This is NOT a buy or sell recommendation. This indicator is a tool to assist in identifying potential trading opportunities. Always use it in conjunction with your own analysis and risk management. The signals generated by this indicator are based on historical data and do not guarantee future performance. It is recommended to use this indicator alongside other technical analysis tools and confirm signals with price action or other strategies. Features: Dashboard: Displays deviation, Bollinger Band status, RSI status, and signals in a clean, movable interface. Customizable Settings: Adjust Bollinger Band length, RSI length, and moving average length to suit your trading style. Visual Enhancements: Color-coded signals and metrics for easy interpretation in both light and dark modes. Disclaimer: Trading involves significant risk, and past performance is not indicative of future results. This indicator is for educational purposes only and should not be considered financial advice. Always consult with a financial advisor before making trading decisions.
Penunjuk Pine Script®
oleh darshakssc
CME Price LimitCalculates the CME Price Limit The reference price is obtained from the previous day's closing settlement price (data pulled from the asset's daily chart with settlement enabled) Percentage limit can be modified in settings Buffer can be enabled (for example, 2% buffer on a 7% limit, so a line gets drawn at 5% too) Alert can be enabled for price crossing a certain percentage from reference on the day You can choose to plot the historical lines on every day, or the current day only The reference price output can be found in the data window, or in the indicator status line if enabled in the settings. Before placing real trades with this, you should compare the indicator's reference price to what's shown on CME's website, to double check that TradingView's data matches for your contract. www.cmegroup.com
Penunjuk Pine Script®
oleh Sews
Smart Grid Scalping (Pullback) Strategy[BullByte]The Smart Grid Scalping (Pullback) Strategy is a high-frequency trading strategy designed for short-term traders who seek to capitalize on market pullbacks. This strategy utilizes a dynamic ATR-based grid system to define optimal entry points, ensuring precise trade execution. It integrates volatility filtering and an RSI-based confirmation mechanism to enhance signal accuracy and reduce false entries. This strategy is specifically optimized for scalping by dynamically adjusting trade levels based on current market conditions. The grid-based system helps capture retracement opportunities while maintaining strict trade management through predefined profit targets and trailing stop-loss mechanisms. Key Features : 1. ATR-Based Grid System : - Uses a 10-period ATR to dynamically calculate grid levels for entry points. - Prevents chasing trades by ensuring price has reached key levels before executing entries. 2. No Trade Zone Protection : - Avoids low-volatility zones where price action is indecisive. - Ensures only high-momentum trades are executed to improve success rate. 3. RSI-Based Entry Confirmation : - Long trades are triggered when RSI is below 30 (oversold) and price is in the lower grid zone. - Short trades are triggered when RSI is above 70 (overbought) and price is in the upper grid zone. 4. Automated Trade Execution : - Long Entry: Triggered when price drops below the first grid level with sufficient volatility. - Short Entry: Triggered when price exceeds the highest grid level with sufficient volatility. 5. Take Profit & Trailing Stop : - Profit target set at a customizable percentage (default 0.2%). - Adaptive trailing stop mechanism using ATR to lock in profits while minimizing premature exits. 6. Visual Trade Annotations : - Clearly labeled "LONG" and "SHORT" markers appear at trade entries for better visualization. - Grid levels are plotted dynamically to aid decision-making. Strategy Logic : - The script first calculates the ATR-based grid levels and ensures price action has sufficient volatility before allowing trades. - An additional RSI filter is used to ensure trades are taken at ideal market conditions. - Once a trade is executed, the script implements a trailing stop and predefined take profit to maximize gains while reducing risks. --- Disclaimer : Risk Warning : This strategy is provided for educational and informational purposes only. Trading involves significant risk, and past performance is not indicative of future results. Users are advised to conduct their own due diligence and risk management before using this strategy in live trading. The developer and publisher of this script are not responsible for any financial losses incurred by the use of this strategy. Market conditions, slippage, and execution quality can affect real-world trading outcomes. Use this script at your own discretion and always trade responsibly.
Strategi Pine Script®
oleh BullByte