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Ultimate MA & PSAR [TARUN]Overview This indicator combines a customizable Moving Average (MA) and Parabolic SAR (PSAR) to generate precise long and short trade signals. A dashboard displays real-time trade conditions, including signal direction, entry price, stop loss, and PnL tracking. Key Features ✅ Customizable MA Type & Period – Choose between SMA or EMA with adjustable length. ✅ Adaptive PSAR Settings – Modify start, increment, and max step values to fine-tune stop levels. ✅ Trade Signal Logic – Identifies potential buy (long) and sell (short) opportunities based on: Price action relative to MA MA trend direction (rising or falling) PSAR confirmation ✅ Dynamic Stop Loss Calculation – Uses lowest low/highest high over a specified period for stop loss placement. ✅ Trade State & Reversal Handling – Manages active trades, pending signals, and stop loss exits dynamically. ✅ PnL & Dashboard Table – Displays real-time signal status, entry price, stop loss, and profit/loss (PnL) in an easy-to-read format. How It Works 1.Buy (Long) Condition: MA is rising Price is above the MA PSAR is below price 2.Sell (Short) Condition: MA is falling Price is below the MA PSAR is above price 3.Stop Loss Handling: For long trades → stop loss is set at the lowest low of the last X candles For short trades → stop loss is set at the highest high of the last X candles 4.Trade Execution & PnL Calculation: If a valid long/short setup is detected, a pending signal is placed. On the next bullish (for long) or bearish (for short) candle, the trade is confirmed. Real-time PnL updates help track trade performance. Customization Options 🔹 Moving Average: SMA or EMA, adjustable period 🔹 PSAR Settings: Start, Increment, Maximum step values 🔹 Stop Loss Lookback: Choose how many candles to consider for stop loss placement 🔹 Dashboard Positioning: Select preferred display location (top/bottom, left/right) 🔹 Trade Signal Selection: Enable/Disable Long and Short signals individually How to Use Add the indicator to your chart. Customize the MA & PSAR settings according to your trading strategy. Follow the dashboard signals for trade setups. Use stop loss levels to manage risk effectively. Disclaimer ⚠️ This indicator is for educational purposes only and does not constitute financial advice. Always perform proper risk management and backtesting before using it in live trading.
Pine Script® 인디케이터
tarun171977의
ATR Amplitude RatioATR Amplitude Ratio The ATR Amplitude Ratio indicator measures price volatility by comparing the current candle's amplitude (high-low range) to the Average True Range (ATR). This helps traders identify when price movement exceeds typical volatility thresholds, potentially signaling unusual market activity. Key Features: Displays the ratio between current candle height and ATR as color-coded histogram bars Customizable ATR calculation with multiple smoothing methods (SMA, EMA, RMA, WMA) Visual reference lines at 1x, 2x, 3x, 4x, and 5x ATR levels Dynamic color coding based on volatility intensity (5 customizable threshold colors) Real-time display of current ratio and ATR values How to Use: Volatility Assessment: Quickly identify if price action is within normal volatility ranges or exhibiting unusual movement Breakout Confirmation: Higher ratios can confirm genuine breakouts versus false moves Entry/Exit Timing: Consider entries when volatility returns to normal ranges after spikes Risk Management: Adjust position sizing based on current volatility ratios Settings: ATR Length: Determines the lookback period for ATR calculation (default: 14) ATR Smoothing Type: Choose from SMA, EMA, RMA, or WMA methods Color Thresholds: Customize colors for different volatility ranges This indicator helps traders make more informed decisions by providing context about current price action relative to recent historical volatility.
Pine Script® 인디케이터
Delsongs의
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.
Pine Script® 인디케이터
QuantEdgeB의
Scalping 15min: EMA + MACD + RSI + ATR-based SL/TP📈 Strategy: 15-Minute Scalping — EMA + MACD + RSI + ATR-based SL/TP This scalping strategy is designed for 15-minute charts and combines trend-following and momentum confirmation with dynamic stop loss and take profit levels based on volatility. 🔧 Indicators Used: EMA 50 — identifies the main trend MACD Histogram — confirms momentum direction RSI (14) — filters overbought/oversold conditions ATR (14) — dynamically sets SL and TP based on market volatility 📊 Entry Conditions: Long Entry: Price is above EMA 50 MACD histogram is positive RSI is above 50 but below 70 Short Entry: Price is below EMA 50 MACD histogram is negative RSI is below 50 but above 30 🛑 Risk Management: Stop Loss: 1×ATR (user-configurable) Take Profit: 2×ATR (user-configurable) These values can be adjusted in the script inputs depending on your risk/reward preference or market conditions. ⚠️ Notes: Strategy is optimized for scalping fast-moving pairs (e.g. crypto, forex). Works best in trending markets. Use backtesting and forward testing before live trading.
Pine Script™ 전략
ionut081의
Relative Momentum Deviation | QuantEdgeB📊 Introducing Relative Momentum Deviation (RMD) by QuantEdgeB 🛠️ Overview Relative Momentum Deviation (RMD) is a precision-crafted momentum-based oscillator that measures relative price deviation through a normalized RSI structure and volatility-weighted SD bands. Unlike standard oscillators, RMD dynamically adapts its thresholds using rolling standard deviation on a DEMA-based foundation, making it uniquely responsive in both trending and ranging environments. Designed to filter out noise and detect critical breakout zones, RMD is a powerful addition to any quantitative trader’s toolkit. Whether used as a standalone entry/exit signal or confirmation layer, RMD excels at identifying momentum inflection points with statistical confidence. ✨ Key Features 🔹 Normalized RSI-Based Core RMD calculates momentum using a custom RSI of a DEMA-filtered source, delivering a smooth and responsive signal. 🔹 Volatility-Adaptive SD Thresholds Dynamic upper and lower thresholds adjust in real-time using standard deviation, reducing false positives during low-volatility phases. 🔹 Dual Confirmation Signal Logic RMD compares both deviation bands to user-defined thresholds to issue high-confidence trend entries. 🔹 Backtesting Integration & Visual Equity Curve With built-in support for the QuantEdgeB Backtesting Framework, RMD allows seamless strategy validation. 🔹 Clean Visuals & Label Customization Includes candle coloring, dynamic overlays, signal labels, and optional trend structure plots. 📊 How It Works 1️⃣ Normalized RSI of a DEMA Source The heart of RMD lies in a momentum oscillator built from: • 📌 Source Input → A DEMA of price (default 30) • 📌 Momentum Foundation → RSI calculated from the DEMA output • 📌 Smoothing Length → Controls the responsiveness of the base signal (default 14) This creates a stable momentum oscillator less prone to fake-outs during sudden volatility spikes. 2️⃣ Standard Deviation Filtering Engine RMD employs volatility-weighted SD bands to define statistically meaningful thresholds: 📌 Formula Breakdown: • NormUp = RSI - SD • NormDn = RSI + SD These boundaries adapt based on recent price dispersion. The upper and lower bands dynamically expand or contract depending on market behavior. 3️⃣ Signal Logic & Triggering Conditions • ✅ Long Signal → NormUp crosses above the long threshold (default: 65) • ❌ Short Signal → NormDn drops below the short threshold (default: 50) This approach means signals only occur during statistically significant deviation from mean momentum, making them less frequent but more robust. ✅ Visual Signal Features • 🔹 Candle coloring based on signal direction (Long/Short) • 🔹 Label plots on crossover confirmations • 🔹 Momentum band plots for discretionary or system-based confirmation 👥 Who Should Use It? ✅ Momentum Traders → Identify directional bias with low noise ✅ Swing Traders → Confirm turning points with volatility-adjusted deviation ✅ Quantitative Developers → Integrate into backtested strategies with ease ✅ Range-Trading Specialists → Use SD bands to anticipate overextended moves ⚙️ Customization & Default Settings 🔧 Core Inputs: • Base RSI Length (Default: 14) • Source Smoothing (DEMA, Default: 7) • SD Length (Default: 40) → Controls volatility window • SD Multiplier (Default: 0.7) → Adjusts sensitivity of deviation thresholds • Signal Thresholds (L/S Default: 65 Long - 50 Short) → Controls breakout trigger levels • Color Mode Themes → Six color themes included • Signal Labels Toggle → Optional signal label plotting • Backtest Table & Equity Curve Options 📊 Backtest Mode RMD includes an optional backtest table, enabling traders to assess its historical effectiveness before applying it in live trading conditions. 🔹 Backtest Metrics Displayed: • Equity Max Drawdown → Largest historical loss from peak equity. • Profit Factor → Ratio of total profits to total losses, measuring system efficiency. • Sharpe Ratio → Assesses risk-adjusted return performance. • Sortino Ratio → Focuses on downside risk-adjusted returns. • Omega Ratio → Evaluates return consistency & performance asymmetry. • Half Kelly → Optimal position sizing based on risk/reward analysis. • Total Trades & Win Rate → Assess historical success rate. 📌 Disclaimer: Backtest results are based on past performance and do not guarantee future success. Always incorporate real-time validation and risk management in live trading. 🚀 Why This Matters? ✅ Strategy Validation → Gain insight into historical trend accuracy. ✅ Customization Insights → See how different settings impact performance. ✅ Risk Awareness → Understand potential drawdowns before deploying capital. 📌 How to Use RMD in Your Strategy 1️⃣ Momentum Breakout Strategy ✔ Go Long when NormUp > L → Indicates strong upward deviation ✔ Go Short when NormDn < S → Indicates sharp downward momentum ✔ Use SD Mult to control sensitivity and smoothness 2️⃣ Volatility Regime Awareness ✔ In low-volatility → Decrease SD multiplier to catch early signals ✔ In high-volatility → Increase SD multiplier to avoid noise 🔍 Bonus: Extra Trend Structure Plots RMD includes optional ALMA + multi-EMA trend band overlays: • Use them to confirm momentum alignment • Great for hybrid strategies (e.g. trend + momentum) 📌 Conclusion Relative Momentum Deviation (RMD) by QuantEdgeB offers a clean and adaptive approach to momentum trading by combining a normalized RSI structure with volatility-driven breakout zones. With built-in signal confirmation, smart filtering, and rich backtest capabilities, RMD excels as a dynamic momentum companion for both discretionary and system traders. 🔹 Key Takeaways: 1️⃣ Adaptive Deviation Zones – Responsive to real-time volatility 2️⃣ Normalized RSI Core – Clean, smoothed momentum insight 3️⃣ Backtest + Visual Toolkit – Strategy-friendly and ready to deploy 📌 Trade with Statistical Precision | Powered by QuantEdgeB 🔹 Disclaimer: Past performance is not indicative of future results. 🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Pine Script® 인디케이터
QuantEdgeB의
HALC SYHALC SY @CK Heikin Ashi Last Candle shows color of the last closed 30m heikin ashi candle for every new candle on your graph indicating local trend for scalp & short term trading in rder to help u choose right direction in your 1-5m tf trading. Non-repainting & designed for use on any graph type incl HA, Renko and other problematic syntetic as well as any of your own. Dont recommend as entry signal but strong support to confirm/deny your trade system entry signal. Enjoy!
Pine Script® 인디케이터
SKrl80의
1
SEMA JMA | QuantEdgeB 📈 Introducing SEMA JMA by QuantEdgeB 🛠️ Overview SEMA JMA is a precision-engineered, dual-signal trend indicator that blends Jurik Moving Average (JMA) logic with Double Exponential Moving Average (DEMA) smoothing and normalized statistical filters. This advanced indicator is built for high-quality trend detection, reducing false signals by confirming momentum through both price-based SD bands and normalized JMA logic. The result is a powerful, noise-filtered tool ideal for directional trading in volatile and ranging environments. SEMA JMA offers adaptive volatility bands, backtest-ready analytics, and dynamic signal labeling, making it a favorite for traders demanding speed, precision, and strategic clarity. ✨ Key Features 🔹 Hybrid JMA + DEMA Core Combines the ultra-smooth JMA with lag-reducing DEMA for exceptional trend clarity. 🔹 Volatility-Based SD Band Filtering Uses rolling standard deviation on JMA for adaptive long/short bands that respond to market dynamics. 🔹 Normalized Price Filter Confirmation A second JMA stream is normalized against price and filtered via SD for added trend confirmation and false signal suppression. 🔹 Backtest Integration & Equity Curve Plotting Built-in compatibility with QuantEdgeB/BacktestingIndV2, delivering historical metrics, equity visualization, and strategic evaluation. 🔹 Fully Customizable UI Includes label toggles, signal overlays, visual themes, and backtest table position selection. 📊 How It Works 1️⃣ JMA-DEMA Hybrid Trend Engine The foundation of SEMA JMA lies in a custom-built JMA engine, enhanced by a DEMA smoothing layer to: • Minimize lag without losing trend integrity. • Maintain responsiveness in noisy or low-volume environments. • Create a central trend structure used by both raw price and normalized filters. 2️⃣ Standard Deviation Band Filtering SEMA JMA applies a rolling SD filter over the JMA signal. This creates adaptive upper and lower bands: • Long Signal = Price > Upper Band • Short Signal = Price < Lower Band These bands adjust based on price volatility, offering a dynamic alternative to traditional fixed thresholds. 3️⃣ Normalized JMA for Momentum Confirmation A second JMA-DEMA structure is normalized by dividing by price, then smoothed: • If the normalized signal rises above -1, it suggests upside pressure. • If it drops below -1, it signals momentum decay. Only when both raw and normalized signals agree does the indicator issue a trade trigger. ✅ Signal Logic 📌 Long Signal → 🔹 Price breaks above volatility-adjusted upper SD band 🔹 AND Normalized JMA rises above -1 📌 Short Signal → 🔹 Price breaks below lower SD band 🔹 AND Normalized JMA falls below -1 ⚙️ SEMA JMA stays in its active trend state until an opposing signal triggers, enabling tren riding while filtering short lived swings. 👥 Who Should Use It? ✅ Swing & Trend Traders → Ride strong directional moves with reduced whipsaws ✅ Volatility-Adaptive Systems → Filter trades using rolling SD-based thresholds ✅ Quantitative Strategy Builders → Deploy within algo-driven strategies using backtest-ready metrics ✅ Risk-Aware Traders → Use dual confirmation to minimize signal risk ⚙️ Customization & Default Settings 🔧 Core Settings: • JMA Length (Default: 35) → Defines JMA sensitivity. • DEMA Length (Default: 20) → Smoothing after JMA to refine structure. • Normalized JMA Lengths → Control confirmation layer smoothness (default: 1 for short and long). • Standard Deviation Length (Default: 30) → Determines the volatility lookback. • SD Weight Factors → Separate values for long (default: 1.0) and short (default: 1.002) bands. 📊 Backtest Mode SEMA JMA includes an optional backtest table, enabling traders to assess its historical effectiveness before applying it in live trading conditions. 🔹 Backtest Metrics Displayed: • Equity Max Drawdown → Largest historical loss from peak equity. • Profit Factor → Ratio of total profits to total losses, measuring system efficiency. • Sharpe Ratio → Assesses risk-adjusted return performance. • Sortino Ratio → Focuses on downside risk-adjusted returns. • Omega Ratio → Evaluates return consistency & performance asymmetry. • Half Kelly → Optimal position sizing based on risk/reward analysis. • Total Trades & Win Rate → Assess historical success rate. 📌 Disclaimer: Backtest results are based on past performance and do not guarantee future success. Always incorporate real-time validation and risk management in live trading. 🚀 Why This Matters? ✅ Strategy Validation → Gain insight into historical trend accuracy. ✅ Customization Insights → See how different settings impact performance. ✅ Risk Awareness → Understand potential drawdowns before deploying capital. 📌 How to Use SEMA JMA 🌀 Trend-Following Strategy ✔ Go Long: When price breaks above SD band and normalized momentum rises ✔ Go Short: When price breaks below SD band and normalized momentum falls ✔ Stay in position: Until signal reversal confirms ⚙️ Volatility-Adaptive Configuration ✔ Tune w1 (Long SD weight) and w2 (Short SD weight) for responsiveness ✔ Increase SD length in noisy markets for smoother bands 📌 Conclusion SEMA JMA by QuantEdgeB delivers surgical precision trend signals using a dual-layer approach: • JMA + DEMA core smoothing • Statistical SD breakout filters • Normalized confirmation logic It’s a versatile indicator suited for trend-following, volatility tracking, and system-based signal generation—engineered for clarity, confidence, and adaptability. 🔹 Key Takeaways: 1️⃣ Multi-Filter Trend Logic – JMA + DEMA + Normalized filtering for high-confidence signals 2️⃣ SD-Based Volatility Control – Reduces noise, avoids ATR limitations 3️⃣ Quant-Ready System – Includes full backtesting 📌 Master your market edge with precision – SEMA JMA | QuantEdgeB 🔹 Disclaimer: Past performance is not indicative of future results. 🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Pine Script® 인디케이터
QuantEdgeB의
Open Range Candle [TradeWithRon]This Open Range Break indicator is a tool designed to help traders identify and visualize key price levels using the Opening Range Breakout (ORB) strategy. This indicator dynamically plots critical levels such as the high, low, and middle of a predefined range, along with Fibonacci retracement levels for further analysis. It also features several customization options to fit various trading styles. Key Features: Session Setup: Allows the user to set the time offset in GMT - or + to adjust the ORB session to their local time zone. The default ORB session is set at 9:45 AM but can be adjusted based on user preferences. Warning: Only supports 5-minute and 15-minute timeframes. Visual Customization: Line Styles: Users can choose from Solid, Dotted, or Dashed lines to represent key price levels. Color Adjustments: Customizable colors for the high, middle, and low levels of the range, as well as Fibonacci levels and vertical lines. Labeling Options: The labels can be customized in terms of size and color, helping to keep the chart clean and clear. Fibonacci Retracement Levels: Fibonacci retracement levels are automatically drawn between the high and low of the range. Users can toggle these on or off and customize the offset to suit different trading instruments. Time-Based Visuals: A vertical line is drawn at the start of the ORB session, providing a clear visual marker of where the breakout starts. This is useful for pinpointing key trade setups. The indicator supports both 5-minute and 15-minute timeframes. EMA Integration: The user can enable an Exponential Moving Average (EMA) on any chosen timeframe with adjustable parameters such as the length and color, providing additional trend context. Dynamic Labeling: The indicator labels the high, middle, and low points of the ORB with custom text. These labels are updated in real-time as new data becomes available. Limit on Lines and Labels: The indicator allows for a limit on the number of lines and labels drawn to maintain a clean chart, preventing unnecessary clutter as more ORB levels are plotted. Daily Bias Information: The indicator assesses the daily trend bias (bullish or bearish) based on the relationship between the open and close prices for the last three daily candles, providing context for the current trading session. Countdown Timer: The remaining time until the end of the current session is displayed in a countdown format, which helps traders to time their entries and exits more precisely. How To Use:, - Set the Timeframe to 15 minutes. - Adjust the Time Zone Offset if needed, based on your local time zone. - Enable the Show ORB feature for the first 15-minute candle to be drawn as the opening range. - The indicator will automatically mark the high, middle, and low points of the range. Identify Breakout Points: Bullish Breakout: If the price breaks above the high of the 15-minute opening range, this indicates a potential bullish breakout. The indicator will plot a vertical line marking the breakout point for further confirmation. Bearish Breakout: If the price breaks below the low of the 15-minute opening range, this signals a potential bearish breakout. Again, the indicator will plot the breakout point with a vertical line for easy identification. 🔶 Disclaimer Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals. Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (Tradewithron) shall not be held responsible for any trading losses incurred as a result of using this indicator. Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies. Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses. No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future
Pine Script® 인디케이터
yeahronc의
AlphaSignal | MindMarketAlphaSignal — Smart Indicator for Precise Entries What does AlphaSignal do? AlphaSignal looks for moments when the price moves too far from its average, volume spikes, and overall market activity increases. When these things line up, it gives you a clean, high-quality trading signal — either to buy or sell. How it works : Activity & Volume Detection It monitors for sudden bursts in trading volume and volatility — clear signs that something important is happening in the market. Price Deviation with Nadaraya-Watson Envelope The indicator uses a smooth curve (called the Nadaraya-Watson estimate) to track the average price. When price drifts too far from this curve, it might be ready to snap back. That’s where AlphaSignal starts paying attention. Signal Rating System Each potential trade gets a score based on: Market activity Volume deviation How far price is from the NW envelope (Optionally) Trend strength and momentum via ADX, RSI, MACD Only if the total score is high enough — a signal is fired. Advanced Filters (Optional) Want more confirmation? Turn on ADX, RSI, and MACD checks to avoid weak setups during choppy, low-trend periods. Cooldown Logic To avoid overtrading, AlphaSignal waits a set number of bars between signals — you can customize this. Trading Suggestions (Signal Panel) AlphaSignal gives you real-time trading guidance with a simple suggestion box: BUY NOW / SELL NOW All conditions are met, rating is strong — take action. PREPARE BUY / PREPARE SELL No full confirmation yet, but the price is very close to key levels (within 1.5% of the NW envelope). Get ready — a signal might appear soon. AWAIT BUY / AWAIT SELL The market is leaning toward a buy or sell, but price isn’t in a good spot yet. Be patient and watch for better positioning.
Pine Script® 인디케이터
mindmarket의
1
Liquidity Volume Panel Liquidity Volume Panel – Precision Tool for Scalpers & Intraday Traders This panel is designed to help traders quickly identify volume-driven moves, liquidity events, and fair-value zones. It combines classic volume analysis with enhanced tools like RVOL and VWAP deviation bands, making it ideal for scalping, momentum trading, and intraday strategies. 🔍 Included Features: ✅ Relative Volume (RVOL) Indicator Displays current volume in relation to its 20-period average – excellent for spotting low-activity zones or high-pressure breakouts. ✅ Dynamic Volume Coloring & Spike Detection Color-coded volume logic highlights normal, strong, and extremely high volume, with visual markers for volume spikes (>200% of average). ✅ VWAP with ±1σ & ±2σ Bands Industry-standard deviation bands show overbought/oversold conditions and dynamic support/resistance based on volume-weighted pricing. ✅ Background Highlighting Subtle orange background alerts you when volume surges beyond extreme levels – making liquidity clusters instantly recognizable. Usage: Use this panel as a decision-making tool for entries, reversals, or breakouts – especially in fast-moving markets. Best used on lower timeframes for precision scalping.
Pine Script® 인디케이터
Mathias81의
Automated Lot Size Calculator // © Laurent3372 The "Automated Lot Size Calculator" is a sophisticated tool for traders who want to calculate the ideal position size based on their capital, risk, and the asset pair they wish to trade. Here is a detailed description of its features: 1. Language Selector You can select the interface language (French, English, Spanish, German, or Italian). This makes the tool accessible and understandable to an international audience. 2. User Settings for Risk Calculation The risk percentage per trade is configurable. The entered percentage is divided by 100 to obtain a fraction (for example, 1% becomes 0.01). 3. Selection of Equity in USD or EUR The user chooses whether their equity is in US dollars or euros. Based on this choice, the calculation is based on the appropriate value. A field for entering equity is available for both currencies, with a default initial amount. 4. Stop Loss in Pips The stop loss can be entered in decimal places (such as 2.8 pips), allowing for high precision in risk calculations. 5. Interface Color Customization You can configure the text and background colors for headers, values, and other visual elements, allowing you to customize the display. 6. Display Table Position and Size You can choose the table location (top right, top left, bottom right, bottom left) as well as the display size (extra small, small, normal, large, extra large). 7. Asset Pair Detection and Pip Value The code automatically detects the financial instrument (currency, crypto, precious metal) and adjusts the pip value according to the asset's characteristics. For example: For JPY pairs, the pip is 0.01. For cryptocurrencies, the pip is adjusted to 0.01. For precious metals such as gold and silver, specific adjustments are also made. 8. Retrieving real-time exchange rates The script uses the request.security function to retrieve real-time exchange rates for currencies or cryptocurrencies. The code automatically adapts according to the trading pair and retrieves the appropriate rate (e.g., EUR/GBP, BTC/USD). 9. Calculating the risk amount in USD or EUR The risk is calculated based on the selected capital (USD or EUR). If the capital is in euros, it is converted to USD to simplify lot calculations. 10. Calculating position sizes in standard lots The formula for calculating position sizes varies depending on the asset: EUR/GBP is calculated with a specific adjustment. Precious metals and cryptocurrencies have their own adapted formulas. Exotic currencies incorporate a special conversion factor, taking into account pairs with more than two decimal places. 11. Lot Type Definition The lot type is automatically adjusted according to the asset: "Micro Lot", "Standard Lot", or "Exotic Lot". 12. Results Display with Dynamic Translation The results (currency, equity, risk, lot type, and size) are displayed in real time and automatically translated into the selected language. The left column contains the parameters, and the right column displays the corresponding values. 13. Dynamically Creating the Results Table The table is dynamically created using the specified position and size options. It contains all essential information, such as currency, equity, risk, and position size in lots. Conclusion: This script allows traders to automatically calculate their ideal position size by taking into account the currency, desired risk, and asset-specific parameters (such as cryptocurrencies and metals). Thanks to its customization options and automatic translations, it is suitable for global use, regardless of user profile.
Pine Script® 인디케이터
Laurent3372의
P-Motion Trend | QuantEdgeB⚡ Introducing P-Motion Trend (PMT) by QuantEdgeB 🧭 Overview P-Motion Trend is a refined trend-following framework built for modern market dynamics. It combines DEMA filtering, percentile-based smoothing, and volatility-adjusted envelopes to create a clear, noise-filtered trend map directly on your chart. This overlay indicator is engineered to detect breakout zones, trend continuation setups, and market regime shifts with maximum clarity and minimum lag. Whether you're swing trading crypto, managing intraday FX moves, or positioning in equities — P-Motion Trend adapts, aligns, and simplifies. 🧠 Core Logic 1️⃣ DEMA Filtering Core The input source is processed through a Double EMA to reduce lag while retaining trend sensitivity. 2️⃣ Percentile Median Smoothing To eliminate short-lived spikes, the DEMA output is passed through a percentile median rank — effectively smoothing without distortion. 3️⃣ Volatility Envelope with EMA Basis An exponential moving average (EMA) is applied to the smoothed median, and standard deviation bands are wrapped around it: • ✅ Long Signal → Price closes above the upper band • ❌ Short Signal → Price closes below the lower band • ➖ Inside Band = Neutral These bands expand/contract with market volatility — protecting against false breakouts in quiet regimes and adapting quickly to strong moves. 📊 Visual & Analytical Layers • 🎯 Bar Coloring: Color-coded candles highlight trend state at a glance. • 📈 EMA Ribbon Overlay: A dynamic ribbon of EMAs helps confirm internal momentum and detect transitions (trend decay or acceleration). • 🔹Gradient Fill Zones: Visually communicates squeeze vs. expansion phases based on band width. ⚙️ Custom Settings • EMA Length – Defines the core trend path (default: 21) • SD Length – Controls volatility band smoothing (default: 30) • SD Mult Up/Down – Sets thresholds for breakout confirmation (default: 1.5) • DEMA Filter Source – Raw input used for trend processing • DEMA Filter Length – Sets DEMA smoothing (default: 7) • Median Length – Percentile-based smoothing window (default: 2) 📌 Use Cases ✅ Trend Confirmation Use PMT to confirm whether the price action is structurally valid for trend continuation. A close above the upper band signals entry alignment. 🛡️ Reversal Guard Avoid early reversion entries. PMT keeps you in-trend until price truly breaks structure. 🔍 Momentum Visualizer With multiple EMA bands, the indicator also functions as a momentum envelope to spot divergence between price and smoothed trend flow. 🔚 Conclusion P-Motion Trend is a hybrid volatility + trend system built with precision smoothing, dynamic filtering, and clean visual output. It balances agility with stability, helping you: • Filter out price noise • Enter with structure • Stay in trades longer • Exit with confidence 🧩 Summary of Benefits • 🔹 Lag-minimized trend structure via DEMA core • 🔹 Real-time volatility band adaptation • 🔹 Gradient visual feedback on compression/expansion • 🔹 EMA ribbon assists in phase detection • 🔹 Suitable for all markets & timeframes 📌 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.
Pine Script® 인디케이터
QuantEdgeB의
4
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.
Pine Script® 인디케이터
QuantEdgeB의
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.
Pine Script® 인디케이터
QuantEdgeB의
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.
Pine Script® 인디케이터
QuantEdgeB의
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!
Pine Script® 인디케이터
QuantEdgeB의
2
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.
Pine Script™ 전략
EdgeTools의
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.
Pine Script® 인디케이터
QuantEdgeB의