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RSI Trend Navigator [QuantAlgo]🟢 Overview The RSI Trend Navigator integrates RSI momentum calculations with adaptive exponential moving averages and ATR-based volatility bands to generate trend-following signals. The indicator applies variable smoothing coefficients based on RSI readings and incorporates normalized momentum adjustments to position a trend line that responds to both price action and underlying momentum conditions. 🟢 How It Works The indicator begins by calculating and smoothing the RSI to reduce short-term fluctuations while preserving momentum information: rsiValue = ta.rsi(source, rsiPeriod) smoothedRSI = ta.ema(rsiValue, rsiSmoothing) normalizedRSI = (smoothedRSI - 50) / 50 It then creates an adaptive smoothing coefficient that varies based on RSI positioning relative to the midpoint: adaptiveAlpha = smoothedRSI > 50 ? 2.0 / (trendPeriod * 0.5 + 1) : 2.0 / (trendPeriod * 1.5 + 1) This coefficient drives an adaptive trend calculation that responds more quickly when RSI indicates bullish momentum and more slowly during bearish conditions: var float adaptiveTrend = source adaptiveTrend := adaptiveAlpha * source + (1 - adaptiveAlpha) * nz(adaptiveTrend , source) The normalized RSI values are converted into price-based adjustments using ATR for volatility scaling: rsiAdjustment = normalizedRSI * ta.atr(14) * sensitivity rsiTrendValue = adaptiveTrend + rsiAdjustment ATR-based bands are constructed around this RSI-adjusted trend value to create dynamic boundaries that constrain trend line positioning: atr = ta.atr(atrPeriod) deviation = atr * atrMultiplier upperBound = rsiTrendValue + deviation lowerBound = rsiTrendValue - deviation The trend line positioning uses these band constraints to determine its final value: if upperBound < trendLine trendLine := upperBound if lowerBound > trendLine trendLine := lowerBound Signal generation occurs through directional comparison of the trend line against its previous value to establish bullish and bearish states: trendUp = trendLine > trendLine trendDown = trendLine < trendLine if trendUp isBullish := true isBearish := false else if trendDown isBullish := false isBearish := true The final output colors the trend line green during bullish states and red during bearish states, creating visual buy/long and sell/short opportunity signals based on the combined RSI momentum and volatility-adjusted trend positioning. 🟢 Signal Interpretation Rising Trend Line (Green): Indicates upward momentum where RSI influence and adaptive smoothing favor continued price advancement = Potential buy/long positions Declining Trend Line (Red): Indicates downward momentum where RSI influence and adaptive smoothing favor continued price decline = Potential sell/short positions Flattening Trend Lines: Occur when momentum weakens and the trend line slope approaches neutral, suggesting potential consolidation before the next move Built-in Alert System: Automated notifications trigger when bullish or bearish states change, sending "RSI Trend Bullish Signal" or "RSI Trend Bearish Signal" messages for timely entry/exit Color Bar Candles Option: Optional candle coloring feature that applies the same green/red trend colors to price bars, providing additional visual confirmation of the current trend direction
Pine Script® göstergesi
QuantAlgo tarafından
Take Profit Strategy by jaxon0007This TradingView indicator implements a sophisticated take profit trading strategy developed by jaxon0007. The indicator provides clear visual signals for entry points, take profit targets, stop loss levels, and confirmation signals to help traders maximize profits while managing risk. Features · EMA Baseline: Uses Exponential Moving Average as the foundation for calculations · Upper/Lower Bands: Dynamic bands set at 0.88% above and below the EMA · Entry Signals: Clear visual markers for optimal trade entry points · Confirmation Level: Intermediate level between entry and take profit for position validation · Take Profit Targets: Precisely calculated profit-taking levels · Stop Loss Protection: Automated risk management with clear stop loss markers · Visual Table: Clean display of all key price levels on the chart Strategy Logic 1. The indicator calculates an EMA as its core reference point 2. Upper and lower bands are established at 0.88% distance from the EMA 3. Entry points are identified based on price action relative to these bands 4. Confirmation levels help validate trade setups 5. Take profit targets are automatically calculated based on the entry price 6. Stop loss levels protect against excessive downside risk Backtest Results Extensive backtesting across multiple markets and timeframes has demonstrated: · Consistent profitability in trending markets · Effective risk management with favorable risk-reward ratios · Reliable performance across forex, stocks, and cryptocurrencies · Robust results in both bull and bear market conditions Usage Instructions 1. Add the indicator to any TradingView chart 2. Adjust parameters according to your trading style: · EMA length (default: 20 periods) · Upper/lower percentage levels · Stop loss and take profit percentages 3. Look for entry signals when price approaches the bands 4. Use confirmation level to validate trades 5. Set take profit and stop loss orders at indicated levels License This indicator is created and licensed by jaxon0007. All rights reserved. Unauthorized distribution, modification, or commercial use of this indicator is prohibited without explicit permission from the author. Disclaimer Trading financial instruments involves significant risk and is not suitable for all investors. Past performance of this indicator is not necessarily indicative of future results. Users should thoroughly test any trading strategy with a demo account before applying it to live trading. This technical indicator represents proprietary trading methodology developed through extensive market analysis and testing. The 0.88% band settings have been optimized for capturing optimal risk-adjusted returns across various market conditions.
Pine Script® göstergesi
Jaxon007 tarafından
CM_Williams_Vix_Fix (v5) + Optional InverseCM_Williams_Vix_Fix (v5) + Optional Inverse This indicator is a modernized Pine v5 rewrite of Larry Williams’ classic Vix Fix, with an optional inverse mode to detect both capitulation lows (buy signals) and euphoric highs (sell signals). 🔎 What It Does Vix Fix (Buy-side): Mimics the behavior of the VIX by detecting panic/fear spikes when price makes unusually deep lows relative to recent closes. Inverse Vix Fix (Sell-side): Flips the logic to highlight euphoric/overbought spikes when price makes unusually high prints relative to recent closes. Works on any timeframe or instrument — originally built for stocks/futures that don’t have their own VIX. ⚙️ Inputs LookBack Period (pd): Number of bars to check for recent highs/lows. Bollinger Band Length (bbl): Period for volatility bands. Std Dev Multiplier (mult): Sensitivity of the bands. Percentile Lookback (lb, ph, pl): Optional percentile thresholds for extra filters. Show Range Lines (hp): Toggle percentile-based high/low markers. Show StdDev Bands (sd): Toggle Bollinger-style envelopes. Show Inverse (Sell) Version: Plots a red histogram for euphoric tops. 📊 Plots Green Histogram: Vix Fix (fear/panic spikes). Red Histogram: Inverse Vix Fix (euphoria spikes, optional). Orange Lines: Percentile-based thresholds (optional). Aqua Lines: Bollinger-style volatility bands (optional). 🧭 How to Use Green Spikes (Buy Vix Fix): Potential market bottoms when fear is high. Red Spikes (Inverse): Potential market tops when greed/euphoria is high. Works best when combined with: Trend filters (e.g. moving averages). Market structure tools (e.g. support/resistance, FVGs, liquidity levels). Other volatility/volume confirmations. ⚠️ Note: This is an indicator only (not a strategy). It highlights potential extremes in sentiment/volatility, but does not provide direct buy/sell orders. Always confirm with price action and risk management.
Pine Script® göstergesi
huhmonkey tarafından
LRSlope - Linear Regression SlopeThis indicator attempts to predict the direction of the trend using least squares moving averages (LSMA). The indicator's core purpose is to determine whether the price trajectory has a positive or negative slope and calculate directional changes. It also measures the strength of price momentum by calculating how strongly the slope. The indicator calculates the slope of the curve for each bar and the EMA of these slopes for the specified period (Curve Length). It is consists of a histogram and two lines named "Average Slope"(white line) and "Simple" (green line). The "Average Slope" is the simple moving average of the calculated EMA values. " Simple " is SMA of calculated slopes. The color of the histogram changes depending on the relative position of these two lines and zero line. Simply put, the green bars of the histogram indicate an uptrend, blue bars indicate a horizontal or reverse movement, and red bars indicate a downtrend. It is possible to see the strength of the momentum by the amount of change in the " Simple" (green line).
Pine Script® göstergesi
oberez tarafından
Supertrend Channel Histogram OscillatorThis histogram is based on the script "Supertrend Channels " The idea of the indicator is to visually represent the interaction of price with several different supertrend channels of various lengths in an oscillator in order to make it much more clear to the trader how the longer trends are interacting with shorter trends of the price movement of an asset. I got this idea from the "Kurutoga Cloud" and "Kurutoga Histogram" by D7R which is based on the centerlines of 3 Donchian Channels, however after I started using the Supertrend Channel by LuxAlgo I found that it was a more reliable price range channel than a standard Donchian Channel and I made this indicator to accompany it. This indicator plots a positive value above 0 when the price is above the centerline of the supertrend channel and a negative value below 0 when the price is below the centerline. The first supertrend's length and multiple can be adjusted in the settings. The given supertrend input is then doubled and quadrupled in both length and multiplication so that a supertrend histogram with the values of 3, 3 will be accompanied by 2 additional supertrend histograms with the values of 6, 6 and 12, 12. The larger price trend histograms are clearly visible behind the short term supertrend channel's histogram, giving traders a balanced view of short and long term trends interacting. The less visible columns of the larger trend remain above or below the 0 line behind the more visible short term channel trend, helping to spot pullbacks within a larger trend. Additionally, when the 3 separate histograms are all positive or all negative but the histogram columns are separating from each other this can indicate a potential trend exhaustion leading to reversal or pullback about to happen. The overbought and oversold lines at 50 and -50 are representative primarily of the short term trend with above 50 or below -50 indicating that the price is pushing the boundary and potentially beginning a new short term supertrend in the opposite direction. If values do not noticably exceed these levels, then the current short term trend movement can be viewed as a pullback within a larger trend, with continuation potentially to follow. I have had troubles converting the original code to v6 so this will be published here in v5 of pinescript to be used in conjunction with the original. I was intending to create a companion indicator for this oscillator that represents 3 supertrends with corresponding 2x and 4x calculations based on LuxAlgo's script, but I can't seem to get it to work correctly in v5. For best visualization of the trends 3 LuxAlgo Supertrend channels with 2x and 4x values should be used in conjunction with each other to fully visualize the histogram. Used in conjunction with other indicators this can be a very effective strategy to capture larger trend moves and pullbacks within trends, as well as warn of potential price trend exhaustion.
Pine Script® göstergesi
nathanieljens tarafından
Volatility Cone Forecaster Lite [PhenLabs]📊 Volatility Cone Forecaster Version: PineScript™v6 📌Description The Volatility Cone Forecaster (VCF) is an advanced indicator designed to provide traders with a forward-looking perspective on market volatility. Instead of merely measuring past price fluctuations, the VCF analyzes historical volatility data to project a statistical “cone” that outlines a probable range for future price movements. Its core purpose is to contextualize the current market environment, helping traders to anticipate potential shifts from low to high volatility periods (and vice versa). By identifying whether volatility is expanding or contracting relative to historical norms, it solves the critical problem of preparing for significant market moves before they happen, offering a clear statistical edge in strategy development. This indicator moves beyond lagging measures by employing percentile analysis to rank the current volatility state. This allows traders to understand not just what volatility is, but how significant it is compared to the recent past. The VCF is built for discretionary traders, system developers, and options strategists who need a sophisticated understanding of market dynamics to manage risk and identify high-probability opportunities. 🚀Points of Innovation Forward-Looking Volatility Projection: Unlike standard indicators that only show historical data, the VCF projects a statistical cone of future volatility. Percentile-Based Regime Analysis: Ranks current volatility against historical data (e.g., 90th, 75th percentiles) to provide objective context. Automated Regime Detection: Automatically identifies and labels the market as being in a ‘High’, ‘Low’, or ‘Normal’ volatility regime. Expansion & Contraction Signals: Clearly indicates whether volatility is currently increasing or decreasing, signaling shifts in market energy. Integrated ATR Comparison: Plots an ATR-equivalent volatility measure to offer a familiar point of reference against the statistical model. Dynamic Visual Modeling: The cone visualization directly on the price chart provides an intuitive guide for future expected price ranges. 🔧Core Components Realized Volatility Engine: Calculates historical volatility using log returns over multiple user-defined lookback periods (short, medium, long) for a comprehensive view. Percentile Analysis Module: A custom function calculates the 10th, 25th, 50th, 75th, and 90th percentiles of volatility over a long-term lookback (e.g., 252 days). Forward Projection Calculator: Uses the calculated volatility percentiles to mathematically derive and draw the upper and lower bounds of the future volatility cone. Volatility Regime Classifier: A logic-based system that compares current volatility to the historical percentile bands to classify the market state. 🔥Key Features Customizable Lookback Periods: Adjust short, medium, and long-term lookbacks to fine-tune the indicator’s sensitivity to different market cycles. Configurable Forward Projection: Set the number of days for the forward cone projection to align with your specific trading horizon. Interactive Display Options: Toggle visibility for percentile labels, ATR levels, and regime coloring to customize the chart display. Data-Rich Information Table: A clean, on-screen table displays all key metrics, including current volatility, percentile rank, regime, and trend. Built-in Alert Conditions: Set alerts for critical events like volatility crossing the 90th percentile, dropping below the 10th, or switching between expansion and contraction. 🎨Visualization Volatility Cone: Shaded bands projected onto the future price axis, representing the probable price range at different statistical confidence levels (e.g., 75th-90th percentile). Color-Coded Volatility Line: The primary volatility plot dynamically changes color (e.g., red for high, green for low) to reflect the current volatility regime, providing instant context. Historical Percentile Bands: Horizontal lines plotted across the indicator pane mark the key percentile levels, showing how current volatility compares to the past. On-Chart Labels: Clear labels automatically display the current volatility reading, its percentile rank, the detected regime, and trend (Expanding/Contracting). 📖Usage Guidelines Setting Categories Short-term Lookback: Default: 10, Range: 5-50. Controls the most sensitive volatility calculation. Medium-term Lookback: Default: 21, Range: 10-100. The primary input for the current volatility reading. Long-term Lookback: Default: 63, Range: 30-252. Provides a baseline for long-term market character. Percentile Lookback Period: Default: 252, Range: 100-1000. Defines the period for historical ranking; 252 represents one trading year. Forward Projection Days: Default: 21, Range: 5-63. Determines how many bars into the future the cone is projected. ✅Best Use Cases Breakout Trading: Identify periods of deep consolidation when volatility falls to low percentile ranks (e.g., below 25th) and begins to expand, signaling a potential breakout. Mean Reversion Strategies: Target trades when volatility reaches extreme high percentile ranks (e.g., above 90th), as these periods are often unsustainable and lead to contraction. Options Strategy: Use the cone’s projected upper and lower bounds to help select strike prices for strategies like iron condors or straddles. Risk Management: Widen stop-losses and reduce position sizes when the indicator signals a transition into a ‘High’ volatility regime. ⚠️Limitations Probabilistic, Not Predictive: The cone represents a statistical probability, not a guarantee of future price action. Extreme, unpredictable news events can drive prices outside the cone. Lagging by Nature: All calculations are based on historical price data, meaning the indicator will always react to, not pre-empt, market changes. Non-Directional: The indicator forecasts the *magnitude* of future moves, not the *direction*. It should be paired with a directional analysis tool. 💡What Makes This Unique Forward Projection: Its primary distinction is projecting a data-driven, statistical forecast of future volatility, which standard oscillators do not do. Contextual Analysis: It doesn’t just provide a number; it tells you what that number means through percentile ranking and automated regime classification. 🔬How It Works 1. Data Calculation: The indicator first calculates the logarithmic returns of the asset’s price. It then computes the annualized standard deviation of these returns over short, medium, and long-term lookback periods to generate realized volatility readings. 2. Percentile Ranking: Using a 252-day lookback, it analyzes the history of the medium-term volatility and determines the values that correspond to the 10th, 25th, 50th, 75th, and 90th percentiles. This builds a statistical map of the asset’s volatility behavior. 3. Cone Projection: Finally, it takes these historical percentile values and projects them forward in time, calculating the potential upper and lower price bounds based on what would happen if volatility were to run at those levels over the next 21 days. 💡Note: The Volatility Cone Forecaster is most effective on daily and weekly charts where statistical volatility models are more reliable. For lower timeframes, consider shortening the lookback periods. Always use this indicator as part of a comprehensive trading plan that includes other forms of analysis.
Pine Script® göstergesi
PhenLabs tarafından
RSI OB/OSRSI OB/OS Signals indicator The RSI OB/OS Signals indicator is an analysis and training tool that uses simple statistical learning (rolling correlations and z-scoring) to produce a smoothed, adaptive RSI weighting and signal line intended to highlight probable short-term RSI movements. The script does not attempt black-box machine-learning model export instead, it uses transparent building blocks — returns, RSI, ATR percentage, volume change (log), and raw volume — as predictors to estimate the likely next-bar RSI, then converts that estimate into a bounded “weight” and a smoothed signal line. The objective is educational: show how simple correlation-based weighting of standardized features can serve as an RSI augmentation and help traders identify higher-probability bullish or bearish RSI cross conditions, while making all internal reasoning visible and explainable. At its core the indicator performs three conceptual steps each bar: first it computes a set of per-bar features aligned to the target (prior bar RSI) — specifically prior-bar log returns, prior-bar RSI, ATR as percent of price, the log change in volume and the prior-bar raw volume. Second it standardizes these predictors through rolling z-scoring and computes rolling Pearson correlations between each standardized predictor and the target RSI over a user-configurable learning window. These correlations act as signed linear weights: predictors with higher absolute correlation are treated as more informative for that window. Third it forms a linear prediction by summing correlation × z(feature) across the top correlated predictors, then maps that standardized prediction back to RSI scale using the rolling mean and standard deviation of the target. The mapped prediction is finally converted to a bounded “rsiWeight,” smoothed by a signal moving average, and used to produce bullish/bearish events on crossovers of preconfigured thresholds. VWAP, buy/sell volume breakdown and simple tracking of the price move since the last signal are also displayed to help traders interpret the quality of signals. The components are chosen for clear, complementary roles rather than as a random mashup. Prior-bar RSI embodies short-term momentum and is the natural prediction target. Log returns add price-direction information; ATR percent encodes the intrabar volatility regime (helpful because RSI behaviour differs in high vs low volatility); the volume log-change and raw volume provide a participation signal indicating whether structural moves are supported by real activity. Standardizing predictors and using rolling correlations lets the script adapt its emphasis to the current regime: when volume changes correlate strongly with subsequent RSI moves, the algorithm will weight that predictor more heavily; when returns correlate more, weight shifts accordingly. Because the method is linear, transparent and computed on rolling windows you can reproduce and reason about the weight changes — a key requirement for educational clarity and TradingView compliance. How to read and use the indicator practically: treat the smoothed rsiWeight line (ma_rsi) and its threshold crossings as an RSI-augmentation alert — not as a standalone automated buy/sell system. A practical workflow is: first inspect the dashboard and confirm the underlying drivers (which predictors show strong z-scores and which had high rolling correlation in the learning window); second check VWAP position and volume split to ensure that the price move is supported; third only consider signals that coincide with your higher-timeframe bias or structural support/resistance. For example, a bullish crossover (ma_rsi crossing above −0.5) that occurs while VWAP is below price, buy volume share is elevated, and ATR is moderate is a higher-quality setup than the same crossing on thin volume and extreme ATR. Use ATR or recent swing structure for stop placement and predefine risk per trade. Because the indicator tracks max points since the last signal, you can also use that metric as a simple intraday performance monitor. Parameter tuning guidance: the learning window (learnLen) controls how quickly the correlation weights adapt; a short window (e.g., 10–20) makes the predictor weights responsive to regime shifts but also noisier; a longer window (e.g., 40–80) smooths weights and emphasizes longer-term relationships. The rsiLen (target RSI length) should match your intended horizon — 14 is standard and balances responsiveness and smoothness. sigLen controls the smoothing of the predicted RSI weight: lower values make the signal line more reactive (useful for scalping), higher values produce smoother signals (useful for swing trades). For low-liquidity instruments increase learnLen and sigLen to reduce false alarms; for high-speed intra-day work shorten them. Volume heuristics (volume thresholds) are instrument dependent — calibrate volume formatting and volumetric thresholds for equities versus futures or crypto. Limitations and failure modes are explicit and important: the feature-selection approach is linear and based on Pearson correlation — it cannot capture nonlinear dependencies or temporal lags beyond the single lag studied, so it may miss relationships that require higher-order features. The volume split used (close>open vs closeopen vs close
Pine Script® göstergesi
aiTrendview-Charting-System tarafından
🎮 Liquidity Checklist – EFI + CMF + Centered MFIWhat it is A confirmation dashboard combining EFI (Elder Force Index), CMF (Chaikin Money Flow), and MFI (Money Flow Index). Provides a checklist table with / conditions, glow plots, and theme/override system. Intended as confirmation tool, not a standalone signal generator. Why combine these three? EFI (Force): captures impulse of price change × volume strength of push. CMF (Flow): measures accumulation/distribution capital inflow or outflow. MFI (Liquidity/Momentum): RSI with volume liquidity stretch or balance. Aligning force + flow + liquidity avoids weak setups and highlights agreement. How it works EFI: EMA of ( Close × Volume). Positive = buying pressure; Negative = selling pressure. CMF: Money Flow Multiplier × Volume, averaged relative to total volume. Above 0 = inflow; Below 0 = outflow. MFI: built-in 0 100 oscillator. On chart: plotted centered as (MFI 50). In table: shown as real 0 100 value. Checklist logic Long bias: EFI > 0; CMF > 0; MFI > 35. Short bias: EFI < 0; CMF < 0; MFI < 65. Between 35 65, MFI may allow both long and short (neutral liquidity zone). What s original here Centered MFI plotting so all indicators share a zero baseline. Dashboard checklist table with live indicator values. Theme engine with custom color overrides (separate plot vs. table). Normalization toggle for EFI/CMF readability on high-volume tickers. Inputs & settings Lengths: EFI (13), CMF (20), MFI (14). Themes: Arcade, Feng Shui, Samurai, Irish, Cyberpunk. Override plot colors option; table stays theme-based. Normalize EFI/CMF (default OFF). ON scales EFI/CMF to 100 +100 for visual balance with MFI. Logic uses raw values. How to read Chart: EFI & CMF as glowing columns; MFI as centered line; reference lines at 0, +15 ( 65), 15 (35). Table: / for each condition and live values; READY row lights when all align. Suggested use Use as confirmation filter: 1) Define trade idea (structure, catalyst). 2) Check EFI and CMF align with bias. 3) Confirm MFI not stretched (avoid longs >65, shorts <35). 4) Look for READY tick when all three align. Works across timeframes; many prefer 15m 1H for intraday. Limitations Not a trading system on its own. CMF may be na when High == Low. Normalization affects visuals only, not logic. Always backtest and manage risk. Credits EFI by Alexander Elder. CMF by Marc Chaikin. MFI standard oscillator. Centered-MFI plotting, checklist UI, themes, normalization: NICK789. Disclaimer Educational use only; not financial advice. No guarantees of accuracy or profitability. Markets involve risk; past performance does not guarantee results.
Pine Script® göstergesi
NICK789 tarafından
DNSE VN301!, ADX Momentum StrategyDiscover the tailored Pine Script for trading VN30F1M Futures Contracts intraday. This strategy applies the Statistical Method (IQR) to break down the components of the ADX, calculating the threshold of "normal" momentum fluctuations in price to identify potential breakouts for entry and exit signals. The script automatically closes all positions by 14:30 to avoid overnight holdings. www.tradingview.com Settings & Backtest Results: - Chart: 30-minute timeframe - Initial capital: VND 100 million - Position size: 4 contracts per trade (includes trading fees, excludes tax) - Backtest period: Sep-2021 to Sep-2025 - Return: over 270% (with 5 ticks slippage) - Trades executed: 1,000+ - Win rate: ~40% - Profit factor: 1.2 Default Script Settings: Calculates the acceleration of changes in the +DI and -DI components of the ADX, using IQR to define "normal" momentum fluctuations (adjustable via Lookback period). Calculates the difference between each bar’s Open and Close prices, using IQR to define "normal" gaps (adjustable via Lookback period). Entry & Exit Conditions: Entry Long: Change in +DI or -DI > Avg IQR Value AND Close Price > Previous Close Exit Long: (all 4 conditions must be met) - Change in +DI or -DI > Avg IQR Value - RSI < Previous RSI - Close–Open Gap > Avg IQR Gap - Close Price < Previous Close Entry Short: Change in +DI or -DI > Avg IQR Value AND Close Price < Previous Close Exit Short: (all 4 conditions must be met) - Change in +DI or -DI > Avg IQR Value - RSI > Previous RSI - Close–Open Gap > Avg IQR Gap - Close Price > Previous Close Disclaimers: Trading futures contracts carries a high degree of risk, and price movements can be highly volatile. This script is intended as a reference tool only. It should be used by individuals who fully understand futures trading, have assessed their own risk tolerance, and are knowledgeable about the strategy’s logic. All investment decisions are the sole responsibility of the user. DNSE bears no liability for any potential losses incurred from applying this strategy in real trading. Past performance does not guarantee future results. Please contact us directly if you have specific questions about this script.
Pine Script® stratejisi
DNSE tarafından
1
RSI Momentum Trend MM with Risk Per Trade [MTF]This is a comprehensive and highly customizable trend-following strategy based on RSI momentum. The core logic identifies strong directional moves when the RSI crosses user-defined thresholds, combined with an EMA trend confirmation. It is designed for traders who want granular control over their strategy's parameters, from signal generation to risk management and exit logic. This script evolves a simple concept into a powerful backtesting tool, allowing you to test various money management and trade management theories across different timeframes. Key Features - RSI Momentum Signals: Uses RSI crosses above a "Positive" level or below a "Negative" level to generate trend signals. An EMA filter ensures entries align with the immediate trend. - Multi-Timeframe (MTF) Analysis: The core RSI and EMA signals can be calculated on a higher timeframe (e.g., using 4H signals to trade on a 1H chart) to align trades with the larger trend. This feature helps to reduce noise and improve signal quality. Advanced Money Management - Risk per Trade %: Calculate position size based on a fixed percentage of equity you want to risk per trade. - Full Equity: A more aggressive option to open each position with 100% of the available strategy equity. Flexible Exit Logic: Choose from three distinct exit strategies to match your trading style - Percentage (%) Based: Set a fixed Stop Loss and Take Profit as a percentage of the entry price. - ATR Multiplier: Base your Stop Loss and Take Profit on the Average True Range (ATR), making your exits adaptive to market volatility. - Trend Reversal: A true trend-following mode. A long position is held until an opposite "Negative" signal appears, and a short position is held until a "Positive" signal appears. This allows you to "let your winners run." Backtest Date Range Filter: Easily configure a start and end date to backtest the strategy's performance during specific market periods (e.g., bull markets, bear markets, or high-volatility periods). How to Use RSI Settings - Higher Timeframe: Set the timeframe for signal calculation. This must be higher than your chart's timeframe. - RSI Length, Positive above, Negative below: Configure the core parameters for the RSI signals. Money Management Position Sizing Mode - Choose "Risk per Trade" to use the Risk per Trade (%) input for precise risk control. - Choose "Full Equity" to use 100% of your capital for each trade. - Risk per Trade (%): Define the percentage of your equity to risk on a single trade (only works with the corresponding sizing mode). SL/TP Calculation Mode Select your preferred exit method from the dropdown. The strategy will automatically use the relevant inputs (e.g., % values, ATR Multiplier values, or the trend reversal logic). Backtest Period Settings Use the Start Date and End Date inputs to isolate a specific period for your backtest analysis. License & Disclaimer © waranyu.trkm — MIT License. This script is for educational purposes only and should not be considered financial advice. Trading involves significant risk, and past performance is not indicative of future results. Always conduct your own research and risk assessment before making any trading decisions.
Pine Script® stratejisi
waranyutrkm tarafından
Chanpreet RSI(3) Extreme Rays (4H, Adjustable Style)Chanpreet RSI(3) Extreme Rays (4H) This indicator applies a short-length RSI (3) on the 4-hour timeframe and highlights momentum extremes directly on the chart. 🔎 What it does Detects when RSI(3) moves into overbought (>80) or oversold (<20) territory. Groups consecutive candles inside these zones into one “event” instead of marking each bar individually. For each event: • In overbought → records the highest high of the stretch and marks it with a horizontal ray. • In oversold → records the lowest low of the stretch and marks it with a horizontal ray. Keeps only the most recent N rays (default 5, adjustable). ⚙️ Inputs Max Rays to Keep → how many unique events are kept visible. Ray Thickness → adjust line thickness. Overbought Ray Color → default red. Oversold Ray Color → default green. 📈 How to use Apply on any chart; RSI(3) values are always calculated from 4H data (via request.security). Use rays as reference levels that highlight recent momentum extremes or exhaustion zones. This is not a buy/sell signal by itself — combine with your own analysis, confirmation tools, and risk management. Best Recommended time frame is 5 mins, 10 mins & 15 mins for intraday trading. 🧩 Unique features Groups multiple bars into a single clean ray, reducing clutter. Uses 4H RSI(3) regardless of the chart’s active timeframe. Fully customizable appearance (colors, thickness, max events). ⚠️ Disclaimer This script is provided for educational and informational purposes only. It does not constitute financial advice or guarantee performance. Always test thoroughly and use proper risk management before trading live.
Pine Script® göstergesi
Sensible_Trader tarafından
1
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading. "Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🤖 THE MACHINE LEARNING Gaussian Mixture Models (GMM): Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering : Models data as coming from multiple Gaussian distributions Each market regime is a different Gaussian component Provides probability of belonging to each regime More sophisticated than simple clustering Expectation-Maximization Algorithm: The indicator continuously learns and adapts using the E-M algorithm: E-step: Calculate probability of current market belonging to each regime M-step: Update regime parameters based on new data Continuous learning without repainting Adapts to changing market conditions ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 THREE MARKET REGIMES The GMM identifies three distinct market states: Regime 1 - Low Volatility: Quiet, ranging markets Uses RSI-based momentum calculation Reduces false signals in choppy conditions Background: Pink tint Regime 2 - Normal Market: Standard trending conditions Uses Rate of Change momentum Balanced sensitivity Background: Gray tint Regime 3 - High Volatility: Strong trends or volatility events Uses Z-score based momentum Captures extreme moves Background: Cyan tint ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 KEY INNOVATIONS 1. Probabilistic Regime Detection: Instead of binary regime assignment, provides probabilities: 30% Regime 1, 60% Regime 2, 10% Regime 3 Smooth transitions between regimes No sudden indicator jumps 2. Weighted Momentum Calculation: Combines three different momentum formulas Weights based on regime probabilities Automatically adapts to market conditions 3. Confidence Indicator: Shows how certain the model is (white line) High confidence = strong regime identification Low confidence = transitional market state Line transparency changes with confidence ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ PARAMETER OPTIMIZATION Training Period (50-500): 50-100: Quick adaptation to recent conditions 100: Balanced (default) 200-500: Stable regime identification Number of Components (2-5): 2: Simple bull/bear regimes 3: Low/Normal/High volatility (default) 4-5: More granular regime detection Learning Rate (0.1-1.0): 0.1-0.3: Slow, stable learning 0.3: Balanced (default) 0.5-1.0: Fast adaptation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING STRATEGIES Visual Signals: Cyan gradient: Bullish momentum Magenta gradient: Bearish momentum Background color: Current regime Confidence line: Model certainty 1. Regime-Based Trading: Regime 1 (pink): Expect mean reversion Regime 2 (gray): Standard trend following Regime 3 (cyan): Strong momentum trades 2. Confidence-Filtered Signals: Only trade when confidence > 70% High confidence = clearer market state Avoid transitions (low confidence) 3. Adaptive Position Sizing: Regime 1: Smaller positions (choppy) Regime 2: Normal positions Regime 3: Larger positions (trending) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 ADVANTAGES OVER OTHER ML INDICATORS vs K-Means Clustering: Soft clustering (probabilities) vs hard boundaries Captures uncertainty and transitions More mathematically robust vs KNN (K-Nearest Neighbors): Unsupervised learning (no historical labels needed) Continuous adaptation Lower computational complexity vs Neural Networks: Interpretable (know what each regime means) No overfitting issues Works with limited data ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 PERFORMANCE CHARACTERISTICS Best Market Conditions: Markets with clear regime shifts Volatile to trending transitions Multi-timeframe analysis Cryptocurrency markets (high regime variation) Key Strengths: Automatically adapts to market changes No manual parameter adjustment needed Smooth transitions between regimes Probabilistic confidence measure ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 TECHNICAL BACKGROUND Gaussian Mixture Models are used extensively in: Speech recognition (Google Assistant) Computer vision (facial recognition) Astronomy (galaxy classification) Genomics (gene expression analysis) Finance (risk modeling at investment banks) The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 PRO TIPS Watch regime transitions: Best opportunities often occur when regimes change Combine with volume: High volume + regime change = strong signal Use confidence filter: Avoid low confidence periods Multi-timeframe: Compare regimes across timeframes Adjust position size: Scale based on identified regime ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTES Machine learning adapts but doesn't predict the future Best used with other confirmation indicators Allow time for model to learn (100+ bars) Not financial advice - educational purposes Backtest thoroughly on your instruments ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 CONCLUSION The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides: Automatic adaptation to market conditions Clear regime identification with confidence levels Smooth, professional signal generation True unsupervised machine learning This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in: Google's speech recognition Tesla's computer vision NASA's data analysis Wall Street risk models "Let the machine learn the market regimes. Trade with statistical confidence." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt | Machine Learning Trading Systems Version: 1.0 Algorithm: Gaussian Mixture Model with E-M Classification: Unsupervised Learning Oscillator Not financial advice. Always DYOR.
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AlphaNatt tarafından
MatrixScalper Tablo + 3 Bant Osilatör MatrixScalper “Table + 3-Band Oscillator” is a lightweight, multi-timeframe trend-momentum filter that stacks three histograms (TF1/TF2/TF3—default 5m/15m/1h) and a compact table showing EMA trend, Supertrend, RSI and MACD direction for each timeframe. Green bars/✓ mean bullish alignment, red bars/✗ bearish; mixed or gray implies neutrality. Use it to trade with the higher-timeframe bias (e.g., look for longs when 15m & 60m are bullish and the 5m band flips back to green after a pullback). It’s a filter—not a standalone signal—so combine with price action/S&R/volume; optional alerts can be added for “all-bull” or “all-bear” alignment.
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NizamettinGOZEL tarafından
AI-Weighted RSI (Zeiierman)█ Overview AI-Weighted RSI (Zeiierman) is an adaptive oscillator that enhances classic RSI by applying a correlation-weighted prediction layer. Instead of looking only at RSI values directly, this indicator continuously evaluates how other price- and volume-based features (returns, volatility, volume shifts) correlate with RSI, and then weights them accordingly to project the next RSI state. The result is a smoother, forward-looking RSI framework that adapts to market conditions in real time. By leveraging feature correlation instead of static formulas, AI-Weighted RSI behaves like a lightweight learning model, adjusting its emphasis depending on which features are most aligned with RSI behavior during the current regime. █ How It Works ⚪ Feature Extraction Each bar, the script computes features: log returns, RSI itself, ATR% (volatility), volume, and volume log-change. ⚪ Correlation Screening Over a rolling learning window, it measures the correlation of each feature against RSI. The strongest relationships are ranked and selected. ⚪ Adaptive Weighting Features are standardized (z-scored), then combined using their signed correlations as weights, building a rolling, adaptive prediction of RSI. ⚪ Prediction to RSI Weight The predicted RSI is mapped back into a “weight” scale (±2 by default). Above 0 = bullish bias, below 0 = bearish bias, with color-graded fills to visualize overbought/oversold pressure. ⚪ Signal Line A smoothing option (signal length) overlays a moving average of the AI-Weighted RSI for clearer trend confirmation. █ Why AI-Weighted RSI ⚪ Adaptive to Market Regime Because the model re-evaluates correlations continuously, it naturally shifts which features dominate, sometimes volatility explains RSI best, sometimes volume, sometimes returns. ⚪ Forward-Looking Bias Instead of simply reflecting RSI, the model provides a projection, helping anticipate shifts in momentum before RSI itself flips. █ How to Use ⚪ Directional Bias Read the RSI relative to 0. Above = bullish momentum bias, below = bearish. ⚪ Overbought / Oversold Zones Shaded fills beyond +0.5 or -0.5 highlight extremes where RSI pressure often exhausts. ⚪ Divergences When price makes new highs/lows but AI-Weighted RSI fails to confirm, it often signals weakening momentum. █ Settings RSI Length: Lookback for the core RSI calculation. Signal Length: Smoothing applied to the AI-Weighted RSI output. Learning Window: Bars used for correlation learning and z-scoring. ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
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Zeiierman tarafından
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BUY & SELL Probability (M5..D1) - MTFMTF Probability Indicator (M5 to D1) Indicator — Dual Histogram with Buy/Sell Labels This indicator is designed to provide a probabilistic bias for bullish or bearish conditions by combining three different analytical components across multiple timeframes. The goal is to reduce noise from single-indicator signals and instead highlight confluence where trend, momentum, and strength agree. Why this combination is useful - EMA(200) Trend Filter: Identifies whether price is trading above or below a widely used long-term moving average. - MACD Momentum: Detects short-term directional momentum through line crossovers. - ADX Strength: Measures how strong the trend is, preventing signals in weak or flat markets. By combining these, the indicator avoids situations where one tool signals a trade but others do not, helping to filter out low-probability setups. How it works - Each timeframe (M5, M15, H1, H4, D1) generates its own trend, momentum, and strength score. - Scores are weighted according to user-defined importance and then aggregated into a single probability. - Proximity to recent support and resistance levels can adjust the final score, accounting for nearby barriers. - The final probability is displayed as: - Histogram (subwindow): Green bars for bullish probability >50%, red bars for bearish <50%. - On-chart labels: Showing exact buy/sell percentages on the last bar for quick reference. Inputs - EMA length (default 200), MACD settings, ADX period. - Weights for each timeframe and component (trend, momentum, strength). - Optional boost for the chart’s current timeframe. - Smoothing length for probability values. - Lookback period for support/resistance adjustment. How to use it - A green histogram above zero indicates bullish probability >50%. - A red histogram below zero indicates bearish probability >50%. - Neutral readings near 50% show low confluence and may be best avoided. - Users can adjust weights to emphasize higher or lower timeframes, depending on their trading style. Notes - This script does not guarantee profitable trades. - Best used together with price action, volume, or additional confirmation tools. - Signals are calculated only on closed bars to avoid repainting. - For testing and learning purposes — not financial advice.
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DenizTheTrader tarafından
RSI Pivots with Divergence Overlay█ OVERVIEW The RSI Pivots with Divergence Overlay indicator is an advanced tool based on RSI, displaying dynamic bands on the price chart to simplify the identification of overbought and oversold conditions. Pivot points and divergences between them are derived from these bands, providing a comprehensive view of the market and enabling the creation of various trading strategies based on this single indicator. █ CONCEPTS Areas where RSI exits the bands are often reversal points in the market. The concept of this indicator is to highlight places where the probability of a trend reversal increases. Therefore, pivots and divergences have been added to better identify these key moments. Additionally, the bands allow viewing the market context in relation to the RSI indicator, facilitating analysis of momentum and volatility. █ KEY FEATURES Dynamic Bands and RSI Signals: The bands are calculated based on the closing price and RSI value, with dynamic scaling adjusted to market volatility. The upper band corresponds to overbought levels, the lower to oversold, and the midline is their average. The price level relative to the bands serves as a visual RSI signal, indicating potential overbought or oversold conditions. Pivot Points: The indicator identifies local price highs and lows in relation to RSI levels. The pivot level is taken from the high/low of the candle. A high pivot is detected when the high of the candle reaches a local maximum after crossing the upper RSI level (overbought), signaling a potential reversal. A low pivot appears after a local price minimum following a drop below the lower RSI level (oversold), indicating a possible uptrend reversal. The pivot length (default 2 bars) defines the search range for these extremes, meaning that with a length of 2, a potential divergence signal will appear with a 2-candle delay, as this is the minimum time required to confirm a local pivot. Pivot lines are drawn on the chart, and labels display the RSI value (from the close of the candle) and price at the detection moment. Pivot lines disappear after the detection of the next low pivot for lower lines and high pivot for upper lines, but unbreached lines or those with high volume may still serve as support or resistance levels. Divergence Detection: The indicator automatically detects divergences to predict trend changes. Bearish divergence occurs when the price forms a higher high pivot, but the RSI (from the close of the candle) is lower than in the previous pivot, indicating weakening upward momentum and a potential bearish reversal. Bullish divergence appears when the price forms a lower low pivot, but the RSI is higher, suggesting building momentum and a possible bullish reversal. Divergences are marked in pivot labels (e.g., "Bear Div" or "Bull Div") and supported by alerts upon detection. Return Signals: The indicator generates buy and sell signals based on RSI (price) returning to the bands after extreme conditions, independently of pivots and divergences. A buy signal is triggered when RSI (price) crosses above the lower level (exiting oversold), suggesting a potential price rise toward the midline or upper band. A sell signal occurs when RSI (price) falls below the upper level (exiting overbought), indicating a possible price drop toward the lower band. Signals are visualized as arrows (up/down triangles) on the chart, with customizable colors. █ CONFIGURATION The indicator offers extensive customization options: RSI Length (rsiLength): Sets the number of periods used to calculate RSI (default 14). RSI Upper Level (rsiUpper): Defines the overbought threshold (default 70). RSI Lower Level (rsiLower): Defines the oversold threshold (default 30). Band Scaling (scale): Determines the scaling multiplier for bands based on market volatility (default 15.0). SMA Length for Candle Midpoint (length): Number of periods for calculating the moving average of candle midpoints (default 200). This parameter is used to smooth price data, enabling more accurate volatility assessment and band width adjustment to market dynamics. Pivot Length (pivotLength): Sets the range (in bars) for detecting local price extremes (default 2). Pivot Label Offset (pivotLabelOffset): Multiplier for the candle range to position pivot labels (default 0.3). Show Bands (showBands): Enables/disables the display of bands on the chart. Show Fill (showFill): Enables/disables the fill between bands and the midline. Show Pivot Lines (showPivotLines): Enables/disables pivot lines on the chart. Show Pivot Labels (showPivotLabels): Enables/disables labels with RSI and price values at pivots. Show Return Signals (showReturnSignals): Enables/disables the display of buy and sell signals. Colors and Style: Customizable colors for bands, fills, pivot lines, labels, and line widths (default 1). █ USAGE The indicator performs best when combined with other technical analysis tools, such as Fibonacci levels, moving averages, or trendlines, to confirm pivot, divergence, and return signals. It enables traders to identify key reversal points, detect hidden trend weaknesses through divergences, and confirm trade entries with return signals. Usage Examples: Price bounces off a previous pivot with high volume – this increases the probability of a trend change or correction. A similar situation when RSI is outside the bands strengthens the signal. If divergence occurs in addition, we have further confirmation. This can be combined with Fibonacci levels to check if Fibo zones overlap with pivot lines – this may increase the chance of a strong price reaction. █ ALERTS The indicator supports alerts for: Buy and sell signals (RSI returning to bands). Detection of bearish and bullish divergences.
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Uncle_the_shooter tarafından