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RSI Full Forecast [Titans_Invest]RSI Full Forecast Get ready to experience the ultimate evolution of RSI-based indicators – the RSI Full Forecast, a boosted and even smarter version of the already powerful: RSI Forecast Now featuring over 40 additional entry conditions (forecasts), this indicator redefines the way you view the market. AI-Powered RSI Forecasting: Using advanced linear regression with the least squares method – a solid foundation for machine learning - the RSI Full Forecast enables you to predict future RSI behavior with impressive accuracy. But that’s not all: this new version also lets you monitor future crossovers between the RSI and the MA RSI, delivering early and strategic signals that go far beyond traditional analysis. You’ll be able to monitor future crossovers up to 20 bars ahead, giving you an even broader and more precise view of market movements. See the Future, Now: • Track upcoming RSI & RSI MA crossovers in advance. • Identify potential reversal zones before price reacts. • Uncover statistical behavior patterns that would normally go unnoticed. 40+ Intelligent Conditions: The new layer of conditions is designed to detect multiple high-probability scenarios based on historical patterns and predictive modeling. Each additional forecast is a window into the price's future, powered by robust mathematics and advanced algorithmic logic. Full Customization: All parameters can be tailored to fit your strategy – from smoothing periods to prediction sensitivity. You have complete control to turn raw data into smart decisions. Innovative, Accurate, Unique: This isn’t just an upgrade. It’s a quantum leap in technical analysis. RSI Full Forecast is the first of its kind: an indicator that blends statistical analysis, machine learning, and visual design to create a true real-time predictive system. ⯁ SCIENTIFIC BASIS LINEAR REGRESSION Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥. The general formula for a simple linear regression is given by: y = β₀ + β₁x + ε β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²) β₀ = ȳ - β₁x̄ Where: y   = is the predicted variable (e.g. future value of RSI) x ​​  = is the explanatory variable (e.g. time or bar index) β0 = is the intercept (value of 𝑦 when 𝑥 = 0) 𝛽1 = is the slope of the line (rate of change) ε   = is the random error term The goal is to estimate the coefficients 𝛽0 and 𝛽1 ​​so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares. ⯁ LEAST SQUARES ESTIMATION To minimize the error between predicted and observed values, we use the following formulas: β₁ = / β₀ = ȳ - β₁x̄ Where: ∑ = sum x̄ = mean of x ȳ = mean of y x_i, y_i = individual values ​​of the variables. Where: x_i and y_i are the means of the independent and dependent variables, respectively. i ranges from 1 to n, the number of observations. These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity. ⯁ LINEAR REGRESSION IN MACHINE LEARNING Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies. By applying this model to the RSI, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis. ⯁ VISUAL INTERPRETATION Imagine an RSI time series like this: Time → RSI    → The regression line will smooth these values ​​and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted RSI, which can be crossed with the actual RSI to generate more intelligent signals. ⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED Linear Regression Models the relationship between variables using a straight line. Least Squares Minimizes the sum of squared errors between prediction and reality. Time Series Forecasting Estimates future values ​​based on historical data. Supervised Learning Trains models to predict outputs from known inputs. Statistical Smoothing Reduces noise and reveals underlying trends. ⯁ WHY THIS INDICATOR IS REVOLUTIONARY Scientifically-based: Based on statistical theory and mathematical inference. Unprecedented: First public RSI with least squares predictive modeling. Intelligent: Built with machine learning logic. Practical: Generates forward-thinking signals. Customizable: Flexible for any trading strategy. ⯁ CONCLUSION By combining RSI with linear regression, this indicator allows a trader to predict market momentum, not just follow it. RSI Full Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology. ⯁ Example of simple linear regression, which has one independent variable: ⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ). ⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values ​​using Matlab: ⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables. ⯁ The result of fitting a set of data points with a quadratic function: _________________________________________________ 🔮 Linear Regression: PineScript Technical Parameters 🔮 _________________________________________________ Forecast Types: • Flat: Assumes prices will remain the same. • Linreg: Makes a 'Linear Regression' forecast for n periods. Technical Information: ta.linreg (built-in function) Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values ​​calculated using the least squares method on the source series. Syntax: • Function: ta.linreg() Parameters: • source: Source price series. • length: Number of bars (period). • offset: Offset. • return: Linear regression curve. This function has been cleverly applied to the RSI, making it capable of projecting future values ​​based on past statistical trends. ______________________________________________________ ______________________________________________________ ⯁ WHAT IS THE RSI❓ The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend. ⯁ HOW TO USE THE RSI❓ The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:   •  Overbought: When the RSI is above 70, indicating that the asset may be overbought.   •  Oversold: When the RSI is below 30, indicating that the asset may be oversold.   •  Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions. ______________________________________________________ ______________________________________________________ ⯁ ENTRY CONDITIONS The conditions below are fully flexible and allow for complete customization of the signal. ______________________________________________________ ______________________________________________________ 🔹 CONDITIONS TO BUY 📈 ______________________________________________________   •  Signal Validity: The signal will remain valid for X bars .   •  Signal Sequence: Configurable as AND or OR . 📈 RSI Conditions: 🔹 RSI > Upper 🔹 RSI < Upper 🔹 RSI > Lower 🔹 RSI < Lower 🔹 RSI > Middle 🔹 RSI < Middle 🔹 RSI > MA 🔹 RSI < MA 📈 MA Conditions: 🔹 MA > Upper 🔹 MA < Upper 🔹 MA > Lower 🔹 MA < Lower 📈 Crossovers: 🔹 RSI (Crossover) Upper 🔹 RSI (Crossunder) Upper 🔹 RSI (Crossover) Lower 🔹 RSI (Crossunder) Lower 🔹 RSI (Crossover) Middle 🔹 RSI (Crossunder) Middle 🔹 RSI (Crossover) MA 🔹 RSI (Crossunder) MA 🔹 MA (Crossover) Upper 🔹 MA (Crossunder) Upper 🔹 MA (Crossover) Lower 🔹 MA (Crossunder) Lower 📈 RSI Divergences: 🔹 RSI Divergence Bull 🔹 RSI Divergence Bear 📈 RSI Forecast: 🔹 RSI (Crossover) MA Forecast 🔹 RSI (Crossunder) MA Forecast 🔹 RSI Forecast 1 > MA Forecast 1 🔹 RSI Forecast 1 < MA Forecast 1 🔹 RSI Forecast 2 > MA Forecast 2 🔹 RSI Forecast 2 < MA Forecast 2 🔹 RSI Forecast 3 > MA Forecast 3 🔹 RSI Forecast 3 < MA Forecast 3 🔹 RSI Forecast 4 > MA Forecast 4 🔹 RSI Forecast 4 < MA Forecast 4 🔹 RSI Forecast 5 > MA Forecast 5 🔹 RSI Forecast 5 < MA Forecast 5 🔹 RSI Forecast 6 > MA Forecast 6 🔹 RSI Forecast 6 < MA Forecast 6 🔹 RSI Forecast 7 > MA Forecast 7 🔹 RSI Forecast 7 < MA Forecast 7 🔹 RSI Forecast 8 > MA Forecast 8 🔹 RSI Forecast 8 < MA Forecast 8 🔹 RSI Forecast 9 > MA Forecast 9 🔹 RSI Forecast 9 < MA Forecast 9 🔹 RSI Forecast 10 > MA Forecast 10 🔹 RSI Forecast 10 < MA Forecast 10 🔹 RSI Forecast 11 > MA Forecast 11 🔹 RSI Forecast 11 < MA Forecast 11 🔹 RSI Forecast 12 > MA Forecast 12 🔹 RSI Forecast 12 < MA Forecast 12 🔹 RSI Forecast 13 > MA Forecast 13 🔹 RSI Forecast 13 < MA Forecast 13 🔹 RSI Forecast 14 > MA Forecast 14 🔹 RSI Forecast 14 < MA Forecast 14 🔹 RSI Forecast 15 > MA Forecast 15 🔹 RSI Forecast 15 < MA Forecast 15 🔹 RSI Forecast 16 > MA Forecast 16 🔹 RSI Forecast 16 < MA Forecast 16 🔹 RSI Forecast 17 > MA Forecast 17 🔹 RSI Forecast 17 < MA Forecast 17 🔹 RSI Forecast 18 > MA Forecast 18 🔹 RSI Forecast 18 < MA Forecast 18 🔹 RSI Forecast 19 > MA Forecast 19 🔹 RSI Forecast 19 < MA Forecast 19 🔹 RSI Forecast 20 > MA Forecast 20 🔹 RSI Forecast 20 < MA Forecast 20 ______________________________________________________ ______________________________________________________ 🔸 CONDITIONS TO SELL 📉 ______________________________________________________   •  Signal Validity: The signal will remain valid for X bars .   •  Signal Sequence: Configurable as AND or OR . 📉 RSI Conditions: 🔸 RSI > Upper 🔸 RSI < Upper 🔸 RSI > Lower 🔸 RSI < Lower 🔸 RSI > Middle 🔸 RSI < Middle 🔸 RSI > MA 🔸 RSI < MA 📉 MA Conditions: 🔸 MA > Upper 🔸 MA < Upper 🔸 MA > Lower 🔸 MA < Lower 📉 Crossovers: 🔸 RSI (Crossover) Upper 🔸 RSI (Crossunder) Upper 🔸 RSI (Crossover) Lower 🔸 RSI (Crossunder) Lower 🔸 RSI (Crossover) Middle 🔸 RSI (Crossunder) Middle 🔸 RSI (Crossover) MA 🔸 RSI (Crossunder) MA 🔸 MA (Crossover) Upper 🔸 MA (Crossunder) Upper 🔸 MA (Crossover) Lower 🔸 MA (Crossunder) Lower 📉 RSI Divergences: 🔸 RSI Divergence Bull 🔸 RSI Divergence Bear 📉 RSI Forecast: 🔸 RSI (Crossover) MA Forecast 🔸 RSI (Crossunder) MA Forecast 🔸 RSI Forecast 1 > MA Forecast 1 🔸 RSI Forecast 1 < MA Forecast 1 🔸 RSI Forecast 2 > MA Forecast 2 🔸 RSI Forecast 2 < MA Forecast 2 🔸 RSI Forecast 3 > MA Forecast 3 🔸 RSI Forecast 3 < MA Forecast 3 🔸 RSI Forecast 4 > MA Forecast 4 🔸 RSI Forecast 4 < MA Forecast 4 🔸 RSI Forecast 5 > MA Forecast 5 🔸 RSI Forecast 5 < MA Forecast 5 🔸 RSI Forecast 6 > MA Forecast 6 🔸 RSI Forecast 6 < MA Forecast 6 🔸 RSI Forecast 7 > MA Forecast 7 🔸 RSI Forecast 7 < MA Forecast 7 🔸 RSI Forecast 8 > MA Forecast 8 🔸 RSI Forecast 8 < MA Forecast 8 🔸 RSI Forecast 9 > MA Forecast 9 🔸 RSI Forecast 9 < MA Forecast 9 🔸 RSI Forecast 10 > MA Forecast 10 🔸 RSI Forecast 10 < MA Forecast 10 🔸 RSI Forecast 11 > MA Forecast 11 🔸 RSI Forecast 11 < MA Forecast 11 🔸 RSI Forecast 12 > MA Forecast 12 🔸 RSI Forecast 12 < MA Forecast 12 🔸 RSI Forecast 13 > MA Forecast 13 🔸 RSI Forecast 13 < MA Forecast 13 🔸 RSI Forecast 14 > MA Forecast 14 🔸 RSI Forecast 14 < MA Forecast 14 🔸 RSI Forecast 15 > MA Forecast 15 🔸 RSI Forecast 15 < MA Forecast 15 🔸 RSI Forecast 16 > MA Forecast 16 🔸 RSI Forecast 16 < MA Forecast 16 🔸 RSI Forecast 17 > MA Forecast 17 🔸 RSI Forecast 17 < MA Forecast 17 🔸 RSI Forecast 18 > MA Forecast 18 🔸 RSI Forecast 18 < MA Forecast 18 🔸 RSI Forecast 19 > MA Forecast 19 🔸 RSI Forecast 19 < MA Forecast 19 🔸 RSI Forecast 20 > MA Forecast 20 🔸 RSI Forecast 20 < MA Forecast 20 ______________________________________________________ ______________________________________________________ 🤖 AUTOMATION 🤖 • You can automate the BUY and SELL signals of this indicator. ______________________________________________________ ______________________________________________________ ⯁ UNIQUE FEATURES ______________________________________________________ Linear Regression: (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Condition Table: BUY/SELL Condition Labels: BUY/SELL Plot Labels in the Graph Above: BUY/SELL Automate and Monitor Signals/Alerts: BUY/SELL Linear Regression (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Condition Table: BUY/SELL Condition Labels: BUY/SELL Plot Labels in the Graph Above: BUY/SELL Automate and Monitor Signals/Alerts: BUY/SELL ______________________________________________________ 📜 SCRIPT : RSI Full Forecast 🎴 Art by  : @Titans_Invest & @DiFlip 👨‍💻 Dev by : @Titans_Invest & @DiFlip 🎑 Titans Invest — The Wizards Without Gloves 🧤 ✨ Enjoy! ______________________________________________________ o Mission 🗺 • Inspire Traders to manifest Magic in the Market. o Vision 𐓏 • To elevate collective Energy 𐓷𐓏
Pine Script® indicator
by Titans_Invest
RSI Donchian Channel [DCAUT]█ RSI Donchian Channel 📊 ORIGINALITY & INNOVATION The RSI Donchian Channel represents an important synthesis of two complementary analytical frameworks: momentum oscillators and breakout detection systems. This indicator addresses a common limitation in traditional RSI analysis by replacing fixed overbought/oversold thresholds with adaptive zones derived from historical RSI extremes. Key Enhancement: Traditional RSI analysis relies on static threshold levels (typically 30/70), which may not adequately reflect changing market volatility regimes. This indicator adapts the reference zones dynamically based on the actual RSI behavior over the lookback period, helping traders identify meaningful momentum extremes relative to recent price action rather than arbitrary fixed levels. The implementation combines the proven momentum measurement capabilities of RSI with Donchian Channel's breakout detection methodology, creating a framework that identifies both momentum exhaustion points and potential continuation signals through the same analytical lens. 📐 MATHEMATICAL FOUNDATION Core Calculation Process: Step 1: RSI Calculation The Relative Strength Index measures momentum by comparing the magnitude of recent gains to recent losses: Calculate price changes between consecutive periods Separate positive changes (gains) from negative changes (losses) Apply selected smoothing method (RMA standard, also supports SMA, EMA, WMA) to both gain and loss series Compute Relative Strength (RS) as the ratio of smoothed gains to smoothed losses Transform RS into bounded 0-100 scale using the formula: RSI = 100 - (100 / (1 + RS)) Step 2: Donchian Channel Application The Donchian Channel identifies the highest and lowest RSI values within the specified lookback period: Upper Channel: Highest RSI value over the lookback period, represents the recent momentum peak Lower Channel: Lowest RSI value over the lookback period, represents the recent momentum trough Middle Channel (Basis): Average of upper and lower channels, serves as equilibrium reference Channel Width Dynamics: The distance between upper and lower channels reflects RSI volatility. Wide channels indicate high momentum variability, while narrow channels suggest momentum consolidation and potential breakout preparation. The indicator monitors channel width over a 100-period window to identify squeeze conditions that often precede significant momentum shifts. 📊 COMPREHENSIVE SIGNAL ANALYSIS Primary Signal Categories: Breakout Signals: Upper Breakout: RSI crosses above the upper channel, indicates momentum reaching new relative highs and potential trend continuation, particularly significant when accompanied by price confirmation Lower Breakout: RSI crosses below the lower channel, suggests momentum reaching new relative lows and potential trend exhaustion or reversal setup Breakout strength is enhanced when the channel is narrow prior to the breakout, indicating a transition from consolidation to directional movement Mean Reversion Signals: Upper Touch Without Breakout: RSI reaches the upper channel but fails to break through, may indicate momentum exhaustion and potential reversal opportunity Lower Touch Without Breakout: RSI reaches the lower channel without breakdown, suggests potential bounce as momentum reaches oversold extremes Return to Basis: RSI moving back toward the middle channel after touching extremes signals momentum normalization Trend Strength Assessment: Sustained Upper Channel Riding: RSI consistently remains near or above the upper channel during strong uptrends, indicates persistent bullish momentum Sustained Lower Channel Riding: RSI stays near or below the lower channel during strong downtrends, reflects persistent bearish pressure Basis Line Position: RSI position relative to the middle channel helps identify the prevailing momentum bias Channel Compression Patterns: Squeeze Detection: Channel width narrowing to 100-period lows indicates momentum consolidation, often precedes significant directional moves Expansion Phase: Channel widening after a squeeze confirms the initiation of a new momentum regime Persistent Narrow Channels: Extended periods of tight channels suggest market indecision and accumulation/distribution phases 🎯 STRATEGIC APPLICATIONS Trend Continuation Strategy: This approach focuses on identifying and trading momentum breakouts that confirm established trends: Identify the prevailing price trend using higher timeframe analysis or trend-following indicators Wait for RSI to break above the upper channel in uptrends (or below the lower channel in downtrends) Enter positions in the direction of the breakout when price action confirms the momentum shift Place protective stops below the recent swing low (long positions) or above swing high (short positions) Target profit levels based on prior swing extremes or use trailing stops to capture extended moves Exit when RSI crosses back through the basis line in the opposite direction Mean Reversion Strategy: This method capitalizes on momentum extremes and subsequent corrections toward equilibrium: Monitor for RSI reaching the upper or lower channel boundaries Look for rejection signals (price reversal patterns, volume divergence) when RSI touches the channels Enter counter-trend positions when RSI begins moving back toward the basis line Use the basis line as the initial profit target for mean reversion trades Implement tight stops beyond the channel extremes to limit risk on failed reversals Scale out of positions as RSI approaches the basis line and closes the position when RSI crosses the basis Breakout Preparation Strategy: This approach positions traders ahead of potential volatility expansion from consolidation phases: Identify squeeze conditions when channel width reaches 100-period lows Monitor price action for consolidation patterns (triangles, rectangles, flags) during the squeeze Prepare conditional orders for breakouts in both directions from the consolidation Enter positions when RSI breaks out of the narrow channel with expanding width Use the channel width expansion as a confirmation signal for the breakout's validity Manage risk with stops just inside the opposite channel boundary Multi-Timeframe Confluence Strategy: Combining RSI Donchian Channel analysis across multiple timeframes can improve signal reliability: Identify the primary trend direction using a higher timeframe RSI Donchian Channel (e.g., daily or weekly) Use a lower timeframe (e.g., 4-hour or hourly) to time precise entry points Enter long positions when both timeframes show RSI above their respective basis lines Enter short positions when both timeframes show RSI below their respective basis lines Avoid trades when timeframes provide conflicting signals (e.g., higher timeframe below basis, lower timeframe above) Exit when the higher timeframe RSI crosses its basis line in the opposite direction Risk Management Guidelines: Effective risk management is essential for all RSI Donchian Channel strategies: Position Sizing: Calculate position sizes based on the distance between entry point and stop loss, limiting risk to 1-2% of capital per trade Stop Loss Placement: For breakout trades, place stops just inside the opposite channel boundary; for mean reversion trades, use stops beyond the channel extremes Profit Targets: Use the basis line as a minimum target for mean reversion trades; for trend trades, target prior swing extremes or use trailing stops Channel Width Context: Increase position sizes during narrow channels (lower volatility) and reduce sizes during wide channels (higher volatility) Correlation Awareness: Monitor correlations between traded instruments to avoid over-concentration in similar setups 📋 DETAILED PARAMETER CONFIGURATION RSI Source: Defines the price data series used for RSI calculation: Close (Default): Standard choice providing end-of-period momentum assessment, suitable for most trading styles and timeframes High-Low Average (HL2): Reduces the impact of closing auction dynamics, useful for markets with significant end-of-day volatility High-Low-Close Average (HLC3): Provides a more balanced view incorporating the entire period's range Open-High-Low-Close Average (OHLC4): Offers the most comprehensive price representation, helpful for identifying overall period sentiment Strategy Consideration: Use Close for end-of-period signals, HL2 or HLC3 for intraday volatility reduction, OHLC4 for capturing full period dynamics RSI Length: Controls the number of periods used for RSI calculation: Short Periods (5-9): Highly responsive to recent price changes, produces more frequent signals with increased false signal risk, suitable for short-term trading and volatile markets Standard Period (14): Widely accepted default balancing responsiveness with stability, appropriate for swing trading and intermediate-term analysis Long Periods (21-28): Produces smoother RSI with fewer signals but more reliable trend identification, better for position trading and reducing noise in choppy markets Optimization Approach: Test different lengths against historical data for your specific market and timeframe, consider using longer periods in ranging markets and shorter periods in trending markets RSI MA Type: Determines the smoothing method applied to price changes in RSI calculation: RMA (Relative Moving Average - Default): Wilder's original smoothing method providing stable momentum measurement with gradual response to changes, maintains consistency with classical RSI interpretation SMA (Simple Moving Average): Treats all periods equally, responds more quickly to changes than RMA but may produce more whipsaws in volatile conditions EMA (Exponential Moving Average): Weights recent periods more heavily, increases responsiveness at the cost of potential noise, suitable for traders prioritizing early signal generation WMA (Weighted Moving Average): Applies linear weighting favoring recent data, offers a middle ground between SMA and EMA responsiveness Selection Guidance: Maintain RMA for consistency with traditional RSI analysis, use EMA or WMA for more responsive signals in fast-moving markets, apply SMA for maximum simplicity and transparency DC Length: Specifies the lookback period for Donchian Channel calculation on RSI values: Short Periods (10-14): Creates tight channels that adapt quickly to changing momentum conditions, generates more frequent trading signals but increases sensitivity to short-term RSI fluctuations Standard Period (20): Balances channel responsiveness with stability, aligns with traditional Bollinger Bands and moving average periods, suitable for most trading styles Long Periods (30-50): Produces wider, more stable channels that better represent sustained momentum extremes, reduces signal frequency while improving reliability, appropriate for position traders and higher timeframes Calibration Strategy: Match DC length to your trading timeframe (shorter for day trading, longer for swing trading), test channel width behavior during different market regimes, consider using adaptive periods that adjust to volatility conditions Market Adaptation: Use shorter DC lengths in trending markets to capture momentum shifts earlier, apply longer periods in ranging markets to filter noise and focus on significant extremes Parameter Combination Recommendations: Scalping/Day Trading: RSI Length 5-9, DC Length 10-14, EMA or WMA smoothing for maximum responsiveness Swing Trading: RSI Length 14, DC Length 20, RMA smoothing for balanced analysis (default configuration) Position Trading: RSI Length 21-28, DC Length 30-50, RMA or SMA smoothing for stable signals High Volatility Markets: Longer RSI periods (21+) with standard DC length (20) to reduce noise Low Volatility Markets: Standard RSI length (14) with shorter DC length (10-14) to capture subtle momentum shifts 📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES Adaptive Threshold Mechanism: Unlike traditional RSI analysis with fixed 30/70 thresholds, this indicator's Donchian Channel approach provides several improvements: Context-Aware Extremes: Overbought/oversold levels adjust automatically based on recent momentum behavior rather than arbitrary fixed values Volatility Adaptation: In low volatility periods, channels narrow to reflect tighter momentum ranges; in high volatility, channels widen appropriately Market Regime Recognition: The indicator implicitly adapts to different market conditions without manual threshold adjustments False Signal Reduction: Adaptive channels help reduce premature reversal signals that often occur with fixed thresholds during strong trends Signal Quality Characteristics: The indicator's dual-purpose design provides distinct advantages for different trading objectives: Breakout Trading: Channel boundaries offer clear, objective breakout levels that update dynamically, eliminating the ambiguity of when momentum becomes "too high" or "too low" Mean Reversion: The basis line provides a natural profit target for reversion trades, representing the midpoint of recent momentum extremes Trend Strength: Persistent channel boundary riding offers an objective measure of trend strength without additional indicators Consolidation Detection: Channel width analysis provides early warning of potential volatility expansion from compression phases Comparative Analysis: When compared to traditional RSI implementations and other momentum frameworks: vs. Fixed Threshold RSI: Provides market-adaptive reference levels rather than static values, helping to reduce false signals during trending markets where RSI can remain "overbought" or "oversold" for extended periods vs. RSI Bollinger Bands: Offers clearer breakout signals and more intuitive extreme identification through actual high/low boundaries rather than statistical standard deviations vs. Stochastic Oscillator: Maintains RSI's momentum measurement advantages (unbounded calculation avoiding scale compression) while adding the breakout detection capabilities of Donchian Channels vs. Standard Donchian Channels: Applies breakout methodology to momentum space rather than price, providing earlier signals of potential trend changes before price breakouts occur Performance Characteristics: The indicator exhibits specific behavioral patterns across different market conditions: Trending Markets: Excels at identifying momentum continuation through channel breakouts, RSI tends to ride one channel boundary during strong trends, providing trend confirmation Ranging Markets: Channel width narrows during consolidation, offering early preparation signals for potential breakout trading opportunities High Volatility: Channels widen to reflect increased momentum variability, automatically adjusting signal sensitivity to match market conditions Low Volatility: Channels contract, making the indicator more sensitive to subtle momentum shifts that may be significant in calm market environments Transition Periods: Channel squeezes often precede major trend changes, offering advance warning of potential regime shifts Limitations and Considerations: Users should be aware of certain operational characteristics: Lookback Dependency: Channel boundaries depend entirely on the lookback period, meaning the indicator has no predictive element beyond identifying current momentum relative to recent history Lag Characteristics: As with all moving average-based indicators, RSI calculation introduces lag, and channel boundaries update only as new extremes occur within the lookback window Range-Bound Sensitivity: In extremely tight ranges, channels may become very narrow, potentially generating excessive signals from minor momentum fluctuations Trending Persistence: During very strong trends, RSI may remain at channel extremes for extended periods, requiring patience for mean reversion setups or commitment to trend-following approaches No Absolute Levels: Unlike traditional RSI, this indicator provides no fixed reference points (like 50), making it less suitable for strategies that depend on absolute momentum readings USAGE NOTES This indicator is designed for technical analysis and educational purposes to help traders understand momentum dynamics and identify potential trading opportunities. The RSI Donchian Channel has limitations and should not be used as the sole basis for trading decisions. Important considerations: Performance varies significantly across different market conditions, timeframes, and instruments Historical signal patterns do not guarantee future results, as market behavior continuously evolves Effective use requires understanding of both RSI momentum principles and Donchian Channel breakout concepts Risk management practices (stop losses, position sizing, diversification) are essential for any trading application Consider combining with additional analytical tools such as volume analysis, price action patterns, or trend indicators for confirmation Backtest thoroughly on your specific instruments and timeframes before live trading implementation Be aware that optimization on historical data may lead to curve-fitting and poor forward performance The indicator performs best when used as part of a comprehensive trading methodology that incorporates multiple forms of market analysis, sound risk management, and realistic expectations about win rates and drawdowns.
Pine Script® indicator
by DCAUT
RSI Zones Background + Optional RSI PaneOverview This Pine Script indicator does two things at once: Colors the background of the main price chart whenever the RSI value is below a lower threshold (default 30) or above an upper threshold (default 70). This highlights oversold and overbought zones directly on the price chart itself. Optionally displays a separate RSI panel with the RSI line and shaded region between the two threshold levels for reference. The indicator is fully customizable through the settings panel—color choices, transparency, and whether to show the separate RSI pane can all be adjusted. Key Parts of the Code 1. Inputs src: The source price series for RSI calculation. len: RSI lookback length (default 14). lowerThr and upperThr: The lower and upper thresholds (defaults: 30 and 70). lowColor and highColor: Colors for the background when RSI is below or above the thresholds. bgTrans: Transparency level for the background shading. showRSI: Boolean to toggle the optional RSI pane on or off. 2. RSI Calculation rsi = ta.rsi(src, len) This computes the RSI from the chosen price source. 3. Background Coloring on the Price Chart bgCol = rsi <= lowerThr ? color.new(lowColor,bgTrans) : rsi >= upperThr ? color.new(highColor,bgTrans) : na bgcolor(bgCol) If RSI ≤ lower threshold: background turns lowColor (oversold zone). If RSI ≥ upper threshold: background turns highColor (overbought zone). Otherwise, no background color. 4. Optional RSI Pane plot(showRSI ? rsi : na, display=display.pane) Plots the RSI line in a separate pane when showRSI is true; otherwise hides it. 5. Horizontal Lines for Thresholds hLower = hline(lowerThr, ...) hUpper = hline(upperThr, ...) Two horizontal lines at the lower and upper thresholds. Because hline() can’t be wrapped inside if blocks, the script always creates them but makes them transparent (using na color) when the pane is hidden. 6. Filling Between Threshold Lines fill(hLower, hUpper, color=showRSI ? color.new(color.gray,95) : na) When the RSI pane is visible, the area between the two threshold lines is shaded in gray to create a “mid-zone” effect. This fill also switches off (becomes na) if the pane is hidden. 7. Alerts The script also includes two alert conditions: When RSI crosses below the lower threshold. When RSI crosses above the upper threshold. How It Works in Practice On the price chart, you’ll see the background turn blue (or your chosen color) when RSI is ≤30, and red when RSI is ≥70. If you enable “Show RSI” in the settings, a separate RSI pane will appear below the price chart, plotting the RSI line with two threshold lines and a shaded region in between. You can fully adjust transparency and colors to suit your chart style. Benefits Quickly visualize overbought and oversold conditions without opening a separate RSI window. Optional RSI pane provides context when needed. Customizable colors and transparency make it easy to integrate with any chart theme. Alerts give you automatic notifications when RSI crosses key levels. ------------------------------------------------------------------------------------------------------------------ 개요 이 지표는 두 가지 기능을 동시에 수행합니다. 가격 차트 뒤 배경에 색상 표시 RSI 값이 설정한 하단 임계값(기본 30) 이하이거나 상단 임계값(기본 70) 이상일 때, 가격 차트 뒤쪽에 과매도·과매수 구간을 색으로 표시해줍니다. 선택적으로 RSI 보조창 표시 옵션을 켜면 별도의 RSI 패널이 나타나서 RSI 라인과 두 임계값(30, 70)을 연결한 구간을 음영 처리하여 보여줍니다. 설정 창에서 색상·투명도·보조창 표시 여부를 전부 조정할 수 있습니다. 코드 핵심 설명 1. 입력값 src: RSI 계산에 사용할 가격 소스(기본 종가). len: RSI 기간(기본 14). lowerThr / upperThr: RSI 하단·상단 임계값(기본 30, 70). lowColor / highColor: RSI가 각각 하단 이하·상단 이상일 때 배경 색상. bgTrans: 배경 투명도(0=불투명, 100=투명). showRSI: RSI 보조창을 켜고 끌 수 있는 스위치. 2. RSI 계산 rsi = ta.rsi(src, len) 지정한 가격 소스를 기반으로 RSI를 계산합니다. 3. 가격 차트 배경 색칠 bgCol = rsi <= lowerThr ? color.new(lowColor,bgTrans) : rsi >= upperThr ? color.new(highColor,bgTrans) : na bgcolor(bgCol) RSI ≤ 하단 임계값 → lowColor(과매도 색) RSI ≥ 상단 임계값 → highColor(과매수 색) 나머지 구간은 색상 없음. 4. 선택적 RSI 보조창 plot(showRSI ? rsi : na, display=display.pane) showRSI가 켜져 있으면 RSI 라인을 보조창에 표시하고, 꺼져 있으면 숨깁니다. 5. 임계값 가로선 hLower = hline(lowerThr, ...) hUpper = hline(upperThr, ...) 하단·상단 임계값을 가로선으로 표시합니다. hline은 if 블록 안에서 쓸 수 없기 때문에 항상 그려지지만, 보조창이 꺼지면 색을 na로 처리해 안 보이게 합니다. 6. 임계값 사이 영역 음영 처리 fill(hLower, hUpper, color=showRSI ? color.new(color.gray,95) : na) 보조창이 켜져 있을 때만 두 가로선 사이를 회색으로 채워 “중립 구간”을 강조합니다. 7. 알림 조건 RSI가 하단 임계값을 아래로 돌파할 때 알림. RSI가 상단 임계값을 위로 돌파할 때 알림. 실제 작동 모습 가격 차트 뒤쪽에 RSI ≤30이면 파란색, RSI ≥70이면 빨간색 배경이 나타납니다(색상은 설정에서 변경 가능). RSI 보조창을 켜면, RSI 라인과 임계값 가로선, 그리고 그 사이 음영 영역이 함께 나타납니다. 투명도를 높이거나 낮추어 강조 정도를 조절할 수 있습니다. 장점 별도의 RSI창을 열지 않고도 가격 차트 배경만으로 과매수·과매도 상태를 직관적으로 확인 가능. 필요하면 보조창으로 RSI를 직접 확인하면서 임계값 가이드와 음영 영역을 함께 볼 수 있음. 색상·투명도를 자유롭게 조절할 수 있어 차트 스타일에 맞게 커스터마이징 가능. RSI가 임계값을 돌파할 때 자동 알림을 받을 수 있음.
Pine Script® indicator
by yahooejrdus
RSI Forecast [Titans_Invest]RSI Forecast Introducing one of the most impressive RSI indicators ever created – arguably the best on TradingView, and potentially the best in the world. RSI Forecast is a visionary evolution of the classic RSI, merging powerful customization with groundbreaking predictive capabilities. While preserving the core principles of traditional RSI, it takes analysis to the next level by allowing users to anticipate potential future RSI movements. Real-Time RSI Forecasting: For the first time ever, an RSI indicator integrates linear regression using the least squares method to accurately forecast the future behavior of the RSI. This innovation empowers traders to stay one step ahead of the market with forward-looking insight. Highly Customizable: Easily adapt the indicator to your personal trading style. Fine-tune a variety of parameters to generate signals perfectly aligned with your strategy. Innovative, Unique, and Powerful: This is the world’s first RSI Forecast to apply this predictive approach using least squares linear regression. A truly elite-level tool designed for traders who want a real edge in the market. ⯁ SCIENTIFIC BASIS LINEAR REGRESSION Linear Regression is a fundamental method of statistics and machine learning, used to model the relationship between a dependent variable y and one or more independent variables 𝑥. The general formula for a simple linear regression is given by: y = β₀ + β₁x + ε Where: y   = is the predicted variable (e.g. future value of RSI) x ​​  = is the explanatory variable (e.g. time or bar index) β0 = is the intercept (value of 𝑦 when 𝑥 = 0) 𝛽1 = is the slope of the line (rate of change) ε   = is the random error term The goal is to estimate the coefficients 𝛽0 and 𝛽1 ​​so as to minimize the sum of the squared errors — the so-called Random Error Method Least Squares. ⯁ LEAST SQUARES ESTIMATION To minimize the error between predicted and observed values, we use the following formulas: β₁ = / β₀ = ȳ - β₁x̄ Where: ∑ = sum x̄ = mean of x ȳ = mean of y x_i, y_i = individual values ​​of the variables. Where: x_i and y_i are the means of the independent and dependent variables, respectively. i ranges from 1 to n, the number of observations. These equations guarantee the best linear unbiased estimator, according to the Gauss-Markov theorem, assuming homoscedasticity and linearity. ⯁ LINEAR REGRESSION IN MACHINE LEARNING Linear regression is one of the cornerstones of supervised learning. Its simplicity and ability to generate accurate quantitative predictions make it essential in AI systems, predictive algorithms, time series analysis, and automated trading strategies. By applying this model to the RSI, you are literally putting artificial intelligence at the heart of a classic indicator, bringing a new dimension to technical analysis. ⯁ VISUAL INTERPRETATION Imagine an RSI time series like this: Time → RSI    → The regression line will smooth these values ​​and extend them n periods into the future, creating a predicted trajectory based on the historical moment. This line becomes the predicted RSI, which can be crossed with the actual RSI to generate more intelligent signals. ⯁ SUMMARY OF SCIENTIFIC CONCEPTS USED Linear Regression Models the relationship between variables using a straight line. Least Squares Minimizes the sum of squared errors between prediction and reality. Time Series Forecasting Estimates future values ​​based on historical data. Supervised Learning Trains models to predict outputs from known inputs. Statistical Smoothing Reduces noise and reveals underlying trends. ⯁ WHY THIS INDICATOR IS REVOLUTIONARY Scientifically-based: Based on statistical theory and mathematical inference. Unprecedented: First public RSI with least squares predictive modeling. Intelligent: Built with machine learning logic. Practical: Generates forward-thinking signals. Customizable: Flexible for any trading strategy. ⯁ CONCLUSION By combining RSI with linear regression, this indicator allows a trader to predict market momentum, not just follow it. RSI Forecast is not just an indicator — it is a scientific breakthrough in technical analysis technology. ⯁ Example of simple linear regression, which has one independent variable: ⯁ In linear regression, observations ( red ) are considered to be the result of random deviations ( green ) from an underlying relationship ( blue ) between a dependent variable ( y ) and an independent variable ( x ). ⯁ Visualizing heteroscedasticity in a scatterplot against 100 random fitted values ​​using Matlab: ⯁ The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables. ⯁ The result of fitting a set of data points with a quadratic function: _______________________________________________________________________ 🥇 This is the world’s first RSI indicator with: Linear Regression for Forecasting 🥇_______________________________________________________________________ _________________________________________________ 🔮 Linear Regression: PineScript Technical Parameters 🔮 _________________________________________________ Forecast Types: • Flat: Assumes prices will remain the same. • Linreg: Makes a 'Linear Regression' forecast for n periods. Technical Information: ta.linreg (built-in function) Linear regression curve. A line that best fits the specified prices over a user-defined time period. It is calculated using the least squares method. The result of this function is calculated using the formula: linreg = intercept + slope * (length - 1 - offset), where intercept and slope are the values ​​calculated using the least squares method on the source series. Syntax: • Function: ta.linreg() Parameters: • source: Source price series. • length: Number of bars (period). • offset: Offset. • return: Linear regression curve. This function has been cleverly applied to the RSI, making it capable of projecting future values ​​based on past statistical trends. ______________________________________________________ ______________________________________________________ ⯁ WHAT IS THE RSI❓ The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend. ⯁ HOW TO USE THE RSI❓ The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:   •  Overbought: When the RSI is above 70, indicating that the asset may be overbought.   •  Oversold: When the RSI is below 30, indicating that the asset may be oversold.   •  Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions. ______________________________________________________ ______________________________________________________ ⯁ ENTRY CONDITIONS The conditions below are fully flexible and allow for complete customization of the signal. ______________________________________________________ ______________________________________________________ 🔹 CONDITIONS TO BUY 📈 ______________________________________________________   •  Signal Validity: The signal will remain valid for X bars .   •  Signal Sequence: Configurable as AND or OR . 📈 RSI Conditions: 🔹 RSI > Upper 🔹 RSI < Upper 🔹 RSI > Lower 🔹 RSI < Lower 🔹 RSI > Middle 🔹 RSI < Middle 🔹 RSI > MA 🔹 RSI < MA 📈 MA Conditions: 🔹 MA > Upper 🔹 MA < Upper 🔹 MA > Lower 🔹 MA < Lower 📈 Crossovers: 🔹 RSI (Crossover) Upper 🔹 RSI (Crossunder) Upper 🔹 RSI (Crossover) Lower 🔹 RSI (Crossunder) Lower 🔹 RSI (Crossover) Middle 🔹 RSI (Crossunder) Middle 🔹 RSI (Crossover) MA 🔹 RSI (Crossunder) MA 🔹 MA (Crossover) Upper 🔹 MA (Crossunder) Upper 🔹 MA (Crossover) Lower 🔹 MA (Crossunder) Lower 📈 RSI Divergences: 🔹 RSI Divergence Bull 🔹 RSI Divergence Bear 📈 RSI Forecast: 🔮 RSI (Crossover) MA Forecast 🔮 RSI (Crossunder) MA Forecast ______________________________________________________ ______________________________________________________ 🔸 CONDITIONS TO SELL 📉 ______________________________________________________   •  Signal Validity: The signal will remain valid for X bars .   •  Signal Sequence: Configurable as AND or OR . 📉 RSI Conditions: 🔸 RSI > Upper 🔸 RSI < Upper 🔸 RSI > Lower 🔸 RSI < Lower 🔸 RSI > Middle 🔸 RSI < Middle 🔸 RSI > MA 🔸 RSI < MA 📉 MA Conditions: 🔸 MA > Upper 🔸 MA < Upper 🔸 MA > Lower 🔸 MA < Lower 📉 Crossovers: 🔸 RSI (Crossover) Upper 🔸 RSI (Crossunder) Upper 🔸 RSI (Crossover) Lower 🔸 RSI (Crossunder) Lower 🔸 RSI (Crossover) Middle 🔸 RSI (Crossunder) Middle 🔸 RSI (Crossover) MA 🔸 RSI (Crossunder) MA 🔸 MA (Crossover) Upper 🔸 MA (Crossunder) Upper 🔸 MA (Crossover) Lower 🔸 MA (Crossunder) Lower 📉 RSI Divergences: 🔸 RSI Divergence Bull 🔸 RSI Divergence Bear 📉 RSI Forecast: 🔮 RSI (Crossover) MA Forecast 🔮 RSI (Crossunder) MA Forecast ______________________________________________________ ______________________________________________________ 🤖 AUTOMATION 🤖 • You can automate the BUY and SELL signals of this indicator. ______________________________________________________ ______________________________________________________ ⯁ UNIQUE FEATURES ______________________________________________________ Linear Regression: (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Condition Table: BUY/SELL Condition Labels: BUY/SELL Plot Labels in the Graph Above: BUY/SELL Automate and Monitor Signals/Alerts: BUY/SELL Linear Regression (Forecast) Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Condition Table: BUY/SELL Condition Labels: BUY/SELL Plot Labels in the Graph Above: BUY/SELL Automate and Monitor Signals/Alerts: BUY/SELL ______________________________________________________ 📜 SCRIPT : RSI Forecast 🎴 Art by  : @Titans_Invest & @DiFlip 👨‍💻 Dev by : @Titans_Invest & @DiFlip 🎑 Titans Invest — The Wizards Without Gloves 🧤 ✨ Enjoy! ______________________________________________________ o Mission 🗺 • Inspire Traders to manifest Magic in the Market. o Vision 𐓏 • To elevate collective Energy 𐓷𐓏
Pine Script® indicator
by Titans_Invest
3
RSI of RSI Deviation (RoRD)RSI of RSI Deviation (RoRD) - Advanced Momentum Acceleration Analysis What is RSI of RSI Deviation (RoRD)? RSI of RSI Deviation (RoRD) is a insightful momentum indicator that transcends traditional oscillator analysis by measuring the acceleration of momentum through sophisticated mathematical layering. By calculating RSI on RSI itself (RSI²) and applying advanced statistical deviation analysis with T3 smoothing, RoRD reveals hidden market dynamics that single-layer indicators miss entirely. This isn't just another RSI variant—it's a complete reimagining of how we measure and visualize momentum dynamics. Where traditional RSI shows momentum, RoRD shows momentum's rate of change . Where others show static overbought/oversold levels, RoRD reveals statistically significant deviations unique to each market's character. Theoretical Foundation - The Mathematics of Momentum Acceleration 1. RSI² (RSI of RSI) - The Core Innovation Traditional RSI measures price momentum. RoRD goes deeper: Primary RSI (RSI₁) : Standard RSI calculation on price Secondary RSI (RSI²) : RSI calculated on RSI₁ values This creates a "momentum of momentum" indicator that leads price action Mathematical Expression: RSI₁ = 100 - (100 / (1 + RS₁)) RSI² = 100 - (100 / (1 + RS₂)) Where RS₂ = Average Gain of RSI₁ / Average Loss of RSI₁ 2. T3 Smoothing - Lag-Free Response The T3 Moving Average, developed by Tim Tillson, provides: Superior smoothing with minimal lag Adaptive response through volume factor (vFactor) Noise reduction while preserving signal integrity T3 Formula: T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3 Where e1...e6 are cascaded EMAs and c1...c4 are volume-factor-based coefficients 3. Statistical Z-Score Deviation RoRD employs dual-layer Z-score normalization : Initial Z-Score : (RSI² - SMA) / StDev Final Z-Score : Z-score of the Z-score for refined extremity detection This identifies statistically rare events relative to recent market behavior 4. Multi-Timeframe Confluence Compares current timeframe Z-score with higher timeframe (HTF) Provides directional confirmation across time horizons Filters false signals through timeframe alignment Why RoRD is Different & More Sophisticated Beyond Traditional Indicators: Acceleration vs. Velocity : While RSI measures momentum (velocity), RoRD measures momentum's rate of change (acceleration) Adaptive Thresholds : Z-score analysis adapts to market conditions rather than using fixed 70/30 levels Statistical Significance : Signals are based on mathematical rarity, not arbitrary levels Leading Indicator : RSI² often turns before price, providing earlier signals Reduced Whipsaws : T3 smoothing eliminates noise while maintaining responsiveness Unique Signal Generation: Quantum Orbs : Multi-layered visual signals for statistically extreme events Divergence Detection : Automated identification of price/momentum divergences Regime Backgrounds : Visual market state classification (Bullish/Bearish/Neutral) Particle Effects : Dynamic visualization of momentum energy Visual Design & Interpretation Guide Color Coding System: Yellow (#e1ff00) : Neutral/balanced momentum state Red (#ff0000) : Overbought/extreme bullish acceleration Green (#2fff00) : Oversold/extreme bearish acceleration Orange : Z-score visualization Blue : HTF Z-score comparison Main Visual Elements: RSI² Line with Glow Effect Multi-layer glow creates depth and emphasis Color dynamically shifts based on momentum state Line thickness indicates signal strength Quantum Signal Orbs Green Orbs Below : Statistically rare oversold conditions Red Orbs Above : Statistically rare overbought conditions Multiple layers indicate signal strength Only appear at Z-score extremes for high-conviction signals Divergence Markers Green Circles : Bullish divergence detected Red Circles : Bearish divergence detected Plotted at pivot points for precision Background Regimes Green Background : Bullish momentum regime Grey Background : Bearish momentum regime Blue Background : Neutral/transitioning regime Particle Effects Density indicates momentum energy Color matches current RSI² state Provides dynamic market "feel" Dashboard Metrics - Deep Dive RSI² ANALYSIS Section: RSI² Value (0-100) Current smoothed RSI of RSI reading >70 : Strong bullish acceleration <30 : Strong bearish acceleration ~50 : Neutral momentum state RSI¹ Value Traditional RSI for reference Compare with RSI² for acceleration/deceleration insights Z-Score Status 🔥 EXTREME HIGH : Z > threshold, statistically rare bullish ❄️ EXTREME LOW : Z < threshold, statistically rare bearish 📈 HIGH/📉 LOW : Elevated but not extreme ➡️ NEUTRAL : Normal statistical range MOMENTUM Section: Velocity Indicator ▲▲▲ : Strong positive acceleration ▼▼▼ : Strong negative acceleration Shows rate of change in RSI² Strength Bar ██████░░░░ : Visual power gauge Filled bars indicate momentum strength Based on deviation from center line SIGNALS Section: Divergence Status 🟢 BULLISH DIV : Price making lows, RSI² making highs 🔴 BEARISH DIV : Price making highs, RSI² making lows ⚪ NO DIVERGENCE : No divergence detected HTF Comparison 🔥 HTF EXTREME : Higher timeframe confirms extremity 📊 HTF NORMAL : Higher timeframe is neutral Critical for multi-timeframe confirmation Trading Application & Strategy Signal Hierarchy (Highest to Lowest Priority): Quantum Orb + HTF Alignment + Divergence Highest conviction reversal signal Z-score extreme + timeframe confluence + divergence Quantum Orb + HTF Alignment Strong reversal signal Wait for price confirmation Divergence + Regime Change Medium-term reversal signal Monitor for orb confirmation Threshold Crosses Traditional overbought/oversold Use as alert, not entry Entry Strategies: For Reversals: Wait for Quantum Orb signal Confirm with HTF Z-score direction Enter on price structure break Stop beyond recent extreme For Continuations: Trade with regime background color Use RSI² pullbacks to center line Avoid signals against HTF trend For Scalping: Focus on Z-score extremes Quick entries on orb signals Exit at center line cross Risk Management: Reduce position size when signals conflict with HTF Avoid trades during regime transitions (blue background) Tighten stops after divergence completion Scale out at statistical mean reversion Development & Uniqueness RoRD represents months of research into momentum dynamics and statistical analysis. Unlike indicators that simply combine existing tools, RoRD introduces several genuine innovations : True RSI² Implementation : Not a smoothed RSI, but actual RSI calculated on RSI values Dual Z-Score Normalization : Unique approach to finding statistical extremes T3 Integration : First RSI² implementation with T3 smoothing for optimal lag reduction Quantum Orb Visualization : Revolutionary signal display method Dynamic Regime Detection : Automatic market state classification Statistical Adaptability : Thresholds adapt to market volatility This indicator was built from first principles, with each component carefully selected for its mathematical properties and practical trading utility. The result is a professional-grade tool that provides insights unavailable through traditional momentum analysis. Best Practices & Tips Start with default settings - they're optimized for most markets Always check HTF alignment before taking signals Use divergences as early warning , orbs as confirmation Respect regime backgrounds - trade with them, not against Combine with price action - RoRD shows when, price shows where Adjust Z-score thresholds based on market volatility Monitor dashboard metrics for complete market context Conclusion RoRD isn't just another indicator—it's a complete momentum analysis system that reveals market dynamics invisible to traditional tools. By combining momentum acceleration, statistical analysis, and multi-timeframe confluence with intuitive visualization, RoRD provides traders with a sophisticated edge in any market condition. Whether you're scalping rapid reversals or positioning for major trend changes, RoRD's unique approach to momentum analysis will transform how you see and trade market dynamics. See momentum's future. Trade with statistical edge. Trade with insight. Trade with anticipation. — Dskyz, for DAFE Trading Systems
Pine Script® indicator
by DskyzInvestments
4
RSI Candlestick Oscillator [LuxAlgo]The RSI Candlestick Oscillator displays a traditional Relative Strength Index (RSI) as candlesticks. This indicator references OHLC data to locate each candlestick point relative to the current RSI Value, leading to a more accurate representation of the Open, High, Low, and Close price of each candlestick in the context of RSI. In addition to the candlestick display, Divergences are detected from the RSI candlestick highs and lows and can be displayed over price on the chart. 🔶 USAGE Translating candlesticks into the RSI oscillator is not a new concept and has been attempted many times before. This indicator stands out because of the specific method used to determine the candlestick OHLC values. When compared to other RSI Candlestick indicators, you will find that this indicator clearly and definitively correlates better to the on-chart price action. Traditionally, the RSI indicator is simply one running value based on (typically) the close price of the chart. By introducing high, low, and open values into the oscillator, we can better gauge the specific price action throughout the intrabar movements. Interactions with the RSI levels can now take multiple forms, whether it be a full-bodied breakthrough or simply a wick test. Both can provide a new analysis of price action alongside RSI. An example of wick interactions and full-bodied interactions can be seen below. As a result of the candlestick display, divergences become simpler to spot. Since the candlesticks on the RSI closely resemble the candlesticks on the chart, when looking for divergence between the chart and RSI, it is more obvious when the RSI and price are diverging. The divergences in this indicator not only show on the RSI oscillator, but also overlay on the price chart for clearer understanding. 🔹 Filtering Divergence With the candlesticks generating high and low RSI values, we can better sense divergences from price, since these points are generally going to be more dramatic than the (close) RSI value. This indicator displays each type of divergence: Bullish Divergence Bearish Divergence Hidden Bullish Divergence Hidden Bearish Divergence From these, we get many less-than-useful indications, since every single divergence from price is not necessarily of great importance. The Divergence Filter disregards any divergence detected that does not extend outside the RSI upper or lower values. This does not replace good judgment, but this filter can be helpful in focusing attention towards the extremes of RSI for potential reversal spotting from divergence. 🔶 DETAILS In order to get the desired results for a display that resembles price action while following RSI, we must scale. The scaling is the most important part of this indicator. To summarize the process: Identify a range on Price and RSI Consider them as equal to create a scaling factor Use the scaling factor to locate RSI's "Price equivalent" Upper, Lower, & Mid on the Chart Use those prices (specifically the RSI Mid) to check how far each OHLC value lies from it Use those differences to translate the price back to the RSI Oscillator, pinning the OHLC values at their relative location to our anchor (RSI Mid) 🔹 RSI Channel To better understand, and for your convenience, the indicator includes the option to display the RSI Channel on the chart. This channel helps to visualize where the scaled RSI values are relative to price. If you analyze the RSI channel, you are likely to notice that the price movement throughout the channel matches the same movement witnessed in the RSI Oscillator below. This makes sense since they are the exact same thing displayed on different scales. 🔹 Scaling the Open While the scaling method used is important, and provides a very close view of the real price bar's relative locations on the RSI oscillator… It is designed for a single purpose. The scaling does NOT make the price candles display perfectly on the RSI oscillator. The largest place where this is noticeable is with the opening of each candle. For this reason, we have included a setting that modifies the opening of each RSI candle to be more accurate to the chart's price candles. This setting positions the current bar's opening RSI candlestick value accurately relative to the price's open location to the previous closing price. As seen below. 🔶 SETTINGS 🔹 RSI Candles RSI Length: Sets the Length for the RSI Oscillator. Overbought/Oversold Levels: Sets the Overbought and Oversold levels for the RSI Oscillator. Scale Open for Chart Accuracy: As described above, scales the open of each candlestick bar to more accurately portray the chart candlesticks. 🔹 Divergence Show on Chart: Choose to display divergence line on the chart as well as on the Oscillator. Divergence Length: Sets the pivot width for divergence detection. Normal Fractal Pivot Detection is used. Divergence Style: Change color and line style for Regular and Hidden divergences, as well as toggle their display. Divergence Filter: As described above, toggle on or off divergence filtering. 🔹 RSI Channel Toggle: Display RSI Channel on Chart. Color: Change RSI Channel Color
Pine Script® indicator
by LuxAlgo
19
RSI Divergence + Sweep + Signal + Alerts Toolkit [TrendX_]The RSI Toolkit is a powerful set of tools designed to enhance the functionality of the traditional Relative Strength Index (RSI) indicator. By integrating advanced features such as Moving Averages, Divergences, and Sweeps, it helps traders identify key market dynamics, potential reversals, and newly-approach trading stragies. The toolkit expands on standard RSI usage by incorporating features from smart money concepts (Just try to be creative 🤣 Hope you like it), providing a deeper understanding of momentum, liquidity sweeps, and trend reversals. It is suitable for RSI traders who want to make more informed and effective trading decisions. 💎 FEATURES RSI Moving Average The RSI Moving Average (RSI MA) is the moving average of the RSI itself. It can be customized to use various types of moving averages, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Relative Moving Average (RMA), and Volume-Weighted Moving Average (VWMA). The RSI MA smooths out the RSI fluctuations, making it easier to identify trends and crossovers. It helps traders spot momentum shifts and potential entry/exit points by observing when the RSI crosses above or below its moving average. RSI Divergence RSI Divergence identifies discrepancies between price action and RSI momentum. There are two types of divergences: Regular Divergence - Indicates a potential trend reversal; Hidden Divergence - Suggests the continuation of the current trend. Divergence is a critical signal for spotting weakness or strength in a trend. Regular divergence highlights potential trend reversals, while hidden divergence confirms trend continuation, offering traders valuable insights into market momentum and possible trade setups. RSI Sweep RSI Sweep detects moments when the RSI removes liquidity from a trend structure by sweeping above or below the price at key momentum level crossing. These sweeps are overlaid on the RSI chart for easier visualized. RSI Sweeps are significant because they indicate potential turning points in the market. When RSI sweeps occur: In an uptrend - they suggest buyers' momentum has peaked, possibly leading to a reversal; In a downtrend - they indicate sellers’ momentum has peaked, also hinting at a reversal. (Note: This feature incorporates Liquidity Sweep concepts from Smart Money Concepts into RSI analysis, helping RSI traders identify areas where liquidity has been removed, which often precedes a trend reversal) 🔎 BREAKDOWN RSI Moving Average How MA created: The RSI value is calculated first using the standard RSI formula. The MA is then applied to the RSI values using the trader’s chosen type of MA (SMA, EMA, RMA, or VWMA). The flexibility to choose the type of MA allows traders to adjust the smoothing effect based on their trading style. Why use MA: RSI by itself can be noisy and difficult to interpret in volatile markets. Applying moving average would provide a smoother, more reliable view of RSI trends. RSI Divergence How Regular Divergence created: Regular Divergence is detected when price forms HIGHER highs while RSI forms LOWER highs (bearish divergence) or when price forms LOWER lows while RSI forms HIGHER lows (bullish divergence). How Hidden Divergence created: Hidden Divergence is identified when price forms HIGHER lows while RSI forms LOWER lows (bullish hidden divergence) or when price forms LOWER highs while RSI forms HIGHER highs (bearish hidden divergence). Why use Divergence: Divergences provide early warning signals of a potential trend change. Regular divergence helps traders anticipate reversals, while hidden divergence supports trend continuation, enabling traders to align their trades with market momentum. RSI Sweep How Sweep created: Trend Structure Shift are identified based on the RSI crossing key momentum level of 50. To track these sweeps, the indicator pinpoints moments when liquidity is removed from the Trend Structure Shift. This is a direct application of Liquidity Sweep concepts used in Smart Money theories, adapted to RSI. Why use Sweep: RSI Sweeps are created to help traders detect potential trend reversals. By identifying areas where momentum has exhausted during a certain trend direction, the indicator highlights opportunities for traders to enter trades early in a reversal or continuation phase. ⚙️ USAGES Divergence + Sweep This is an example of combining Devergence & Sweep in BTCUSDT (1 hour) Wait for a divergence (regular or hidden) to form on the RSI. After the divergence is complete, look for a sweep to occur. A potential entry might be formed at the end of the sweep. Divergences indicate a potential trend change, but confirmation is required to ensure the setup is valid. The RSI Sweep provides that confirmation by signaling a liquidity event, increasing the likelihood of a successful trade. Sweep + MA Cross This is an example of combining Devergence & Sweep in BTCUSDT (1 hour) Wait for an RSI Sweep to form then a potential entry might be formed when the RSI crosses its MA. The RSI Sweep highlights a potential turning point in the market. The MA cross serves as additional confirmation that momentum has shifted, providing a more reliable and more potential entry signal for trend continuations. DISCLAIMER This indicator is not financial advice, it can only help traders make better decisions. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur. Therefore, one should always exercise caution and judgment when making decisions based on past performance.
Pine Script® indicator
by TrendXvn
9