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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
Indicatore Pine Script®
di Titans_Invest
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
Indicatore Pine Script®
di DskyzInvestments
4
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
Indicatore Pine Script®
di Titans_Invest
3
RSI Dynamic Bands█ OVERVIEW The "RSI Dynamic Bands" indicator is a variant of the Relative Strength Index (RSI) oscillator that brings its signals directly onto the price chart. It displays dynamic bands around the price, adjusted based on RSI levels, enabling easy identification of potential overbought or oversold conditions. The indicator also integrates a multi-timeframe RSI table, facilitating the analysis of trend strength across different timeframes. █ CONCEPTS The "RSI Dynamic Bands" indicator is designed to simplify the interpretation of price levels in the context of support and resistance zones, which can be correlated with other technical indicators and RSI values. Since the price itself does not display RSI values, a table showing RSI for four selected timeframes has been added, allowing traders to quickly assess trend strength across different time intervals. The most effective approach is to combine the indicator with other technical analysis tools, such as Fibonacci levels or pivot points, to confirm signals when the price approaches the bands and RSI values indicate a potential reversal. Band Calculation The bands are calculated based on the current closing price and RSI values, incorporating dynamic scaling to better adapt to market conditions. The formulas for the bands are as follows: • Upper Band: close + (rsiUpper - rsi) * scaleFactor, where rsiUpper is the upper RSI level (default: 70), and scaleFactor accounts for market volatility. • Lower Band: close + (rsiLower - rsi) * scaleFactor, where rsiLower is the lower RSI level (default: 30). • Midline: The arithmetic average of the upper and lower bands: (upperBand + lowerBand) / 2. Why Scaling? Without scaling, the bands would be chaotic and jagged, making them difficult to interpret. Scaling smooths the bands, making them wider during periods of high volatility and narrower during consolidation, better reflecting potential support and resistance levels. Indicator Features • Dynamic Price Bands: The bands adapt to market conditions, facilitating the identification of key price levels. • Multi-Timeframe RSI Table: Displays RSI values for four selected timeframes (default: 15m, 1h, 4h, Daily), enabling comparison of trend strength across different perspectives. • Style Customization: Users can adjust band colors, line thickness, and toggle the visibility of bands, fills, and the table. How to Set Up the Indicator 1 — Add the "RSI Dynamic Bands" indicator to your TradingView chart. 2 — Configure parameters in the settings, such as RSI length, upper/lower levels, and scaling multiplier, to match your trading style. 3 — Enable or disable the display of bands, fills, or the RSI table based on your needs. 4 — Adjust band and table colors in the input section and line thickness in the "Style" section to better align the indicator with your chart. █ OTHER SECTIONS FEATURES • RSI Length: The period for calculating RSI (default: 14). • RSI Levels: Thresholds for overbought (default: 70) and oversold (default: 30). • Scaling Multiplier: Adjusts bands based on market volatility (default: 0.15). • Table Timeframes: Select four timeframes for the RSI table (default: 15m, 1h, 4h, Daily). • Style Options: Customize band colors, fills, table, and line thickness. HOW TO USE Add the indicator to your chart, configure the parameters, and observe price interactions with the bands to identify potential entry and exit points. The RSI table allows you to compare RSI values across different timeframes, aiding in trading decisions. The most effective approach is to combine the indicator with other technical analysis tools, such as Fibonacci levels or pivot points, to confirm signals when the price approaches the bands and RSI values indicate a potential reversal. Trading Strategies: • Scalping: Use lower timeframes (e.g., 5m, 15m) in the RSI table to quickly identify short-term lows and highs. Wait for the price to approach the lower band in the RSI oversold zone, with RSI on lower timeframes starting to rise, and other tools, such as Fibonacci levels (e.g., 38.2%) or pivot points, confirming support. • Medium-Term Trading: Focus on 1h and 4h timeframes. Look for confirmation of a low on a lower timeframe (e.g., 1h), where RSI indicates oversold conditions or starts rising, then check if RSI on a higher timeframe (e.g., 4h) confirms the trend. Confirmation from other tools, such as a Fibonacci level (e.g., 50%) or pivot point near the bands, strengthens the signal. • Long-Term Trading: Use Daily and higher timeframes (e.g., Weekly). Wait for all relevant timeframes to confirm a low (e.g., RSI near oversold and price at the lower band), with lower timeframes (e.g., 4h) showing rising RSI. Other tools, such as Fibonacci levels (e.g., 61.8%) or pivot points near the bands, can further confirm a trend reversal signal.
Indicatore Pine Script®
di Uncle_the_shooter
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
Indicatore Pine Script®
di LuxAlgo
18