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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®指標
由Titans_Invest提供
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®指標
由Titans_Invest提供
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®指標
由DskyzInvestments提供
4
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®指標
由TrendX_提供
8
RSI Multiple TimeFrame, Version 1.0RSI Multiple TimeFrame, Version 1.0 Overview The RSI Multiple TimeFrame script is designed to enhance trading decisions by providing a comprehensive view of the Relative Strength Index (RSI) across multiple timeframes. This tool helps traders identify overbought and oversold conditions more accurately by analyzing RSI values on different intervals simultaneously. This is particularly useful for traders who employ multi-timeframe analysis to confirm signals and make more informed trading decisions. Unique Feature of the new script (described in detail below) Multi-Timeframe RSI Analysis Customizable Timeframes Visual Signal Indicators (dots) Overbought and Oversold Layers with gradual Background Fill Enhanced Trend Confirmation Originality and Usefulness This script combines the RSI indicator across three distinct timeframes into a single view, providing traders with a multi-dimensional perspective of market momentum. It also provides associated signals to better time dips and peaks. Unlike standard RSI indicators that focus on a single timeframe, this script allows users to observe RSI trends across short, medium, and long-term intervals, thereby improving the accuracy of entry and exit signals. This is particularly valuable for traders looking to align their short-term strategies with longer-term market trends. Signal Description The script also includes a unique signal feature that plots green and red dots on the chart to highlight potential buy and sell opportunities: Green Dots : These appear when all three RSI values are under specific thresholds (RSI of the shortest timeframe < 30, the medium timeframe < 40, and the longest timeframe < 50) and the RSI of the shortest timeframe is showing an upward trend (current value is greater than the previous value, and the value two periods ago is greater than the previous value). This indicates a potential buying opportunity as the market may be shifting from an oversold condition. Red Dots : These appear when all three RSI values are above specific thresholds (RSI of the shortest timeframe > 70, the medium timeframe > 60, and the longest timeframe > 50) and the RSI of the shortest timeframe is showing a downward trend (current value is less than the previous value, and the value two periods ago is less than the previous value). This indicates a potential selling opportunity as the market may be shifting from an overbought condition. These signals help traders identify high-probability turning points in the market by ensuring that momentum is aligned across multiple timeframes. Detailed Description Input Variables RSI Period (`len`) : The number of periods to calculate the RSI. Default is 14. RSI Source (`src`) : The price source for RSI calculation, defaulting to the average of the high and low prices (`hl2`). Timeframes (`tf1`, `tf2`, `tf3`) : The different timeframes for which the RSI is calculated, defaulting to 5 minutes, 1 hour, and 8 hours respectively. Functionality RSI Calculations : The script calculates the RSI for each of the three specified timeframes using the `request.security` function. This allows the RSI to be plotted for multiple intervals, providing a layered view of market momentum. ```pine rsi_tf1 = request.security(syminfo.tickerid, tf1, ta.rsi(src, len)) rsi_tf2 = request.security(syminfo.tickerid, tf2, ta.rsi(src, len)) rsi_tf3 = request.security(syminfo.tickerid, tf3, ta.rsi(src, len)) ``` Plotting : The RSI values for the three timeframes are plotted with different colors and line widths for clear visual distinction. This makes it easy to compare RSI values across different intervals. ```pine p1 = plot(rsi_tf1, title="RSI 5m", color=color.rgb(200, 200, 255), linewidth=2) p2 = plot(rsi_tf2, title="RSI 1h", color=color.rgb(125, 125, 255), linewidth=2) p3 = plot(rsi_tf3, title="RSI 8h", color=color.rgb(0, 0, 255), linewidth=2) ``` Overbought and Oversold Levels : Horizontal lines are plotted at standard RSI levels (20, 30, 40, 50, 60, 70, 80) to visually identify overbought and oversold conditions. The areas between these levels are filled with varying shades of blue for better visualization. ```pine h80 = hline(80, title="RSI threshold 80", color=color.gray, linestyle=hline.style_dotted, linewidth=1) h70 = hline(70, title="RSI threshold 70", color=color.gray, linestyle=hline.style_dotted, linewidth=1) ... fill(h70, h80, color=color.rgb(33, 150, 243, 95), title="Background") ``` Signal Plotting : The script adds green and red dots to indicate potential buy and sell signals, respectively. A green dot is plotted when all RSI values are under specific thresholds and the RSI of the shortest timeframe is rising. Conversely, a red dot is plotted when all RSI values are above specific thresholds and the RSI of the shortest timeframe is falling. ```pine plotshape(series=(rsi_tf1 < 30 and rsi_tf2 < 40 and rsi_tf3 < 50 and (rsi_tf1 > rsi_tf1 ) and (rsi_tf1 > rsi_tf1 )) ? 1 : na, location=location.bottom, color=color.green, style=shape.circle, size=size.tiny) plotshape(series=(rsi_tf1 > 70 and rsi_tf2 > 60 and rsi_tf3 > 50 and (rsi_tf1 < rsi_tf1 ) and (rsi_tf1 < rsi_tf1 )) ? 1 : na, location=location.top, color=color.red, style=shape.circle, size=size.tiny) ``` How to Use Configuring Inputs : Adjust the RSI period and source as needed. Modify the timeframes to suit your trading strategy. Interpreting the Indicator : Use the plotted RSI values to gauge momentum across different timeframes. Look for overbought conditions (RSI above 70, 60 and 50) and oversold conditions (RSI below 30, 40 and 50) across multiple intervals to confirm trade signals. Signal Confirmation : Pay attention to the green and red dots that provide signals to better time dips and peaks. dots are printed when the lower timeframe (5mn by default) shows sign of reversal. These signals are more reliable when confirmed across all three timeframes. This script provides a nuanced view of RSI, helping traders make more informed decisions by considering multiple timeframes simultaneously. By combining short, medium, and long-term RSI values, traders can better align their strategies with overarching market trends, thus improving the precision of their trading actions.
Pine Script®指標
由adridem提供
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®指標
由LuxAlgo提供
17
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions. Understanding RSI What is RSI? The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset. How RSI Works: Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods. Range: The RSI oscillates between 0 and 100. Interpretation: Key Features of RSI: Momentum Indicator: RSI helps identify the momentum of price movements. Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals. Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50. Understanding Bollinger Bands What is Bollinger Bands? Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines: Upper Band: SMA + (Standard Deviation × Multiplier) Middle Band (Basis): SMA Lower Band: SMA - (Standard Deviation × Multiplier) How Bollinger Bands Work: Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility. Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands. Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels. Key Features of Bollinger Bands: Volatility Indicator: Bollinger Bands help traders understand the volatility of the market. Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands. Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout. Combining RSI and Bollinger Bands Strategy Overview: The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are: RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe. RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes. Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band. Strategy Details: RSI Calculation: Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes. Check if the RSI crosses above 60 on the 15-minute timeframe. Ensure the RSI is above 60 on the 1-hour and 1-day timeframes. Bollinger Bands Calculation: Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations. Check if the price is above the 20-period moving average or walking on the upper Bollinger Band. Entry and Exit Signals: Long Signal: When all the above conditions are met, consider a long entry. Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit. Example Usage Setup: Add the indicator to your TradingView chart. Configure the inputs as per your requirements. Monitoring: Look for the long signal on the chart. Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes. Check that the price is above the 20-period moving average or walking on the upper Bollinger Band. Trading: Enter a long position when the criteria are met. Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules. Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average. House Rules Compliance No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice. Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing. Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis. TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines. Conclusion This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
Pine Script®指標
由deepakks444提供
4
RSI BandsOverview The RSI Bands indicator is a tool designed to calculate and display overbought, oversold, and middle bands based on the Relative Strength Index (RSI). Its primary purpose is to provide traders with a clue on whether to place limit buy or limit sell orders, or to set stop-loss orders effectively. The bands represent the price levels the asset must reach for the RSI to align with specific thresholds: Overbought Band: Displays the upper band representing the price level the asset must reach for the RSI to become overbought. Oversold Band: Displays the lower band representing the price level the asset must reach for the RSI to become oversold. Middle Band: Displays the middle band representing the price level the asset must reach for the RSI to hit the middle level. It uses both traditional RSI calculations and a dynamic period adjustment mechanism for improved adaptability to market conditions. The script also offers smoothing options for the bands. Features Calculates overbought, oversold, and middle bands using RSI values. Dynamically adjusts the RSI period based on pivot points if enabled. Offers smoothing options for the bands: EMA, SMA, or None. Customizable input parameters for flexibility. Inputs Source Value: Selects the data source (e.g., close price) for RSI calculation. Period: Sets the static RSI calculation period. Used if dynamic period is disabled. Use Dynamic Period?: Toggles the use of a dynamic RSI period. Pivot Left/Right Length: Determines the range of bars for pivot detection when using dynamic periods. Dynamic Period Multiplier: Scales the dynamically calculated RSI period. Overbought Level: RSI level that marks the overbought threshold. Oversold Level: RSI level that marks the oversold threshold. Middle Level: RSI level used as a midpoint reference. Smoothing Type: Specifies the smoothing method for the bands (EMA, SMA, or None). Smoothing Length: Length used for the selected smoothing method. Key Calculations RSI Calculation: Computes RSI using gains and losses over the specified period (dynamic or static). Incorporates a custom function for calculating RSI with dynamic periods. Dynamic Period Adjustment: Uses pivot points to determine an adaptive RSI period. Multiplies the base dynamic period by the Dynamic Period Multiplier. Band Calculation: Calculates price changes (deltas) required to achieve the overbought, oversold, and middle RSI levels. The price changes (deltas) are determined using an iterative approximation technique. For each target RSI level (overbought, oversold, or middle), the script estimates the required change in price by adjusting a hypothetical delta value until the calculated RSI aligns with the target RSI. This approximation ensures precise calculation of the price levels necessary for the RSI to reach the specified thresholds. Computes the upper (overbought), lower (oversold), and middle bands by adding these deltas to the source price. Smoothing: Applies the selected smoothing method (EMA or SMA) to the calculated bands. Plots Overbought Band: Displays the upper band representing the price level the asset must reach for the RSI to become overbought. Oversold Band: Displays the lower band representing the price level the asset must reach for the RSI to become oversold. Middle Band: Displays the middle band representing the price level the asset must reach for the RSI to hit the middle level. Usage Choose the source value (e.g., close price). Select whether to use a dynamic RSI period or a static one. Adjust pivot lengths and multipliers for dynamic period calculation as needed. Set the overbought, oversold, and middle RSI levels based on your analysis. Configure smoothing options for the bands. Observe the plotted bands and use them to identify potential overbought and oversold market conditions.
Pine Script®指標
由CrimsonVault提供
RSI Difference (Fast and Slow)Introduction Oscillators like the RSI are fundamental tools for identifying trends in financial markets. Their ability to measure price momentum allows traders to detect overbought, oversold levels, and divergences, anticipating trend changes. Are there ways to improve the use of traditional RSI? How can we obtain more detailed information about current trends? This indicator answers these questions by expanding the functionalities of the traditional RSI and offering an additional tool for analysis. How does it work? This indicator provides a framework for trend analysis based on the following setup: Fast RSI Slow RSI SMA of the fast RSI SMA of the slow RSI Histogram Custom Indicator Settings My preferred configuration is based on the 13 and 55 moving averages. The rest of the setup is as follows: I typically use the 13 and 55 moving averages to configure both the RSI and short- and long-term moving averages. Interpretation and Signals: Including a Long-Period RSI Including a long-period RSI helps identify key patterns in market behavior. Crossovers between the two can be used to establish entry patterns: If the fast RSI crosses above the slow RSI, this could indicate a long-entry pattern. If the fast RSI crosses below the slow RSI, this could indicate a short-entry pattern. Interpretation and Signals: Including Moving Averages Including moving averages for both the short- and long-period RSI can help identify the base trend of the movement and, consequently: Avoid false signals. Trade in favor of the trend. A simple way to start working with these is to use the crossover of the moving averages to identify the current trend: If the short-period SMA is above the long-period SMA, the trend is bullish. If the short-period SMA is below the long-period SMA, the trend is bearish. Interpretation and Signals: The Histogram The histogram represents the difference between the moving averages. If the histogram is positive, the short average is above the long average. If the histogram is below zero, the short average is below the long average. Divergences with price provide signals of potential exhaustion in the movement, indicating a possible reversal. Indicator Details This indicator builds upon the traditional RSI by integrating additional features that enhance its utility for traders. Here’s how each component is calculated and how they contribute to the originality of the script: Fast RSI and Slow RSI: The fast RSI is calculated using a shorter lookback period, allowing it to capture rapid changes in momentum. The slow RSI uses a longer period to smooth out fluctuations and provide a broader view of the trend. These two RSIs work together to identify significant momentum shifts. SMA of RSI values: The simple moving averages (SMA) of the fast and slow RSI help filter out noise and provide clear crossover signals. The SMAs are calculated using standard formulas but applied to the RSI values rather than price data, which adds a layer of insight into momentum trends. Histogram calculation: The histogram represents the difference between the SMA of the fast RSI and the SMA of the slow RSI. This value gives a visual representation of the convergence or divergence of momentum. When the histogram crosses zero, it signifies a potential shift in the underlying trend. This indicator combines multiple layers of analysis: fast and slow momentum, trend confirmation through SMAs, and divergence detection via the histogram. This multi-dimensional approach provides traders with a more comprehensive tool for trend analysis and decision-making. Conclusion This article has explored how to use this indicator to identify trends, leverage entry patterns, and analyze divergences by combining the fast RSI, slow RSI, their moving averages, and a histogram. Additionally, I’ve detailed how I usually interpret this indicator: Identifying RSI patterns to anticipate momentum changes. Using SMAs to confirm base trends. Leveraging the histogram to detect divergences and potential price reversals.
Pine Script®指標
由Fractanomics提供