RSI-VA modified RSI script with a a slight modified net volume formula
red is bearish
green is bullish
just attempt to make the RSI more easy and better to use
best entry is when green bellow 30
and vice versa when red start to cross down the 70
Cari dalam skrip untuk "rsi"
RSIStandard RSI that uses the highest and lowest output plots of the RSI formula using open, high, low, close formulas.
RSI Phan Ky FullThe RSI divergence indicator is like a magnifying glass that spots gaps between price swings and momentum. When price keeps climbing but RSI quietly sags, it’s a flashing U‑turn sign: the bulls are winded, and the bears are lacing up their boots. Flip it around—price is sliding yet RSI edges higher—and you’ve got bulls secretly stockpiling. Hidden divergences shore up the trend; regular divergences hint at a pivot. Blend those signals with overbought/oversold zones, support‑resistance, and volume, and RSI divergence turns into a radar that helps traders jump in with swagger and bail out just in time.
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
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
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
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.
RSI based MAGot it! Here’s some information in English specifically about the **RSI-based Moving Average (RSI-based MA)** that we wrote the Pine Script code for:
### RSI-Based Moving Average (RSI-based MA)
An **RSI-based Moving Average (RSI-based MA)** is a technical analysis tool that combines the Relative Strength Index (RSI) with moving averages to provide more insight into market trends and potential reversals. This indicator can be particularly useful for identifying the beginning and end of trends, allowing traders to make more informed decisions.
### How RSI-based MA Works
The RSI-based MA indicator calculates the moving average of the RSI values rather than the asset's price itself. In the script you asked for, we implemented two RSI-based moving averages: one for a 1-minute timeframe and another for a 5-minute timeframe. This dual timeframe approach can help traders spot trends more accurately and identify shifts in momentum across different time periods.
#### Key Features of RSI-based MA:
1. **Dual Timeframe Analysis**:
- The script plots two RSI-based moving averages on the same chart:
- **1-minute RSI-based MA**: A moving average calculated based on RSI values over a 1-minute interval.
- **5-minute RSI-based MA**: A moving average calculated based on RSI values over a 5-minute interval.
- Using different timeframes helps traders see both short-term and longer-term trends simultaneously.
2. **RSI Levels**:
- The RSI-based MA plots values between 0 and 100, similar to the RSI itself. Traders can use typical RSI levels, such as 70 (overbought) and 30 (oversold), to identify potential entry and exit points.
- **Overbought condition**: When the RSI-based MA moves above 70, it indicates the asset might be overbought, suggesting a potential for price to drop.
- **Oversold condition**: When the RSI-based MA drops below 30, it signals that the asset might be oversold, indicating a potential price increase.
3. **Crossovers**:
- **Bullish signal**: If the shorter 1-minute RSI-based MA crosses above the longer 5-minute RSI-based MA, this could indicate a new upward trend beginning.
- **Bearish signal**: Conversely, if the 1-minute RSI-based MA crosses below the 5-minute RSI-based MA, it could suggest the beginning of a downward trend.
### Potential Advantages
- **Smoother Trend Identification**: By applying moving averages to RSI, you can smooth out the short-term fluctuations in RSI values, making it easier to identify the underlying trend.
- **Versatility**: The indicator can be customized for different timeframes and settings, allowing it to be tailored to various trading strategies and asset classes.
- **Enhanced Signals**: Combining RSI and moving averages helps filter out noise, providing more reliable signals for potential trend changes or continuations.
### Potential Limitations
- **Lagging Indicator**: Like most moving averages, RSI-based MAs are lagging indicators. They tend to react after price movements have already begun, which could result in delayed signals.
- **False Signals**: In ranging or highly volatile markets, RSI-based MA may give false signals, indicating a trend reversal or continuation that does not occur.
- **Should Not Be Used Alone**: It's often recommended to use RSI-based MA alongside other technical indicators (like MACD, Bollinger Bands, or moving average crossovers) to confirm signals and reduce the risk of false readings.
### Conclusion
The RSI-based MA can be a powerful tool for traders looking to enhance their understanding of market trends and momentum. By combining RSI with moving averages, traders can smooth out RSI readings and gain a clearer view of the market’s direction. However, as with any indicator, it should be used in conjunction with other tools and strategies to maximize its effectiveness and reduce risk.
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.
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.
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.
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.
RSI ProfitGuard [CHE]The RSI ProfitGuard Indicator is a comprehensive tool designed to assist traders in making informed decisions by integrating the Relative Strength Index (RSI) with automated Take Profit (TP) and Stop Loss (SL) levels. This indicator enhances trading strategies by providing clear entry signals and risk management parameters.
Key Features
RSIBased Signals: Utilizes RSI crossovers and crossunders to generate trade signals.
Automated TP and SL: Automatically calculates and plots Take Profit and Stop Loss levels based on userdefined methods.
Customizable Trade Types: Supports Long trades, Short trades, or both simultaneously.
Flexible Calculation Methods: Choose between Percentagebased or ATRbased methods for determining TP and SL levels.
Visual Enhancements: Highlights overbought and oversold RSI regions with background colors and marks trade entries with arrows.
Alerts: Provides realtime alerts when TP or SL levels are reached, ensuring timely trade management.
How It Works
1. RSI Calculation: The indicator calculates the RSI value based on the specified length.
2. Trade Signals:
Long Entry: Triggered when RSI crosses above the defined crossover threshold.
Short Entry: Triggered when RSI crosses below the defined crossunder threshold.
3. TP/SL Level Determination:
Percentage Method: Sets TP and SL as a percentage above and below the entry price.
ATR Method: Sets TP and SL based on the Average True Range (ATR), allowing for dynamic adjustments based on market volatility.
4. Visualization: Draws lines and labels on the chart to indicate TP, SL, and entry points.
5. Trade Management: Monitors price movements to determine if TP or SL levels are hit, automatically managing the trade state.
Customization Options
Trade Type Selection: Choose to execute Long trades, Short trades, or both.
RSI Settings:
RSI Length: Defines the period for RSI calculation (default is 14).
Crossover Threshold: RSI level above which a Long entry is signaled (default is 65).
Crossunder Threshold: RSI level below which a Short entry is signaled (default is 35).
Delay Settings: Sets the minimum number of bars between consecutive trade signals to avoid overtrading.
TP/SL Settings:
Method Selection: Choose between Percentage or ATRbased calculations.
Percentage Values: Define the percentage for TP and SL levels.
ATR Settings: Define ATR length and multipliers for TP and SL when using the ATR method.
Visual Settings:
Line Colors and Styles: Customize the appearance of TP, SL, crossover, and crossunder lines.
Transparency: Adjust the transparency of lines for better chart visibility.
Label Offset: Position labels at a specified number of bars to the right for clarity.
Using the Indicator
1. Add to Chart: Apply the RSI ProfitGuard Indicator to your TradingView chart.
2. Configure Settings: Adjust the parameters according to your trading strategy and risk tolerance.
3. Interpret Signals:
Long Entries: Look for green upward arrows indicating potential buy opportunities.
Short Entries: Look for red downward arrows indicating potential sell opportunities.
4. Monitor TP and SL Levels: Observe the plotted lines and labels to manage your trades effectively.
5. Set Up Alerts: Enable alerts to receive notifications when TP or SL levels are reached, ensuring you can act promptly.
Benefits
Enhanced DecisionMaking: Combines RSI signals with clear risk management levels.
Time Efficiency: Automates the calculation and plotting of TP and SL, saving time and reducing manual errors.
Flexibility: Adapts to various trading styles and market conditions through customizable settings.
Risk Management: Helps in defining and adhering to risk parameters, essential for longterm trading success.
Conclusion
The RSI ProfitGuard Indicator is an invaluable tool for traders seeking to integrate technical analysis with automated risk management. Its customizable features and realtime alerts provide a robust framework for executing and managing trades with confidence.
Disclaimer
The content provided with our RSI ProfitGuard Indicator, including all code, scripts, lessons, and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell, or an offer of any financial product or service.
Key Points:
Educational Purpose:
All strategies, tools, and examples included within the RSI ProfitGuard Indicator are provided solely for illustrative purposes. They are designed to demonstrate coding techniques and the functionality of Pine Script within a trading context.
No Financial Advice:
The RSI ProfitGuard Indicator does not constitute financial advice. Users should not rely on it as a basis for making investment or trading decisions.
Hypothetical Results:
Any results or performance metrics derived from using the RSI ProfitGuard Indicator are purely hypothetical. Past performance is not indicative of future results, and there is no guarantee of profitability.
Risk Disclosure:
Trading and investing involve significant risks, including the potential loss of principal. The RSI ProfitGuard Indicator is not suitable for all persons, and users should be aware of the inherent risks involved in trading.
Professional Consultation:
Before making any trading decisions, it is strongly recommended to consult with a qualified financial professional to fully understand the risks and ensure that such decisions align with your financial situation and goals.
User Responsibility:
By using the RSI ProfitGuard Indicator, you acknowledge and agree that all trading decisions are made solely at your own discretion and risk. The developers and providers of the RSI ProfitGuard Indicator assume no responsibility or liability for any losses or damages resulting from its use.
Additional Notes:
No Guarantees:
There are no guarantees regarding the accuracy, reliability, or completeness of the RSI ProfitGuard Indicator. Users utilize the tool at their own risk.
No Endorsement:
Any mention of third-party products, services, or strategies within the RSI ProfitGuard Indicator does not constitute an endorsement or recommendation.
Updates and Modifications:
The RSI ProfitGuard Indicator may be updated or modified over time. Users are responsible for staying informed about any changes and understanding how they may impact the use of the tool.
Summary
This disclaimer clearly states that the RSI ProfitGuard Indicator is intended for educational purposes and should not be used as financial advice. It highlights the risks associated with trading, the hypothetical nature of any results, and the importance of consulting with a financial professional. Additionally, it emphasizes that users are solely responsible for their trading decisions and any outcomes that result from using the indicator.
Tips for Implementation:
Visibility:
Ensure that this disclaimer is prominently displayed wherever the RSI ProfitGuard Indicator is offered, such as on your website, within the TradingView description, or in any accompanying documentation.
Clarity:
Use clear and concise language to make sure that all users understand the limitations and responsibilities associated with using the indicator.
Legal Review:
Consider having the disclaimer reviewed by a legal professional to ensure that it meets all necessary legal requirements and adequately protects your interests.
Regular Updates:
Periodically review and update the disclaimer to reflect any changes in the indicator's functionality or in relevant laws and regulations.
RSI K-Means Clustering [UAlgo]The "RSI K-Means Clustering " indicator is a technical analysis tool that combines the Relative Strength Index (RSI) with K-means clustering techniques. This approach aims to provide more nuanced insights into market conditions by categorizing RSI values into overbought, neutral, and oversold clusters.
The indicator adjusts these clusters dynamically based on historical RSI data, allowing for more adaptive and responsive thresholds compared to traditional fixed levels. By leveraging K-means clustering, the indicator identifies patterns in RSI behavior, which can help traders make more informed decisions regarding market trends and potential reversals.
🔶 Key Features
K-means Clustering: The indicator employs K-means clustering, an unsupervised machine learning technique, to dynamically determine overbought, neutral, and oversold levels based on historical RSI data.
User-Defined Inputs: You can customize various aspects of the indicator's behavior, including:
RSI Source: Select the data source used for RSI calculation (e.g., closing price).
RSI Length: Define the period length for RSI calculation.
Training Data Size: Specify the number of historical RSI values used for K-means clustering.
Number of K-means Iterations: Set the number of iterations performed by the K-means algorithm to refine cluster centers.
Overbought/Neutral/Oversold Levels: You can define initial values for these levels, which will be further optimized through K-means clustering.
Alerts: The indicator can generate alerts for various events, including:
Trend Crossovers: Alerts for when the RSI crosses above/below the neutral zone, signaling potential trend changes.
Overbought/Oversold: Alerts when the RSI reaches the dynamically determined overbought or oversold thresholds.
Reversals: Alerts for potential trend reversals based on RSI crossing above/below the calculated overbought/oversold levels.
RSI Classification: Alerts based on the current RSI classification (ranging, uptrend, downtrend).
🔶 Interpreting Indicator
Adjusted RSI Value: The primary plot represents the adjusted RSI value, calculated based on the relative position of the current RSI compared to dynamically adjusted overbought and oversold levels. This value provides an intuitive measure of the market's momentum. The final overbought, neutral, and oversold levels are determined by K-means clustering and are displayed as horizontal lines. These levels serve as dynamic support and resistance points, indicating potential reversal zones.
Classification Symbols : The "RSI K-Means Clustering " indicator uses specific symbols to classify the current market condition based on the position of the RSI value relative to dynamically determined clusters. These symbols provide a quick visual reference to help traders understand the prevailing market sentiment. Here's a detailed explanation of each classification symbol:
Ranging Classification ("R")
This symbol appears when the RSI value is closest to the neutral threshold compared to the overbought or oversold thresholds. It indicates a ranging market, where the price is moving sideways without a clear trend direction. In this state, neither buyers nor sellers are in control, suggesting a period of consolidation or indecision. This is often seen as a time to wait for a breakout or reversal signal before taking a position.
Up-Trend Classification ("↑")
The up-trend symbol, represented by an upward arrow, is displayed when the RSI value is closer to the overbought threshold than to the neutral or oversold thresholds. This classification suggests that the market is in a bullish phase, with buying pressure outweighing selling pressure. Traders may consider this as a signal to enter or hold long positions, as the price is likely to continue rising until the market reaches an overbought condition.
Down-Trend Classification ("↓")
The down-trend symbol, depicted by a downward arrow, appears when the RSI value is nearest to the oversold threshold. This indicates a bearish market condition, where selling pressure dominates. The market is likely experiencing a downward movement, and traders might view this as an opportunity to enter or hold short positions. This symbol serves as a warning of potential further declines, especially if the RSI continues to move toward the oversold level.
Bullish Reversal ("▲")
This signal occurs when the RSI value crosses above the oversold threshold. It indicates a potential shift from a downtrend to an uptrend, suggesting that the market may start to move higher. Traders might use this signal as an opportunity to enter long positions.
Bearish Reversal ("▼")
This signal appears when the RSI value crosses below the overbought threshold. It suggests a possible transition from an uptrend to a downtrend, indicating that the market may begin to decline. This signal can alert traders to consider entering short positions or taking profits on long positions.
These classification symbols are plotted near the adjusted RSI line, with their positions adjusted based on the standard deviation and a distance multiplier. This placement helps in visualizing the classification's strength and ensuring clarity in the indicator's presentation. By monitoring these symbols, traders can quickly assess the market's state and make more informed trading decisions.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
RSI Analysis with Statistical Summary Scientific Analysis of the Script "RSI Analysis with Statistical Summary"
Introduction
I observed that there are outliers in the price movement liquidity, and I wanted to understand the RSI value at those points and whether there are any notable patterns. I aimed to analyze this statistically, and this script is the result.
Explanation of Key Terms
1. Outliers in Price Movement Liquidity: An outlier is a data point that significantly deviates from other values. In this context, an outlier refers to an unusually high or low liquidity of price movement, which is the ratio of trading volume to the price difference between the open and close prices. These outliers can signal important market changes or unusual trading activities.
2. RSI (Relative Strength Index): The RSI is a technical indicator that measures the speed and change of price movements. It ranges from 0 to 100 and helps identify overbought or oversold conditions of a trading instrument. An RSI value above 70 indicates an overbought condition, while a value below 30 suggests an oversold condition.
3. Mean: The mean is a measure of the average of a dataset. It is calculated by dividing the sum of all values by the number of values. In this script, the mean of the RSI values is calculated to provide a central tendency of the RSI distribution.
4. Standard Deviation (stdev): The standard deviation is a measure of the dispersion or variation of a dataset. It shows how much the values deviate from the mean. A high standard deviation indicates that the values are widely spread, while a low standard deviation indicates that the values are close to the mean.
5. 68% Confidence Interval: A confidence interval indicates the range within which a certain percentage of values of a dataset lies. The 68% confidence interval corresponds to a range of plus/minus one standard deviation around the mean. It indicates that about 68% of the data points lie within this range, providing insight into the distribution of values.
Overview
This Pine Script™, written in Pine version 5, is designed to analyze the Relative Strength Index (RSI) of a stock or other trading instrument and create statistical summaries of the distribution of RSI values. The script identifies outliers in price movement liquidity and uses this information to calculate the frequency of RSI values. At the end, it displays a statistical summary in the form of a table.
Structure and Functionality of the Script
1. Input Parameters
- `rsi_len`: An integer input parameter that defines the length of the RSI (default: 14).
- `outlierThreshold`: An integer input parameter that defines the length of the outlier threshold (default: 10).
2. Calculating Price Movement Liquidity
- `priceMovementLiquidity`: The volume is divided by the absolute difference between the close and open prices to calculate the liquidity of the price movement.
3. Determining the Boundary for Liquidity and Identifying Outliers
- `liquidityBoundary`: The boundary is calculated using the Exponential Moving Average (EMA) of the price movement liquidity and its standard deviation.
- `outlier`: A boolean value that indicates whether the price movement liquidity exceeds the set boundary.
4. Calculating the RSI
- `rsi`: The RSI is calculated with a period length of 14, using various moving averages (e.g., SMA, EMA) depending on the settings.
5. Storing and Limiting RSI Values
- An array `rsiFrequency` stores the frequency of RSI values from 0 to 100.
- The function `f_limit_rsi` limits the RSI values between 0 and 100.
6. Updating RSI Frequency on Outlier Occurrence
- On an outlier occurrence, the limited and rounded RSI value is updated in the `rsiFrequency` array.
7. Statistical Summary
- Various variables (`mostFrequentRsi`, `leastFrequentRsi`, `maxCount`, `minCount`, `sum`, `sumSq`, `count`, `upper_interval`, `lower_interval`) are initialized to perform statistical analysis.
- At the last bar (`bar_index == last_bar_index`), a loop is run to determine the most and least frequent RSI values and their frequencies. Sum and sum of squares of RSI values are also updated for calculating mean and standard deviation.
- The mean (`mean`) and standard deviation (`stddev`) are calculated. Additionally, a 68% confidence interval is determined.
8. Creating a Table for Result Display
- A table `resultsTable` is created and filled with the results of the statistical analysis. The table includes the most and least frequent RSI values, the standard deviation, and the 68% confidence interval.
9. Graphical Representation
- The script draws horizontal lines and fills to indicate overbought and oversold regions of the RSI.
Interpretation of the Results
The script provides a detailed analysis of RSI values based on specific liquidity outliers. By calculating the most and least frequent RSI values, standard deviation, and confidence interval, it offers a comprehensive statistical summary that can help traders identify patterns and anomalies in the RSI. This can be particularly useful for identifying overbought or oversold conditions of a trading instrument and making informed trading decisions.
Critical Evaluation
1. Robustness of Outlier Identification: The method of identifying outliers is solely based on the liquidity of price movement. It would be interesting to examine whether other methods or additional criteria for outlier identification would lead to similar or improved results.
2. Flexibility of RSI Settings: The ability to select various moving averages and period lengths for the RSI enhances the adaptability of the script, allowing users to tailor it to their specific trading strategies.
3. Visualization of Results: While the tabular representation is useful, additional graphical visualizations, such as histograms of RSI distribution, could further facilitate the interpretation of the results.
In conclusion, this script provides a solid foundation for analyzing RSI values by considering liquidity outliers and enables detailed statistical evaluation that can be beneficial for various trading strategies.
RSI / Connectable [Azullian]Enhance your trading approach with the modular RSI indicator, skilled in identifying market extremes. Simplify pattern visualization and signal weighting for more efficient strategy formulation.
This connectable RSI indicator is part of an indicator system designed to help test, visualize and build strategy configurations without coding. Like all connectable indicators , it interacts through the TradingView input source, which serves as a signal connector to link indicators to each other. All connectable indicators send signal weight to the next node in the system until it reaches either a connectable signal monitor, signal filter and/or strategy.
█ UNIFORM SETTINGS AND A WAY OF WORK
Although connectable indicators may have specific weight scoring conditions, they all aim to follow a standardized general approach to weight scoring settings, as outlined below.
■ Connectable indicators - Settings
• 🗲 Energy: Energy applies an ATR multiplier to the plotted shapes on the chart. A higher value plots shapes farther away from the candle, enhancing visibility.
• ☼ Brightness: Brightness determines the opacity of the shape plotted on the chart, aiding visibility. Indicator weight also influences opacity.
• → Input: Use the input setting to specify a data source for the indicator. Here you can connect the indicator to other indicators.
• ⌥ Flow: Determine where you want to receive signals from:
○ Both: Weights from this indicator and the connected indicator will apply
○ Indicator only: Only weights from this indicator will apply
○ Input only: Only weights from the connected indicator will apply
• ⥅ Weight multiplier: Multiply all weights in the entire indicator by a given factor, useful for quickly testing different indicators in a granular setup.
• ⥇ Threshold: Set a threshold to indicate the minimum amount of weight it should receive to pass it through to the next indicator.
• ⥱ Limiter: Set a hard limit to the maximum amount of weight that can be fed through the indicator.
■ Connectable indicators - Weight scoring settings
▢ Weight scoring conditions
• SM – Signal mode: Enable specific conditions for weight scoring
○ All: All signals will be scored.
○ Entries only: Only entries will score.
○ Exits only: Only exits will score.
○ Entries & exits: Both entries and exits will score.
○ Zone: Continuous scoring for each candle within the zone.
• SP – Signal period: Defines a range of candles within which a signal can score.
• SC - Signal count: Specifies the number of bars to retrospectively examine and score.
○ Single: Score for a single occurrence
○ All occurrences: Score for all occurrences
○ Single + Threshold: Score for single occurrences within the signal period (SP)
○ Every + Threshold: Score for all occurrences within the signal period (SP)
▢ Weight scoring direction
• ES: Enter Short weight
• XL: Exit long weight
• EL: Enter Long weight
• XS: Exit Short weight
▢ Weight scoring values
• Weights can hold either positive or negative scores. Positive weights enhance a particular trading direction, while negative weights diminish it.
■ Entries, exits and zone illustrated on a standard RSI indicator when the RSI is overbought.
█ RSI - INDICATOR SETTINGS
■ Main settings
• Enable/Disable Indicator: Toggle the entire indicator on or off.
• S - Source: Choose an alternative data source for the RSI calculation.
• T - Timeframe: Select an alternative timeframe for the RSI calculation.
• LE - Length: Define the number of bars or periods used in the RSI calculation.
• OB - Overbought Level: Determine the RSI value at which overbought conditions are met.
• OS - Oversold Level: Specify the RSI value at which oversold conditions are met.
■ Scoring functionality
• The RSI scores long entries when the RSI enters OS: oversold area
• The RSI scores long exits when the RSI exits OS: oversold area
• The RSI scores long zones the entire time the RSI is in OS: oversold area
• The RSI scores short entries when the RSI enters OB: overbought area
• The RSI scores short exits when the RSI exits OB: overbought area
• The RSI scores short zones the entire time the RSI is in OB: overbought area
█ PLOTTING
• Standard: Symbols (EL, XS, ES, XL) appear relative to candles based on set conditions. Their opacity and position vary with weight.
• Conditional Settings: A larger icon appears if global conditions are met. For instance, with a Threshold(⥇) of 12, Signal Period (SP) of 3, and Scoring Condition (SC) set to "EVERY", an RSI signaling over two times in 3 candles (scoring 6 each) triggers a larger icon.
█ USAGE OF CONNECTABLE INDICATORS
■ Connectable chaining mechanism
Connectable indicators can be connected directly to the signal monitor, signal filter or strategy , or they can be daisy chained to each other while the last indicator in the chain connects to the signal monitor, signal filter or strategy. When using a signal filter you can chain the filter to the strategy input to make your chain complete.
• Direct chaining: Connect an indicator directly to the signal monitor, signal filter or strategy through the provided inputs (→).
• Daisy chaining: Connect indicators using the indicator input (→). The first in a daisy chain should have a flow (⌥) set to 'Indicator only'. Subsequent indicators use 'Both' to pass the previous weight. The final indicator connects to the signal monitor, signal filter, or strategy.
■ Set up this indicator with a signal filter and strategy
The indicator provides visual cues based on signal conditions. However, its weight system is best utilized when paired with a connectable signal filter, signal monitor, or strategy .
Let's connect the RSI to a connectable signal filter and a strategy :
1. Load all relevant indicators
• Load RSI / Connectable
• Load Signal filter / Connectable
• Load Strategy / Connectable
2. Signal Filter: Connect the RSI to the Signal Filter
• Open the signal filter settings
• Choose one of the three input dropdowns (1→, 2→, 3→) and choose : RSI / Connectable: Signal Connector
• Toggle the enable box before the connected input to enable the incoming signal
3. Signal Filter: Update the filter signals settings if needed
• The default settings of the filter enable EL (Enter Long), XL (Exit Long), ES (Enter Short) and XS (Exit Short).
4. Signal Filter: Update the weight threshold settings if needed
• All connectable indicators load by default with a score of 6 for each direction (EL, XL, ES, XS)
• By default, weight threshold (TH) is set at 5. This allows each occurrence to score, as the default score in each connectable indicator is 1 point above the threshold. Adjust to your liking.
5. Strategy: Connect the strategy to the signal filter in the strategy settings
• Select a strategy input → and select the Signal filter: Signal connector
6. Strategy: Enable filter compatible directions
• Set the signal mode of the strategy to a compatible direction with the signal filter.
Now that everything is connected, you'll notice green spikes in the signal filter representing long signals, and red spikes indicating short signals. Trades will also appear on the chart, complemented by a performance overview. Your journey is just beginning: delve into different scoring mechanisms, merge diverse connectable indicators, and craft unique chains. Instantly test your results and discover the potential of your configurations. Dive deep and enjoy the process!
█ BENEFITS
• Adaptable Modular Design: Arrange indicators in diverse structures via direct or daisy chaining, allowing tailored configurations to align with your analysis approach.
• Streamlined Backtesting: Simplify the iterative process of testing and adjusting combinations, facilitating a smoother exploration of potential setups.
• Intuitive Interface: Navigate TradingView with added ease. Integrate desired indicators, adjust settings, and establish alerts without delving into complex code.
• Signal Weight Precision: Leverage granular weight allocation among signals, offering a deeper layer of customization in strategy formulation.
• Advanced Signal Filtering: Define entry and exit conditions with more clarity, granting an added layer of strategy precision.
• Clear Visual Feedback: Distinct visual signals and cues enhance the readability of charts, promoting informed decision-making.
• Standardized Defaults: Indicators are equipped with universally recognized preset settings, ensuring consistency in initial setups across different types like momentum or volatility.
• Reliability: Our indicators are meticulously developed to prevent repainting. We strictly adhere to TradingView's coding conventions, ensuring our code is both performant and clean.
█ COMPATIBLE INDICATORS
Each indicator that incorporates our open-source 'azLibConnector' library and adheres to our conventions can be effortlessly integrated and used as detailed above.
For clarity and recognition within the TradingView platform, we append the suffix ' / Connectable' to every compatible indicator.
█ COMMON MISTAKES, CLARIFICATIONS AND TIPS
• Removing an indicator from a chain: Deleting a linked indicator and confirming the "remove study tree" alert will also remove all underlying indicators in the object tree. Before removing one, disconnect the adjacent indicators and move it to the object stack's bottom.
• Point systems: The azLibConnector provides 500 points for each direction (EL: Enter long, XL: Exit long, ES: Enter short, XS: Exit short) Remember this cap when devising a point structure.
• Flow misconfiguration: In daisy chains the first indicator should always have a flow (⌥) setting of 'indicator only' while other indicator should have a flow (⌥) setting of 'both'.
• Hide attributes: As connectable indicators send through quite some information you'll notice all the arguments are taking up some screenwidth and cause some visual clutter. You can disable arguments in Chart Settings / Status line.
• Layout and abbreviations: To maintain a consistent structure, we use abbreviations for each input. While this may initially seem complex, you'll quickly become familiar with them. Each abbreviation is also explained in the inline tooltips.
• Inputs: Connecting a connectable indicator directly to the strategy delivers the raw signal without a weight threshold, meaning every signal will trigger a trade.
█ A NOTE OF GRATITUDE
Through years of exploring TradingView and Pine Script, we've drawn immense inspiration from the community's knowledge and innovation. Thank you for being a constant source of motivation and insight.
█ RISK DISCLAIMER
Azullian's content, tools, scripts, articles, and educational offerings are presented purely for educational and informational uses. Please be aware that past performance should not be considered a predictor of future results.
