Global M2 Money Supply Top20 + Offset & WaveThe M2 Top20 is a global aggregation of the M2 money supply from the 20 largest economies in the world , providing a comprehensive view of the total liquidity in the global financial system. It is expressed in trillions of USD.
This script calculates and visualizes the M2 Money Supply of the Top 20 Global Economies, adjusted to various timeframes (4H, 1D, 1W, 1M) with customizable offset adjustments (in days) from -1000 days to +1000 days. This indicator includes data from the Americas, Europe, Africa, and the Asia Middle East , offering a diverse and balanced representation of major economic regions. The M2 of each country has been converted to USD.
Additionally, the user can set a minimum and maximum offset to create a wave around the main offset and expand the comparison.
Combining these options, this indicator enables users to visualize a range of the global money supply, making it useful for market analysis, economic forecasting, and understanding macroeconomic trends. This indicator is particularly valuable for traders and analysts interested in understanding the dynamics of global monetary systems and their potential impact on financial markets.
Key Features:
Global M2 Money Supply calculation from the Top 20 Economies.
Adjustable Offset: Adjust the offset to align the indicator with the best bar. Adjustment in days, usable on different timeframes (1D, 1W, 4H, 1M).
Wave Projection: Displays a "probability cloud"—a smoothed area that shows the probable path of Bitcoin, derived from shifts in global liquidity.
Min/Max Offset Adjustments: Customizable offsets allow you to determine the range of future windows, helping to shape the wave and better identify liquidity-driven turning points.
Use Cases:
Economic Forecasting: Identify trends in global money supply and their potential market impact (e.g., historically leads Bitcoin price by +/- 78 days to +/-108 days).
Market Analysis: Track the growth or contraction of money supply across key economies.
Macro-Economic Analysis: Understand the relationship between monetary policies and market performance.
How to use:
Add the indicator to your chart.
Set the timeframe to 1D to customize the offset.
Set the Offset (in days).
Set the Offset Range Minimum and Maximum.
Show/Hide the Range Wave
.
Use offset = 0 to have the indicator align directly with the current data, without any shift, providing a baseline for comparison with the most recent market conditions.
Countries included in the M2 Top20:
China (CN), Japan (JP), South Korea (KR), Hong Kong (HK), Taiwan (TW), India (IN), Saudi Arabia (SA), Thailand (TH), Vietnam (VN), United Arab Emirates (AE), Malawi (MW) – Africa, United States (US), Canada (CA), Brazil (BR), Mexico (MX), Eurozone (EU), United Kingdom (GB), Russia (RU), Poland (PL), Switzerland (CH).
These countries were selected from the ranking of the World Economy Indicator of Trading View .
Forecasting
EPS & Sales/Revenue Growth MarkerThis script plots the Revenue Growth and EPS Growth % on Earnings Date.
Idea Credit: Special thanks to @dharmeshrbhatt for inspiring the concept behind this tool.
Developed and Published by learningvitals.
Plots Revenue Growth % and EPS Growth % on earnings date.
Choose label position: Above Bar, Below Bar, Top, or Bottom.
Customizable growth colors based on combined EPS and Revenue performance.
Customizable line style and colors.
Controls max number of labels to keep the chart clean.
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:
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🔮 Linear Regression: PineScript Technical Parameters 🔮
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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.
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⯁ 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.
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⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
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🔹 CONDITIONS TO BUY 📈
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• 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
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🔸 CONDITIONS TO SELL 📉
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• 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
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🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
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⯁ UNIQUE FEATURES
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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
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📜 SCRIPT : RSI Full Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
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o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Market Timing(Mastersinnifty)Overview
Market Timing (Mastersinnifty) is a proprietary visualization tool designed to help traders study historical market behavior through structural pattern similarity.
The script analyzes the most recent session’s price action and identifies the closest-matching historical sequence among thousands of past patterns. Once a match is found, the script projects the subsequent historical price path onto the current chart for easy visual reference.
Unlike traditional indicators, Market Timing (Mastersinnifty) does not generate trade signals. Instead, it offers a unique historical scenario analysis based on quantified structural similarity.
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How It Works
- The script captures the last 20 closing prices and compares them to historical price sequences from the past 8000 bars.
- Similarity is computed using the Euclidean distance formula (sum of squared differences) between the current pattern and historical candidates.
- Upon finding the most similar past pattern, the subsequent historical movement is normalized relative to session opening and plotted onto the current chart using projection lines.
- The projection automatically adapts to intraday, daily, weekly, or monthly timeframes, with the option for manual or automatic projection length settings.
- Session start detection is handled automatically based on volume thresholds and price-time analysis to adjust for market openings across different instruments.
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Key Features
- Historical Pattern Matching: Quantitative matching of the most similar past price structure.
- Dynamic Projections: Visualizes likely historical scenarios based on past market behavior.
- Auto/Manual Projection Length: Flexible control over the number of projected bars.
- Multi-Timeframe Support: Works seamlessly across intraday, daily, weekly, and monthly charts.
- Purely Visual Context: Designed to support human decision-making without replacing it with automatic trade signals.
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Who Can Benefit
- Traders studying market structure repetition and price symmetry.
- Visual thinkers who prefer scenario-based planning over fixed indicator systems.
- Intraday, swing, and position traders looking for historical context to complement price action, volume, and momentum studies.
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How to Use
- Apply the script to any asset — including indices, stocks, commodities, forex, or crypto.
- Select your preferred timeframe.
- Choose "Auto" or "Custom" for the projection length.
- Observe the projected lines:
- Upward slope = Historical bullish continuation.
- Downward slope = Historical bearish continuation.
- Flat movement = Historical sideways movement.
- Combine insights with volume, support/resistance, and price action for better decision-making.
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Important Notes
- This script does not predict the future. It offers a visual reference based on historical similarity.
- Always validate projected scenarios with live market conditions.
- Market structure evolves; past behavior may not repeat under new market dynamics.
- Use this tool for educational and research purposes only.
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Disclaimer
This is not financial advice. The Market Timing (Mastersinnifty) tool is intended for research and educational purposes only. Trading involves risk, and past performance does not guarantee future results. Always apply sound risk management practices.
Bitcoin as % Global M2 signalThis script provides signal system:
Buy signal: each time the YoY of the Global M2 rises more than 2.5% while the distance between the bitcoin price as a percentage of the Global M2 is below its yearly SMA.
Sell signal: the distance between the bitcoin price as a percentage of the Global M2 and its yearly SMA is > 0.7
This is a very simple system, but it seems to work pretty well to ride the bitcoin price cycle wave.
The parameters are hard coded but they can be easily changed to test different levels for both the buy and sell signals.
Global M2 YoY % Increase signalThe script produces a signal each time the global M2 increases more than 2.5%. This usually coincides with bitcoin prices pumps, except when it is late in the business cycle or the bitcoin price / halving cycle.
It leverages dylanleclair Global M2 YoY % change, with several modifications:
adding a 10 week lead at the YoY Change plot for better visibility, so that the bitcoin pump moreless coincides with the YoY change.
signal increases > 2.5 in Global M2 at the point at which they occur with a green triangle up.
BTST By ANTThe BTST Indicator is a powerful tool specifically designed for traders in the Indian stock market. This unique indicator identifies and highlights key price movements at a pivotal time—3:15 PM. This time is crucial for making BTST (Buy Today, Sell Tomorrow) decisions, a popular trading strategy in India.
Key Features:
Gap Identification : The indicator detects whether the current price action represents a gap-up or gap-down situation compared to the Heikinashi candle close price. This information is vital for short-term traders looking to capitalize on price momentum.
Visual Alerts : When a gap-up trend is detected, a green label "Gap Up" is displayed above the relevant bar. Similarly, a red label "Gap Down" appears below the bar for gap-down movements. These visual indicators help traders make quick and informed decisions.
User-Friendly Insights: The BTST Indicator provides vital information about last closed prices and the dynamics between normal candles and Heikinashi candles. With detailed logs, users can see the exact conditions leading to buy or sell signals, helping optimize trading strategies.
Why Use the BTST Indicator?
Timeliness: The focus on the 3:15 PM mark aligns perfectly with trading patterns and market behavior specific to the Indian stock market, making it an invaluable addition to your trading arsenal.
Enhanced Decision-Making: By receiving immediate visual cues on significant price movements, traders can execute their BTST strategies with greater confidence and speed.
Designed for Indian Markets: This indicator caters specifically to the nuances of Indian stock trading, ensuring relevance and effectiveness for local traders.
Start utilizing the BTST Indicator today to enhance your trading strategies and position yourself for successful trades in the Indian stock market!
Global M2 [BizFing]MARKETSCOM:BITCOIN ECONOMICS:USM2
This is an indicator designed to show the correlation between the global M2 money supply and Bitcoin.
This indicator basically provides a Global M2 index by summing the M2 money supply data from the United States, South Korea, China, Japan, the EU, and the United Kingdom.
Furthermore, it is configured to allow you to add or remove the M2 data of desired countries within the settings.
I hope this proves to be a small aid in predicting the future price of Bitcoin.
If you have any questions or require any improvements while using it, please feel free to contact me.
Thank you.
Sharpe & Sortino Ratio PROSharpe & Sortino Ratio PRO offers an advanced and more precise way to calculate and visualize the Sharpe and Sortino Ratios for financial assets on TradingView. Its main goal is to provide a scientifically accurate method for assessing the risk-adjusted performance of assets, both in the short and long term. Unlike TradingView’s built-in metrics, this script correctly handles periodic returns, uses optional logarithmic returns, properly annualizes both returns and volatility, and adjusts for the risk-free rate — all critical factors for truly meaningful Sharpe and Sortino calculations.
Users can customize the rolling analysis window (e.g., 252 periods for one year on daily data) and the long-term smoothing period (e.g., 1260 periods for five years). There’s also an option to select between linear and logarithmic returns and to manually input a risk-free rate if real-time data from FRED (the 3-Month T-Bill Rate via FRED:DGS3MO) is unavailable. Based on the chart’s timeframe (daily, weekly, or monthly), the script automatically adjusts the risk-free rate to a per-period basis.
The Sharpe Ratio is calculated by first determining the asset’s excess returns (returns after subtracting the risk-free return per period), then computing the average and standard deviation of those excess returns over the specified window, and finally annualizing these figures separately — in line with best scientific practices (Sharpe, 1994). The Sortino Ratio follows a similar approach but only considers negative returns, focusing specifically on downside risk (Sortino & Van der Meer, 1991).
To enhance readability, the script visualizes the ratios using a color gradient: strong negative values are shown in red, neutral values in yellow, and strong positive values in green. Additionally, the long-term averages for both Sharpe and Sortino are plotted with steady colors (teal and orange, respectively), making it easier to spot enduring performance trends.
Why calculating Sharpe and Sortino Ratios manually on TradingView is necessary?
While TradingView provides basic Sharpe and Sortino Ratios, they come with significant methodological flaws that can lead to misleading conclusions about an asset’s true risk-adjusted performance.
First, TradingView often computes volatility based on the standard deviation of price levels rather than returns (TradingView, 2023). This method is problematic because it causes the volatility measure to be directly dependent on the asset’s absolute price. For instance, a stock priced at $1,000 will naturally show larger absolute daily price moves than a $10 stock, even if their percentage changes are similar. This artificially inflates the measured standard deviation and, as a result, depresses the calculated Sharpe Ratio.
Second, TradingView frequently neglects to adjust for the risk-free rate. By treating all returns as risky returns, the computed Sharpe Ratio may significantly underestimate risk-adjusted performance, especially when interest rates are high (Sharpe, 1994).
Third, and perhaps most critically, TradingView doesn’t properly annualize the mean excess return and the standard deviation separately. In correct financial math, the mean excess return should be multiplied by the number of periods per year, while the standard deviation should be multiplied by the square root of the number of periods per year (Cont, 2001; Fabozzi et al., 2007). Incorrect annualization skews the Sharpe and Sortino Ratios and can lead to under- or overestimating investment risk.
These flaws lead to three major issues:
• Overstated volatility for high-priced assets.
• Incorrect scaling between returns and risk.
• Sharpe Ratios that are systematically biased downward, especially in high-price or high-interest environments.
How to properly calculate Sharpe and Sortino Ratios in Pine Script?
To get accurate results, the Sharpe and Sortino Ratios must be calculated using the correct methodology:
1. Use returns, not price levels, to calculate volatility. Ideally, use logarithmic returns for better mathematical properties like time additivity (Cont, 2001).
2. Adjust returns by subtracting the risk-free rate on a per-period basis to obtain true excess returns.
3. Annualize separately:
• Multiply the mean excess return by the number of periods per year (e.g., 252 for daily data).
• Multiply the standard deviation by the square root of the number of periods per year.
4. Finally, divide the annualized mean excess return by the annualized standard deviation to calculate the Sharpe Ratio.
The Sortino Ratio follows the same structure but uses downside deviations instead of standard deviations.
By following this scientifically sound method, you ensure that your Sharpe and Sortino Ratios truly reflect the asset’s real-world risk and return characteristics.
References
• Cont, R. (2001). Empirical properties of asset returns: stylized facts and statistical issues. Quantitative Finance, 1(2), pp. 223–236.
• Fabozzi, F.J., Gupta, F. and Markowitz, H.M. (2007). The Legacy of Modern Portfolio Theory. Journal of Investing, 16(3), pp. 7–22.
• Sharpe, W.F. (1994). The Sharpe Ratio. Journal of Portfolio Management, 21(1), pp. 49–58.
• Sortino, F.A. and Van der Meer, R. (1991). Downside Risk: Capturing What’s at Stake in Investment Situations. Journal of Portfolio Management, 17(4), pp. 27–31.
• TradingView (2023). Help Center - Understanding Sharpe and Sortino Ratios. Available at: www.tradingview.com (Accessed: 25 April 2025).
Death Metal Fire & IceA dynamic support/resistance system built from modified Fibonacci-based moving averages, designed to assist with structure identification in trending markets — particularly when price is moving into uncharted territory.
🧠 Core Logic
Twelve Fibonacci-based moving averages are mathematically adjusted by the square root of a standard trading Fibonacci ratio to create projected zones above and around price. These dynamic levels are labeled L1 to L12 and automatically adjust with trend velocity and volatility.
Faster levels (L1–L5) often serve as immediate reaction zones in volatile markets and provide ceilings for rising price action.
Slower levels (L6–L12) tend to behave as longer-term structure — both above and below current price.
These levels are dynamic, non-static, and provide forward-looking structure that adapts as markets move. Price tends to range between these levels until conditions change, which becomes visually apparent through the breaking of support/resistance.
⚙️ Features
Smart Mode: Hides levels that are not relevant to current price proximity. Price action needs to get within 10% of the level for it to appear. If price action moves away from the level, there will be a cooldown period for the line to cease printing on the chart.
Gradient Mode: Fills space between levels with a visual overlay to help visualize distance and potential volatility.
Levels can be toggled on/off individually.
🧩 Use Case
Designed for trending markets where traditional support/resistance is unavailable or unreliable.
Applicable across all assets and timeframes — stocks, crypto, futures, etc.
ka66: ADR EstimationThis is based on Daryl Guppy's Average Daily Range indicator, the link is difficult to find, but it is an estimation/projection indicator for a daily range.
The thesis is (if I understand correctly):
The range (high - low) of a particular day can be determined, with 85% probability, by taking the ranges of the last 5 days, and getting their average, then multiplying this average value by 0.75. This final value is the estimated range for the next day.
The indicator does not say anything about potential direction, so it may be used as a Take Profit or Stop Loss estimator for the trading strategy in use. Either on the daily timeframe, or an intraday timeframe.
And if we enter the market intraday for a day trade, when the day's range has already exceeded or is close to exceeding the estimated/projected value, perhaps the move is already quite exhausted, and the trade needs to be reconsidered.
A further implication is: if 0.75 multiple occurs with 85% probability, then a lower multiple is even more probable, if one was looking for a more conservative estimate.
The indicator shows three things for a visual inspection of the validity of this concept (and allows basic customisation of parameters):
The day's range, shown in a translucent gray/deep green, as columns. This is the current bar's range. If intraday, it will repaint.
The 5 day average up to the current bar, shown as a step-line plot in orange. If intraday, it will repaint.
The projected range: a thinner blue histogram column, this is offset one bar forward, as it is a future estimate/forward-looking. It too will repaint if the current day is still not complete.
To evaluate the historical results of the chosen settings visually (eye-ball it!), compare the blue histogram bar to the gray bar/column, i.e. the estimate vs. actual range:
When the blue bar is generally within the gray column, and close enough to that column's size/range, then the projected estimation has been reasonable.
if the blue bar tends to be relatively smaller than the gray bar, then we are underestimating often. Increase the projection multiple setting, as a simple fix.
if the blue bar tends to exceed the range of the gray bar a lot, we are overestimating often. Lower the projection multiple setting, as a simple fix.
Guppy's document says that they basically calculate this ADR for multiple markets and focus on markets with the top 5 ranges (in descending order, of course), to maximise the profit potential on intraday trades planned for the next day. Because it is an estimation, this calculation can be run at the end of the day on completed bars.
This indicator also allows displaying the value as percentages, taking the logic of the ATR% (ATR Percent) indicator, which divides the ATR by the close value and multiplies it by 100 to get a normalised percentage value, allowing it to be compared across markets (but in the same timeframe!).
QuantumSync Pulse [ w.aritas ]QuantumSync Pulse (QSP) is an advanced technical indicator crafted for traders seeking a dynamic and adaptable tool to analyze diverse market conditions. By integrating momentum, mean reversion, and regime detection with quantum-inspired calculations and entropy analysis, QSP offers a powerful histogram that reflects trend strength and market uncertainty. With multi-timeframe synchronization, adaptive filtering, and customizable visualization, it’s a versatile addition to any trading strategy.
Key Features
Hybrid Signals: Combines momentum and mean reversion, dynamically weighted by market regime.
Quantum Tunneling: Enhances responsiveness in volatile markets using volatility-adjusted calculations.
3-State Entropy: Assesses market uncertainty across up, down, and neutral states.
Regime Detection: Adapts signal weights with Hurst exponent and volatility ROC.
Multi-Timeframe Alignment: Syncs with higher timeframe trends for context.
Customizable Histogram: Displays trend strength with ADX-based visuals and flexible styling.
How to Use and Interpret
Histogram Interpretation
Positive (Above Zero): Bullish momentum; color intensity shows trend strength.
Negative (Below Zero): Bearish momentum; gradients indicate weakness.
Overlaps: Alignment of final_z (signal) and ohlc4 (price) histograms highlights key price levels or turning points.
Regime Visualization
Green Background: Trending market; prioritize momentum signals.
Red Background: Mean-reverting market; focus on reversion signals.
Blue Background: Neutral state; balance both signal types.
Trading Signals
Buy: Histogram crosses above zero or shows positive divergence between histograms.
Sell: Histogram crosses below zero or exhibits negative divergence.
Confirmation: Match signals with regime background—green for trends, red for ranges.
Customization
Tweak Momentum Length, Entropy Lookback, and Hurst Exponent Lookback for sensitivity.
Adjust color themes and transparency to suit your charts.
Tips for Optimal Use
Timeframes: Use higher timeframes (1h, 4h) for trend context and lower (5m, 15m) for entries.
Pairing: Combine with RSI, MACD, or volume indicators for confirmation.
Backtesting: Test settings on historical data for asset-specific optimization.
Overlaps: Watch for histogram overlaps to identify support, resistance, or reversals.
Simulated Performance
Trending Markets: Histogram stays above/below zero, with overlaps at retracements for entries.
Range-Bound Markets: Oscillates around zero; overlaps signal reversals in red regimes.
Volatile Markets: Quantum tunneling ensures quick reactions, with filters reducing noise.
Elevate your trading with QuantumSync Pulse—a sophisticated tool that adapts to the market’s rhythm and your unique style.
Auto Trend Channel + Buy/Sell AlertsThis indicator automatically detects trend channels using a linear regression line, and dynamically plots upper and lower channel boundaries based on standard deviation. It helps traders identify potential Buy and Sell zones with clear visual signals and customizable alerts.
💡 How It Works:
🧠 Regression-Based Channel: Calculates the central trend line using ta.linreg() over a user-defined length.
📏 Dynamic Boundaries: Upper and lower channel lines are offset by a multiplier of the standard deviation for precision volatility tracking.
✅ Buy Signals: Triggered when price crosses above the lower boundary — potential bounce entry.
❌ Sell Signals: Triggered when price crosses below the upper boundary — potential reversal exit.
🔔 Alerts Enabled: Get real-time alerts when price touches the channel lines.
NIG Probability TableNormal-Inverse Gaussian Probability Table
This indicator implements the Normal-Inverse Gaussian (NIG) distribution to estimate the likelihood of future price based on recent market behavior.
📊 Key Features:
- Estimates the parameters (α: tail heaviness, β: skewness, δ: scale, μ: location)
of the NIG distribution using a sliding window over log returns.
- Uses a numerically approximated version of the modified Bessel function (K₁)
to calculate the NIG probability density function (PDF).
- Normalizes the total probability across all bins to ensure the values are interpretable.
- Displays a dynamic probability table showing the chance of future returns falling into each bin.
⚠️ Notes:
- This is a real-time approximation. The Bessel function and posterior inference are simplified.
- Tail probabilities and shape parameters are sensitive to the window size and input settings.
- Useful for risk analysis, option overlays, and strategy filters.
M2 Global Liquidity Index [Extended + Offset]M2 Global Liquidity Index
This indicator visualizes global M2 money supply, weighted in USD, based on major economic regions.
Features:
Standard Mode: Includes M2 data from the USA, China, Eurozone, Japan, and the UK.
Extended Mode: Adds Switzerland, Canada, India, Russia, Brazil, South Korea, Mexico, and South Africa.
Offset Function: Adjustable time lag (78 or 108 days) to analyze the delayed impact of liquidity on financial markets.
Use Case:
Designed to help identify global liquidity cycles and assess potential turning points in financial markets. Rising global liquidity generally supports risk assets like equities and crypto, while declining liquidity can put downward pressure on these markets.
Technical Details:
Non-USD M2 values are converted using real-time FX rates.
All values are displayed in trillions of USD (Tn).
Note:
Not all countries release M2 data in real-time or at the same frequency. Minor delays and discrepancies may occur.
Example:
Log-Normal Price ForecastLog-Normal Price Forecast
This Pine Script creates a log-normal forecast model of future price movements on a TradingView chart, based on historical log returns. It plots expected price trajectories and bands representing different levels of statistical deviation.
Parameters
Model Length – Number of bars used to calculate average and standard deviation of log returns (default: 100).
Forecast Length – Number of bars into the future for which the forecast is projected (default: 100, max: 500).
Volatility SMA Length – The smoothing length for the standard deviation (default: 20).
Confidence Intervals – Confidence intervals for price bands (default: 95%, 99%, 99.9%).
for your comparison: Global M2 Money Supply // Days Offset =📈 Global M2 Money Supply Overlay – Offset Adjustable
This script plots an aggregated, FX-adjusted global M2 money supply index directly on your TradingView chart. It pulls M2 data from multiple global regions—including North America, Europe, Asia, Latin America, and more—and normalizes it for comparison in USD terms.
You can apply a custom time offset to the M2 line using the settings, allowing you to test potential leading or lagging correlations between global liquidity and market price action (e.g., Bitcoin, equities, commodities).
💡 Ideal for macro traders, long-term investors, and anyone interested in liquidity-driven market behavior.
Features:
Combines M2 data from 20+ countries and currency zones
FX-adjusted for consistency in USD terms
Offset slider to shift M2 data forward or backward in time
Scaled to trillions for readability
Plots directly on the main chart for visual comparison
Log-Normal Price DistributionThis Pine Script indicator plots a log-normal distribution model of future price projections on a TradingView chart. It visualizes the potential price ranges based on the statistical properties (mean and standard deviation) of log returns over a defined period. It's particularly useful for analyzing potential volatility and predicting future price ranges.
John M Oscillator with Zero-Cross Range ScalingThis oscillator tries to measure momentum by comparing the current price to the Heikin Ashi open price, then scales that signal based on how much the price has moved since the last time the signal crossed zero. This makes the strength of the move relative to the recent market activity, which can help identify overbought/oversold zones more adaptively than traditional oscillators.
Helps you spot trend shifts early by watching for zero crossings.
The scaling helps you judge if the trend is weak or strong, instead of just relying on absolute price movement.
Ideal for momentum-based entries/exits, divergence spotting, and avoiding fakeouts.
Components:
1. Heikin Ashi Values:
- Heikin Ashi open is the average of the previous period's open and close.
- Heikin Ashi close is the average of the current period's open, high, low, and close.
2. Basic Oscillator Calculation:
- Calculated by subtracting the Heikin Ashi open from the current close price.
3. Smoothing:
- An EMA is applied to the basic oscillator value for noise reduction.
4. Zero-Cross Range Scaling:
- Identifies the range between the last two zero crossings.
- Finds the largest candle range (High to Low) within this zero-cross range.
- Scales the oscillator as a percentage of this largest range.
5. Color Coding:
- The oscillator plot is green when positive and red when negative.
6. Reference Lines:
- Horizontal lines are drawn at -100, -80, -70, -50, 0, 50, 70, 80, and 100 for reference.
Use Case:
This oscillator helps traders identify trends and momentum with a percentage scale based on recent price action. The scaling provides a view of the oscillator's strength relative to the most significant price movement since the last trend change, making it easier to identify potential reversals or trend continuations
Note: the script is set to default time frame of 6hr. Personally, i use the 1 hr time frame. play with it to find what works for your style of trading.
Daily ATR BandsATR Finder – Volatility Scanner for Smarter Trade Setups
The ATR Finder is a precision tool designed to help traders quickly identify high-volatility assets using the Average True Range (ATR) – a key metric in assessing market momentum and potential breakout zones. By automatically scanning and highlighting tickers or candles with elevated ATR values relative to their recent historical range, this indicator helps you filter for setups that are more likely to experience significant price moves.
Whether you're a day trader seeking intraday momentum or a swing trader looking for setups with strong follow-through potential, the ATR Finder cuts through the noise and visually signals which assets are "on the move." It can be paired with other indicators or price action tools to create a high-conviction trading strategy focused on volatility expansion.
Key Features:
Dynamic ATR Calculation over a user-defined period
Visual Alerts or Color-Coding for above-threshold volatility spikes
Supports Multiple Timeframes for both short- and long-term volatility analysis
Great for spotting breakout opportunities, gap continuations, or trend reversals
Use the ATR Finder to stay ahead of price action and build a watchlist that moves with purpose. Perfect for scalpers, breakout traders, and anyone who respects the power of volatility.
Gabriel's Asset Rotation System📈 Gabriel's Asset Rotation System
Overview
Gabriel’s Asset Rotation System is an advanced multi-asset trend-following tool that dynamically ranks and rotates up to 6 assets (plus USD) based on a customizable trend scoring matrix. Using enhanced signal detection techniques like Cauchy-weighted Supertrend, Jurík RSX, Fisherized CCI, Kalman-filtered PSAR, and Dynamic DMI Smoothing, the system identifies the most dominant asset and simulates strategy equity performance compared to buy-and-hold benchmarks.
🔍 Key Features
✅ Multi-Asset Rotation: Analyze up to 6 symbols and USD simultaneously.
✅ Relative Strength Matrix: Compares every asset against each other to find outperformers.
✅ Custom Trend Engine:
Jurik RSX with advanced RSX logic
Fisherized CCI for momentum confirmation
Kalman-smoothed PSAR for trend bias
SuperTrend using a Cauchy Moving Average
Smoothed DMI signal across looped periods (10–17)
✅ Dynamic Best Asset Detection: Identifies and tracks the asset with the highest trend score over time.
✅ Performance Table: Displays Sharpe, Sortino, and Omega Ratios along with drawdowns and means for both strategy and each asset.
✅ Visual Trend Matrix: Tabular view of asset strength comparisons against each other + final scoring.
✅ Realistic Strategy Equity Curve: Tracks performance assuming full capital rotation into the best asset.
✅ Alerts: Get notified when the top-performing asset changes.
⚙️ Inputs
🔹 Assets: Customize 6 tickers (crypto, stocks, ETFs, etc.)
🔹 Trend Classification Method:
RSI
CCI
SuperTrend
DMI
PSAR
or use all together
🔹 Jurik RSX Length
🔹 Fisherized CCI Length
🔹 Cauchy MA Gamma and ATR Settings
🔹 DMI Range and MA Type (SMA, EMA, HMA, etc.)
🔹 PSAR Parameters with Kalman smoothing
🔹 Custom Backtest Start Date
📊 Outputs
Plot 1: Best Asset Equity (colored dynamically)
Plot 2–7: Buy & Hold Curves for each asset (with labels)
Tables:
Rotation Matrix (bottom-right)
Best Performing Asset (bottom-center)
Performance Metrics Table (optional toggle)
🧠 Use Case Ideas
🔁 Dynamic Portfolio Rebalancing
⚖️ Compare Risk-Adjusted Returns Across Crypto or Stocks
🧪 Backtest Rotation Hypotheses
🚀 Identify Strongest Breakout Assets in Trend Environments
📉 Avoid Weakening Assets with Rising Drawdowns
🚨 Alerts
🔔 "New Optimal Asset": Triggers when a new top-ranking asset replaces the current one.
Open - CSC Bars - 33 CSC Bars – Early Session Price Action Filter
This script detects when the first three bars of the RTH (Regular Trading Hours) session all move in the same direction — either all bullish or all bearish.
It’s a tool for price action traders who want to develop structured opening strategies by observing clean directional agreement at the session start. The indicator highlights the third bar when the sequence confirms directional bias.
🔍 How It Works:
Monitors the first three bars after the RTH session begins.
If all three bars are bullish, it highlights the third bar (same for bearish sequences).
No projections, signals, or entries—purely a visual tool to observe and study opening behavior.
🎯 Use Case:
This script is designed to help traders build and test opening-based frameworks by identifying potential trend bias early in the day.
Note: This is an open-source utility script with a simple function. It does not generate signals or predictions and is intended to assist with observation and discretionary strategy building.
Oath KeeperOath Keeper - Advanced Money Flow & Market Dynamics Indicator
A sophisticated indicator that analyzes market dynamics through money flow patterns, volume analysis, and liquidation detection to identify high-probability trading opportunities.
Core Features:
• Smart Money Flow Analysis: Proprietary calculation of institutional money movement
• Volume-Enhanced Signals: Multi-timeframe volume confirmation
• Liquidation Detection: Identifies potential forced liquidation events
• Advanced Signal Classification: Regular, Super, and Fakeout signals
Signal Types:
1. Regular Signals (Green/Purple Circles)
• Volume-confirmed momentum shifts
• Money flow threshold breaches
• Institutional participation confirmation
2. Super Signals (Green/Purple Squares)
• Deep oversold/overbought reversals
• High-volume rejection patterns
• Liquidation event confirmation
3. Fakeout Signals (Red X)
• Rapid sentiment shifts
• Trap detection
• False breakout warnings
Visual Components:
• Dynamic Money Flow Line (White/Purple)
• Order Flow Clouds (Green/Red with high transparency)
• Reference Levels (20, 50, 80)
• Multi-type Signal Markers
• Color-coded momentum visualization
Interpretation Guide:
• Green Cloud: Bullish money flow dominance
• Red Cloud: Bearish money flow dominance
• Circle Markers: Standard reversals
• Square Markers: High-conviction moves
• X Markers: Potential trap zones
Best Practices:
• Most effective on 1H+ timeframes
• Use with major trading pairs
• Wait for candle close confirmation
• Combine with support/resistance levels
• Monitor volume confirmation
• Use multiple timeframe analysis
This indicator helps traders identify institutional money flow, potential liquidation events, and market reversals by analyzing volume patterns and money flow dynamics, providing multiple confirmation layers for trade decisions.
Note: Performance varies with market conditions and timeframes. Always employ proper risk management.
