[SGM VaR Stats VS Empirical]

How it works

The signal starts by capturing logarithmic returns from historical closing prices and storing them in a dynamic array with a configurable maximum size. It then calculates key statistical metrics including mean, median, standard deviation, and z-scores using an approximation of the inverse error function.

The system generates two distinct projection types: an empirical projection based on median cumulative returns with a confidence filter, and a statistical projection using mean and standard deviation. These projections are visualized through polylines, with a blue line representing traditional statistical methods and an orange line representing empirical data analysis.

Why it may be useful

This trading signal provides traders with a comprehensive approach to understanding potential future asset performance by combining both statistical and empirical methodologies. It offers insights into the underlying distribution of returns, helping traders identify potential trends and variations in market behavior.

By generating multiple projection types, the signal allows for a more nuanced assessment of potential price movements. The ability to customize parameters like confidence levels, data array size, and projection length makes it a flexible tool for different trading strategies and market conditions.

When to explore it

The signal is most effective when analyzing assets with complex return distributions that might not follow traditional normal distribution assumptions. It works particularly well for traders seeking to understand both the central tendency and variability of historical returns.

Traders can leverage this signal when they want to compare traditional statistical projections with empirical observations, especially in markets with potential skewness or kurtosis. It is particularly useful for assets with non-linear price movements or when standard statistical methods might not fully capture the underlying market dynamics.

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