Z-Score Statistical Modeling

Z-score statistical modeling measures how many standard deviations a data point is from the mean. In finance, it is used to identify outliers in price or volatility that are statistically unlikely to persist.

A high absolute Z-score indicates that an asset's current price is far from its historical average, suggesting a potential mean reversion trade. This provides a quantitative, objective basis for trading decisions, removing emotional bias.

However, the model assumes that the data follows a normal distribution, which is often not the case in crypto markets characterized by fat tails. Therefore, traders must be careful to account for these non-normal market behaviors.

It is a powerful tool for systematic and quantitative traders.