Z-Score Scaling
Z-score scaling is a statistical method used to normalize data by subtracting the mean and dividing by the standard deviation. This process transforms data points into a standardized distribution with a mean of zero and a variance of one.
In quantitative finance, it is widely used to identify outliers and determine how far a price movement deviates from its historical average. For cryptocurrency traders, it helps in assessing whether an asset is overbought or oversold relative to its recent performance.
It is particularly useful for comparing the volatility of different digital assets regardless of their nominal price. By focusing on standard deviations, traders can make more informed decisions about mean reversion strategies.
It effectively filters out noise and highlights significant market events that warrant attention. This technique is a cornerstone of statistical arbitrage, where traders look for assets that have drifted too far from their normal relationship.
It provides a consistent metric for risk assessment across various market conditions.