Sampling Error

Sampling error is the statistical discrepancy that occurs when the characteristics of a sample do not perfectly match the characteristics of the total population. This difference arises naturally because only a subset of the data is observed rather than the entire universe of transactions.

In high-frequency trading, even a small sampling error can lead to significant miscalculations in risk parameters like Value at Risk. Because crypto markets operate 24/7 with massive transaction volumes, it is computationally impossible to analyze every single tick, forcing traders to rely on samples.

If the sampling method is not properly designed, this error compounds, leading to inaccurate forecasting of price movements. Minimizing this error requires rigorous statistical design and an understanding of the underlying market structure.