An Assessment of the Prediction Quality of VPIN

Abstract

VPIN is a tool designed to predict extreme events like flash crashes. Some concerns have been raised about its reliability. In this chapter we assess VPIN prediction quality (precision and recall rates) of extreme volatility events including its sensitivity to the starting point of computation in a given data set. We benchmark the results with the ones of a "naive classifier." The test data used in this study contains 5.6 year's worth of trading data of the five most liquid futures contracts of this time period. We found that VPIN has poor "flash crash" prediction power with the traditional 0.99 decision threshold. Increasing the decision threshold does not significantly improve overall prediction quality. Nevertheless we found VPIN has a more interesting predictive power for flash events of lower amplitude. Finally, we found that, for practice, the last bar price structure is the least sensitive to the starting point of computation.