Predicting the Volatility Index Returns Using Machine Learning

We probe how predictable the short term future behaviour of the Chicago Board Options Exchange (CBOE) Volatility Index (ticker symbol VIX) is given past market price data within the constraints of a simple classic machine learning framework. We use past VIX and SPX price time windows as input to predict the movement direction, i.e. sign of the return, of VIX over the next 1 to 6 weekdays. For successful cases of pre- dicting return direction from one particular weekday to another particular future weekday, we have moderately reliable accuracies of between about 55% and 65% depending on the particular time bridge. We find that 1 day returns are difficult to predict except for a few particular cases, and as the prediction window grows we have models that can predict more and more accurately up to a consistent 62% for both 5 days and 6 days in the future.M.Sc