Forecasting stock market volatility: The sum of the parts is more than the whole

Abstract

The volatility of financial assets can be decomposed into upside volatility and downside volatility. However, these two components have unique properties, so their predictability is completely different. In this paper, we explore a new forecasting method to predict the S&P 500 volatility by separately modeling upside volatility and downside volatility and summing the forecasts up. Our new method is proved to have better performance compared with directly modeling aggregate volatility. Moreover, the gains in forecast accuracy are robust concerning the individual and combined models.