Stochastic volatility with missing data: Assessing the effects of holidays

Abstract In empirical finance, it is usual to consider holidays as if they do not exist. The main goal of this paper is to assess the effects of holidays on volatility estimation and prediction. Holidays are taken into account by assuming they are missing values in a time series of returns generated by a Stochastic volatility (SV) model. Estimation is evaluated through Monte Carlo experiments. In addition, we assess the effects of holidays on one-step ahead Value-at-Risk forecasting using several time series returns. The results are slightly better when we take into account the missing values, especially for VaR forecasting.