Forecasting Financial Volatility with Interval-Valued Time Series Data

In this paper, we propose an interval-based model to capture the dynamics of the range process of asset prices. Particularly, this model is an alternative in forecasting the range-based volatility. By modelling the evolution of interval-valued price process over time, the proposed model utilizes more information than modelling the range process only. In the empirical study, the in-sample and out-of-sample forecasting performances based on the U.S. stock market daily data show that the interval-based model produces