A0760
Title: A realized multi-factor regression model with realized stochastic volatility
Authors: Tsunehiro Ishihara - Takasaki City University of Economics (Japan) [presenting]
Abstract: Estimation of high-dimensional stochastic volatility models tends to be computationally expensive. A stochastic volatility model is proposed that can be computed in parallel, even in high dimensions, and does not increase the computational cost. Realized covariance is computed from indices' high-frequency data of market, size, and value quasi-factors. Using them, a time-varying coefficient regression model or a low-dimensional stochastic volatility model is estimated to forecast high-dimensional volatility. 33-dimensional Japanese sector indices data are applied.
