Research Details

Abstract

Estimation and forecasting for realistic continuous-time stochastic volatility models is hampered by the lack of closed-form expressions for the likelihood. In response, Andersen, Bollerslev, Diebold, and Labys (Econometrica, 71 (2003), 579625) advocate forecasting integrated volatility via reduced-form models for the realized volatility, constructed by summing high-frequency squared returns. Building on the eigenfunction stochastic volatility models, we present analytical expressions for the forecast efficiency associated with this reduced-form approach as a function of sampling frequency. For popular models like GARCH, multifactor affine, and lognormal diffusions, the reduced form procedures perform remarkably well relative to the optimal (infeasible) forecasts.

Type

Article

Author(s)

Torben Andersen, Tim Bollerslev, Nour Meddahi

Date Published

2004

Citations

Andersen, Torben, Tim Bollerslev, and Nour Meddahi. 2004. Analytic Evaluation of Volatility Forecasts. International Economic Review.(4): 1079-1110.