ANALYTICAL EVALUATION OF VOLATILITY FORECASTS
Tim Bollerslev () and
International Economic Review, 2004, vol. 45, issue 4, 1079-1110
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), 579-625) 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. Copyright 2004 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.
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Working Paper: Analytic Evaluation of Volatility Forecasts (2002)
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