Analytical evaluation of volatility forecasts

• 成果类型: Article
• 署名作者: Andersen, TG; Bollerslev, T; Meddahi, N
• 署名单位: Northwestern University; National Bureau of Economic Research; Duke University; Universite de Montreal
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/j.0020-6598.2004.00298.x
• 发表日期: 2004
• 页码: 1079-1110
• 关键词: stochastic volatility; temporal aggregation; models; options

摘要

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, multi-factor affine, and lognormal diffusions, the reduced form procedures perform remarkably well relative to the optimal (infeasible) forecasts.