Correcting the errors: Volatility forecast evaluation using high-frequency data and realized volatilities

• 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: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.1111/j.1468-0262.2005.00572.x
• 发表日期: 2005
• 页码: 279-296
• 关键词: stochastic volatility; econometric-analysis; models; options

摘要

We develop general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit recent nonparametric asymptotic distributional results, are both easy-to-implement and highly accurate in empirically realistic situations. We also illustrate that properly accounting for the measurement errors in the volatility forecast evaluations reported in the existing literature can result in markedly higher estimates for the true degree of return volatility predictability.