A model for long memory conditional heteroscedasticity

• 成果类型: Article
• 署名作者: Giraitis, L; Robinson, PM; Surgailis, D
• 署名单位: University of London; London School Economics & Political Science; Vilnius University
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• 发表日期: 2000
• 页码: 1002-1024
• 关键词: stochastic volatility; heteroskedasticity; persistence; returns

摘要

For a particular conditionally heteroscedastic nonlinear (ARCH) process for which the conditional variance of the observable sequence r(t) is the square of an inhomogeneous linear combination of r(s), s < t, we give conditions under which, for integers l 2, r(t)(l) has long memory autocorrelation and normalized partial sums of r(t)(l) converge to fractional Brownian motion.