Nonstationarities in Financial Time Series, the Long-Range Dependence, and the IGARCH Effects
为长期对数收益率序列中观察到的波动率长程依赖性和IGARCH效应提供理论解释，指出这两种现象均可由数据的非平稳性假设来解释。
We give the theoretical basis of a possible explanation for two stylized facts observed in long log-return series: the long-range dependence (LRD) in volatility and the integrated GARCH (IGARCH). Both these effects can be explained theoretically if one assumes that the data are nonstationary. 2004 President and Fellows of Harvard College and the Massachusetts Institute of Technology.