期刊名称：CORE Discussion Papers / Center for Operations Research and Econometrics (UCL), Louvain
出版年度：2008
卷号：1
出版社：Center for Operations Research and Econometrics (UCL), Louvain
摘要：This paper proposes an easy test for two stationary autoregressive fractionally integrated
moving average (ARFIMA) processes being uncorrelated via AR approximations. We
prove that an ARFIMA process can be approximated well by an autoregressive (AR) model
and establish the theoretical foundation of Haugh's (1976) statistics to test two ARFIMA
processes being uncorrelated. Using AIC or Mallow's Cp criterion as a guide, we
demonstrate through Monte Carlo studies that a lower order AR(k) model is sufficient to
prewhiten an ARFIMA process and the Haugh test statistics perform very well in finite
sample. We illustrate the methodology by investigating the independence between the
volatility of two daily nominal dollar exchange rates-Euro and Japanese Yen and find that
there exists "strongly simultaneous correlation" between the volatilities of Euro and Yen
within 25 days.
关键词：forecasting, long memory process, structural break.
