APPARENT LONG MEMORY IN TIME SERIES AS AN ARTIFACT OF A TIME-VARYING MEAN: CONSIDERING ALTERNATIVES TO THE FRACTIONALLY INTEGRATED MODEL

作者：Ashley Richard A^*; Patterson Douglas M

来源：Macroeconomic Dynamics, 2010, 14(S1): 59-87.

DOI：10.1017/S1365100509991052

• Long Memory
• Fractional Integration
• Detrending
• Stock Returns
• Volatility

Structural breaks and switching processes are known to induce apparent long memory in a time series. Here we show that any significant time variation in the mean renders the sample correlogram (and related spectral estimates) inconsistent. In particular, smooth time variation in the mean-i.e., even a weak trend, either stochastic or deterministic-induces apparent long memory. This apparent long memory can be eliminated by either high-pass filtering or by detrending. Here we demonstrate the effectiveness in this regard of nonlinear detrending via penalized-spline nonparametric regression. A time-varying mean can be of economic interest in its own right. This suggests that isolating out and separately examining both a local mean (i.e., a nonlinear trend or the realization of a stochastic trend) and deviations from it is preferable as a modeling strategy to simply estimating a fractionally integrated model. We illustrate the superiority of This strategy using stock return volatility data.

• 出版日期2010-5
• 单位美国弗吉尼亚理工大学(Virginia Tech)