期刊
JOURNAL OF ECONOMETRICS
卷 131, 期 1-2, 页码 539-578出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jeconom.2005.01.016
关键词
fractional integration; long memory; parameter estimation error; stock returns; long horizon prediction
This paper addresses the notion that many fractional I(d) processes may fall into the empty box category, as discussed in Granger (Aspects of research strategies for time series analysis, Presentation to the Conference oil New Developments in Time Series Economics, Yale University, 1999). We present ex ante forecasting evidence which suggests that ARFIMA models estimated using a variety of standard estimation procedures yield approximations to the true unknown underlying DGPs that sometimes provide significantly better out-of-sample predictions than AR, MA, ARMA, GARCH, and related models, based on analysis of point mean-square forecast errors (MSFEs), and based on the use of predictive accuracy tests. The strongest evidence in favor of ARFIMA models arises when various transformations of 5 major stock index returns are examined. Additional evidence based on analysis of the Stock and Watson (J. Bus. Econom. Stat. 20 (2002) 147-162) data set, the returns series data set examined by Ding et al. (J. Empirical Finance 1 (1993) 83-106). and based on a series of Monte Carlo experiments is also discussed. (c) 2005 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据