Forecasting time series with long memory and level shifts

被引:5
|
作者
Hyung, N
Frances, PH
机构
[1] Erasmus Univ, Inst Econometr, NL-3000 DR Rotterdam, Netherlands
[2] Seoul Natl Univ, Dept Econ, Seoul, South Korea
关键词
long memory; level shifts; forecasting; stock returns;
D O I
10.1002/for.937
中图分类号
F [经济];
学科分类号
02 ;
摘要
It is well known that some economic time series can be described by models which allow for either long memory or for occasional level shifts. In this paper we propose to examine the relative merits of these models by introducing a new model, which jointly captures the two features. We discuss representation and estimation. Using simulations, we demonstrate its forecasting ability, relative to the one-feature models, both in terms of point forecasts and interval forecasts. We illustrate the model for daily S&P500 volatility. Copyright (C) 2005 John Wiley Sons, Ltd.
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页码:1 / 16
页数:16
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