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Market timing and return prediction under model instability

By M. Hashem Pesaran and Allan Timmermann

Abstract

Despite mounting empirical evidence to the contrary, the literature on predictability of stock returns almost uniformly assumes a time-invariant relationship between state variables and returns. In this paper we propose a two-stage approach for forecasting of financial return series that are subject to breaks. The first stage adopts a reversed ordered Cusum (ROC) procedure to determine in real time when the most recent break has occurred. In the second stage, post-break data is used to estimate the parameters of the forecasting model. We compare this approach to existing alternatives for dealing with parameter instability such as the Bai-Perron method and the time-varying parameter model. An out-of-sample forecasting experiment demonstrates considerable gains in market timing precision from adopting the proposed two-stage forecasting method

Topics: HF Commerce, HG Finance, HB Economic Theory
Publisher: Financial Markets Group, London School of Economics and Political Science
Year: 2002
OAI identifier: oai:eprints.lse.ac.uk:24932
Provided by: LSE Research Online

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