Testing directional forecast value in the presence of serial correlation

Oliver J. Blaskowitz and Helmut Herwartz

No 2008-073, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: Common approaches to test for the economic value of directional forecasts are based on the classical Chi-square test for independence, Fisher’s exact test or the Pesaran and Timmerman (1992) test for market timing. These tests are asymptotically valid for serially independent observations. Yet, in the presence of serial correlation they are markedly oversized as confirmed in a simulation study. We summarize serial correlation robust test procedures and propose a bootstrap approach. By means of a Monte Carlo study we illustrate the relative merits of the latter. Two empirical applications demonstrate the relevance to account for serial correlation in economic time series when testing for the value of directional forecasts.

Keywords: Directional forecasts; directional accuracy; forecast evaluation; testing independence; contingency tables; bootstrap (search for similar items in EconPapers)
JEL-codes: C32 C52 C53 E17 E27 E47 F17 F37 F47 G11 G17 (search for similar items in EconPapers)
Date: 2008
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