Resource title

Testing directional forecast value in the presence of serial correlation

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image for OpenScout resource :: Testing directional forecast value in the presence of serial correlation

Resource description

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.

Resource author

Oliver J. Blaskowitz, Helmut Herwartz

Resource publisher

Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/25316

Resource license

Adapt according to the presented license agreement and reference the original author.