Tests for equal forecast accuracy under heteroskedasticity
David I. Harvey,
Stephen J. Leybourne,
Yang Zu
Abstract:SummaryHeteroskedasticity is a common feature in empirical time series analysis, and in this paper, we consider the effects of heteroskedasticity on statistical tests for equal forecast accuracy. In such a context, we propose two new Diebold–Mariano‐type tests for equal accuracy that employ nonparametric estimation of the loss differential variance function. We demonstrate that these tests have the potential to achieve power improvements relative to the original Diebold–Mariano test in the presence of heterosk… Show more
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