On empirical likelihood test for predictability

Kun Chen and Man Wang

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 10, 2499-2508

Abstract: Predicting asset prices is a critical issue in statistics and finance. In this article, by incorporating the recent advances in nonparametric approaches, we propose the empirical likelihood test for the predictability for the direction of price changes. Under some regularity conditions, the test statistic has an asymptotic χ2 distribution under the null hypothesis that the direction of price change cannot be predicted. This test procedure is easy to implement and presents better finite sample performances than other popular causality tests, as reported in some Monte Carlo experiments. HightlightsWe propose a non parametric likelihood test for predictability.The test involves no user-chosen parameter or estimation of covariance matrix.The test is simple to implement and has standard asymptotics.The test has significantly better sizes than several popular tests with satisfactory power.

Date: 2019
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DOI: 10.1080/03610926.2018.1465092

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