 Testing for Asymmetric ComovementsO‐Chia Chuang, Xiaojun Song and Abderrahim Taamouti Oxford Bulletin of Economics and Statistics, 2022, vol. 84, issue 5, 1153-1180 Abstract: This paper aims to provide non‐parametric tests for asymmetric comovements between random variables. We consider the popular Cramér‐von Mises and Kolmogorov–Smirnov test statistics based on the distance between positive and negative joint conditional exceedance distribution functions. These tests can capture both linear and nonlinear dependence in the data and do not require selecting kernel functions and bandwidths. We derive the asymptotic distributions of the tests and establish the validity of a block multiplier‐type bootstrap that one can use in finite‐sample settings. We also show that these tests are consistent for any fixed alternative and have non‐trivial power for detecting local alternatives converging to the null at the parametric rate. Monte Carlo simulations and a real financial data analysis illustrate satisfactory performance of the proposed tests. Date: 2022 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:obuest:v:84:y:2022:i:5:p:1153-1180 Ordering information: This journal article can be ordered from Access Statistics for this article Oxford Bulletin of Economics and Statistics is currently edited by Christopher Adam, Anindya Banerjee, Christopher Bowdler, David Hendry, Adriaan Kalwij, John Knight and Jonathan Temple More articles in Oxford Bulletin of Economics and Statistics from Department of Economics, University of Oxford Contact information at EDIRC. |
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