Journal of Time Series Analysis · 1996 · 93 citations · 22 references
Social SciencesEconomicsFinancial EconometricsFinancial EconomicsTime Series AnalysisCointegration AnalysisDependence ModelingForeign Exchange RiskMicroeconometricsNonparametric EconometricsSerial AnalysisAsymptotic Distribution TheoryJoint Distribution EstimationNonparametric InferenceNonparametric RegressionSample DistributionSerial CorrelationSerial Correlation TestingSerial Dependence
Abstract. This paper presents and discusses a nonparametric test for detecting serial dependence. We consider a Cramèer‐von Mises statistic based on the difference between the joint sample distribution and the product of the marginals. Exact critical values can be approximated from the asymptotic null distribution, or by resampling, randomly permuting the original series. A Monte Carlo experiment illustrates the test performance with small sample sizes. The paper also includes an application, testing the random walk hypothesis of exchange rate returns for several currencies.
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On a measure of lack of fit in time series models
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A Non-Parametric Test of Independence
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