2023/03/20 by Kwun Chuen Gary Chan, Chan, Kwun Chuen Gary, Hok Kan Ling +5
Economics, Econometrics and Finance · Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Methodology (stat.ME) #Random Matrices and Applications
paper · pdf · doi:10.48550/arxiv.2303.11388
openalex publication_date 2023/03/20 · openalex created_date 2023/03/23 · openalex updated_date 2026/07/28
In this article, we propose a new class of consistent tests for p-variate normality. These tests are based on the characterization of the standard multivariate normal distribution, that the Hessian of the corresponding cumulant generating function is identical to the p× p identity matrix and the idea of decomposing the information from the joint distribution into the dependence copula and all marginal distributions. Under the null hypothesis of multivariate normality, our proposed test statistic is independent of the unknown mean vector and covariance matrix so that the distribution-free critical value of the test can be obtained by Monte Carlo simulation. We also derive the asymptotic null distribution of proposed test statistic and establish the consistency of the test against different fixed alternatives. Last but not least, a comprehensive and extensive Monte Carlo study also illustrates that our test is a superb yet computationally convenient competitor to many well-known existing test statistics.