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Testing Symmetry in Multivariate Probabilistic Model

Student: Mikhail Bazarin

Supervisor: Petr Koldanov

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 9

Year of Graduation: 2020

In this paper, multiple hypothesis testing procedures are constructed to test symmetry of a multivariate probabilistic model. The resulting procedures are applied to test stock returns distribution symmetry (the US stock market data is used). The procedures are constructed under the assumption of a zero mean and without the assumption. The set of procedures includes Holm’s method, Lehmann-Romano method and Benjamini-Hochberg method. It is shown which stocks have the most negative impact on symmetry and whether their removal leads to a non-rejection of the symmetry hypothesis.

Full text (added May 25, 2020)

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