MULTIPLE TESTING OF SIGN SYMMETRY FOR STOCK RETURN DISTRIBUTIONS

Petr Koldanov () and Nina Lozgacheva ()
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Petr Koldanov: Laboratory of Algorithms and Technologies for Network Analysis, National Research University, Higher School of Economics, Nizhny Novgorod, Rodionova St. 136, 603093, Russia
Nina Lozgacheva: National Research University Higher School of Economics, Nizhny Novgorod, Rodionova St. 136, 603093, Russia

International Journal of Theoretical and Applied Finance (IJTAF), 2016, vol. 19, issue 08, 1-14

Abstract: Multiple statistical procedure for testing elliptical model for stock returns distribution is proposed. Sign symmetry conditions are chosen as individual hypotheses for multiple testing. Distribution free uniformly most powerful tests of Neyman structure are constructed for individual hypotheses testing. Associated stepwise multiple testing procedure is applied for the real market data. Numerical experiments shows that hypothesis of elliptical model is rejected. At the same time it is observed that the graph of rejected individual hypotheses has unexpected structure. Namely, this graph is sparse and has a few hubs of high degree. Removing this hubs leads to nonrejection of hypothesis of elliptical model.

Keywords: Stock returns distribution; elliptical model; properties of symmetry; multiple hypotheses testing; distribution free tests (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219024916500497

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