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Bivariate sub-Gaussian model for stock index returns

Author

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  • Jabłońska-Sabuka, Matylda
  • Teuerle, Marek
  • Wyłomańska, Agnieszka

Abstract

Financial time series are commonly modeled with methods assuming data normality. However, the real distribution can be nontrivial, also not having an explicitly formulated probability density function. In this work we introduce novel parameter estimation and high-powered distribution testing methods which do not rely on closed form densities, but use the characteristic functions for comparison. The approach applied to a pair of stock index returns demonstrates that such a bivariate vector can be a sample coming from a bivariate sub-Gaussian distribution. The methods presented here can be applied to any nontrivially distributed financial data, among others.

Suggested Citation

  • Jabłońska-Sabuka, Matylda & Teuerle, Marek & Wyłomańska, Agnieszka, 2017. "Bivariate sub-Gaussian model for stock index returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 628-637.
    • Handle: RePEc:eee:phsmap:v:486:y:2017:i:c:p:628-637
    DOI: 10.1016/j.physa.2017.05.080
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