A Bayesian analysis of gain-loss asymmetry

Andrea Giuseppe Di Iura and Giulia Terenzi

Papers from arXiv.org

Abstract: We perform a quantitative analysis of the gain/loss asymmetry for financial time series by using a Bayesian approach. In particular, we focus on some selected indices and analyze the statistical significance of the asymmetry amount through a Bayesian generalization of the t-Test, which relaxes the normality assumption on the underlying distribution. We propose two different models for data distribution, we study the convergence of our method and we provide several graphical representations of our numerical results. Finally, we perform a sensitivity analysis with respect to model parameters in order to study the reliability and robustness of our results.

Date: 2021-04
New Economics Papers: this item is included in nep-cwa and nep-ecm
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