A Bayesian analysis of gain-loss asymmetry

Andrea Di Iura () and Giulia Terenzi ()
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Andrea Di Iura: Enel SpA
Giulia Terenzi: Enel SpA

SN Business & Economics, 2022, vol. 2, issue 5, 1-23

Abstract: 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 analyse 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. We observe that the magnitude of the asymmetry depends on several factors, such as the considered time-series as well as the threshold parameters used to define the gain/loss asymmetry.

Keywords: Financial time series; Gain-loss asymmetry; Bayesian analysis; Statistics (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s43546-022-00207-4

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