Distributions of Historic Market Data -- Relaxation and Correlations

M. Dashti Moghaddam, Zhiyuan Liu and R. A. Serota

Papers from arXiv.org

Abstract: We investigate relaxation and correlations in a class of mean-reverting models for stochastic variances. We derive closed-form expressions for the correlation functions and leverage for a general form of the stochastic term. We also discuss correlation functions and leverage for three specific models -- multiplicative, Heston (Cox-Ingersoll-Ross) and combined multiplicative-Heston -- whose steady-state probability density functions are Gamma, Inverse Gamma and Beta Prime respectively, the latter two exhibiting "fat" tails. For the Heston model, we apply the eigenvalue analysis of the Fokker-Planck equation to derive the correlation function -- in agreement with the general analysis -- and to identify a series of time scales, which are observable in relaxation of cumulants on approach to the steady state. We test our findings on a very large set of historic financial markets data.

Date: 2019-07, Revised 2020-02
New Economics Papers: this item is included in nep-rmg
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Published in Eur. Phys. J. B 94, 83 (2021)

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1907.05348

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