A novel heavy tail distribution of logarithmic returns of cryptocurrencies

Quang Tran and Jaromir Kukal

Finance Research Letters, 2022, vol. 47, issue PA

Abstract: We propose a novel distribution derived from the generalized gamma distribution by symmetrization and regularization around the mean. Besides location and scale parameters, the distribution has three shape parameters with many sub-models as special cases. Its parameters can be estimated by non-linear regression with parameter significance verification and sub-model testing. The applicability of this family of novel distributions is verified on returns of three cryptocurrencies and its suitability is tested by χ2 goodness of fit testing. The obtained results show that this novel distribution and its sub-models can be viable candidates for modeling the returns of cryptocurrencies.

Keywords: Generalized gamma distribution; Regularization; Parameter estimation; Logarithmic returns; Cryptocurrencies (search for similar items in EconPapers)
JEL-codes: C51 C52 C58 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321005250

DOI: 10.1016/j.frl.2021.102574

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