Bitcoin cash: stochastic models of fat-tail returns and risk modeling

Author Affiliation

Muhammad Sheraz is Assistant Professor of Mathematical Sciences and Economics & Finance at Institute of Business Administration (IBA), Karachi

Faculty / School

Faculty of Computer Sciences (FCS)

Department

Department of Mathematical Sciences

Was this content written or created while at IBA?

Yes

Document Type

Article

Source Publication

Economic Computation and Economic Cybernetics Studies and Research

ISSN

0424-267X

Disciplines

Applied Mathematics | Computer Sciences | Econometrics | Economics | Finance | Mathematics

Abstract

Bitcoin (BTC) is a digital currency that has gained significant attention from researchers. The aim of this paper consists in analyzing some stochastic models of fat-tail returns and risk models. The evidence of fat-tailed returns distribution for the BCH data is investigated, by performing a statistical analysis of Bitcoin Cash (BCH) in the U.S. dollar. By using daily Close, Open, Low, and High returns of BCH data series, the monthly-divided daily returns study describes further properties such as skewness, kurtosis, and correlation analysis. The results obtained prove that variance gamma distribution best fit the close, open and low returns, where high returns follow the generalized hyperbolic distribution. In addition, for the best-fitted fat-tailed returns distributions, several risk measures such as volatility, Value-at-Risk and Expected Shortfall measures are computed, analyzed and compared.

Indexing Information

HJRS - Y Category, Scopus, Web of Science - Social Sciences Citation Index (SSCI), Web of Science - Science Citation Index Expanded (SCI)

Journal Quality Ranking

Impact Factor: 0.743

Publication Status

Published

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