Speculative investment, heavy-tailed distribution and risk management of Bitcoin exchange rate returns

Pedro Bonillo Bueno; Emilio Aragon Fortes; Konstantinos Vlachoski

Pedro Bonillo Bueno Departamento de Economía y Empresa, Unversity of Almería, Spain
Emilio Aragon Fortes Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Spain
Konstantinos Vlachoski Leeds University Business School, Leeds, United Kingdom

Keywords: Skewed t distribution; goodness of fit; Value at Risk; risk management; Bitcoin

Abstract

Since its launch in 2008, Bitcoin becomes one of the most successful and fast-growing alternative currencies. As of 2017, the market capitalization is around $46 billions and arguably expected to continue growing. The Bitcoin to the US dollar exchange rate has been very volatile and fluctuating significantly. Although Bitcoin was designed as a medium of exchange, it is now more as an investment tool and thus the development of effective quantitative risk management tools becomes quite urgent for all the market participants. In this paper, we investigate empirical distribution of the Bitcoin exchange rate returns by using four types of widely-used heavy-tailed distribution and show that the Skewed t distribution has the best empirical performance. We further calculate the VaR based risk measures and found the Skewed t distribution generates the VaR values, which are closest to historical VaR values. Our results could be directly used in the industry’s stress testing practice, and help financial institutions fulfill the regulatory requirements.

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