Abstract
Extreme value theory(EVT) has been used to study the frequency and probability related to extreme situations in finance. This approach focuses on the extreme values and able to provide a better estimation for risk models. In this study, Generalized Pareto Distribution (GPD) is employed to model daily extreme returns in the Bitcoin market from 2017 to 2019. These periods have witnessed three phases of extreme volatility for the cryptocurrency market. The returns level for the Bitcoin range between 17.011 and 18.746. The results demonstrate heavy tail and finite tail distribution characteristics for the tails. The findings provide a better understanding of the tails’ behaviour in the cryptocurrency market and help investors to make a financial decision.
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