Statistical Modelling and Risk Analysis of Bitcoins Exchange Rate

Abstract

Bitcoin is a phenomenon that is new and there is little information on how and why it behaves as volatile as it does. This thesis uses existing data on Bitcoin’s exchange rate to estimate a model that describes the pattern and use it in a financial risk analysis. We also aim to contribute as a foundation for further studies in this field. The statistical properties of the log-return of the exchange rate are analysed and it is deemed to be iid. From the eleven distributional candidates we study is the fitted skew generalised t distribution proven to represent the data best after evaluation by criteria and statistics. The estimated VaR and ES show that the rate is volatile and that the risk from investments is still high. The findings show that it is necessary to describe the exchange rate with complex and flexible distributions, and even if the data shows more stability today than earlier is it important to show caution in interpretations and evaluations on the topic. Keywords: Bitcoin, cryptocurrencies, statistical distributions, statistical analysis, exchange rate, modelling