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Institute
The digital currency Bitcoin offers investors high returns
and a low correlation with other asset classes. However, Bit-
coin's unusually high volatility raises doubt about its eligibility
for investors.
The objective of this thesis is to ascertain, if the market risk
of Bitcoin can be adequately forecasted with the prevalent risk
measures Value-at-Risk and Expected Shortfall. To this end, an
empirical analysis is performed, which applies commonly used
techniques of risk modeling on seven years of Bitcoin return
data. Forecasts for VaR and ES are backtested and the results
compared with those of other asset classes.
The empirical results show, that although Bitcoin's fore-
casts perform significantly worse than those of other asset classes,
risk models with conditional volatility are able to estimate re-
liable VaR and ES for Bitcoin. Other findings incluce the inef-
fectiveness of historical simulation models and the importance
of the assumed distribution of returns.