Posch, Peter N.
|Title:||Volatility forecasting accuracy for Bitcoin|
|Abstract:||We analyse the quality of Bitcoin volatility forecasting of GARCH-type models applying the commonly used volatility proxy based on squared daily returns as well as a jump-robust proxy based on intra-day returns and vary the degrees of asymmetry in robust loss functions. We construct model confidence sets (MCS) which contain superior models with a high probability and find them to be systematically smaller for asymmetric loss functions and the jump robust proxy. Our findings suggest a cautious use of GARCH models in forecasting Bitcoin's volatility.|
model confidence set
robust loss function
|Appears in Collections:||Sonderforschungsbereich (SFB) 823|
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|DP_1419_SFB823_Köchling_Schmidtke_Posch.pdf||DNB||325.54 kB||Adobe PDF||View/Open|
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