Volatility forecasting accuracy for Bitcoin
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Date
2019
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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.
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Keywords
bitcoin, cryptocurrency, GARCH, volatility, model confidence set, robust loss function