Volatility forecasting accuracy for Bitcoin

dc.contributor.author	Köchling, Gerrit
dc.contributor.author	Schmidtke, Philipp
dc.contributor.author	Posch, Peter N.
dc.date.accessioned	2019-08-05T12:52:14Z
dc.date.available	2019-08-05T12:52:14Z
dc.date.issued	2019
dc.description.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.	en
dc.identifier.uri	http://hdl.handle.net/2003/38165
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-20144
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB823;14/2019	en
dc.subject	bitcoin	en
dc.subject	cryptocurrency	en
dc.subject	GARCH	en
dc.subject	volatility	en
dc.subject	model confidence set	en
dc.subject	robust loss function	en
dc.subject.ddc	310
dc.subject.ddc	330
dc.subject.ddc	620
dc.title	Volatility forecasting accuracy for Bitcoin	en
dc.type	Text	de
dc.type.publicationtype	workingPaper	de
dcterms.accessRights	open access
eldorado.secondarypublication	false	de

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