On the volatility of cryptocurrencies

Thanasis Stengos, Theodore Panagiotidis and Georgios Papapanagiotou

No 2202, Working Papers from University of Guelph, Department of Economics and Finance

Abstract: We perform a large-scale analysis to evaluate the performance of traditional and Markov-switching GARCH models for the volatility of 292 cryptocurrencies. For each cryptocurrency, we estimate a total of 27 alternative GARCH specifications. We consider models that allow up to three different regimes. First, the models are compared in terms of goodness-of-fit using the Deviance Information Criterion and the Bayesian Predictive Information Criterion. Next, we evaluate the ability of the models in forecasting one-day ahead conditional volatility and Value-at-Risk. The results indicate that for a wide range of cryptocurrencies, time-varying models outperform traditional ones.

Keywords: Bitcoin; Cryptocurrency; Volatility; GARCH; Markov-switching; Information criteria (search for similar items in EconPapers)
JEL-codes: C12 C13 C15 C22 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2022
New Economics Papers: this item is included in nep-ban, nep-cwa, nep-ets, nep-mon, nep-pay and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:gue:guelph:2022-02

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