Forecasting returns of major cryptocurrencies: Evidence from regime-switching factor models

Elie Bouri, Christina Christou and Rangan Gupta

Finance Research Letters, 2022, vol. 49, issue C

Abstract: The returns of cryptocurrencies tend to co-move, with their degree of co-movement being contingent on the (bullish- or bearish-) states. Given this, we use standard factor models and regime-switching factor loadings to forecast the returns of a specific cryptocurrency based on its lagged information and informational contents of 14 other cryptocurrencies, with these 15 together constituting 65% of the market capitalization. Considering top five cryptocurrencies namely, Bitcoin, Ethereum, Ripple, Dogecoin, and Litecoin, we find significant forecastability and evidence that factor models, in general, outperform the benchmark random-walk model, with the regime-switching versions standing out in the majority of the cases.

Keywords: Cryptocurrencies; Factor model; Markov-switching; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 G15 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (7)

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Working Paper: Forecasting Returns of Major Cryptocurrencies: Evidence from Regime-Switching Factor Models (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:49:y:2022:i:c:s1544612322003993

DOI: 10.1016/j.frl.2022.103193

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