This paper examines how the Bitcoin-altcoin return relationship has evolved in periods between 2015 and 2020. To understand this relation, we observe data on the cryptocurrency Bitcoin and prominent altcoins Ethereum, Litecoin, Ripple, Stellar, and Monero, which collectively represent over 90% of the market throughout the observed period. We employ a vector autoregressive model (VAR) to produce forecast error variance decompositions, orthogonal impulse response functions, and Granger-causality tests. We find evidence that Bitcoin return variation has increasingly explained altcoin returns and that market inefficiency increased between 2017 and 2020, as shown by increased Granger causality between Bitcoin and altcoins. These results align with the academic consensus that efficiency within the cryptocurrency market varies substantially over time and that inefficiency has increased after 2017.The findings suggest that the properties of the cryptocurrency market are highly dynamic and that researchers should be hesitant to generalize market properties observed during idiosyncratic periods.
Gouffray, J. (2022). Dynamic return relationships in the market for cryptocurrency: A VAR approach. James Madison Undergraduate Research Journal, 9(1) 44-53. http://commons.lib.jmu.edu/jmurj/vol9/iss1/5
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