Cross-cryptocurrency return predictability

IF 1.9 3区 经济学 Q2 ECONOMICS Journal of Economic Dynamics & Control Pub Date : 2024-04-20 DOI:10.1016/j.jedc.2024.104863
Li Guo , Bo Sang , Jun Tu , Yu Wang
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Abstract

Using data from Binance, we find strong evidence of cross-cryptocurrency return predictability. The lagged returns of other cryptocurrencies serve as significant predictors of focal cryptocurrencies. The results are robust across various methods, including the adaptive LASSO and principal component analysis. Furthermore, a long-short portfolio formed on the past returns of cryptocurrencies can generate a sizable return out-of-sample after accounting for transaction costs. Overall, our findings corroborate cross-cryptocurrency return predictability and are consistent with the spillover effect mechanism, where common shocks among cryptocurrencies coupled with the limited attention of investors lead to slow information diffusion across coins.

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跨加密货币回报的可预测性
利用 Binance 的数据,我们发现了跨加密货币收益可预测性的有力证据。其他加密货币的滞后收益率是焦点加密货币的重要预测因素。在使用自适应 LASSO 和主成分分析等各种方法时,结果都是稳健的。此外,在考虑交易成本后,基于加密货币过去收益率形成的多空投资组合可以在样本外产生可观的收益。总体而言,我们的研究结果证实了跨加密货币收益的可预测性,并与溢出效应机制相一致,即加密货币之间的共同冲击加上投资者的有限关注导致跨币信息扩散缓慢。
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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