In-Sample and Out-of-Sample Predictability of Cryptocurrency Returns

IF 1 Q3 ECONOMICS
Kyungjin Park, Hojin Lee
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Abstract

This paper investigates whether the price of cryptocurrency is determined by the US dollar index, the price of investment assets such gold and oil, and the implied volatility of the KOSPI. Overall, the returns on cryptocurrencies are best predicted by the trading volume of the cryptocurrency both in-sample and out-of-sample. The estimates of gold and the dollar index are negative in the return prediction, though they are not significant. The dollar index, gold, and the cryptocurrencies seem to share characteristics which hedging instruments have in common. When investors take notice of the imminent market risks, they increase the demand for one of these assets and thereby increase the returns on the asset. The most notable result in the out-of-sample predictability is the predictability of the returns on value-weighted portfolio by gold. The empirical results show that the restricted model fails to encompass the unrestricted model. Therefore, the unrestricted model is significant in improving out-of-sample predictability of the portfolio returns using gold. From the empirical analyses, we can conclude that in-sample predictability cannot guarantee out-of-sample predictability and vice versa. This may shed light on the disparate results between in-sample and out-of-sample predictability in a large body of previous literature.
加密货币回报的样本内和样本外可预测性
本文研究了加密货币的价格是否由美元指数、黄金和石油等投资资产的价格以及韩国综合指数的隐含波动率决定。总体而言,加密货币的回报最好通过样本内和样本外的加密货币交易量来预测。对黄金和美元指数的预测在回报预测中是负的,尽管它们并不显著。美元指数、黄金和加密货币似乎具有对冲工具的共同特征。当投资者注意到即将到来的市场风险时,他们会增加对其中一种资产的需求,从而增加该资产的回报。样本外可预测性中最显著的结果是黄金价值加权投资组合收益的可预测性。实证结果表明,受限制的模型不能包含不受限制的模型。因此,无限制模型在提高使用黄金的投资组合收益的样本外可预测性方面具有重要意义。从实证分析中,我们可以得出样本内可预测性不能保证样本外可预测性的结论,反之亦然。这可能会揭示在大量以前的文献中样本内和样本外可预测性之间的不同结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
12.50%
发文量
10
审稿时长
10 weeks
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