预测比特币回报:中美贸易战会起作用吗?

IF 0.3 4区 经济学 Q4 BUSINESS, FINANCE
Vasilios Plakandaras, Elie Bouri, Rangan Gupta
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引用次数: 13

摘要

先前的研究提供证据表明,与贸易相关的不确定性往往会预测比特币回报的增加。在本文中,我们通过研究中美贸易战的信息是否可以用来预测比特币收益的未来路径来扩展相关文献,控制各种解释变量。我们应用了普通最小二乘(OLS)回归、支持向量回归(SVR)以及源自机器学习领域的最小绝对收缩和选择算子(LASSO)技术,并找到了贸易战在预测比特币回报方面作用的微弱证据。鉴于样本外测试比样本内测试更可靠,我们的结果倾向于表明,未来比特币的回报不受贸易相关不确定性的影响,在这种情况下,投资者可以将比特币作为避风港。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Bitcoin Returns: Is There a Role for the US–China Trade War?
Previous studies provide evidence that trade related uncertainty tends to predict an increase in Bitcoin returns. In this paper, we extend the related literature by examining whether the information on the U.S. – China trade war can be used to forecast the future path of Bitcoin returns controlling for various explanatory variables. We apply ordinary least square (OLS) regression, support vector regression (SVR), and the least absolute shrinkage and selection operator (LASSO) techniques that stem from the field of machine learning, and find weak evidence of the role of the trade war in forecasting Bitcoin returns. Given that out-of-sample tests are more reliable than in-sample tests, our results tend to suggest that future Bitcoin returns are unaffected by trade related uncertainties, and investors can use Bitcoin as a safe haven in this context.
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来源期刊
Journal of Risk
Journal of Risk BUSINESS, FINANCE-
CiteScore
1.00
自引率
14.30%
发文量
10
期刊介绍: This international peer-reviewed journal publishes a broad range of original research papers which aim to further develop understanding of financial risk management. As the only publication devoted exclusively to theoretical and empirical studies in financial risk management, The Journal of Risk promotes far-reaching research on the latest innovations in this field, with particular focus on the measurement, management and analysis of financial risk. The Journal of Risk is particularly interested in papers on the following topics: Risk management regulations and their implications, Risk capital allocation and risk budgeting, Efficient evaluation of risk measures under increasingly complex and realistic model assumptions, Impact of risk measurement on portfolio allocation, Theoretical development of alternative risk measures, Hedging (linear and non-linear) under alternative risk measures, Financial market model risk, Estimation of volatility and unanticipated jumps, Capital allocation.
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