Spillover effects, lead and lag relationships, and stable coins time series

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Seongcheol Paeng , Dave Senteney , Taewon Yang
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引用次数: 0

Abstract

This research explores plausible spillover effects among S&P 500 Index, stable coins, and selected cryptocurrency time series by examining observable lead and lag interrelationships among the series. Considering the heteroscedastic and “fat-tailed” nature of the data distributions underlying the empirical analyses, we employ quantile Granger Causality tests to improve the validity of our statistical findings. Our test results suggest that stable coins, USDT, and USDC offer diversification benefits by decreasing portfolio risk. The log returns of the S&P 500 Index, stable coins, Bitcoin, Ethereum, and Binance coins demonstrate clear bidirectional causality and spillover effects in low and high quantiles. Interestingly, however, stable coin and USDT returns strongly lead S&P 500 Index returns in nearly all quantiles for post COVID-19 time periods. These findings indirectly support intuition based upon market co-movement or integration assertions and suggest that investors can obtain added diversification benefits deriving from causality or spillover effects of holding stable coins when forming investment portfolios.

溢出效应、领先和滞后关系以及稳定硬币时间序列
本研究通过考察 S&P 500 指数、稳定币和特定加密货币时间序列之间可观察到的前导和滞后相互关系,探讨了这些序列之间看似合理的溢出效应。考虑到实证分析所依据的数据分布的异方差和 "胖尾 "性质,我们采用了量子格兰杰因果检验来提高统计结果的有效性。我们的检验结果表明,稳定币、USDT 和 USDC 通过降低投资组合风险带来了多样化收益。S&P 500 指数、稳定币、比特币、以太坊和 Binance 币的对数收益率在低和高分位数中显示出明显的双向因果关系和溢出效应。然而,有趣的是,在 COVID-19 之后的时间段,稳定币和 USDT 的回报几乎在所有量化值中都强烈领先于 S&P 500 指数的回报。这些发现间接支持了基于市场共动或整合论断的直觉,并表明投资者在形成投资组合时,可以从持有稳定币的因果关系或溢出效应中获得额外的多样化收益。
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
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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