Safe-Haven Effectiveness of Cryptocurrency: Evidence from Stock Markets of COVID-19 Worst-Hit African Countries

I. Raifu, A. E. Ogbonna
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引用次数: 1

Abstract

The study assessed the hedge or safe-haven property of five cryptocurrencies for stocks of three COVID-19 worst-hit African countries. We address two main concerns bordering on the predictive capacity of African stocks for cryptocurrency returns and the safe-haven property that cryptocurrencies could offer to African stocks. A distributed lag model, with explicitly incorporated salient statistical features, was adopted based on its efficient management of parameter proliferation and estimation biases. We ascertained the model’s in-sample predictability and evaluate its out-of-sample forecasts performance in comparison with the historical average model, using Clark and West statistics. While African stocks significantly predicted cryptocurrency returns, the cryptocurrency-stocks nexus revealed the diversifier and safe-haven property of cryptocurrencies for African stocks in periods of normalcy and crisis/pandemic, respectively. Our predictive model outperformed the historical average model in the out-of-sample. Our results may be sensitive to cryptocurrency-stocks nexus and sample periods but not the out-of-sample forecast horizons
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加密货币的避险有效性:来自受COVID-19影响最严重的非洲国家股市的证据
该研究评估了五种加密货币对三个受COVID-19影响最严重的非洲国家股票的对冲或避险属性。我们解决了两个主要问题,即非洲股票对加密货币回报的预测能力,以及加密货币可以为非洲股票提供的避险资产。基于对参数扩散和估计偏差的有效管理,采用了明确纳入显著统计特征的分布式滞后模型。我们确定了模型的样本内可预测性,并使用Clark和West统计数据与历史平均模型进行比较,评估了其样本外预测性能。虽然非洲股票显著地预测了加密货币的回报,但加密货币与股票的关系分别揭示了加密货币在正常时期和危机/大流行时期对非洲股票的多元化和避险属性。我们的预测模型在样本外的表现优于历史平均模型。我们的结果可能对加密货币-股票关系和样本周期敏感,但对样本外预测范围不敏感
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