{"title":"Safe-Haven Effectiveness of Cryptocurrency: Evidence from Stock Markets of COVID-19 Worst-Hit\n African Countries","authors":"I. Raifu, A. E. Ogbonna","doi":"10.57017/jorit.v1.2(2).02","DOIUrl":null,"url":null,"abstract":"The study assessed the hedge or safe-haven property of five cryptocurrencies for stocks of\n three COVID-19 worst-hit African countries. We address two main concerns bordering on the\n predictive capacity of African stocks for cryptocurrency returns and the safe-haven property\n that cryptocurrencies could offer to African stocks. A distributed lag model, with explicitly\n incorporated salient statistical features, was adopted based on its efficient management of\n parameter proliferation and estimation biases. We ascertained the model’s in-sample\n predictability and evaluate its out-of-sample forecasts performance in comparison with the\n historical average model, using Clark and West statistics. While African stocks significantly\n predicted cryptocurrency returns, the cryptocurrency-stocks nexus revealed the diversifier and\n safe-haven property of cryptocurrencies for African stocks in periods of normalcy and\n crisis/pandemic, respectively. Our predictive model outperformed the historical average model in\n the out-of-sample. Our results may be sensitive to cryptocurrency-stocks nexus and sample\n periods but not the out-of-sample forecast horizons\n","PeriodicalId":165708,"journal":{"name":"Journal of Research, Innovation and Technologies (JoRIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Research, Innovation and Technologies (JoRIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.57017/jorit.v1.2(2).02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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