{"title":"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","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":"{\"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}","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}
Safe-Haven Effectiveness of Cryptocurrency: Evidence from Stock Markets of COVID-19 Worst-Hit
African Countries
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