{"title":"新冠肺炎大流行期间,情绪高涨、封锁严格、石油波动和清洁能源股票","authors":"S. Solarin, Muhammed Sehid Gorus, Veli Yılancı","doi":"10.1108/ijmf-09-2021-0457","DOIUrl":null,"url":null,"abstract":"PurposeThis study seeks to investigate role of the coronavirus disease 2019 (COVID-19) pandemic on clean energy stocks for the United States for the period 21 January 2020–16 August 2021.Design/methodology/approachAt the empirical stage, the Fourier-augmented vector autoregression approach has been used.FindingsAccording to the empirical results, the response of the clean energy stocks to the feverish sentiment, lockdown stringency, oil volatility, dirty assets, and monetary policy dies out within a short period of time. In addition, the authors find that there is a unidirectional causality from the feverish sentiment index and the lockdown stringency index to the clean energy stock returns; and from the monetary policy to the clean energy stocks. At the same time, there is a bidirectional causality between the lockdown stringency index and the feverish sentiment index. The empirical findings can be helpful to both practitioners and policy-makers.Originality/valueAmong the COVID-19 variables used in this study is a new feverish sentiment index, which has been constructed using principal component analysis. The importance of the feverish sentiment index is that it allows us to examine the impact of the aggregate level of fear in the economy on clean energy stocks.","PeriodicalId":51698,"journal":{"name":"International Journal of Managerial Finance","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2022-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Feverish sentiment, lockdown stringency, oil volatility, and clean energy stocks during COVID-19 pandemic\",\"authors\":\"S. Solarin, Muhammed Sehid Gorus, Veli Yılancı\",\"doi\":\"10.1108/ijmf-09-2021-0457\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PurposeThis study seeks to investigate role of the coronavirus disease 2019 (COVID-19) pandemic on clean energy stocks for the United States for the period 21 January 2020–16 August 2021.Design/methodology/approachAt the empirical stage, the Fourier-augmented vector autoregression approach has been used.FindingsAccording to the empirical results, the response of the clean energy stocks to the feverish sentiment, lockdown stringency, oil volatility, dirty assets, and monetary policy dies out within a short period of time. In addition, the authors find that there is a unidirectional causality from the feverish sentiment index and the lockdown stringency index to the clean energy stock returns; and from the monetary policy to the clean energy stocks. At the same time, there is a bidirectional causality between the lockdown stringency index and the feverish sentiment index. The empirical findings can be helpful to both practitioners and policy-makers.Originality/valueAmong the COVID-19 variables used in this study is a new feverish sentiment index, which has been constructed using principal component analysis. The importance of the feverish sentiment index is that it allows us to examine the impact of the aggregate level of fear in the economy on clean energy stocks.\",\"PeriodicalId\":51698,\"journal\":{\"name\":\"International Journal of Managerial Finance\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2022-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Managerial Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/ijmf-09-2021-0457\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Managerial Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijmf-09-2021-0457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Feverish sentiment, lockdown stringency, oil volatility, and clean energy stocks during COVID-19 pandemic
PurposeThis study seeks to investigate role of the coronavirus disease 2019 (COVID-19) pandemic on clean energy stocks for the United States for the period 21 January 2020–16 August 2021.Design/methodology/approachAt the empirical stage, the Fourier-augmented vector autoregression approach has been used.FindingsAccording to the empirical results, the response of the clean energy stocks to the feverish sentiment, lockdown stringency, oil volatility, dirty assets, and monetary policy dies out within a short period of time. In addition, the authors find that there is a unidirectional causality from the feverish sentiment index and the lockdown stringency index to the clean energy stock returns; and from the monetary policy to the clean energy stocks. At the same time, there is a bidirectional causality between the lockdown stringency index and the feverish sentiment index. The empirical findings can be helpful to both practitioners and policy-makers.Originality/valueAmong the COVID-19 variables used in this study is a new feverish sentiment index, which has been constructed using principal component analysis. The importance of the feverish sentiment index is that it allows us to examine the impact of the aggregate level of fear in the economy on clean energy stocks.
期刊介绍:
Treasury and Financial Risk Management ■Redefining, measuring and identifying new methods to manage risk for financing decisions ■The role, costs and benefits of insurance and hedging financing decisions ■The role of rating agencies in managerial decisions Investment and Financing Decision Making ■The uses and applications of forecasting to examine financing decisions measurement and comparisons of various financing options ■The public versus private financing decision ■The decision of where to be publicly traded - including comparisons of market structures and exchanges ■Short term versus long term portfolio management - choice of securities (debt vs equity, convertible vs non-convertible)