{"title":"Climate risks and state-level stock market realized volatility","authors":"Matteo Bonato , Oguzhan Cepni , Rangan Gupta , Christian Pierdzioch","doi":"10.1016/j.finmar.2023.100854","DOIUrl":null,"url":null,"abstract":"<div><p>We analyze the predictive value of climate risks for state-level realized stock market volatility, computed, along with other realized moments, based on high-frequency intra-day U.S. data (September, 2011 to October, 2021). A model-based bagging algorithm recovers that climate risks have predictive value for realized volatility at intermediate and long (one and two months) forecast horizons. This finding also holds for upside (“good”) and downside (“bad”) realized volatility. The benefits of using climate risks for predicting state-level realized stock market volatility depend on the shape and (as-)symmetry of a forecaster’s loss function.</p></div>","PeriodicalId":47899,"journal":{"name":"Journal of Financial Markets","volume":"66 ","pages":"Article 100854"},"PeriodicalIF":2.1000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Financial Markets","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1386418123000526","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 1
Abstract
We analyze the predictive value of climate risks for state-level realized stock market volatility, computed, along with other realized moments, based on high-frequency intra-day U.S. data (September, 2011 to October, 2021). A model-based bagging algorithm recovers that climate risks have predictive value for realized volatility at intermediate and long (one and two months) forecast horizons. This finding also holds for upside (“good”) and downside (“bad”) realized volatility. The benefits of using climate risks for predicting state-level realized stock market volatility depend on the shape and (as-)symmetry of a forecaster’s loss function.
期刊介绍：
The Journal of Financial Markets publishes high quality original research on applied and theoretical issues related to securities trading and pricing. Area of coverage includes the analysis and design of trading mechanisms, optimal order placement strategies, the role of information in securities markets, financial intermediation as it relates to securities investments - for example, the structure of brokerage and mutual fund industries, and analyses of short and long run horizon price behaviour. The journal strives to maintain a balance between theoretical and empirical work, and aims to provide prompt and constructive reviews to paper submitters.
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