气候风险与国家级股市波动

IF 2.1 2区经济学 Q2 BUSINESS, FINANCE

Journal of Financial Markets Pub Date : 2023-11-01 DOI:10.1016/j.finmar.2023.100854

Matteo Bonato , Oguzhan Cepni , Rangan Gupta , Christian Pierdzioch

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引用次数: 1

摘要

我们基于美国高频日内数据(2011年9月至2021年10月)，分析了气候风险对州级已实现股票市场波动的预测价值，并与其他已实现时刻一起计算。基于模型的bagging算法恢复了气候风险在中期和长期(一个月和两个月)预测范围内对实现波动率具有预测价值。这一发现也适用于上行(“好”)和下行(“坏”)实现的波动性。使用气候风险来预测国家层面已实现的股市波动的好处取决于预测者损失函数的形状和(as-)对称性。

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Climate risks and state-level stock market realized volatility

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.

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来源期刊

Journal of Financial Markets BUSINESS, FINANCE-

CiteScore

3.40

自引率

3.60%

发文量

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.