Climate risks and state-level stock market realized volatility
Loading...
Date
Authors
Bonato, Matteo
Cepni, Oguzhan
Gupta, Rangan
Pierdzioch, Christian
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
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.
Description
DATA AVAILABILITY : Data will be made available on request.
Keywords
Prediction models, Climate-related predictors, Realized stock market volatility, Finance state-level data, SDG-13: Climate action, SDG-08: Decent work and economic growth
Sustainable Development Goals
Citation
Bonato, M., Cepni, O., Gupta, R. et al. 2023, 'Climate risks and state-level stock market realized volatility', Journal of Financial Markets, vol. 66, art. 100854, pp. 1-18, doi : 10.1016/j.finmar.2023.100854.