Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Daily Overview |
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Egg-timer session: (Non-)Renewable resources Location: Auditorium J: Aina Uhde Session Chair: Pedro Henrique Batista de Barros, University of Exeter | |
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Forecasting Volatility of Currencies and Oil with Brown Firms: A Mixed-Frequency Approach 1: Sacred Heart University, United States of America; 2: National Chengchi University Climate risk is unequal: it affects different countries and assets differently, with important impacts on commodity-related currencies and energy markets. Moreover, financial markets possess useful information about climate expectations (Schlenker and Taylor (2021); Downey et al. (2023); Hale (2024)). We assess the forecasting power of firms’ climate exposure for realized volatility of commodity currencies and oil futures. Since information about climate risk arises at multiple frequencies, we construct ‘green’ and ‘brown’ indices using a mixed data frequency model. We collect intraday data for commodity currencies (Australia, Euro, Canada, and Norway); oil futures (WTI and Brent); and green and brown firms. We calculate realized volatility at multiple frequencies, then extract a latent green and brown index. We use a heterogeneous autoregressive (HAR) model to forecast volatility, and assess robustness with a machine learning framework. The HAR model plus a brown index consistently outperforms other models in terms of mean square error and out of sample R-squared. | |