Abstract: We present a statistic to generally represent extremes in the distribution of temperature anomalies and demonstrate its consequences on financial markets. The diverse shocks that our measure portrays are established to be primary drivers of electricity consumption and the weather futures market. We find that this metric is a significant factor in the cross-section of equity returns in specific industries. A spatial hedging strategy is developed to account for differentially exposed firms to temperature extremes, resulting in a large market-adjusted alpha for the least vulnerable firms. We end by explicitly investigating whether the price reaction to extreme temperatures results from firm operations or investor attention. In each step of our exercise, we contrast our measure with average temperature anomalies and demonstrate that our metric is the first-order feature.
Joint work with Leonardo Bortolan (University of Bologna) and Atreya Dey (University of Edinburgh Business School).
The WP version is available here.