Assessing and hedging the cost of unseasonal weather: Case of the apparel sector (2015)
European Journal of Operational Research
Volume 244, Issue 1, 1 July 2015, Pages 261-276
Jean-Louis Bertrand, Xavier Brusset, Maxime Fortin
Summary
Retail operations are increasingly exposed to unseasonal weather that leads to lost sales and profits as climate change exacerbates climate variability. Although research has provided insight into the role of weather on consumption, little is known about the precise relationship between weather and sales for strategic and financial decision-making. Using clothing as an illustration for all seasons, we estimate the impact on sales caused by unexpected deviations in daily temperature from seasonal patterns. We apply seasonal trend decomposition using Loess to isolate changes in sales volumes. We use linear regression to find the relationship between temperature and sales anomalies, and we construct the historical distribution to determine sales at risk due to unseasonal weather. We show how to use weather derivatives to offset the potential loss. Our contribution is twofold: we provide a new general method for managers to understand how their performance is linked to weather conditions, and we propose a tailored weather derivatives model to mitigate this risk.