Does weather drive the renewable energy and financial stock markets ? Evidence from France using a Threshold Autoregressive model

This study investigates the influence of weather conditions, including temperature, wind speed, humidity, and precipitation, on financial market performance in France, with a particular focus on the renewable energy sector. To this end, we construct a new French Renewable Energy Financial Index (REFI) that aggregates listed companies involved in renewable energy production and distribution across multiple industries. The REFI introduces an original benchmark that enables a comprehensive assessment of the sector’s financial dynamics and its sensitivity to weather variations, thereby contributing to the literature through the construction of a dedicated renewable energy index for the French market. Using data from 54 weather stations, we apply Principal Component Analysis to reduce data dimensionality and extract the main weather factors. Furthermore, we employ both linear and non-linear econometric models, including the Threshold Autoregressive model, to forecast daily returns for the REFI and the CAC40 index. The results show that weather variables exert a statistically significant, though economically moderate, influence on market returns, with more pronounced effects observed for the REFI. The non-linear TAR model captures regime-dependent dynamics more effectively than linear benchmarks, suggesting that weather-return relationships intensify under specific market conditions. While the overall explanatory power remains limited, the findings enhance the understanding of how renewable energy-related assets respond to meteorological variability and offer useful insights for managing climate-related financial risks.