Risk measures in renewable energy sector using extreme value theory

Abstract

The present study aims to calculate the risk measures in the renewable energy stock market through the use of the extreme value theory. The theory of extreme market value centers on infrequent and exceptional occurrences within each renewable energy index, which are utilized to compute extreme risk measures, including the Value at Risk and the Expected Shortfall. The present study effectively employed the extreme value theory to analyze the log returns of the renewable energy stock market, resulting in the successful prediction of both Value at Risk (VaR) and Expected Shortfall (ES). The research was conducted on a dataset comprising five daily renewable energy indices spanning from October 15th, 2010, to December 13th, 2022. The main conclusions of this study are as follows: 1.) Geothermal, Fuel, and Solar have the greatest VaR and ES at 1%, 5%, and 10% probability, respectively, according to calculations of risk using historical simulation. 2-) The application of the extreme value theory revealed that Fuel and Solar included the greatest VaR and ES at 1%, 5%, and 10% probability.