Stochastic modelling of climate risk with applications in insurance and finance

This thesis explores the intersection of climate change and financial markets, focusing on the challenges posed by increasing climate variability and the development of financial instruments for managing associated risks. Anthropogenic climate change has resulted in rising global temperatures and a growing frequency of extreme weather events, leading to significant economic, environmental, and societal impacts. These events have highlighted the need for innovative solutions in the insurance and financial sectors to address climate risk. The first chapter of the thesis considers the modelling of climate-related variables, particularly those underlying parametric insurance products, which offer alternative risk transfer mechanisms for weather-related exposures. By addressing issues such as spatial dependencies and increasing likelihood of extreme events, the research provides efficient methodologies for valuing and managing these instruments. The second chapter examines carbon markets designed to reduce greenhouse gas emissions and promote a low-carbon economy. We analyze the European Emission Trading Scheme (EU-ETS) with high-frequency data and present a methodology for pricing carbon-related financial products. We conclude this thesis by describing weather regimes, an essential tool for weather forecasting. We describe the methodology for constructing Mediterranean weather regimes and present a consistent data pre-processing method for developing year-round weather regimes that opens the possibility of future research to a dynamic probabilistic framework. The methodologies developed in this research can effectively be used to assess and quantify different aspects of climate risk.