Assessing Climate Change Impacts and Associated Risks: Applications in Finance and Insurance

Abstract

The focus of this thesis is to investigate the application of sustainable and green investments in the finance and insurance industries, specifically addressing their relevance to climate change and resiliency. To develop a portfolio optimized for both financial returns and sustainability factors, Environmental, Social, and Governance (ESG) scores are integrated into the reward function of a conventional Reinforcement Learning model (a branch of Machine Learning models) in Chapter 2. This approach enables a more robust analysis of the impact of various ESG ratings published by major rating agencies on the coherence of investment strategies. The model addresses the widespread confusion arising from the high heterogeneity in published ESG ratings by treating it as a source of ambiguity (or Knightian uncertainty) and proposes four ESG ensemble strategies catering to investors with different risk and (smooth) ambiguity preference profiles. Additionally, a Double-Mean-Variance model is constructed to combine financial returns and ESG score objectives, define three investor types based on their ambiguity preferences, and develop novel ESG-modified Capital Asset Pricing Models to evaluate the resulting optimized portfolio performance.

In Chapter 3, the ESG score evaluation methods for large companies are expanded to assess sustainability of individual farmers' production in the context of climate change. We propose integrating agricultural sustainability factors into classical personal credit evaluation systems to create a sustainable credit score, called the Environmental, Social, Economics (ESE) score. This ESE score is then incorporated into theoretical joint liability models to derive optimal group size and individual-ESE score propositions. Moreover, the utility function of farmers is refined to a mean-variance form, accounting for the risk associated with expected profit. Simulation exercises are provided to examine the effects of different climatic conditions, offering a deeper understanding of the implications of incorporating ESE scores into the credit evaluation system.

Chapter 4 investigates strategic investments needed to mitigate transition risks, particularly focusing on sectors significantly impacted by the shift to a low-carbon economy. It emphasizes the importance of tailored sector-specific strategies and the role of government interventions, such as carbon taxes and subsidies, in shaping corporate behavior. In providing a multi-period framework, this chapter evaluates the economic and operational trade-offs companies face under four various decarbonization scenarios-immediate, quick, slow, and no transitions. The analysis provides practical insights for both policymakers and business leaders, demonstrating how regulatory frameworks and strategic investments can be aligned to manage transition risks while optimizing long-term sustainability effectively. The findings contribute to a deeper understanding of the economic impacts of regulatory policies and offer a comprehensive framework to navigate the complexities of transitioning to a low-carbon economy.

Finally, Chapter 5 summarizes the thesis and outlines potential directions for further research.