Environmental Financial Derivatives: Pricing and Risk Management

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The general objective of the proposal is the developing of techniques to evaluate environmental financial derivatives, as well as methods for hedging the risk of a company's financial position against climate related variables such as temperature, rainfall, snowfall and, wind and carbon emissions with a focus on the energy and agriculture sectors.***The long-term goal of the project, namely the study of the impact of climate change in the Canadian financial industry and local communities and how its risk can be mitigated, is combined with short-term goals via the implementation of specific policy evaluations and the analysis of financial hedging instruments.***The project involves several facets: Firstly, the modeling of the time and spatial dynamic of underlying climate variables combined with energy and electricity prices, as well as other non-conventional energy resources, and their correlations. Secondly, the fitting and calibration of such models using parameter estimation methods and machine learning techniques. Finally, the implementation of innovative pricing and hedging strategies in the context of real options, weather derivatives and catastrophe bonds with approximated closed-form techniques, together with the analysis of new weather-related financial contracts.***The original character of the proposal is found in different aspects along the project. We intend to evaluate new models based on Levy and more general noises with non-stationary independent increments, new volatility dynamics and stochastic correlation in a multivariate setting. Spatial stochastic models to capture correlation between different locations will be also analyzed. We plan the use of novel statistics techniques that combines likelihood, minimum distance methods based on characteristic functions, with an analysis founded on machine learning and neural networks to manage existing large databases. These models, estimation, pricing and hedging methods will generalize existent ones and/or will translate known models in the context of weather variables.***The results to be obtained are expected to have an impact in companies, regulators and local governments whose performance may be affected by climate change. They will assist in the decision-making process to implement climate change policies, by providing a series of tools to evaluate and manage the inherent risks and offer a guide leading to optimal investment decisions.***Project results will be immediately incorporated to the existing programs in Financial Mathematics at Ryerson University, at undergraduate, MSc and PhD levels. It will be reflected in the development of our research group, the training of 16 HQPs, specifically with the supervision of 1 postdoctoral fellow, 1 PhD, 5 MSc and 7 undergraduate theses plus 2 research assistants. Publication of 6 scientific papers in main stream journals, participation in international conferences, as well as a general improvement in curricular activities are expected.***