Environmental Financial Derivatives: Pricing and Risk Management

环境金融衍生品：定价和风险管理

• 批准号: RGPIN-2019-06117
• 负责人: Olivares, Pablo
• 金额: $ 1.17万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=675730
• 关键词: Environmental; Financial; Derivatives; Pricing; Risk

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.***

该提案的总体目标是开发评估环境金融衍生品的技术，以及针对温度、降雨、降雪、风和碳排放等气候相关变量对冲公司财务状况风险的方法。 ***该项目的长期目标，即研究气候变化对加拿大金融业和当地社区的影响以及如何减轻其风险，与短期目标相结合通过实施具体政策评估和分析来实现目标***该项目涉及几个方面：首先，对基础气候变量的时间和空间动态与能源和电力价格以及其他非常规能源及其相关性进行建模。 其次，利用参数估计方法和机器学习技术对此类模型进行拟合和校准。最后，利用近似封闭式技术在实物期权、天气衍生品和巨灾债券的背景下实施创新定价和对冲策略，并分析新的与天气相关的金融合约。***该提案的原始特征在项目的不同方面都有发现。我们打算评估基于 Levy 和更一般的噪声的新模型，这些模型具有非平稳独立增量、新的波动动态和多变量环境中的随机相关性。还将分析捕捉不同位置之间相关性的空间随机模型。我们计划使用新颖的统计技术，将可能性、基于特征函数的最小距离方法与基于机器学习和神经网络的分析相结合，以管理现有的大型数据库。这些模型、估计、定价和对冲方法将概括现有模型和/或在天气变量的背景下转化已知模型。***所获得的结果预计将对公司、监管机构和地方政府产生影响，这些公司、监管机构和地方政府的绩效可能会受到气候变化的影响。他们将通过提供一系列评估和管理固有风险的工具，协助实施气候变化政策的决策过程，并为最佳投资决策提供指导。***项目结果将立即纳入现有的瑞尔森大学金融数学本科、硕士和博士课程。这将体现在我们研究组的发展、16名高级人才的培训中，具体包括1名博士后、1名博士、5篇硕士和7篇本科论文以及2名研究助理的指导。 预计在主流期刊上发表 6 篇科学论文、参加国际会议以及课程活动的总体改善。***