Risk-Sensitivity in Mean Field Games and Energy Markets

平均场博弈和能源市场的风险敏感性

• 批准号: RGPIN-2022-05337
• 负责人: Firoozi, Dena
• 金额: $ 1.89万
• 依托单位: HEC Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=765256
• 关键词: Risk; Sensitivity; Mean; Field; Games

Motivation: Due to global warming, it is necessary to reduce carbon emissions worldwide. In this light, regulatory acts have been imposed by requiring the regulated firms to generate a specific percentage of their electricity via an eligible renewable energy resource. There is a tracking system via issuing certificates for every 1 MWh renewable energy generation. In case of non-compliance, the firms face a monetary penalty that must be paid to the regulator. These certificates can be traded on markets and their price is driven via supply and demand. Due to the uncertainty associated with intermittent renewables, the price could be very volatile and trading in such markets could incur a higher risk to firms. Moreover, transaction costs in such markets are in general higher than in voluntary markets. Hence, to facilitate the regulation, which in turn contributes to a smoother transition to a low-carbon future, an efficient market design is crucial. Objective: Mean field game (MFG) theory studies a class of large-population games, where agents are not only impacted by their individual behaviour but also by the mass behaviour of all the other agents in the system. The theory provides mathematical characterizations of the Nash equilibria of such games. The objective of this proposal is to introduce a fundamental study of risk-sensitivity in MFGs and to employ it for optimal design of compliance REC markets. Therefore, the first part of this proposal investigates equilibrium pricing and contract design in markets where participants are risk sensitive and there is an influential market participant. In all analyses it is assumed that all market parameters are known as is usually the case in games. However, the latter assumption does not hold in practice and some form of learning is required. For that reason, in the second part, risk-sensitive learning of the individual and the population parameters in MFGs is investigated. This paves the way for extensive data-driven analysis proposed in each case for compliance markets case studies, which ultimately will be used for market design purposes. The setups considered in this proposal are not addressed in the literature. More specifically, this, among others, includes considering risk-sensitivity in MFGs for equilibrium pricing, contract design, modeling an influential market participant (major agent), and learning and adaptation. Methodology: The set of projects in this proposal addresses different aspects of risk-sensitivity in MFGs and is designed in a way that they can be investigated simultaneously and independently of each other. The main analytical tool that is used in all projects is MFG methodology which has proven useful in modeling markets with a large number of interacting participants and a few influential ones. We extend the methodology to account for risk-sensitivity of agents in markets with a clearing condition, a risk-sensitive major agent, and risk-sensitive learning and adaptation.

动机：由于全球变暖，有必要在全球范围内减少碳排放。从这个角度来看，通过要求受监管的公司通过合格的可再生能源产生特定百分比的电力来实施监管行为。通过每次可再生能源生成的每次发行证书，就有一个跟踪系统。如果不遵守，公司面临必须支付给监管机构的货币罚款。这些证书可以在市场上进行交易，其价格是通过供需驱动的。由于与间歇性可再生能源相关的不确定性，价格可能非常波动，在此类市场的交易可能会给公司带来更高的风险。此外，此类市场的交易成本通常高于自愿市场。因此，为了促进该法规，这反过来促进了向低碳未来的更平稳过渡，有效的市场设计至关重要。 目的：平均现场游戏（MFG）理论研究一类大型人口游戏，其中代理不仅受其个人行为的影响，而且还受系统中所有其他代理的质量行为的影响。该理论提供了此类游戏的NASH平衡的数学特征。该提案的目的是介绍MFG中风险敏感性的基本研究，并将其用于最佳的合规性REC市场设计。因此，该提案的第一部分调查了参与者对风险敏感并且有影响力的市场参与者的市场的均衡定价和合同设计。在所有分析中，都假定所有市场参数在游戏中通常都是如此。但是，后一个假设在实践中不存在，需要某种形式的学习。因此，在第二部分中，研究了对个体的风险敏感学习和MFG中的人口参数。这为在每个案例中提出的广泛的数据驱动分析铺平了道路，用于合规市场案例研究，最终将用于市场设计目的。本提案中考虑的设置未在文献中解决。更具体地说，这包括考虑MFG中的风险敏感性，用于平衡定价，合同设计，对有影响力的市场参与者建模（主要代理）以及学习和适应。 方法论：此提案中的一组项目涉及MFG中风险敏感性的不同方面，并以一种可以同时和彼此独立地进行研究的方式设计。所有项目中使用的主要分析工具是MFG方法，它已被证明可用于建模具有大量相互作用的参与者和一些有影响力的市场。我们扩展了方法，以说明具有清除条件，风险敏感的主要代理以及对风险敏感的学习和适应性的市场中代理商的风险敏感性。