Dynamic Games in Management

管理中的动态博弈

• 批准号: RGPIN-2020-05053
• 负责人: Breton, Michèle
• 金额: $ 2.62万
• 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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=716942
• 关键词: Dynamic; Games; Management

The objective of this research program is to develop mathematical models and efficient computational algorithms to solve practical strategic decision-making problems in a dynamic and uncertain context. Two specific application areas will be considered: investment finance and natural resource management. Although these application areas are very different from each other, they share a common methodological approach, that is, stochastic dynamic optimization in a multidimensional framework. In both these areas, solving realistic problems requires the development of efficient numerical methods. Thus, in addition to addressing these specific issues, a broader objective of this research program is to develop innovative methods for numerically solving large-scale stochastic dynamic problems and multi-stage dynamic games, thereby contributing to the advancement of knowledge in the field of decision-making under uncertainty. In the aftermath of the 2008 financial crisis, two important issues in investment finance are managing risk and ensuring compliance with the corresponding regulatory requirements (e.g. capital charge adjustments to account for counterparty risk). While investment finance has all the essential ingredients of dynamic games, where investors, firms, and financial intermediaries have competing interests and interact strategically over time, most valuation models are built from a single perspective. The objectives of our first line of research are to incorporate a strategic dimension in valuation and hedging models, and to develop new computational methods that can be used for realistic scenarios involving multidimensional investment portfolios. In practice, procedures used for risk management and regulatory compliance must be used in real time and should provide accurate results within seconds. A growing concern in environmental and resource management is related to the so-called tragedy of the commons. Access to a common resource (air quality, biodiversity, high-seas fishing) leads to overexploitation and, potentially, to catastrophic consequences. One of the means employed to prevent this from happening is the establishment of agreements between stakeholders (e.g. multilateral agreements under the aegis of the United Nations), to ensure that resources are managed in the best interest of all, including future generations. The objective of our second line of research is to study how the design, stability and implementability of environmental agreements are affected by dynamics and uncertainty, and by the participants' foresight and strategic outlooks. In this context, foresight is defined as the players' ability to account for the evolution over time of key features (environmental damage costs, learning, technological progress, number of signatories, economic development), when this evolution depends on the players' joint strategies. In practice, increasing foresight translates into multidimensional models.

这项研究的目标是开发数学模型和有效的计算算法来解决动态和不确定背景下的实际战略决策问题。将考虑两个具体的应用领域：投资融资和自然资源管理。虽然这些应用领域彼此非常不同，但它们都有一个共同的方法论途径，即多维框架下的随机动态优化。在这两个领域，解决现实问题都需要开发有效的数值方法。因此，除了解决这些具体问题外，本研究计划的一个更广泛的目标是开发用于数值求解大规模随机动态问题和多阶段动态对策的创新方法，从而促进不确定性决策领域知识的进步。 在2008年金融危机之后，投资融资中的两个重要问题是风险管理和确保遵守相应的监管要求(例如，调整资本费用以应对交易对手风险)。虽然投资金融具有动态博弈的所有基本要素，其中投资者、公司和金融中介具有相互竞争的利益，并随着时间的推移进行战略互动，但大多数估值模型都是从单一角度构建的。我们一线研究的目标是在估值和对冲模型中纳入战略维度，并开发可用于涉及多维投资组合的现实场景的新计算方法。在实践中，用于风险管理和监管合规的程序必须实时使用，并应在几秒钟内提供准确的结果。 对环境和资源管理的日益关注与所谓的公地悲剧有关。获取共同资源(空气质量、生物多样性、公海捕捞)会导致过度开发，并可能导致灾难性后果。防止这种情况发生的手段之一是在利益攸关方之间达成协议(例如在联合国主持下的多边协议)，以确保资源的管理符合包括子孙后代在内的所有人的最佳利益。我们第二线研究的目标是研究环境协议的设计、稳定性和可执行性如何受到动态和不确定性以及参与者的远见和战略展望的影响。在这种背景下，远见被定义为玩家对关键特征(环境破坏成本、学习、技术进步、签字国数量、经济发展)随时间演变的能力，而这种演变取决于玩家的联合战略。在实践中，增加远见就会转化为多维模型。