Backward Stochastic Partial Differential Equations: Theory and Applications in Stochastic Control and Mathematical Finance

后向随机偏微分方程：随机控制和数学金融的理论与应用

• 批准号: RGPIN-2018-04325
• 负责人: Qiu, Jinniao
• 金额: $ 1.68万
• 依托单位: University of Calgary
• 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=712374
• 关键词: Backward; Stochastic; Partial; Differential; Equations

This research proposal focuses on the theory and applications of backward stochastic partial differential equations (BSPDEs). Such BSPDEs arise naturally in many applications of probability theory and stochastic processes, especially in mathematical finance and stochastic control. For instance, in the utility maximization with random coefficients the BSPDE is raised as the stochastic Hamilton-Jacobi-Bellman (HJB) equation to characterize the value function and optimal strategies, and in the nonlinear filtering and stochastic control under incomplete information, it can be the adjoint equation of Duncan-Mortensen-Zakai filtration equation. Nevertheless, the mathematical theory of BSPDEs are far from complete. In particular, the wellposedness of fully nonlinear stochastic HJB equations was proposed by Peng in 1992 and claimed to be an open problem first in 1999 and then in his plenary lecture of ICM 2010. The applicant has proposed an ambitious schedule to study the wellposedness of fully nonlinear stochastic HJB equations and some new classes of BSPDEs and discuss their applications in stochastic control and mathematical finance. The proposal involves two long-term aims and two short-term aims. The first long-term aim is the wellposedness of fully nonlinear stochastic HJB equations. The applicant intends to establish a fairly complete theory of viscosity solutions including three main topics: the general uniqueness, the regularity estimate and the construction of optimal feedback controls for general cases. The second long-term aim is to develop the discrete approximations of BSPDEs. The applicant will start from the numerical analysis for semilinear BSPDEs on domains, then turn to numerical approximations for coupled systems of forward-backward SPDEs, and finally for the fully nonlinear stochastic HJB equations. In the first short-term aim, the applicant will study the optimal control problems of reflected stochastic differential equations and associated BSPDEs with Neumann boundary conditions. Applications include controlled queueing problems and power controls in wireless communications. The second short-term aim is devoted to the optimal liquidation in target zone models, a type of stochastic optimal control problems of stochastic differential equations with obstacles and terminal state constraints. The research program is devoted to a fairly complete theory of stochastic control and associated BSPDEs that are tailor-made to study models of optimal decision making under uncertainty, especially in the areas of energy, commodity and environmental finance. It fits very well with and complements the research activities of the applied probability groups in Canada. Advanced methods will be developed and applications will be discussed. The involved undergraduate, graduate and postdoctoral researchers will have training opportunities in relevant fields.

本研究计画主要探讨倒向随机偏微分方程之理论与应用。这样的BSPDE自然出现在概率论和随机过程的许多应用中，特别是在数学金融和随机控制中。例如，在随机系数效用最大化问题中，BSPDE可以作为随机Hamilton-Jacobi-Bellman（HJB）方程来刻画价值函数和最优策略;在不完全信息下的非线性滤波和随机控制问题中，BSPDE可以作为Duncan-Mortensen-Zakai滤波方程的伴随方程。然而，BSPDE的数学理论还远未完成。特别是，完全非线性随机HJB方程的适定性由Peng于1992年提出，并在1999年和2010年的ICM全体会议上首次提出。 申请人提出了一个雄心勃勃的计划，研究完全非线性随机HJB方程和一些新的类别的BSPDE的适定性，并讨论它们在随机控制和数学金融中的应用。这个建议包括两个长期目标和两个短期目标。 第一个长期目标是完全非线性随机HJB方程的适定性。申请人打算建立一个相当完整的理论粘性解决方案，包括三个主要议题：一般的唯一性，正则性估计和建设的最佳反馈控制的一般情况下。 第二个长期目标是发展BSPDE的离散近似。申请人将从域上的半线性BSPDE的数值分析开始，然后转向前向-后向SPDE的耦合系统的数值近似，最后是完全非线性随机HJB方程。 在第一个短期目标中，申请人将研究反射随机微分方程和相关的BSPDE与Neumann边界条件的最优控制问题。其应用包括无线通信中的受控发射问题和功率控制。 第二个短期目标是致力于在目标区模型，一类随机微分方程的障碍和终端状态约束的随机最优控制问题的最优清算。 该研究计划致力于随机控制和相关的BSPDE的一个相当完整的理论，这些理论是量身定制的，用于研究不确定性下的最优决策模型，特别是在能源，商品和环境金融领域。它与加拿大应用概率团体的研究活动非常吻合，并起到补充作用。先进的方法将被开发和应用将被讨论。参与的本科生、研究生和博士后研究人员将有相关领域的培训机会。