报告主题：Investment-consumption Optimization with Transaction Cost and Learning about Return Predictability

时间：2024年12月20日14:30-15:30

地点：上川路校区一号楼218室

报告人：王宁

报告内容简介：

In this paper, we investigate an investment-consumption optimization problem in continuous-time settings, where the expected rate of return from a risky asset is predictable with an observable factor and an unobservable factor. Based on observable information, a decision-maker learns about the unobservable factor while making investment-consumption decisions. Both factors are supposed to follow a mean-reverting process. Also, we relax the assumption of perfect liquidity of the risky asset through incorporating proportional transaction costs incurred in trading the risky asset. In such way, a form of friction posing liquidity risk to the investor is examined. Dynamic programming principle coupled with an Hamilton–Jacobi–Bellman (HJB) equation are adopted to discuss the problem. Applying an asymptotic method with small transaction costs being taken as a perturbation parameter, we determine the frictional value function by solving the first and second corrector equations. For the numerical implementation of the proposed approach, a Monte-Carlo-simulation-based approximation algorithm is adopted to solve the second corrector equation. Finally, numerical examples and their economic interpretations are discussed.

主讲人简介：

王宁，2020年12月获华东师范大学统计学博士学位，2021年2月获澳大利亚麦考瑞大学精算学博士学位。现在任澳大利亚国立大学金融，精算与统计研究学院讲师。目前在精算学，运筹学，数量金融领域知名期刊Insurance: Mathematics and Economics, European Journal of Operational Research, Quantitative Finance, Scandinavian Actuarial Journal, North American Actuarial Journal, International Review of Financial Analysis等发表论文十余篇。