主讲人：Stevens Institute of Technology,崔振嵛副教授

报告时间：2024年7月9日上午10：00—11：00

报告地点：览秀楼105学术报告厅

报告摘要:When designing and evaluating estimators, the mean squared error (MSE) is the most commonly used generic statistical loss function because it captures the bias-variance tradeoff and allows easy analytical and numerical treatment. However, MSE estimators are often applied to decision problems for which the loss function is different, raising questions about how much value there is in using a generic statistical loss function like the MSE rather than a decision loss function. We elucidate this question through the lens of the portfolio selection problem by showing that for several important portfolio rules, there is a positive linear relation between the MSE and a portfolio-decision loss function. Moreover, shrinkage portfolio estimators derived under these two loss functions are typically close to each other. Our findings highlight the economic value of MSE to serve as a general-purpose statistical loss function in portfolio selection.

主讲人简介：

崔振嵛，理学博士，Stevens Institute of Technology商学院副教授，博士生导师，博士毕业于University of Waterloo，现任International Journal of Finance and Economics副主编。主要研究兴趣有金融工程，随机模拟，及金融科技，在Mathematical Finance, SIAM Journal on Financial Mathematics, INFORMS Journal on Computing, Econometric Theory, Journal of Financial Econometrics, European Journal of Operational Research等杂志发表数十篇论文。目前主持NSF CNS-2113906: “Fast Quantum Method for Financial Risk Measurement”科研项目。