主 講 人： Stevens Institute of Technology, 崔振崳 副教授

報告時間：2024年7月9日上午10：00—11：00

報告地點：覽秀樓105學術報告廳

報告摘要:  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.

主講人簡介：

崔振崳，理學博士，Stevens Institute of Technology 商學院副教授，博士生導師，博士畢業于University of Waterloo，現任International Journal of Finance and Economics 副主編。主要研究興趣有金融工程，隨機模擬，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 等雜志發表數十篇論文。目前主持 NSF CNS-2113906: “Fast Quantum Method for Financial Risk Measurement” 科研項目。