Topic:

Averaging Machine Learning Techniques with Applications in Finance, Economics and Marketing

Guest: Prof. Jun YU

Dean of the Faculty of Business Administration, University of Macau

UMDF chair Professor of Finance and Economics, University of Macau

Date: April 21st, 2025 (Monday)

Time: 15:30-17:00

Venue: T2-306

Language: English

Lecture mode: On-site participation

Abstract

We introduce an ensemble learning framework that uses Mallows-type model averaging with machine learning to improve forecasting and decision-making in finance, economics, and marketing. In macroeconomic forecasting, it averages multiple model specifications, outperforming individual methods and simple averages. In marketing, applied to forecasting fashion sales with uncertain demand, it integrates averaging into the predict-then-optimize paradigm, enhancing accuracy and decisions using varied covariates. We prove the weighted estimators are asymptotically optimal and provide finite-sample risk bounds. Tests show it boosts macroeconomic forecast accuracy and, in a footwear sales case study in China, cuts prediction risk by 4.72% to 7.41%, optimizing promotions like discounts. The framework proves versatile and effective across these fields.

About the Speaker

Professor Jun Yu received a Ph.D. in economics at the University of Western Ontario in 1998. He taught at the Business School of the University of Auckland between 1998 and 2003 and Singapore Management University (SMU) between 2004 and 2023. He is currently UMDF chair Professor of Finance and Economics at the University of Macau and Dean of the Faculty of Business Administration at the University of Macau. Before that, he was Lee Kong Chian Professor of Economics and Finance at SMU, director of Sim Kee Boon Institute for Financial Economics at SMU, and the lead principal investigator of the Centre for Research on the Economics of Ageing at SMU. As the lead PI, he successfully obtained the largest research grant from the Singapore government (more than S$11,000,000) in social sciences and business. He was a Changjiang Scholar (长江学者) between 2017 and 2019.