On January 2, 2024, Faculty of Finance at City University of Macau organized the eighth academic salon (2023-2024) at the Taipa campus. The seminar was hosted by Dr. Wei-Han Liu from Southern University of Science and Technology. Dr. Liu delivered a lecture on his research paper titled "Forecasting China's inflation rate: Evidence from machine learning methods" The article employed eight machine learning models, including Partial Least Squares, Scaled Principal Component, Least Absolute Shrinkage and Selection Operator, Ridge Regression, Random Forest, Gradient Boosting Decision Tree, Support Vector Machine, and Neural Network, along with predictive ensembles to forecast China's inflation. The empirical results of the study indicate that these models generally outperform autoregressive benchmarks in terms of out-of-sample R-squared. Gradient Boosting Decision Tree (GBDT) and predictive ensemble models were found to be the most effective machine learning tools for predicting China's inflation rate across various forecast horizons and evaluation criteria.

Dr. Liu is currently an Associate Professor at Department of Finance, Southern University of Science and Technology. His research focuses on applied finance, applied economics, and quantitative risk management. He has published articles in journals such as the Journal of Econometrics, Journal of Futures Markets, and Energy Economics. The academic salon hosted by Dr. Liu brought valuable academic exchange and discussion to the Faculty of Finance at the City University of Macau.

The Academic Salon organized by Faculty of Finance at City University of Macau serves as a platform for exchanging academic ideas and fostering academic awareness. With finance as the main focus, we invite senior scholars/experts from academia and the financial industry to engage in research discussions on cutting-edge topics and share industry development trends, aiming to provide a fresh academic experience and thinking model for CityU students and members of the faculty. Through activities like the Academic Salon, we hope to offer graduate students a better academic platform, encouraging further exploration and research on academic issues.