报告时间：2025年07月02日（星期三）9:00-11:30

报告地点：合肥工业大学管理学院1425会议室

报告人：术洪炜  教授

工作单位：美国马萨诸塞州大学

举办单位：合肥工业大学管理学院

报告简介：

Investor psychology provides an important avenue for modeling non-fundamental behaviors in financial analysis. A burgeoning number of machine learning algorithms have been developed to test the effectiveness of investor psychology in market predictions. With all the merits of machine learning approach, it often suffers from issues such as biases, overfitting, and poor performance. To address these issues, we developed a DeepPsych system to harness the power of high frequency market psychology data for trend prediction. In a “hybridization–generalization–dual-channel-fusion” three-stage experiment, we evaluate each proposed module and the entire framework against the state-of-art machine learning benchmarks on investor psychology and trading data of the SPY (SP500 ETF). Results demonstrate that our deep learning framework can significantly improve prediction and support profitable trading.

报告人简介：

Hongwei Zhu is a professor of Management Information Systems in the Operations and Information Systems Department at the University of Massachusetts Lowell. His research focuses on data quality, analytics and AI, with business applications in areas such as finance and accounting. His work has appeared in MIT Sloan Management Review, Journal of Management Information Systems, Information Systems Research, and transactions and journals of ACM and IEEE. He is an associate editor of the ACM Journal of Data and Information Quality.