Before joining Shandong University, Dr. Zhaohui Jiang obtained his PhD in Finance from the University of York, where his research focused on machine learning in asset pricing and behavioural finance. His work examines how artificial intelligence and neural networks can improve the prediction of future earnings, identify mispriced stocks, and enhance value investing strategies.

His research achieved an AUC of approximately 70% in predicting future company earnings directions, demonstrating strong predictive performance in financial machine learning. He also developed a two-step machine learning framework for value stock selection, which generated average monthly returns of up to 3.92% in U.S. stock market test data (excluding transaction costs).

His research further explores the role of momentum, volatility, liquidity, bid-ask spread, and investor sentiment in stock pricing. He also contributed to the construction of machine learning financial databases for both the Chinese and U.S. markets.

His work received the Best Paper Award at the British Accounting and Finance Association (BAFA) Conference in 2024. His research has also been presented at the BAM 2023 Conference, BFWG 2023 Conference, and CEF 2024 Conference. In addition, he maintains active academic engagement with several international academic organisations, is a member of the British Academy of Management, and serves as a conference reviewer.