Dr. Yang’s research investigates how behavioral biases, emerging technologies, and information frictions influence asset prices and financial decision-making. His work sits at the intersection of empirical asset pricing, machine learning, and natural language processing, with a focus on leveraging alternative data to uncover new sources of risk and return. Recent projects explore topics such as cyber risk, analyst disagreement, retail investor behavior, and the predictive capabilities of large language models in asset markets. By combining rigorous econometric methods with cutting-edge tools from AI, Dr. Yang aims to advance financial theory while generating insights with practical relevance for investors, policymakers, and institutions.
