معرفی
Soohun Kim is an Assistant Professor of Finance at the College of Business at KAIST (Korea Advanced Institute of Science and Technology). Prior to joining KAIST, he was on the faculty at the Scheller College of Business at Georgia Tech. His academic career spans from 2014 to present, with teaching experience in finance, business analytics, and econometrics.
Dr. Kim's research focuses on asset pricing, financial econometrics, machine learning applications in finance, and tail risk analysis in financial markets. His work examines various aspects of investment behavior, market efficiency, and risk management, with particular attention to momentum strategies, ESG investing, and the impact of trading mechanisms on market outcomes.
His recent publications demonstrate a strong focus on advanced statistical methods for asset pricing, including large sample estimators, hidden Markov models, and regression-calibration approaches. His work bridges theoretical finance with practical applications, addressing questions relevant to both academic researchers and investment professionals.
Dr. Kim teaches BIT 500 (Business Analytics), BAF 634 (Financial Econometrics), and BAF 649 (Time Series Analytics) at KAIST (2020-2023), and previously taught Derivatives at Georgia Tech (2014-2020). His teaching portfolio reflects his expertise in quantitative finance and analytical methods, preparing students for careers that require strong analytical and modeling skills.
