SONG Yingda

Yingda SONG is an Associate Professor in the Department of Management Science at Antai College of Economics & Management, Shanghai Jiao Tong University. His research focuses on Financial Engineering, Fintech, Stochastic Models, and Simulation. He has conducted research on Options Pricing under General Regime Switching Models as the Principal Investigator of a National Natural Science Foundation of China project. His work includes publications in journals such as Quantitative Finance, Mathematical Finance, and Operations Research. He teaches courses such as Business Statistics, Financial Engineering, and Investment Science at both undergraduate and graduate levels.

Yingda Song is a researcher in Financial Engineering, Fintech, Stochastic Models, Simulation, and Risk Management. His work focuses on developing computational methods for financial modeling, including pricing complex derivatives such as Asian options and risk-free rate caplets. He has contributed to the analysis of credit ABS using Markov chain approaches and has explored efficient methods for nested estimation of CoVaR. His research also includes approximation techniques for optimal stopping problems and irreversible investment with random delay. Song's publications emphasize the application of stochastic processes, simulation, and numerical methods in financial engineering and fintech.