People / Students / Class of 2023
Zhitao Chen graduated from Case Western Reserve University with double majors in Computer Science and Finance as well as a minor in Economics. He has gained a deep understanding of financial statement analysis, industry analysis, and computer science algorithms during his undergraduate studies. Zhitao is also well-versed in the use of statistical modeling and valuation techniques as well as programming languages such as Java and Python. In the project of the course Options and Other Derivatives, he built a regression model to simulate the given firms’ income growth at the same time controlling the risk. Zhitao applied mathematical modeling and a crowd-sourcing algorithm to manage the portfolio risk, which improved the overall risk-adjusted performance by avoiding significant drawdowns when the market crashes.
Several internships and project experiences prepared Zhitao a lot for the position of data scientist in the financial sector. He is proficient in data gathering and input for stock analysis. During his internship at Ningbo Equity Exchange, he applied a crowd-sourcing algorithm to collect and analyze the data of customers’ reviews towards the products and actions conducted by Pre-IPO companies. After gathering the data, Zhitao would use Python libraries such as pandas, NumPy, and Matplotlib to clean and visualize the data. He is also adept at analyzing industry trends, annual reports, and financial filings. At Ningbo Equity Exchange, his team completed 2 Pre-IPO business plans. When making industrial and financial reports analysis, in addition to focusing on common factors such as demand, industry comparables, and risks, the team also established a correlation regression model including factors such as IPO pricing, early warning index, and Issuing scale to reveal more subtle variables. Zhitao has a strong quantitative background. At Guotai Junan Securities, he developed a hedging strategy for pools of corporate bonds with machine learning models, including regularized regression, neural networks, and support vector regressions. By applying machine learning and NLP, the strategy removed the assumptions of conventional methods of modeling the stock movement with a more precise outcome. The strategy reduced the fluctuation of the portfolio by 8%.
In order to further advance his skills and hone his data analytic prowess, Zhitao joined the MSiA program* at Northwestern University. He also looks forward to learning more about business leadership and interpersonal awareness. Zhitao will be most passionate about working towards the application of data science in the domain of the financial industry.
*later renamed MS in Machine Learning and Data Science
