principal - REPORTING & ANALYTICS
Xin is the mainstay of our internal analytical team and supports the Funds’ portfolio manager in monitoring loan performance. His work includes applying detailed historical data analysis, simulation and machine learning techniques to accurately assess and predict factors that may affect loan default rates. He uses his experience in big data to build predicative models that aim to improve the Fund’s loan selection strategies and which rely on ever-evolving cash flow prediction and valuation models that are based on borrowers’ overall credit behaviors and historical payment information. Xin is also responsible for designing and building web-based data visualization and investor reporting tools that are used in the Fund’s investor interface portal. And when Xin is not engaged with the analytical demands of our managed funds, he is regularly called upon to evaluate emerging loan platforms of interest to Arcadia Funds as well as performing secondary valuation analysis on legacy portfolios of loans for possible purchase by the funds or the funds’ partners.
Before joining the Arcadia Funds team, Xin was employed by MIT’s Center for Computational Engineering. His responsibilities there during the time he worked towards his Masters in Computational Engineering included:
Focusing on computational data analysis, machine learning, numerical simulation and optimization methods
Developing data mining techniques to assess relationship between macroeconomic factors and the Chinese stock market
Working as a research assistant in data visualization and simulation: developed a web-based visualization tool to display large spatio-temporal data
Developing and teaching several courses at MIT in uncertainties, probability, statistics and data analysis
Xin holds the Chartered Financial Analyst (CFA), Chartered Alternative Investment Analyst (CAIA), and Financial Risk Manager (FRM) designations. Xin received a Master of Science degree in Computation for Design and Optimization from MIT and graduated from Imperial College London, with BEng and MEng in Civil Engineering.