Jin Shi graduated from Zhejiang University in 2025 with dual Bachelor鈥檚 degrees in Finance and Law and a minor in Mathematics. He specializes in time series analysis and asset pricing, refined through five quantitative internships. At State Street, he developed SARIMAX models to enhance macroeconomic forecasts and implemented logistic regression for estimating credit default probabilities under stress scenarios. At CICC, he optimized a treasury futures reversal strategy by dynamically combining short- and long-term signals based on volatility, and analyzed institutional positioning to refine timing models. At Guotai Haitong, he constructed a dual-confirmation treasury futures timing strategy using long-short dominance factors and designed an algorithm to filter signals for overnight information and contract rollovers. Earlier roles at BCG and Nanhua Futures complemented these quantitative experiences with industry research and macroeconomic analysis. Beyond his professional pursuits, Jin dedicated a year to machine learning research on slum prediction at UC Berkeley's Haas School of Business, thereby strengthening practical Python capabilities. Outside of finance, he enjoys poker, table tennis, and provides pro bono legal consultancy. Upon graduation, Jin plans to pursue a career in quantitative research, trading, or asset management.
