Shuya Wen

Shuya Wen

Operations Research and Information Engineering
Financial Engineering


MEng Concentration: Financial Engineering
Anticipated Graduation Date: December 2016
Areas of Interest: Trading Strategies, Risk Management, Consulting

Shuya Wen graduated from Wuhan University with a bachelor’s degrees in economics and mathematics. Because of her academic excellence, she was selected into an honor program, the Hongyi School, and graduated with honor from that program.

While interning at Changjiang Securities in the spring of 2015, she collected data from all divisions in the company to assist in daily risk management reports, as well as performed Monte Carlo simulation and VAR test on historical data from the Shanghai Stock Index for annual national pressure test.

During her summer internship with Merrill Lynch in 2014, she collected CFTC COT report data, and connected its positioning with FX market. By applying time series models to describe the internal relationship between COT reports and positioning in the forex market, she increased the prediction accuracy by 20% compared to the multivariate regression models. It was during these experiences that Shuya developed her interests in the finance industry.

Her latest internship is with Macro Analytics for Professionals, where she worked as a quantitative researcher. She analyzed market/sector datasets of daily signals and created ratios to predict market conditions by using data mining methods with R, and reports used in company marketing. Additionally, she performed regression on existing datasets and back tested data collections, with summaries of statistical results.

As the team leader in a mathematical modeling competition in february 2014, she scheduled training sessions for her team, and allocated work to team members with regards to their merits. She developed a macro mathematical model regarding highway transportation, which was verified by simulation later. She also drafted a 35-page presentation paper, a revised vision of which was later published.