Microsoft Office Project

Jun Li

732-***-**** East Brunswick, NJ ******@*******.***

Education

Rutgers Business School, Rutgers University Aug. 2014 – May 2016

Master of Quantitative Finance GPA: 3.6/4.0

South China Normal University Sept. 2009 – Jul. 2013

BS in Financial Mathematics and Financial Engineering GPA: 3.4/4.0

BS in Economics GPA: 3.3/4.0

Experience

Technical, Consulting & Research, Inc., Connecticut

Best We Can Be Program, Intern Jan. 2015 – Jun. 2015

Utilized R to perform 2-D analysis of students’ individual/relative performance

Assessed courses effectiveness based on students’ performance

Automated grading procedure and graphed students’ performance results

China Construction Bank, Guangzhou, China

Corporate Business Department, Intern Jul. 2012 – Sept. 2012

Collaborated with client managers to perform internal credit evaluation

Validated letters of guarantee through the Legal Documents Management Online System

Employed Microsoft Excel to aggregate corporate business reports for Q2 2012

Research Projects

C++ Project, Newark, NJ Sept. 2014 – May 2015

Collaborated with teammate to build vector-based stock transaction platform

Created airline check-in simulation system to predict human capital budget given arrival rate per hour, the maximal serving time of each handler, and the number of handlers

Structured a map-based order book for stock trading system for users to execute, add, delete, and update orders

Financial Time Series Project, Newark, NJ Apr. 2015 – May 2015

Utilized R to analyze the timing and selection ability of 12 mutual funds

Tested level of fit for Treynor-Mazuy, Henriksson-Merton, and Chang-Lewellen models

Performed testing of autocorrelation and ARCH effect, and applied ARIMA/GARCH models

Evaluated and documented 12 mutual fund performance level

Concluded timing and selection ability are not significant factors for the excess annual returns

Market Anomalies and Institutional Ownership Research, Newark, NJ Apr. 2015 – May 2015

Researched on three market anomalies and corresponding institutional investment behavior

Performed testing for market anomalies with Fama-French three-factor model

Applied leading academic research methods to test market performance and documented corresponding reasons

Preprocessed financial data of more than 10000 common stocks from 1980 to 2012 using R

Concluded that institutional investors traded contrary to anomaly prescriptions and tended to buy short-leg stocks

Multi-Factor Equity Trading Strategy, Newark, NJ Sept. 2015 – Dec. 2015

Applied J.P. Morgan Factors Reference Book methodologies to build long-short equity trading strategy based on factors in five different categories: value, quality, sentiment, technical indicator, and volatility

Utilized API in R to retrieve and validate S&P 500 historical values (2005-2015) from Bloomberg

Built five-factor cross-sectional monthly models to long the stocks at top 10% and short stocks at bottom 5% based on predicted returns

Applied MATLAB optimization toolbox to control portfolio volatility, resulting in 27% increase in Sharpe ratio and 26% increase in Sortino ratio

Technical Skills

VBA, R, C++, MySQL, Matlab, Bloomberg API with R, Python, Microsoft Office (Excel, Word, PowerPoint, Outlook), Tableau and SPSS

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