Machine Learning Quantitative Research

Jue (Joey) Liu

949-***-**** • ad5yda@r.postjobfree.com • https://www.linkedin.com/in/jue-l

EDUCATION

Columbia University New York, NY

M.S. in Operations Research, GPA: 3.5/4.0 Sep 2023 - Dec 2024 l Selected Courses: Machine Learning, Time Series Analysis, Stochastic Calculus, Optimization, Algorithmic Trading University of California, Irvine Irvine, CA

B.S. in Mathematics & B.A. in Quantitative Economics, GPA: 3.8/4.0. Sep 2019 - Jun 2023 l Honors: Latin honor cum laude, Dean’s List for 9 quarters (2020-2023) l Selected Courses: Statistics, Probability, Linear Algebra, Derivatives Pricing, Fixed Income, Econometrics, Regression PROFESSIONAL EXPERIENCE

Huatai Securities (AUM: USD100B+) Shenzhen, China

Quantitative Research Intern Jul 2023 - Sep 2023

l Implemented updated Fama-French Five-factor Model (Hou, 2021) in Python for China’s A-share market on 4,064 stocks since 2007; calculated factors’ returns for a multi-factor strategy, achieving a Sharpe ratio of 2.32 and CAGR 4.66%. l Utilized machine learning models including Random Forest, XGBoost, and AdaBoost to analyze financial fraud in China on 39,553 companies from 2007; identified XGBoost outperformed (AUC 0.87) with tangible asset ratio as a key feature. Zhong Ou Asset Management (AUM: USD80B+) Shanghai, China Fundamental Quantitative Research Intern Jun 2023 - Jul 2023 l Developed a Bollinger Bands strategy in Python for 18 global stock indices and 20 MSCI industries since 1990, achieving an average Sharpe ratio of 0.76 and a 2% maximum drawdown; excelled in Chinese Market with a Sharpe ratio over 1.2. l Applied K-means clustering to reduce correlation among 20 MSCI industries by integrating similar ones into single data points; carried out Monte Carlo simulations to visualize and analyze industry relationships as a network, calculating clustering probabilities for each industry pair as edges; applied the Kruskal’s algorithm to finalize network structure. UBS Remote

Quantitative Research Assistant (PTA) Jul 2022 - Sep 2022 l Employed Python to harvest 10-year data on 70 Chinese semiconductor stocks and conducted rolling OLS cointegration analyses, identifying a high-potential stock pair (300236.SZ, 300666.SZ) for pairs trading strategy. l Designed dynamic mean-reversion model using 60-day stats, attaining 7% max drawdown and Sharpe ratio 1.6. l Synthesized and visualized strategy performance metrics into an investment report using Matplotlib and Seaborn libraries. CICC Wealth Management (AUM: USD90B+) Shenzhen, China Asset Management Intern Mar 2021 - Jun 2021

l Tracked asset allocation and investment needs of FOF (fund of funds) clients according to research and return visits. l Prepared analytical reports on M&A and asset restructuring of listed companies to inform clients’ go-forward plans. l Verified clients’ fund holdings; developed Excel sheets to monitor stock pledges and mitigate investment risks. INDUSTRIAL PROJECTS

MathWorks Analyst New York, NY

Computational Techniques for Option Pricing Model Jan 2024 - May 2024 l Developed Monte Carlo algorithms for option pricing in MATLAB and Python, leveraging parallel computing technique. l Trained Physics-Informed Neural Networks (PINNs) for option pricing, reducing training times with GPU acceleration. l Implemented finite difference methods to price options, detailing spatial and temporal discretization in options PDEs. SKILLS

Computer Skills: Python, MATLAB, R, Mathematica, LaTex, Microsoft Office

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