Quantitative Research/Analyst

YUCHEN(Ethan) LIU

Tel: 917-***-**** E-mail: ***********@*******.*** Address: 888 7th Ave, New York City, NY 10019 EDUCATION

Rensselaer Polytechnic Institute NY, U.S.

Master of Science in Quantitative Finance 2017.08 – 2018.12 Northeastern University China

Bachelor of Science in Financial Engineering 2013.09 – 2017.06 PROFESSIONAL EXPERIENCE

GSA Capital Partners New York City, NY

Quantitative Research, Equity 2018.09 – 2019.01

• Work collaboratively with PM and Senior Researchers. Help the team set up Terabyte level database for research and production and explore new alternative datasets.

• Utilize large datasets like Thomson Reuters, Axioma and IHSMarkit for predicting and testing statistical market patterns, build and refine Alpha signals.

• Conceptualize and develop short term Stat Arb strategies in the US Equity Market. Generate and test ideas based on research papers, books and exclusive insights.

• Develop and refine research-level strategies like: Analyst Dispersion, Residual Momentum, Quality Minus Junk and TRMI (Market Psych).

Preston Asset Management Shanghai, China

Quantitative Research, Equity 2018.06 – 2018.08

• Conducted research on Pairs Trading, generated strategy and back tested the strategy in Chinese stock, ETF and index futures market. Found trading pairs among different industries.

• Implemented Quantitative Timing Strategy based on technical indicators/overlays.

• Did research on Perry Kaufman’s Adaptive Moving Average, consulted relevant papers and generated python code of the strategy. Optimized the parameters of given formulae, redesigned the calculation method of filters and back-test the strategy based on different indexes and terms. Asset Management Department, Haitong Futures Co., Ltd Shanghai, China Quantitative Research, CTA 2017.03 – 2017.08

• Event-driven trading system for commodity futures (Python) Get tick-level data directly from Exchange by using automated interface and process the data into usable form. Generate long term, short term and self-made features based on technical indicators/overlays such as AMA, lag of price and lag of return. Modeling based on Machine Learning methods like Logistic Regression, SVM, and ensemble learning to improve the robustness of the model. Evaluate model performance based on accuracy and ROC curve. Generate, back-test and evaluate the CTA strategy and execute the simulated trade in commodity markets. TRADING & INVESTING EXPERIENCE

• Student Fund Manager of RPI James Fund (NY, U.S.) from Jan.2018 to May.2018. Managed portfolio (AUM $125,000) consists of diversified ETFs. Used Quantitative Timing strategy based on Adaptive Moving Average, sentiment analysis strategy based on NLP for market timing.

• Great passion for stock/futures market and solid buy-side knowledge & experience in US and AxJ markets. 5-years’ experience in investing real-time stock market, commodity futures market and ETFs. Obtain 1 million (300% P&L) from Chinese stock market in 2015. SKILLS

• Python: I’ve been using Python for 3 years, mainly for quantitative investment.

• SQL (Microsoft SQL Server): I’ve been using SQL in GSA mainly for setting up the database, handling large dataset, doing back-test and interacting with Python.

• Distributed computing by using Apache Spark (PySpark & Spark SQL)

• Basic kdb+ and q knowledge, Linux, R & MATLAB.

• Hands on experience in cutting-edge machine learning, NLP, regression and portfolio construction.

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