Quantitative Analyst

Yuanhao (Frederick) Guo

Harrison, NJ, ***** *******.***@*******.*** 973-***-****

EDUCATION

Rutgers Business School, Newark, NJ September 2015 – May 2017 Master of Quantitative Finance (GPA: 3.93/4.00)

Courses: Options, Fixed Income Analysis, Econometrics, Object-Oriented Programming, Financial Statement Analysis, Numerical Analysis, Stochastic Calculus, Financial Time Series, Financial Modeling, Data Mining, Hedge Fund, Corporate Finance University of Waterloo, Waterloo, Ontario, Canada July 2013 – May 2015 Bachelor of Arts in Honors Mathematical Economics (GPA: 89.55/100) Economics Achievement Award Recipient (2014-2015) – Mathematical Economics Beijing Institute of Technology, Beijing, China September 2011 – June 2013 Bachelor of Arts in Economics (Renmin Scholarship Recipient) EXPERIENCE

Rotman International Trading Competition – Team Member January 2017 – February 2017 Represented Rutgers MQF Program on a team that developed trading strategies by studying simulated market dynamics and forecasting key parameters including credit risk and GDP

• Credit Risk Case – determined trading decision by estimating the credit spread using structural model (Black Scholes) and Altman- z model; wrote VBA code to help process the news, change the model parameters, and calculate the real-time bond fair value

• Algorithmic Trading Case – coded and backtested the pairs trading strategy in Matlab to exploit the divergence between the equity expected return and the realized return

Sunfo Capital Management Group – Quant Intern, Portfolio Management Team Summer 2016 Supported the portfolio manager for backtesting and developing trading strategies using Python, recording transaction data in the database, and calculating P&L

• Developed a portfolio which seeks alpha returns by using a Multi-Factor Equal Weighted approach with monthly rebalancing and reconstituting based on factor loading – calculated the monthly ICs of four contrarian factors, optimized the weight for each, and generated scores for all securities and renewed the portfolio with the 30 highest scoring securities

• Predicted the movements of stocks in the HS300 using PCA and SVM classification techniques – categorized the stock data by selecting 21 features using PCA to reduce them to 5 categories (history price, momentum, risk, size, and value), fed the SVM with the cleansed data, and predicted the price movements for each stock

• Designed a market-cap rotation strategy by predicting timing signals – constructed a signal via the overall performance of the SSE50 stocks compared to the CSI500 index and another signal based on relative strength, predicted the rotation time changes, and coded to long the index for upward signals and short for downward ACADEMIC PROJECTS

Data Mining – Identifying Alpha Containing Stocks by Text Mining Fall 2016 Determined a trading strategy among the top 30 market cap S&P500 stocks based on financial news releases

• Applied “bag of words” and Tf-idf techniques to digitize textual data (news articles) and to give less weight to meaningless words

• Cleaned the data by deleting highly similar articles, weekend news, and night news

• Trained SVM regression and LASSO models to predict the stock price 20 minutes after the corresponding news is released; compared the predicted stock price with the current price for trading decision making Hedge Fund – Growth at A Reasonable Price (GARP) with Momentum Trading Strategy Fall 2016 Developed and backtested a hedge fund equity long / short strategy in Python by improving the GARP approach through adding the momentum factor; selected equities which outperform the market average in the last two consecutive terms

• Parameters for filtering equities are revenue growth, earnings growth, CFO growth, PE ratio, PEG ratio, and stock price

• Compared two weighting schemes: risk weighted using Sortino ratio, and equally weighted Object-Oriented Programming – Online Stock Transaction Simulation Fall 2015 Designed and implemented a stock order transaction and recording system in C++

• Coded bid and ask priority queues, including the data for price, timestamp, company name, and the number of bid or ask shares

• Exploited class structures to automatically and instantly execute buy-sell matches once there is a bid-ask overlapping

• Created output menu and submenu for clients to manipulate orders (adding, modifying, and cancelling) and query the system SKILLS & OTHERS

Programming languages: proficient in Python / R / VBA / Matlab; intermediate in C++ / MySQL Languages: Mandarin (native) / Cantonese (native) / English (proficient) Teaching experience: Graduate teaching assistant for the course Object-Oriented Programming (C++ & Python) at Rutgers Interests: long-distance cycling / basketball / guitar Others: FRM level 1 May 2017 candidate

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