Tianhao (Roca) Zhao

*** * *** ***** **. **** • Chicago, IL 60607 • 570-***-**** • addv17@r.postjobfree.com EDUCATION

University of Illinois at Urbana-Champaign

• Master of Science in Financial Engineering August 2018 – December 2019 Courses: Risk Management in Finance, Statistical Analysis in Finance, Financial Derivative, Option Trading, Financial Computation, Machine Learning, Stochastic Process.

• Bachelor of Science in Engineering Mechanics August 2015 – May 2018 SKILLS

Technical: Python (3+ years), C++ (2+ years), SQL (2+ years), Excel (5+ years), R (2+ years), MATLAB (4+ years), SAS, VBA, AMPL, Java, Tableau, Bloomberg Terminal.

PROJECT HIGHLIGHTS

Credit Risk Forecasting on Personal Loan portfolio using machine learning method Spring 2020

• Used Python to process and analyze over 15 million observations of personal loan and 140 macroeconomic indexes, including handling missing value, outlier, information leakage issues.

• Used Tableau to visualize and discover relationship between client prior credit history, personal profile and their delinquency/default.

• Used advanced statistical methods and machine learning technics to select features and built Linear Regression, Logistic Regression, and Random Forest model to predict borrower’s Probability of Default (PD).

• Performed extensive feature engineering, identified new factor, materially enhanced model performance AUC by 5%. Stress Testing, Portfolio VaR/Cash flow, Liquidity Risk, Transaction Cost Analysis Spring 2020

• Conduct stress testing on various scenarios (Coronavirus impact, retail business bankruptcy) and cash flow analysis on fixed income portfolio (US Treasury, Corp, MBS, ABS, etc.), Analyzed prepayment behavior of MBS and CMO.

• Calibrate GARCH (1,1) model and calculate 95% VaR using both historical simulation and Monte Carlo simulation after constructing Theta-neutral and Vega-neutral portfolios using Dow 30 Call and Put Options prices and Dow 30 Stock,

• Imported 4 days' worth of 100 Scandinavian Blue Chip Stocks trading tick data in C++ and calculated mean, median, maximum time between trades and tick changes, bid-ask spread, and probability of Round Number Effect.

• Data Visualization in Python to show the distribution of trading frequency, tick change frequency, bid-ask spread, and the round number effect of trading prices and volumes and to better observe the market liquidity. PROFESSIONAL EXPERIENCE

CME Group Inc. Chicago, Illinois

Practicum Project – Quantitative Risk August 2019-Dec 2019 Worked with Market Risk Team to identify the risk of abrupt market move driven by Large Trader Positions based on the model labels generated by CME’s internal platform – MASS, and CFTC large trader reports, including:

• Explore 191 features of Energy Products (eg. Crude Oil, Natural Gas), conducted EAD and generate high quality visualization with Matplotlib and Tableau.

• Extracted features from the COT report and set up Z-score threshold to extract labels from the CME MASS data.

• Built Random Forest, Logistic Regression, XGBoost model with hyperparameter tuning to achieve the binary classification prediction and created Repeated Held-out Evaluation Cross-Validation for time series data.

• Used different methods on imbalanced dataset and overfitting problems, such as implement PCA for feature selection, search and include in more data for further training. iFund Asset Shanghai, China

Data/Quantitative Analyst Internship June 2019 – August 2019

• Extracted financial data from Wind Database using SQL script in python and matched company names and time range of the original data set and created growth features for stock-selection based on the extracted data.

• Back-tested features’ ICIR, average % return of each year on a back-testing platform to select the most efficient features. China Everbright Bank Shanghai, China

Quantitative Investment Analyst Internship June 2018 – August 2018

• Engaged in bond investment of Zhongli Group and GCL-Poly Energy Holdings Ltd and prepared materials and statements for regular meetings.

• Wrote large amount of SQL query to extract, group, and select financial data from Wind Database.

• Coordinated with Auditor Group and assisted in financial statements data organization and created dashboards to visualize research evaluation using Tableau to demonstrate during meetings.

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