portfolio optimization, stochastic calculus, linear regression

Xiao Zhang

631-***-**** acujy1@r.postjobfree.com

Education:

Stony Brook University, Stony Brook, NY

Ph.D., Applied Mathematics and Statistics (Quantitative Finance) 2011-2015

Honor of Awards in May 2012, GPA 4.0

Relevant Coursework: Linear Regression, Probability, Stochastic Calculus, Portfolio optimization, Risk Budgeting, Time Series modeling and risk management, market making, classification, Algorithms and data structure.

Southwest Normal University 2006-2010

B.S, Applied Mathematics and Statistics

Research Projects and Experience:

Selected research topics:

(a) Regime Switching FIGARCH applied to high frequency data

Implemented regime switching GARCH and regime switching FIGARCH model;

Applied various time series models such as ARMA-GARCH, ARMA-RS-GARCH,

ARMA-RS-FIGARCH, to high frequency data of U.S. and China stock market;

Performed both in-sample tests and out-sample tests for all models included;

Improved VaR based backtesting results in RS-FIGARCH by introducing fat-tailed innovation;

Concluded regime switching along with long memory could capture spikes better and thus was

a potential tool for portfolio optimization, and RS-GARCH was a conservative tool for risk management compared to other models.

Coded in MATLAB.

(b) ARMA-FIGARCH and back testing (with Dr. Aaron Kim)

Built ARMA-GARCH fat-tailed innovation(Multivariate NTS) using DAX 30 components;

Forecasted returns under both ARMA-FIGARCH and ARMA-GARCH and performed Gof tests;

Backtested both models using standard procedures;

Discovered from hypothesis test that long range dependence existed, but was of less impact than for higher frequency data.

With a forthcoming publication regarding the results.

Designed model and implemented forecasting model in Matlab.

Worked closely with TAQ database and extracted data with python libraries such as Pandas and Numpy.

Bravo Risk Management Bravo Risk Management Group LLC. NY 12/2015 - present

Quantitative Analyst/Internship

Routinely meet with research team leader and manage a portfolio optimization and risk budgeting project using C++ in conjunction with external libraries.

Generate test cases and executable file, and optimize computational time in a big picture.

Apply different risk measures such as VaR, CVaR, maximum drawdown, and conditional drawdown to portfolio optimization constraints.

Professional Skills:

Programming experience: MATLAB, C++, Python, R, SQL, Excel, Word, PowerPoint

Market making algorithm, Advanced linear regression model such as ridge and lasso regression, hypothesis testing

Data wrangling and HTML Web Scraping with pandas, lxml, numpy, etc.

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