B.S., computational mathematics @
I got my Ph.D. degree in applied mathematics on 2012. My research interests are quantitative finance (interest rate modeling & fixed income derivatives pricing), time series analysis, machine learning & data mining and numerical analysis of stochastic partial differential equations. I have five years of work and research experience on quantitative finance, especially in interest rate modeling,
I got my Ph.D. degree in applied mathematics on 2012. My research interests are quantitative finance (interest rate modeling & fixed income derivatives pricing), time series analysis, machine learning & data mining and numerical analysis of stochastic partial differential equations. I have five years of work and research experience on quantitative finance, especially in interest rate modeling, OTC fixed income derivatives, credit risk derivatives and portfolio risk management.
I have research and practical experience on in quantitative investment strategies and electronic trading, especially in fixed income arbitrage, alpha-generating arbitrage, and statistical arbitrage. And I am experienced in statistical and time series modeling, e.g. ARIMA, GARCH, and Bayesian statistics, optimization, machine-learning and data-mining algorithms.
Specialties: quantitative finance, risk analytic, fixed income derivatives, interest rate modeling, machine learning, quantitative trading strategies, MATLAB, C++, R
Quantitative Analyst, Second Vice President @ Doing research on quantitative investment strategies on fixed income and equity portfolios.
Programming and implementing the investment strategies using MATLAB/Python and then C++.
Back-testing/Stress testing the investment strategies with existing data on an out-of-sample basis.
Using multi-factor models to assess the risk of a long-term duration fixed income portfolio, conduct its performance attribution, and estimate the expected tracking error, for both active and passive strategies.
Assisting to build a C++ based portfolio optimization algorithm to do portfolio optimization and asset allocation, using second-order cone program method. Python/MATLAB is used to analyze the results.
Building and validating the valuation model of bonds, customized fixed income derivatives (interest rate swap/cap/floor) to provide specific investment solutions.
Model Risk Management Group
Assessing investment risks for a wide range of models associated with Northern Trust’s portfolios.
Helping to build models and coordinating with software developers to implement the models.
SAS, MATLAB or R is used to do data processing and model testing.
Types of models worked:
CCAR-related credit risk models: including multi-factor linear regression models or ARMA time series models with macro-economic variables as predictors.
Market risk models: including interest rate risk economic capital prediction model based on VaR method and interest rate forecasting model based on Monte Carlo simulation.
Asset management and wealth management models: including portfolio optimization, asset allocation, portfolio risk and attribution models, for equity or fixed income portfolio. From July 2013 to Present (2 years 6 months) Quantitative Analyst & Consultant @ Built financial products pricing model for clients, including option embedded bond, interest rate swap/cap/floor, mortgage back securities (MBS), and credit default swap (CDS), etc.
Techniques used were: Monte Carlo simulation with special types of sampling, bootstrapping, binomial/binomial tree method and other numerical calculation methods. From December 2012 to June 2013 (7 months) Quantitative Researcher, Internship @ •Assisted the manger to gather and analyze market prices and design the high frequency trading strategies to trade commodities, connecting to CME and ICE.
•Helped the software engineer to build up the trading system using C++ in both Windows and Linux environment and analyzed the trading results using MATLAB, Python and mySQL.
•Back-tested the trading strategies to enhance the profitability of the trading strategies and used methods like VaR to control the risk of portfolios and holding positions. From September 2012 to December 2012 (4 months) Greater Chicago AreaResearch Assistant @ •Created a multiple curve LIBOR market model with SABR type stochastic volatility to model the interest rate movements and their volatility behaviors after 2007 credit crunch.
•Used scaling law and moving average method to clean market data and applied unscented Kalman filter and maximum likelihood estimation to estimate the parameters of the model.
•Used the new model and Monte Carlo simulation/trinomial tree method to price and hedge some credit risk derivatives and fixed income derivatives, for example, caps and swaptions. From September 2010 to September 2012 (2 years 1 month) Teaching Assistant @ •In charge of grading, recitation and tutoring mathematical lab for undergraduate students.
•Assisted course instructors in class design, and sometimes gave lectures. From August 2007 to September 2011 (4 years 2 months)
Ph.D., Applied Mathematics @ Illinois Institute of Technology From 2007 to 2012 B.S., computational mathematics @ Xiamen University From 2003 to 2007 Shengqiang Xu is skilled in: Quantitative Finance, R, VBA, Monte Carlo Simulation, Derivatives, Matlab, C++, Python, LaTeX, Numerical Analysis, Financial Modeling, Fixed Income, Mathematical Modeling, Statistics, SAS
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