Quantitative Analyst Resume

Professional Objective

To seek a full time position in quantitative analysis and contribute my strong analytical and programming skills to conduct exploratory data analysis, develop algorithms and models to solve practical problems, make connections between real problems and statistical solutions, and enhance predictive modeling capability.

Working Experiences

Quantitative Analyst, Confidential, 2011.1 ~ 2011.12
Built swap curves based on different financial instruments of fixed incomes to price bonds, interest rate swaps, and cross currency swaps.
Implemented and calibrated different interest rates models such as short rate models (Hull-White and G2++), Libor market model and SABR model.
Used short rate model to price some complex products such as Bermudan Swaption by numerical methods such as trees.
Calibrated the credit model such as hazard rate model from CDS.
Learning the CVA models.

Research Assistant, Confidential, 2006.8 ~ 2010.8

Project: A new stochastic volatility model with jumps for equities with Bayesian analysis and option pricing

Built stochastic volatility models for Black-Scholes and Levy process based on Non-Gaussian Ornstein-Uhlenbeck process.
Used Levy subordinator to improve the models and made Bayesian estimation and prediction with MCMC algorithm for the volatility and future returns.
Produced more efficient asset pricing for equity options based on the model.

Project: Time series analysis of the US Treasury Bill based on AR-GARCH model.

Analyzed the US Treasury Bill dataset and found the important features of the data and then fit AR model on the returns and GARCH model on volatility.
Provided a simple approach to calculating value at risk of a financial position in risk management.

Project: The analysis of social and natural environmental effects on Boston house prices.

Built an advanced regression model for the environmental factors and the house prices and showed environmental factors are significant to affect house prices.
Concluded that the social environmental factors were more important than natural environmental factors.

Education

Ph.D. in Statistics

Research areas: Regression, ANOVA, Bayesian Analysis, Time Series, Econometrics, Monte Carlo (MCMC, Sequential MC, Kalman and Particle Filters etc), Data Mining, Machine Learning, Principle Component Analysis, Factor Analysis, Classification & Clustering, Financial Modeling, Stochastic Calculus, Applied Probability

M.A. in Mathematics
B.S. and M.S. in Mathematics

Advanced Computer Skills

Extensive experiences in complex statistical modeling using R/S-Plus, SAS, SPSS, Matlab
Proficient in MS office suite (Excel, Word, Power Point).
Proficient with C, C++, SQL and Excel VBA Programming.

Honors & Awards

Bilsland Fellowship
Excellent Prize of Chinese Physics Olympic Contest

Self Evaluation

Highly motivated and confident individual with excellent communication and interpersonal relationship skills.
Both cooperated and independent with responsibility.
Broad scope of knowledge and adaptability to keep learning.

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