Quantitative Analyst Resume Profile
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Chicago, IllinoiS
SUMMARY
Ahighly motivated quantitative analyst with comprehensive mathematical modeling and implementation skillsand in-depthknowledge of quantitative finance including Term Structure Models, Financial Derivatives, Risk Management, Time Series, Statistics, Probability Theory and Stochastic Calculus
HIGHLIGHTS
- Proficient programming skills in C/C , Python, MATLAB, R, SAS, VBA/EXCEL and SQL
- Experience with building advanced statistical methods in a big data environment
- Research in developing risk and valuation models
- Creative self-starter and great team-player
- Expert level in Stochastic Calculus, time series,Brownian motion, PDE, ODE, Monte Carlo simulations, finite difference methods etc.
- Able to work on multiple projects
- Highly self-disciplined, detail-and results-oriented
- Excellent interpersonal and verbal and written communication skills
- Strong organizations skills good time management, capable under pressure
ACCOMPLISHMENTS
Developed a new methodology in pricing options with substantial improvements in pricing accuracy and computational cost
EXPERIENCE
Quantitative Analyst
Confidential
- Studied all types of computational errors such as discretization, truncation and interpolation errors and controlled errors within the limits given.
- Found the most appropriate values of parameters including dampening factor implemented in the CGMY model.
- Priced equity derivatives in the CGMY model using numerical approaches such as the trapezoidal andSimpson's rules.
- Applied Fast Fourier Transform FFT to simultaneously price numerous contracts with the desiredaccuracy.
- Developed a new methodology to effectively price the contracts using Hilbert Transform approach which shows substantial improvements in pricing accuracy and computational cost.
- Assisted managers on trade approvals and finance on price verification methodologies.
Quantitative Researcher
Confidential
- Assisted in building proprietary options pricing models which show improvements in terms of pricingaccuracy and computing efficiency.
- Assisted in developing algorithms for company's Multi-Asset Execution Management Systems MAEMS .
- Implemented various financial derivative models in the quantitative analysis of private equity investments using C programming.
- Created formal modeling of risk, return and trading cost profiles for equities and other firm-wide assets classes.
Credit Risk Model Validation Analyst
Confidential
- Extensively tested the risk models including sensitivity analysis, stress testing, uncertainty analysis, back-testing, and bench-marking to challenge the models effectively.
- Applied Gaussian Copula to model default dependence to evaluate risks in subprime RMBS structured portfolio.
- Found inappropriate use of equity replication model in the counter-party credit risk exposure project, and debugged it.
- Wrote comprehensive independent validation reports explaining the analysis performed and their results.
Confidential
University of Illinois at Urbana
- Term structure models: applied Hull-White one-factor model and LIBOR market model LMM to price and calibrated a range of interest rate products such as European swaption, multi-look trigger swap, caption, Bermudan swaption, constant maturity swap CMS , and a real world CMS derivative results show that the LMM in general leads to better estimation of derivative prices than the Hull-White one-factor model.
- Optimization: conducted Markowitz mean-variance analysis using Black-Litterrman returns using 10 years of data on S P 500 stocks and applied the Black-Litterman model to reconstruct portfolio allocation and studied the sensitivity of portfolio.
- Risk management: developed and implemented the dynamic conditional correlation DCC models to forecast the future correlations among S P 500 stocks and optimized related portfolios.
- Monte Carlo simulations: applied random tree method to price path-dependent options with high computational efficiency by creating a MATLAB application to perform Monte Carlo simulations.