Sr Developer & Analyst

Fan Wang

*** **** ***********, ** ***** Phone: ***-***-*********@****.***.***

Objective

Quantitative Analyst: create/analyze/implement/test/apply financial models

Financial Software Developer: programming

Education

Universtity of california, irvine– Irvine, CA

PhD in Mathematical Finance 2012

Minor in Statistics – Master Level Courses GPA 4.00 2011

Master in Mathematics GPA 3.97 2008

Universtity of Science and technology of china

Bachelor of Science in mathematics GPA 3.86 2007

Skills and Certificates

Programming Language:

• C/C++, Python, VBA

Simulation and Designs:

• MatLab, R

Library and Frameworks:

• NumPy, SciPy, XLW, a little STL, Boost

Certificate:

• CFA level II candidate

• Bloomberg Certified

Other

• Latex, Microsoft Office

• Linux, Windows, Solaris

Professional Experience

OTC Quant InterN Bloomberg L.P New York 2011 Jun. 7th-2011 Sep. 16th

Was placed in FX/Commodity Team, focused on Stochastic Local Volatility(SLV) model calibration

Re-design the calibration method for SLV model in Bloomberg’s pricing function OVML. Change the original historical calibration method to calibrate to market data, write Python/C API to process market quotes, designed new objective functions that more suitable for exotic quotes, tested and implemented various optimization methods(Trust region, Interior Point, LM, BFGS), write alpha stage C code for the new calibration, back testing the calibration results

Implemented a prototype local volatility model for long term FX option pricing problem in MatLab.

Supporting works, including numerically check the MC pricer based on client’s request, filter and clean up specks of raw volatility data.

Financial analyst INTERN merrill Lynch Newport Beach 2010 Jun. - 2011 Sep.

Test trading strategies, create research report by using Excel and Bloomberg terminal

Making presentations of quantitative finance concepts to clients and manager

Research assistant UC, Irvine Irvine 2007 Dec. – 2012 Present

Theory and Numerical: Malliavin calculus, Weiner Chaos expansion of SDEs, and their applications in numerically solving SDEs

Model: Multi-scale stochastic volatility(SV) models, its probabilistic representation and extension to general SV model calibration

Statistics: Various MC variance reduction techniques. MCMC inference for GARCH model parameters

(Earlier work on Math Biology)Modeling and simulation drug’s effect on tumor cell’s surface and bulk, write PDE solver for surface-bulk coupled system.

Information on Request Available for Relocation

Contact this candidate