RESEARCH: Mathematical Finance

The mathematical finance group includes probabilists and stochastic analysts working in problems directly motivated and/or applicable to finance and economics, or supervising PhD students working in those problems. From mathematical side, the members’ specialized research areas include stochastic differential equations (both forward and backward, both ordinary and partial), their related areas such as stochastic control and stochastic filtering, stochastic numerics, and statistics. From the finance/economics side, several research topics include, but are not limited to: option pricing and hedging theory; financial markets with frictions (including transaction cost, liquidity cost, credit risk, and model uncertainty); utility optimization theory with portfolio/consumption control, and contract theory.

The faculty members in the group are also responsible for teaching and advising graduate students at both Master and Ph.D. levels. The Master program of mathematical finance at USC College, a joint venture of Mathematics department and Economics department, prepares students a careers in the quantitative finance industry. Many members of the group have been responsible for teaching courses in the program, and advising Ph.D. students specializing in mathematical finance. The biweekly Mathematical Finance Colloquium brings in experts from both academia and financial industry, providing valuable contacts and opportunities for graduate students.

Regular Faculty
  • Baxendale, Peter: Stochastic dynamical systems; equilibrium, stability and bifurcation for solutions of stochastic differential equations; applications to stochastic neuronal models.
  • Lototsky, Sergey: Stochastic partial differential equations, optimal nonlinear filtering of diffusion processes, statistical inference for continuous-time processes.
  • Ma, Jin: Stochastic analysis, stochastic differential equations, stochastic control theory, mathematical finance and insurance.
  • Mikulevicius, Remigijus (Remi): Stochastic differential equations, stochastic analysis.
  • Minsker, Stanislav (Stas): Statistical learning theory, non-parametric statistics, concentration inequalities, mathematical finance.
  • Zhang, Jianfeng: Stochastic analysis, backward stochastic differential equations, stochastic numerics, and mathematical finance.


  1. Yongjian Kang (Lv/Zhang)
  2. Chandrasekhar Karnam (Ma/Zhang)
  3. Eunjung Noh (Ma)
  4. Rentao Sun (Ma)
  5. Panagiotis Tsilifis (Ghanem/Mikulevicius)
  6. Cong Wu (Zhang)
  7. Weisheng Xie (Ma)
  8. Xiaojing Xing (Ma)




    • Keller, Christian (Zhang), Pathwise Stochastic Analysis and Related Topics
    • Zhang, Tian (Ma), Optimal Investment and Reinsurance Problems and Related Non-Markovian FBSDEs With Constraints


    • Bessam, Diogo (Lototsky), Large Deviations Rates in a Gaussian Setting and Related Topics
    • Ekren, Ibrahim (Zhang), Path-Dependent Partial Differential Equations and Related Topics
    • Sokolov, Grigory (Tartakovsky/Lototsky), Multi-Population Optimal Change-Point Detection
    • Zhuo, Jia (Zhang), Probabilistic Numerical Methods for Fully Nonlinear PDEs and Related Topics


    • Pham, Triet (Zhang), Zero-Sum Stochastic Differential Games in Weak Formulation and Related Norms for Semi-Martingales
    • Wang, Huanhuan (Ma), Asset Management with Incomplete Information
    • Wang, Xin (Ma), Nonlinear Expectations for Continuous Time Model with Jumps and Applications
    • Xu, Li (Lototsky), Parameter Estimate for Hyperbolic SPDE's with Stochastic Coefficients
    • Zhong, Jie (Lototsky), Second Order in Time Stochastic Evolution Equation and Wiener Chaos Approach


    • Du, Jie (Zhang), Stochastic Games on Stopping Times
    • Kaligotla, Sivaditya (Lototsky), Asymptotic Problems in Stochastic Partial Differential Equations: A Wiener Chaos Approach
    • Lin, Ning (Lototsky), Estimation of Coefficients in Stochsatic Differential Equations
    • Moers, Michael (Lototsky), Statistical Inference of Stochastic Differential Equations Driven by Gaussian Noise
    • Xu, Shanshan (Lototsky/Wilcox), Initiative Non-Parametric Multivariate Regression Hypothesis Testing


    • Chen, Jianfu (Ma), Regime Switch Term Structure model with Forward-Backward Stochastic Differential Equations
    • Wang, Xinyang (Ma/Zhang), Dynamic Model for Limit Order Books and Optimal Liquidation Problems
    • Yun, Youngyun (Ma), Analysis of Correlated Defaults and Joint Default Probability in a Contagion Model


    • Liu, Wei (Lototsky), Statistical Inference for Stochastic Hyperbolic Equations
    • Zhang, Changyong (Mikulevicius), Numerical Weak Approximation of Stochastic Differential Equations Driven by Levy Processes


    • Knape, Mathias (Mikulevicius/Zapatero), A General Equilibrium Model for Exchange Rates and Asset Prices in an Economy Subject to Jump-Diffusion Uncertainty
    • Polunchenko, Aleksey (Mikulevicius/Tartakovsky), Quickest Change Detection with Applications to Distributed Multi-Sensor Systems




    • Christian Keller: Postdoc at University of Michigan
    • Tian Zhang: Education Management Systems


    • Diogo Bessam: Postdoc at PUC-RJ/IMPA (Brasil)
    • Ibrahim Ekren: Postdoc at ETH Zurich
    • Grigory Sokolov: Postdoc at the SUNY Binghamton
    • Jia Zhuo: Morgan Stanley


    • Triet Pham: Postdoc at Rutgers
    • Huanhuan Wang: Capital One
    • Xin Wang: Morgan Stanley
    • Li Xu: Google
    • Jie Zhong: Postdoc at Ritsumeikan University (Japan)


    • Jie Du: Guggenheim Partners
    • Sivaditya Kaligotla: Bloomberg LP
    • Ning Lin: Citigroup
    • Michael Moers: Deutsche Bank


    • Jianfu Chen: Union Bank of California
    • Xinyang Wang: Morgan Stanley
    • Youngyun Yun: Union Bank of California


    • Wei Liu: American Express
    • Changyong Zhang: Postdoc at Salzburg University


    • Mathias Knape: Goldman Sachs
    • Aleksey Polunchenko: Postdoc at USC