Jianjun Gao

Jianjun Gao

Professor

Interests:
Optimization theory and applications, Optimal control, Financial engineering, risk management, Financial optimization and numerical algorithms
Courses:
Investment Science, Stochastic model, Dynamic Programming        
Office:
515, School of Information Management and Engineering
 Tel:
021-65901981        
 Email:

gao.jianjun@shufe.edu.cn


Details

Prof. Gao received his Ph.D. and M. Phil degree from the Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, and the Bachelor degree from the University of Science and Technology of China. He used to be the postdoctoral researcher, the lecturer and the visiting researcher in the Chinese University of Hong Kong. Before he joined SHUFE, he was the research professor in the Shanghai Jiao Tong University.

He is currently a committee member of the Financial Engineering and Financial Risk Management Branch of the China Operations Research Society. Professor Gao is the PI of several research projects including the National Natural Science Foundation of China. He has published several papers in top journals, like Operations Research，IEEE Transactions on Automatic Control, Productions and Operations Management, Journal of Banking and Finance, SIAM J. Control & Optimization.

Selected Publications:

  1. Mean-variance hybrid portfolio optimization with quantile-based risk measure.
    J. J. Gao,  S. Liu, Y. Lin, W. P. Wu, K. Zhou
    Operational Research Letters,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3749311#,2025.

  2. Dynamic factor model-based multiperiod mean-variance portfolio selection with portfolio constraints.
    J. J. Gao, C. N. Jin, Y. Shi, X. Y. Cui,
    IEEE Transactions on Automatic Control,  Accepted,  http://dx.doi.org/10.2139/ssrn.5153102, 2025.

  3. An end-to-end direct reinforcement learning approach for multi-factor based portfolio management.
    K. Zhou, X. M. Huang, X. Chen, J. J. Gao
    To appear in European Journal of Finance, https://ssrn.com/abstract=4729683. 2025.

  4. Limited attention allocation in a stochastic linear quadratic system with multiplicative noise.
    X. Y. Cui, J. J. Gao, L. J. Kong, Y. Shi
    IEEE Transactions on Automatic Control, 69, 8798–8803. doi:10. 1109/TAC.2024.3426889. 2024.

  5. Multi-period portfolio choice under loss aversion with dynamic reference point in serially correlated market.
    J. J. Gao, Y. M. Li, Y. Shi, J. Y. Xie
    Omega, 127, 103103. 2024.

  6. When prospect theory meets mean-reverting asset returns: A behavioral dynamic trading model
    J. J. Gao, D. Li, J. Y. Xie, Y. Yang, J. Yao,
    Journal of Banking and Finance, 162, 107159, https://www.sciencedirect.com/science/article/pii/S0378426624000797, 2024.

  7. Price interpretability of prediction markets: A convergence analysis.
    J. J. Gao, Z. Z. Wang, W. P. Wu, D. Yu
    Operations Research, 73, 157–177. https://doi.org/10.1287/opre.2022.0417, 2024.

  8. A customized augmented lagrangian method for block-structured integer programming.
    R. Wang, C. Zhang, S. Pu, J. J. Gao, Z.W. Wen,
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 46, 9439–9455, 2024.

  9. Bayesian Dynamic Learning and Pricing with Strategic Customers.
    X. Chen, J. J. Gao, D.D. Ge, Z. Z. Wang
    Productions and Operations Management, Vol.31, No.8, 3125--3142, DOI: http://doi.org/10.1111/poms.13741, 2022.

  10. Survey on Multi-Period Mean-Variance Portfolio Selection Model.
    X. Y. Cui, J. J. Gao, X. Li, Y. Shi
    Journal of Journal of the Operations Research Society of China, online, \url{https://doi.org/10.1007/s40305-022-00397-6}, 2022.

  11. Price Interpretability of Prediction Markets: A Convergence Analysis.
    D. Yu. Cui, J. J. Gao, W. P. Wu, Z. Z. Wang
    Proceedings of the 23rd ACM Conference on Economics and Computation (EC '22), July 11--15, 2022, Boulder, CO, USA. https://arxiv.org/abs/2205.08913.

  12. JD. com: Operations Research Algorithm Drive Unmanned Warehouse Robots to Work.
    H. L. Qin, J. Xiao, D. Ge, L. W. Xin, J. J. Gao, S. M. He, H. Hu, J. G. Carlsson
    Informs Journal on Applied Analytics, 52, 42–55, https://doi.org/10.1287/inte.2021.1100, 2021.

  13. Betting Market Equilibrium with Heterogeneous Beliefs: A Prospect Theory-Based Model.
    D. Yu, J. J. Gao, T. Y. Wang
    European Journal of Operational Research, Vol.198, No.1, 137--151, DOI: \url{https://doi.org/10.1016/j.ejor.2021.05.024}, 2021.

  14. Multi-period Mean-Variance Optimization with Management Fees.
    Cui, X. Y., J. J. Gao, Y. Shi
    Operational Research - An International Journal, DOI:10.1007/s12351-019-00482-4, 2019

  15. Time-Consistent and Self-Coordination Strategies for MultiPeriod Mean-Conditional Value-at-Risk Portfolio Selection.
    X. Y. Cui, J. J. Gao, Y. Shi, S.S. Zhu
    European Journal of Operational Research, Vol. 276, No.2, 781-789, DOI: \url{ https://doi.org/10.1016/j.ejor.2019.01.045}, 2019

  16. Discrete-Time Mean-CVaR Portfolio Selection and Time-Consistency Induced Term Structure of the CVaR.
    M. S. Strub, D. Li, X.Y. Cui, J. J. Gao
    Journal of Economics Dynamics and Control, Vol.108, DOI: https://doi.org/10.1016/j.jedc.2019.103751.

  17. On Continuous-time Constrained Stochastic Linear-Quadratic Control.
    W.P. Wu, J. J. Gao, J.G. Lu, X. Li
    Automatica, Vol. 114, 2020. DOI:\url{https://doi.org/10.1016/j.automatica.2020.108809}.

  18. Explicit Solution for Constrained Scalar-State Stochastic Linear-Quadratic Control with Multiplicative Noise.
    W. P. Wu, J. J. Gao, D. Li
    IEEE Transations On Automatic Control, Vol.64, No. 5, 1999 – 2012, 2019.https://arxiv.org/abs/1709.05529

  19. Dynamic Mean-LPM and Mean-CVaR Portfolio Optimization in Continuous-Time.
    J. J. Gao, K.Zhou, D. Li, X.R. Cao
    SIAM Journal On Control and Optimization, Vol. 55, No. 3, 1377-1397, 2017.~Available at \url{http://epubs.siam.org/doi/10.1137/140955264}

  20. Dynamic Mean-VaR Portfolio Selection in Continuous Time.
    K. Zhou, J. J. Gao, X.Y. Cui, D. Li
    Quantitative Finance, Vol.17, No. 10, 1631-1643. 2017.
    Available at http://dx.doi.org/10.1080/14697688.2017.1298831.

  21. Dynamic mean-risk portfolio selection with multiple risk measures in continuous-Time.
    J. J. Gao, Y. Xiong, D. Li
    European Journal of Operational Research, vol.249, 647-656, 2016.
    DIO:\url{ http://dx.doi.org/10.1016/j.ejor.2015.09.005http://dx.doi.org/10.1016/j.ejor.2015.09.005}

  22. A polynomial case of quadratic programming problem with box and integer constraint.
    C. L. Liu, J. J. Gao
    Journal of Global Optimization, Vol. 62, No. 4, 661-674, 2015.

  23. Time-cardinality constrained mean-variance portfolio selection: Stochastic control approach.
    J. J. Gao, D. Li, X. Y. Cui, S. Y. Wang
    Automatica, vol. 54, 91-99, 2015.

  24. Optimal multiperiod mean-variance policy under no-shorting constraint.
    X. Y. Cui, J. J. Gao, X. Li, and D. Li
    European Journal of Operational Research, Vol. 234, No. 2, 459-468, 2014.

  25. Optimal cardinality constrained portfolio selection.
    J. J. Gao, D. Li
    Operations Research, Vol. 61, 745-761, 2013.

  26. Linear-Quadratic switching control with switching cost.
    J. J. Gao, D. Li
    Automatica, Vol.48, No. 6, 1138-1143, 2013.

  27. A polynomial case of cardinality constrained quadratic optimization problem.
    J. J. Gao, D. Li
    Journal of Global Optimization, Vol. 56, No. 4, 1441-1455, 2013.

  28. Complete statistical characterization of discrete-time LQG and cumulant control.
    F. C. Qian, J. J. Gao and D. Li
    IEEE Transaction on Automatic Control, Vol.57, No.8, 2110-2115, 2012.

  29. On duality gap in binary quadratic optimization.
    X. L. Sun, C. L. Liu, D. Li and, J. J. Gao
    Journal of Global Optimization, Vol. 53, No.2, 255-269, 2012.

  30. Discrete-time cardinality constrained linear-quadratic optimal control.
    J. J. Gao and D. Li
    IEEE Transaction on Automatic Control, Vol. 56, No.8, 1936--1941. 2011.

  31. Performance-first  control for discrete-time LQG problem.
    D. Li, F. C. Qian and J. J. Gao
    IEEE Transaction on Automatic Control, Vol. 54, No. 9, 2225--2230, 2009.

Book Chapters:

  1. Sparse and Multiple Risk Measures Approach for Data Driven Mean-CVaR Portfolio Optimization Model.
    J. J. Gao, W. P. Wu
    Optimization and Control for Systems in the Big-Data Era, Springer(International Series in Operations Research & Management Science), Edited by Choi, T. M., Gao, J., Lambert, J.H., Ng, C.-K., Wang, J., 2017, pp 167-184.

  2. Continuous-time mean-variance portfolio selection with finite transactions.
    X. Y. Cui, J. J. Gao, D. Li
    Stochastic Analysis and Its Applications to Mathematical Finance, Edited by X. Y. Zhou and T. S. Zhang, World Scientific Publishing Company, 2012, pp.77-98.

  3. Polynomially solvable cases of binary quadratic programs.
    D. Li, X. L. Sun, S. S. Gu, J. J. Gao, C. L. Liu
    Optimization and Optimal Control: Theory and Applications (Springer Optimization and Its Applications, Vol 39, Edited by A. Chinchuluun, P. M. Pardalos, R. Enkhbat and I. Tseveendorj. Springer, 2010, pp 199-225.

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