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高建军


    姓名:


高建军

    最后学位:博士
    职称:教授
    公共职务:
    导师岗位:博导
    办公室:515
    电话:65901981
    Email:gao.jianjun@shufe.edu.cn




个人简介


高建军博士，上海财经大学信息管理与工程学院，交叉科学研究院，教授、博士生导师。中国运筹学学会金融工程与金融风险管理分会常务理事。

研究方向：优化算法、随机控制在金融决策模型中的应用，金融优化，动态投资组合管理，金融风险管理；


学术组织

  1. 中国运筹学会金融工程与金融风险管理分会，秘书长，常务理事;

  2. Institute for Operations Research and the Management Sciences (INFORMS), 会员；

  3. IEEE Control System Society, 会员；


教授课程

本科生：《投资科学》、《运筹学(高级)》
研究生：《随机模型》、《系统工程》、《金融市场与投资策略》


科研项目


  1. 参与：自然科学基金区域合作项目(2025.01-2028.12) No.  72461160315: "基于数据与行为的跨市场金融风险传染与测度"

  2. 主持：自然科学基金面上项目(2020.01-2023.12) No. 71971132:"金融决策模型的泛化问题研究

  3. 主持：自然科学基金面上项目 (2016.01-2019.12)  No. 61573244 ：“乘性噪声不确定系统基于偏距的随机控制及在金融优化中的应用”

  4. 主持：自然科学基金项目 (2013.01-2015.12)  No. 71201102 ：“资产数目与投资周期带有基数约束的投资组合优化 ”

  5. 主持：教育部博士点基金项目(2013.01-2015.12) No. 20120073120037：“鲁棒最优变现问题研究”

  6. 参与香港研究资助局(RGC)项目 “Optimal Dynamic Mean Downside Risk Portfolio Selection”， 2014-2017；



教育背景:

  • 2009. 博士学位，系统工程及工程管理系，香港中文大学，中国香港

  • 2005. 硕士学位，系统工程及工程管理系，香港中文大学，中国香港

  • 2003. 学士学位，中国科学技术大学，合肥，中国


工作经历：

  • 2016至今：教授，信息管理与工程学院， 上海财经大学

  • 2013年-2015年：特别研究、副教授、上海交通大学；(2013年，麻省理工大学斯隆管理学院，访问学者)

  • 2010年-2011年：研究助理，香港中文大学

  • 2009年-2010年： 博士后研究员，香港中文大学


代表性成果：


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

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

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

  • X. Y. Cui,  J. J. Gao, L. J. Kong, Y. Shi,Limited attention allocation in a stochastic linear quadratic system with multiplicative noise.IEEE Transactions on Automatic Control,69, 8798–8803. doi:10.1109/TAC.2024.3426889. 2024.

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

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

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

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

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

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

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

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

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

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

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

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

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

  • W. P. Wu, J. J. Gao, D. Li,Explicit Solution for Constrained Scalar-State StochasticLinear-Quadratic Control with Multiplicative Noise,IEEE Transactions On Automatic Control, Vol.64(5), 1999-2012, 2019. \url{https://arxiv.org/abs/1709.05529}.

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

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

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

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

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

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

  • J. J. Gao and D. Li,Optimal Cardinality Constrained Portfolio Selection,Operations Research, Vol. 61, 745-761, 2013.

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

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

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

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

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

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

著作章节

  1. J.J. Gao, W.P. Wu, Sparse and Multiple Risk Measures Approach for Data Driven Mean-CVaR Portfolio Optimization Model, Optimization and Control for Systems in the Big-Data Era: Theory and Applications, edited by T. M. Choi, J.J. Gao, J. H. Lambert, C.K, Ng, J. Wang, Springer, 2017.

  2. X.Y. Cui, J.J. Gao,  D. Li,  Continuous-Time Mean-Variance Portfolio Selection with Finite Transactions, Stochastic Analysis and Its Applications to Mathematical Finance, edited by X.Y. Zhou, T. S. Zhang, World Scientific Publishing Company, 2011.

  3. D. Li, X.L. Sun, S.S. Gu, J.J. Gao, C.L. Liu, Polynomially solvable cases of binary quadratic programs, pp 199-225, Optimization and Optimal Control: Theory and Applications, Springer, 2010.





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