Research Areas: Machine Learning and Quantitative Finance; Financial Economics and Financial
Mathematics; Backward Stochastic Differential Equations and Nonlinear Expectation Theory and its
Applications; Stochastic Optimization Problems and their Applications in Economics and Finance
0531-88364760
jsl@sdu.edu.cn
- 1996.09-1999.07, School of Mathematics and Systems Science, Shandong University, Applied Mathematics, Ph.D.
- 1993.09-1996.07, Department of Mathematics, Shandong University, Operations Research and Control Theory, Master's degree
- 1989.09-1993.07, Department of Mathematics, Shandong University, Control Science, Bachelor's degree
Currently serving as the Executive Vice-President of the Zhongtai Securities Institute for Financial Studies of Shandong University
Selected for the 2011 Ministry of Education's New Century Excellent Talents Support Program
1. Machine Learning and Quantitative Finance
(1) Larry G. Epstein and Shaolin Ji, Optimal Learning Under Robustness and Time-Consistency, Operations Research, 70(3): 1317-1329, 2022.
(2) Shaolin Ji, Shige Peng, Ying Peng and Xichuan Zhang，Solving stochastic optimal control problem via stochastic maximum principle with deep learning method，Journal of scientific computing, 2023.
(3) Qiang Han and Shaolin Ji, Solving BSDEs based on novel multi-step schemes and multilevel Monte Carlo, Journal of Computational and Applied Mathematics (2023).
(4) Shaolin Ji, Shige Peng, Ying Peng, and Xichuan Zhang, Three Algorithms for Solving High-Dimensional Fully Coupled FBSDEs Through Deep Learning, IEEE Intelligent Systems, 35(3) May-June 1 (2020), 71-84.
2. Finance and Economics
(1) Larry G. Epstein and Shaolin Ji, Ambiguous Volatility and Asset Pricing in Continuous Time, The Review of Financial Studies, 26 (7): 1740-1786, 2013.
(2) Larry G. Epstein and Shaolin Ji, Ambiguous volatility, possibility and utility in continuous time, Journal of Mathematical Economics, 50: 269-282, 2014.
(3) Carole Bernard, Shaolin Ji and Weidong Tian, An optimal insurance design problem under Knightian uncertainty, Decisions in economics and finance, 36(2): 99-124, 2013.
(4) Shaolin ji, Li Li and Jianjun Miao, Dynamic Contracts with Learning Under Ambiguity, Preprint (download), 2016.
3. Backward Stochastic Differential Equations and Nonlinear Expectations
(1) Shaolin Ji and Shige Peng, Terminal perturbation method for the backward approach to continuous time mean-variance portfolio selection, Stochastic processes and their Applications, 118(6): 952-967, 2008.
(2) Shaolin Ji and Xun Yu Zhou, A generalized Neyman–Pearson lemma under g-probabilities, Probability theory and related fields, 148: 645-669, 2010.
(3) Mingshang Hu, Shaolin Ji, Shige Peng, Yongsheng Song, Backward stochastic differential equations driven by G-Brownian motion, Stochastic Processes and their Applications, 124(1): 759–784, 2014.
(4) Mingshang Hu, Shaolin Ji, Shige Peng, Yongsheng Song, Comparison theorem, Feynman–Kac formula and Girsanov transformation for BSDEs driven by G-Brownian motion, Stochastic Processes and their Applications, 124(2): 1170–1195, 2014.
4. Stochastic Optimization
(1) Mingshang Hu and Shaolin Ji Stochastic maximum principle for stochastic recursive optimal control problem under volatility uncertainty, SIAM Journal on Control and Optimization 54(2):918-945, 2016.
(2) Mingshang Hu, Shaolin Ji and Xiaole Xue, A Global stochastic maximum principle for fully coupled forward-backward stochastic systems, SIAM Journal on Control and Optimization 56(6): 4309-4335, 2018.
(3) Mingshang Hu, Shaolin Ji and Xiaole Xue, The Existence and Uniqueness of Viscosity Solution to a Kind of Hamilton–Jacobi–Bellman Equation. SIAM Journal on Control and Optimization 57 (2019), no. 6, 3911–3938.
(4) Ji, Shaolin; Kong, Chuiliu; Sun, Chuanfeng; A robust Kalman-Bucy filtering problem. Automatica 122 (2020).
(5) Shaolin Ji, Chuiliu Kong, Chuanfeng Sun and Jifeng Zhang, Kalman-Bucy filtering and minimum mean square estimator under uncertainty, SIAM Journal on Control and Optimization 59(4): 2669–2692, 2021.
(6) Mingshang Hu, Shaolin Ji, and Rundong Xu，A Global Stochastic Maximum Principle for Forward-Backward Stochastic Control Systems with Quadratic Generators，SIAM Journal on Control and Optimization，60(3)，2022.
(7) Shaolin Ji, and Rundong Xu，A Modified Method of Successive Approximations for Forward-Backward Stochastic Control Systems，SIAM Journal on Control and Optimization，2022.
(8) Shaolin Ji and Xun Yu Zhou, A maximum principle for stochastic optimal control with terminal state constraints, and its applications, A special issue dedicated Tyrone Duncan on the occation of his 65th birthday, Communications in Information and Systems, 6(4): 321-338, 2006.
(9) Mingshang Hu, Shaolin Ji and Shuzhen Yang A Stochastic Recursive Optimal Control Problem Under the G-expectation Framework，Applied Mathematics and Optimization, 70(2): 253-278, 2014.
(10) Mingshang Hu and Shaolin Ji, Dynamic programming principle for stochastic recursive optimal control problem driven by a G-Brownian motion, Stochastic Processes and their Applications 127 (2017) 107–1.
2009-2011: Dynamic Risk Management in Incomplete Markets (General Program of National Natural Science Foundation of China), Principal Investigator
2012—2014: Risk Measurement in Financial Markets (Ministry of Education's New Century Excellent Talents Support Program), Principal Investigator
2012—2015: G-Expectation Theory and Its Applications in Recursive Utility, Asset Pricing, and Dynamic Risk Management (General Program of National Natural Science Foundation of China), Principal Investigator
2016—2019: Robust Monetary Policy and Fiscal Policy Design based on Nonlinear Expectation Theory (General Program of National Natural Science Foundation of China), Principal Investigator
2020-2024: Study on Learning-based Robust Optimal Stopping Problems (General Program of National Natural Science Foundation of China), Principal Investigator
