| Ambiguous volatility and asset pricing in continuous time LG Epstein, S Ji Review of Financial Studies 26 (7), 1740-1786, 2013 | 250 | 2013 |
| Ambiguous Volatility and Asset Pricing in Continuous Time LG Epstein, S Ji, MR Goetz, L Laeven, R Levine, G Jostova, S Nikolova, ... | 250* | |
| Backward stochastic differential equations driven by G-Brownian motion M Hu, S Ji, S Peng, Y Song Stochastic Processes and their Applications 124 (1), 759-784, 2014 | 189 | 2014 |
| Backward stochastic differential equations driven by G-Brownian motion,(2012) M Hu, S Ji, S Peng, Y Song arXiv preprint arXiv:1206.5889, 0 | 189* | |
| Ambiguous volatility, possibility and utility in continuous time LG Epstein, S Ji Journal of Mathematical Economics 50, 269-282, 2014 | 170 | 2014 |
| Comparison theorem, Feynman–Kac formula and Girsanov transformation for BSDEs driven by G-Brownian motion M Hu, S Ji, S Peng, Y Song Stochastic Processes and their Applications 124 (2), 1170-1195, 2014 | 165 | 2014 |
| A maximum principle for stochastic optimal control with terminal state constraints, and its applications S Ji, XY Zhou Communications in Information & Systems 6 (4), 321-338, 2006 | 112 | 2006 |
| Three algorithms for solving high-dimensional fully coupled fbsdes through deep learning S Ji, S Peng, Y Peng, X Zhang IEEE Intelligent Systems 35 (3), 71-84, 2020 | 61 | 2020 |
| A global stochastic maximum principle for fully coupled forward-backward stochastic systems M Hu, S Ji, X Xue SIAM Journal on Control and Optimization 56 (6), 4309-4335, 2018 | 59 | 2018 |
| Dynamic programming principle for stochastic recursive optimal control problem driven by a G-Brownian motion M Hu, S Ji Stochastic Processes and their Applications 127 (1), 107-134, 2017 | 36 | 2017 |
| Stochastic maximum principle for stochastic recursive optimal control problem under volatility ambiguity M Hu, S Ji arXiv preprint arXiv:1508.07693, 2015 | 33 | 2015 |
| A stochastic recursive optimal control problem under the G-expectation framework M Hu, S Ji, S Yang Applied Mathematics & Optimization 70 (2), 253-278, 2014 | 33 | 2014 |
| Terminal perturbation method for the backward approach to continuous time mean–variance portfolio selection S Ji, S Peng Stochastic Processes and their Applications 118 (6), 952-967, 2008 | 33 | 2008 |
| A generalized Neyman–Pearson lemma for g-probabilities S Ji, XY Zhou Probability theory and related fields 148 (3-4), 645-669, 2010 | 30 | 2010 |
| A maximum principle for fully coupled forward–backward stochastic control systems with terminal state constraints S Ji, Q Wei Journal of Mathematical Analysis and Applications 407 (2), 200-210, 2013 | 26 | 2013 |
| Sublinear Expectations and Martingales in discrete time S Cohen, S Ji, S Peng arXiv preprint arXiv:1104.5390, 2011 | 26 | 2011 |
| Optimal learning under robustness and time-consistency LG Epstein, S Ji Operations Research, 2020 | 19 | 2020 |
| Solving stochastic optimal control problem via stochastic maximum principle with deep learning method S Ji, S Peng, Y Peng, X Zhang arXiv preprint arXiv:2007.02227, 2020 | 18 | 2020 |
| The Existence and Uniqueness of Viscosity Solution to a Kind of Hamilton--Jacobi--Bellman Equation M Hu, S Ji, X Xue SIAM Journal on Control and Optimization 57 (6), 3911-3938, 2019 | 16 | 2019 |
| Maximum principle for stochastic optimal control problem of forward–backward stochastic difference systems S Ji, H Liu International Journal of Control, 1-14, 2021 | 15 | 2021 |
