| Time-consistent mean–variance portfolio optimization: A numerical impulse control approach PM Van Staden, DM Dang, PA Forsyth Insurance: Mathematics and Economics 83, 9-28, 2018 | 42 | 2018 |
| The surprising robustness of dynamic mean-variance portfolio optimization to model misspecification errors PM van Staden, DM Dang, PA Forsyth European Journal of Operational Research 289 (2), 774-792, 2021 | 40 | 2021 |
| On the distribution of terminal wealth under dynamic mean-variance optimal investment strategies PM van Staden, DM Dang, PA Forsyth SIAM Journal on Financial Mathematics 12 (2), 566-603, 2021 | 26 | 2021 |
| Mean-quadratic variation portfolio optimization: A desirable alternative to time-consistent mean-variance optimization? PM Van Staden, DM Dang, PA Forsyth SIAM Journal on Financial Mathematics 10 (3), 815-856, 2019 | 19 | 2019 |
| Beating a benchmark: dynamic programming may not be the right numerical approach PM Van Staden, PA Forsyth, Y Li SIAM Journal on Financial Mathematics 14 (2), 407-451, 2023 | 11 | 2023 |
| Across-time risk-aware strategies for outperforming a benchmark PM van Staden, PA Forsyth, Y Li European Journal of Operational Research 313 (2), 776-800, 2024 | 6 | 2024 |
| Beating a constant weight benchmark: easier done than said PA Forsyth, PM Van Staden, Y Li International Journal of Theoretical and Applied Finance (IJTAF) 26 (04n05 …, 2023 | 4 | 2023 |
| A parsimonious neural network approach to solve portfolio optimization problems without using dynamic programming PM van Staden, PA Forsyth, Y Li arXiv preprint arXiv:2303.08968, 2023 | 3 | 2023 |
| Practical Investment Consequences Of The Scalarization Parameter Formulation In Dynamic Mean–Variance Portfolio Optimization PM Van Staden, DM Dang, PA Forsyth International Journal of Theoretical and Applied Finance 24 (05), 2150029, 2021 | 1 | 2021 |
| A data-driven neural network approach to dynamic factor investing PM van Staden, PA Forsyth, Y Li Working paper, University of Waterloo, 2021. Available at https://cs …, 0 | 1 | |
| A parsimonious neural network approach portfolio optimization PM van Staden, PA Forsyth, Y Li | | 2023 |
| A parsimonious neural network approach to solve portfolio PM van Staden, PA Forsyth, Y Li | | 2023 |
| Beating a benchmark: dynamic programming may not be the right PM van Staden, PA Forsyth, Y Li | | 2022 |
| Dynamic optimal investment strategies for benchmark PM van Staden, PA Forsyth, Y Li | | 2022 |
| Practical investment consequences of the scalarization parameter PM van Staden, DM Dang, PA Forsyth | | 2021 |
| Wealth-dependent risk-aversion in dynamic mean-variance portfolio PM van Staden, DM Dang, PA Forsyth | | 2020 |
| Numerical methods for mean-risk portfolio optimization PM Van Staden | | 2020 |
| On the distribution of terminal wealth under dynamic mean-variance PM van Staden, DM Dang, PA Forsyth | | 2019 |
| Mean-Quadratic Variation Portfolio Optimization: A desirable PM van Staden, DM Dang, PA Forsyth | | |
| Time-consistent mean-variance portfolio optimization: a numerical P Van Staden, DM Dang, PA Forsyth | | |
Peter ForsythDistinguished Professor Emeritus, Cheriton School of Computer Science, University of WaterlooVerified email at uwaterloo.ca
