| A framework for online investment decisions AB Paskaramoorthy, TJ Gebbie, TL van Zyl Investment Analysts Journal 49 (3), 215-231, 2020 | 18 | 2020 |
| Parden: Surrogate assisted hyper-parameter optimisation for portfolio selection TL van Zyl, M Woolway, A Paskaramoorthy 2021 8th international conference on soft computing & machine intelligence …, 2021 | 13 | 2021 |
| Deep learning for financial time series forecast fusion and optimal portfolio rebalancing S Laher, A Paskaramoorthy, TL Van Zyl 2021 IEEE 24th International Conference on Information Fusion (FUSION), 1-8, 2021 | 11 | 2021 |
| Dricorn-k: A dynamic risk correlation-driven non-parametric algorithm for online portfolio selection S Sooklal, TL van Zyl, A Paskaramoorthy Southern African Conference for Artificial Intelligence Research, 183-196, 2020 | 9 | 2020 |
| Cryptocurrency Trading Agent Using Deep Reinforcement Learning U Suliman, TL van Zyl, A Paskaramoorthy 2022 9th International Conference on Soft Computing & Machine Intelligence …, 2022 | 6 | 2022 |
| An empirical evaluation of sensitivity bounds for mean-variance portfolio optimisation A Paskaramoorthy, M Woolway Finance Research Letters 44, 102065, 2022 | 5 | 2022 |
| MA-FDRNN: Multi-asset fuzzy deep recurrent neural network reinforcement learning for portfolio management T Skeepers, TL van Zyl, A Paskaramoorthy 2021 8th International Conference on Soft Computing & Machine Intelligence …, 2021 | 5 | 2021 |
| A simple learning agent interacting with an agent-based market model M Dicks, A Paskaramoorthy, T Gebbie Physica A: Statistical Mechanics and its Applications 633, 129363, 2024 | 4 | 2024 |
| The efficient frontiers of mean-variance portfolio rules under distribution misspecification A Paskaramoorthy, T Gebbie, TL Van Zyl 2021 IEEE 24th International Conference on Information Fusion (FUSION), 1-8, 2021 | 4 | 2021 |
| AMA-K: Aggressive multi-temporal allocation with K experts for online portfolio selection M Kruger, TL van Zyl, A Paskaramoorthy 2021 8th International Conference on Soft Computing & Machine Intelligence …, 2021 | 2 | 2021 |
| Many learning agents interacting with an agent-based market model M Dicks, A Paskaramoorthy, T Gebbie arXiv preprint arXiv:2303.07393, 2023 | 1 | 2023 |
| Volatility forecasting using Deep Learning and sentiment analysis V Ncume, TL van Zyl, A Paskaramoorthy arXiv preprint arXiv:2210.12464, 2022 | 1 | 2022 |
| An Empirical Comparison of Cross-Validation Procedures for Portfolio Selection A Paskaramoorthy, TL van Zyl, T Gebbie 2022 IEEE Symposium on Computational Intelligence for Financial Engineering …, 2022 | 1 | 2022 |
| Surrogate-assisted hyper-parameter search for portfolio optimisation: multi-period considerations TL van Zyl, M Woolway, A Paskaramoorthy Neural Computing and Applications, 1-18, 2023 | | 2023 |
| Pareto Driven Surrogate (Par Den-Sur) Assisted Optimisation of Multi-period Portfolio Backtest Simulations T van Zyl, M Woolway, A Paskaramoorthy Authorea Preprints, 2023 | | 2023 |
| Sector exposures in factor portfolios: Why neutralise when you can optimise? A Paskaramoorthy, E Flint Investment Analysts Journal 52 (3), 259-280, 2023 | | 2023 |
| Pareto Driven Surrogate (ParDen-Sur) Assisted Optimisation of Multi-period Portfolio Backtest Simulations TL van Zyl, M Woolway, A Paskaramoorthy arXiv preprint arXiv:2209.13528, 2022 | | 2022 |
| An Algorithmic Approach to Investment AB PASKARAMOORTHY School of Computer Science and Applied Mathematics, University of the …, 2019 | | 2019 |
| Many Learning Agents Interacting with an Agent-Based Market Model A Paskaramoorthy, T Gebbie | | |
| A Simple Learning Agent Interacting with an Agent-Based Market Model A Paskaramoorthy, T Gebbie | | |
