Andrew Paskaramoorthy

According to our database, Andrew Paskaramoorthy authored at least 13 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Surrogate-assisted hyper-parameter search for portfolio optimisation: multi-period considerations.

Terence L. van Zyl, Matthew Woolway, Andrew Paskaramoorthy

Neural Comput. Appl., June, 2025

2023

Many learning agents interacting with an agent-based market model.

Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie

CoRR, 2023

2022

Volatility forecasting using Deep Learning and sentiment analysis.

V. Ncume, Terence L. van Zyl, Andrew Paskaramoorthy

CoRR, 2022

Pareto Driven Surrogate (ParDen-Sur) Assisted Optimisation of Multi-period Portfolio Backtest Simulations.

Terence L. van Zyl, Matthew Woolway, Andrew Paskaramoorthy

CoRR, 2022

Cryptocurrency Trading Agent Using Deep Reinforcement Learning.

Uwais Suliman, Terence L. van Zyl, Andrew Paskaramoorthy

Proceedings of the 9th International Conference on Soft Computing & Machine Intelligence, 2022

An Empirical Comparison of Cross-Validation Procedures for Portfolio Selection.

Andrew Paskaramoorthy, Terence L. van Zyl, Tim Gebbie

Proceedings of the IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, 2022

2021

AMA-K: Aggressive Multi-Temporal Allocation An Algorithm for Aggressive Online Portfolio Selection.

Matthew Kruger, Terence L. van Zyl, Andrew Paskaramoorthy

CoRR, 2021

ParDen: Surrogate Assisted Hyper-Parameter Optimisation for Portfolio Selection.

Terence L. van Zyl, Matthew Woolway, Andrew Paskaramoorthy

Proceedings of the 8th International Conference on Soft Computing & Machine Intelligence, 2021

MA-FDRNN: Multi-Asset Fuzzy Deep Recurrent Neural Network Reinforcement Learning for Portfolio Management.

Tarrin Skeepers, Terence L. van Zyl, Andrew Paskaramoorthy

Proceedings of the 8th International Conference on Soft Computing & Machine Intelligence, 2021

AMA-K: Aggressive Multi-temporal Allocation with K Experts for Online Portfolio Selection.

Matthew Kruger, Terence L. van Zyl, Andrew Paskaramoorthy

Proceedings of the 8th International Conference on Soft Computing & Machine Intelligence, 2021

The efficient frontiers of mean-variance portfolio rules under distribution misspecification.

Andrew Paskaramoorthy, Tim Gebbie, Terence L. van Zyl

Proceedings of the 24th IEEE International Conference on Information Fusion, 2021

Deep Learning for Financial Time Series Forecast Fusion and Optimal Portfolio Rebalancing.

Siddeeq Laher, Andrew Paskaramoorthy, Terence L. van Zyl

Proceedings of the 24th IEEE International Conference on Information Fusion, 2021

2020

DRICORN-K: A Dynamic RIsk CORrelation-driven Non-parametric Algorithm for Online Portfolio Selection.

Shivaar Sooklal, Terence L. van Zyl, Andrew Paskaramoorthy

Proceedings of the Artificial Intelligence Research, 2020