14 citations · 25 across the 8 of their papers we have counts for
8 papers
The bias of IID resampled backtests for rolling-window mean-variance portfolios
Andrew Paskaramoorthy, Terence van Zyl, Tim Gebbie
Backtests on historical data are the basis for practical evaluations of portfolio selection rules, but their reliability is often limited by reliance on a single sample path. This…
Many learning agents interacting with an agent-based market model
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
We consider the dynamics and the interactions of multiple reinforcement learning optimal execution trading agents interacting with a reactive Agent-Based Model (ABM) of a financial…
Volatility forecasting using Deep Learning and sentiment analysis
V Ncume, T. L van Zyl, A Paskaramoorthy
Several studies have shown that deep learning models can provide more accurate volatility forecasts than the traditional methods used within this domain. This paper presents a comp…
Pareto Driven Surrogate (ParDen-Sur) Assisted Optimisation of Multi-period Portfolio Backtest Simulations
Terence L. van Zyl, Matthew Woolway, Andrew Paskaramoorthy
Portfolio management is a multi-period multi-objective optimisation problem subject to a wide range of constraints. However, in practice, portfolio management is treated as a singl…
AMA-K: Aggressive Multi-Temporal Allocation An Algorithm for Aggressive Online Portfolio Selection
Matthew Kruger, Terence L. van Zyl, Andrew Paskaramoorthy
Online portfolio selection is an integral componentof wealth management. The fundamental undertaking is tomaximise returns while minimising risk given investor con-straints. We aim…
ParDen: Surrogate Assisted Hyper-Parameter Optimisation for Portfolio Selection
Terence van Zyl, Matthew Woolway, Andrew Paskaramoorthy
Portfolio optimisation is a multi-objective optimisation problem (MOP), where an investor aims to optimise the conflicting criteria of maximising a portfolio's expected return whil…
The efficient frontiers of mean-variance portfolio rules under distribution misspecification
Andrew Paskaramoorthy, Tim Gebbie, Terence van Zyl
Mean-variance portfolio decisions that combine prediction and optimisation have been shown to have poor empirical performance. Here, we consider the performance of various shrinkag…
A Framework for Online Investment Algorithms
Andrew Paskaramoorthy, Terence van Zyl, Tim Gebbie
The artificial segmentation of an investment management process into a workflow with silos of offline human operators can restrict silos from collectively and adaptively pursuing a…