Research Repository

A dynamic fuzzy money management approach for controlling the intraday risk-adjusted performance of ai trading algorithms

Vella, Vince and Ng, Wing Lon (2014) 'A dynamic fuzzy money management approach for controlling the intraday risk-adjusted performance of ai trading algorithms.' Intelligent Systems in Accounting, Finance and Management. ISSN 1055-615X

Full text not available from this repository.

Abstract

The majority of existing artificial intelligence (AI) studies in computational finance literature are devoted solely to predicting market movements. In this paper we shift the attention to how AI can be applied to control risk-based money management decisions. We propose an innovative fuzzy logic approach which identifies and categorizes technical rules performance across different regions in the trend and volatility space. The model dynamically prioritizes higher performing regions at an intraday level and adapts money management policies with the objective to maximize global risk-adjusted performance. By adopting a hybrid method in conjunction with a popular neural network (NN) trend prediction model, our results show significant performance improvements compared with both standard NN and buy-and-hold approaches.

Item Type: Article
Subjects: H Social Sciences > HG Finance
Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of > Centre for Computational Finance and Economic Agents
Depositing User: Jim Jamieson
Date Deposited: 18 May 2015 12:58
Last Modified: 18 May 2015 12:58
URI: http://repository.essex.ac.uk/id/eprint/13716

Actions (login required)

View Item View Item