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Improving Risk-adjusted Performance in High Frequency Trading Using Interval Type-2 Fuzzy Logic

Vella, Vince and Ng, Wing Lon (2016) 'Improving Risk-adjusted Performance in High Frequency Trading Using Interval Type-2 Fuzzy Logic.' Expert Systems with Applications, 55. pp. 70-86. ISSN 0957-4174

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Abstract

In this paper, we investigate the ability of higher order fuzzy systems to handle increased uncertainty, mostly induced by the market microstructure noise inherent in a high frequency trading (HFT) scenario. Whilst many former studies comparing type-1 and type-2 Fuzzy Logic Systems (FLSs) focus on error reduction or market direction accuracy, our interest is predominantly risk-adjusted performance and more in line with both trading practitioners and upcoming regulatory regimes. We propose an innovative approach to design an interval type-2 model which is based on a generalisation of the popular type-1 ANFIS model. The significance of this work stems from the contributions as a result of introducing type-2 fuzzy sets in intelligent trading algorithms, with the objective to improve the risk-adjusted performance with minimal increase in the design and computational complexity. Overall, the proposed ANFIS/T2 model scores significant performance improvements when compared to both standard ANFIS and Buy-and-Hold methods. As a further step, we identify a relationship between the increased trading performance benefits of the proposed type-2 model and higher levels of microstructure noise. The results resolve a desirable need for practitioners, researchers and regulators in the design of expert and intelligent systems for better management of risk in the field of HFT.

Item Type: Article
Uncontrolled Keywords: High-Frequency Trading; ANFIS; Type-2 Fuzzy Logic; ANFIS/T2
Subjects: H Social Sciences > HG Finance
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
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: 12 Feb 2016 16:06
Last Modified: 12 Feb 2017 02:00
URI: http://repository.essex.ac.uk/id/eprint/16066

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