- author = "Dario Bernardo and Hani Hagras and Edward Tsang",
- title = "An interval type-2 Fuzzy Logic based system for model generation and summarization of arbitrage opportunities in stock markets",
- booktitle = "12th UK Workshop on Computational Intelligence (UKCI 2012)",
- year = "2012",
-
DOI = "
doi:10.1109/UKCI.2012.6335765",
- abstract = "Today stock market exchange and finance are centres of attention all over the world. In finance, arbitrage is the practice of taking advantage of a price misalignment between two or more stock markets where profit can be earned by striking a combination of matching deals that capitalise upon the misalignment. If one strikes when misalignment has been observed, such deals are practically risk-free. However, when risk-free profit is around, everyone would compete to take advantage of it. Therefore, the question is whether arbitrage opportunities can be predicted; after all, misalignment does not happen instantaneously. Furthermore, financial operators do not like black boxes in forecasting. In this paper, we will present a type-2 Fuzzy Logic System (FLS) for the modelling and prediction of financial applications. The proposed system is capable of generating summarised models from pre-specified number of linguistic rules, which enables the user to understand the generated models for arbitrage opportunities prediction. The system is able to use this summarised model for the prediction of arbitrage opportunities in stock markets. We have performed several experiments based on the arbitrage data which is used in stock markets to spot ahead of time arbitrage opportunities. The proposed type-2 FLS has outperformed the Evolving Decision Rule (EDR) procedure (which is based on Genetic Programming (GP) and decision trees). Like GP, the type-2 FLS is capable of providing a white box model which could be easily understood and analysed by the lay user.",
- keywords = "genetic algorithms, genetic programming, fuzzy logic, pricing, profitability, risk management, stock markets, financial application modelling, financial application prediction, financial operators, interval type-2 fuzzy logic based system, linguistic rules, model generation, model summarisation, price misalignment, risk-free profit, stock market exchange, type-2 FLS, Finance, Firing, Fuzzy logic, Fuzzy sets, Predictive models, Stock markets, Uncertainty, Financial Applications, Type-2 Fuzzy logic Systems, arbitrage, prediction",
-
notes = "'We have compared the proposed approach with one of
the most powerful white box modeling and prediction
systems for spotting arbitrage opportunities which is
EDR procedure [31]. The EDR method evolves a set of
decision rules by using Genetic Programming (GP)'
'type-2 FLS' ' much better'
Also known as \cite{6335765}",
