An interval type-2 Fuzzy Logic based system for model generation and summarization of arbitrage opportunities in stock markets

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@InProceedings{Bernardo:2012:UKCI,
  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}",
}

Genetic Programming entries for Dario Bernardo Hani Hagras Edward P K Tsang

Citations