Investment portfolio trading based on Markov chain and fuzzy logic

dc.contributor.authorRuiz-Cruz, Riemann
dc.contributor.authorDíaz-González, Armando D.
dc.date.accessioned2019-06-11T21:01:23Z
dc.date.available2019-06-11T21:01:23Z
dc.date.issued2018-10
dc.descriptionIn the present paper, a trading strategy is proposed for a portfolio composed of shares in the stock exchange. The proposed strategy is based mainly on three blocks: 1) a K-means clustering algorithm is used to determine and learn the internal hidden patterns in the time series of stock market prices, 2) a pattern predictor is performed based on a simple Markov chain, and 3) a fuzzy inference system take the decision to trade based on the estimation. The fuzzy inference system is composed of the rules provided by an expert trader. The performance of the trading algorithm is validated through simulations using real prices of the Mexican stock exchange.es
dc.identifier.citationR. Ruiz-Cruz and A. D. Díaz-González (2018). Investment Portfolio Trading based on Markov Chain and Fuzzy Logic, 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI), Gudalajara, Mexico.es
dc.identifier.isbn978-1-5386-4626-7
dc.identifier.urihttp://hdl.handle.net/11117/5887
dc.language.isoenges
dc.publisherIEEEes
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes
dc.subjectTrading Algorithmes
dc.subjectMarkov Chaines
dc.subjectFuzzy Logices
dc.titleInvestment portfolio trading based on Markov chain and fuzzy logices
dc.typeinfo:eu-repo/semantics/conferencePaperes
rei.peerreviewedYeses
rei.revisor2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI)

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