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Technical market indicators optimization using evolutionary algorithms

dc.contributor.authorFernández, Pablo
dc.contributor.authorSoltero, Francisco José
dc.contributor.authorHidalgo, José Ignacio
dc.date.accessioned2024-01-25T12:59:16Z
dc.date.available2024-01-25T12:59:16Z
dc.date.issued2008-07-12
dc.identifier.citation10.1145/1388969.1388989es
dc.identifier.isbn9781605581316
dc.identifier.urihttps://hdl.handle.net/10115/28914
dc.description.abstractReal world stock markets predictions such as stock prices, unpredictability, and stock selection for portfolios, are challenging problems. Technical indicators are applied to interpret stock market trending and investing decision. The main difficulty of an indicator usage is deciding its appropriate parameter values, as number of days of the periods or quantity and kind of indicators. Each stock index, price or volatility series is different among the rest. In this work, Evolutionary Algorithms are proposed to discover correct indicator parameters in trading. In order to check this proposal the Moving Average Convergence-Divergence (MACD) technical indicator has been selected. Preliminary results show that this technique could work well on stock index trending. Indexes are smoother and easier to predict than stock prices. Required future works should include several indicators and additional parameters.es
dc.language.isoenges
dc.publisherAssociation for Computing Machinery New York, NY, United Stateses
dc.subjectalgoritmos evolutivos, mercados financieroses
dc.titleTechnical market indicators optimization using evolutionary algorithmses
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.1145/1388969.1388989es
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses


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