Abstract
In this chapter an innovative methodology for pattern discovery in financial time series will be presented. The combination of SAX representation method with the use of GA to optimize the search and creation of new investment strategies will be explored. Taking advantage of the symbolic representation and dimensional reduction provided by SAX, several financial time series will be analyzed in order to search for meaningful patterns to reveal periods of time to invest on the stock market. The search and investment criteria will be defined and optimized by the use of GA, several chromosomes structures were considered in order to provide more accurate results. Basically two approaches will be presented, a first one will try to discover patterns that indicate a bull market condition, in order to invest long; another approach will combine the previous one with the detection of patterns signaling a bear market, to invest short and long. These two approaches will be investigated and compared in the results section.
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Canelas, A.M.L., Neves, R.F.M.F., Horta, N.C.G. (2013). SAX-GA Approach. In: Investment Strategies Optimization based on a SAX-GA Methodology. SpringerBriefs in Applied Sciences and Technology(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33110-7_3
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DOI: https://doi.org/10.1007/978-3-642-33110-7_3
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