000 02669nam a22005415i 4500
001 978-3-642-33110-7
003 DE-He213
005 20200420221302.0
007 cr nn 008mamaa
008 120928s2013 gw | s |||| 0|eng d
020 _a9783642331107
_9978-3-642-33110-7
024 7 _a10.1007/978-3-642-33110-7
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aCanelas, Ant�onio M.L.
_eauthor.
245 1 0 _aInvestment Strategies Optimization based on a SAX-GA Methodology
_h[electronic resource] /
_cby Ant�onio M.L. Canelas, Rui F.M.F. Neves, Nuno C.G. Horta.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _aXII, 81 p. 81 illus., 19 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Applied Sciences and Technology,
_x2191-530X
505 0 _aIntroduction -- Market Analysis Background and Related Work -- SAX-GA Approach -- Results -- Conclusions and Future Work.
520 _aThis book presents a new computational finance approach combining a Symbolic Aggregate approXimation (SAX) technique with an optimization kernel based on genetic algorithms (GA). While the SAX representation is used to describe the financial time series, the evolutionary optimization kernel is used in order to identify the most relevant patterns and generate investment rules. The proposed approach considers several different chromosomes structures in order to achieve better results on the trading platform The methodology presented in this book has great potential on investment markets.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aEconomics, Mathematical.
650 0 _aComputational intelligence.
650 0 _aMacroeconomics.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aMacroeconomics/Monetary Economics//Financial Economics.
650 2 4 _aQuantitative Finance.
700 1 _aNeves, Rui F.M.F.
_eauthor.
700 1 _aHorta, Nuno C.G.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642331091
830 0 _aSpringerBriefs in Applied Sciences and Technology,
_x2191-530X
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-33110-7
912 _aZDB-2-ENG
942 _cEBK
999 _c53229
_d53229