02788nam 2200673 a 450 991043805890332120200520144314.0978128390903712839090309783642331107364233110610.1007/978-3-642-33110-7(CKB)3400000000086050(EBL)1082649(OCoLC)812289658(SSID)ssj0000767069(PQKBManifestationID)11421292(PQKBTitleCode)TC0000767069(PQKBWorkID)10732972(PQKB)10844750(DE-He213)978-3-642-33110-7(MiAaPQ)EBC1082649(PPN)168323559(EXLCZ)99340000000008605020120810d2013 uy 0engur|n|---|||||txtccrInvestment strategies optimization based on a SAX-GA methodology /Antonio M.L. Canelas, Rui F.M.F. Neves, Nuno C.G. Horta1st ed. 2013.New York Springer20131 online resource (89 p.)SpringerBriefs in applied sciences and technology.Computational intelligenceDescription based upon print version of record.9783642331091 3642331092 Includes bibliographical references.Introduction -- Market Analysis Background and Related Work -- SAX-GA Approach -- Results -- Conclusions and Future Work.This 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.SpringerBriefs in Computational Intelligence,2625-3704Portfolio managementInvestmentsGenetic algorithmsPortfolio management.Investments.Genetic algorithms.332.60285Canelas AntonioM.L.1060091Neves Rui F. M. F1756700Horta Nuno C. G1756701MiAaPQMiAaPQMiAaPQBOOK9910438058903321Investment strategies optimization based on a SAX-GA methodology4194143UNINA