LEADER 04429nam 22007215 450 001 9910437909703321 005 20200630231704.0 010 $a9781447151555 010 $a1447151550 024 7 $a10.1007/978-1-4471-5155-5 035 $a(CKB)3390000000037132 035 $a(SSID)ssj0000880237 035 $a(PQKBManifestationID)11956626 035 $a(PQKBTitleCode)TC0000880237 035 $a(PQKBWorkID)10895108 035 $a(PQKB)10036309 035 $a(DE-He213)978-1-4471-5155-5 035 $a(MiAaPQ)EBC3096957 035 $a(PPN)169135497 035 $a(EXLCZ)993390000000037132 100 $a20130406d2013 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aStock Market Modeling and Forecasting $eA System Adaptation Approach /$fby Xiaolian Zheng, Ben M. Chen 205 $a1st ed. 2013. 210 1$aLondon :$cSpringer London :$cImprint: Springer,$d2013. 215 $a1 online resource (XII, 161 p. 92 illus.) 225 1 $aLecture Notes in Control and Information Sciences,$x0170-8643 ;$v442 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9781447151548 311 08$a1447151542 327 $aA System Adaptation Framework -- Market Input Analysis -- Analysis of Dow Jones Industrial Average -- Selected Asian Markets -- Forecasting of Market Major Turning Periods -- Technical Analysis Toolkit -- Further Research. 330 $aStock Market Modeling translates experience in system adaptation gained in an engineering context to the modeling of financial markets with a view to improving the capture and understanding of market dynamics. The modeling process is considered as identifying a dynamic system in which a real stock market is treated as an unknown plant and the identification model proposed is tuned by feedback of the matching error. Like a physical system, a stock market exhibits fast and slow dynamics corresponding to internal (such as company value and profitability) and external forces (such as investor sentiment and commodity prices) respectively. The framework presented here, consisting of an internal model and an adaptive filter, is successful at considering both fast and slow market dynamics. A double selection method is efficacious in identifying input factors influential in market movements, revealing them to be both frequency- and market-dependent.   The authors present work on both developed and developing markets in the shape of the US, Hong Kong, Chinese and Singaporean stock markets. Results from all these sources demonstrate the efficiency of the model framework in identifying significant influences and the quality of its predictive ability; promising results are also obtained by applying the model framework to the forecasting of major market-turning periods. Having shown that system-theoretic ideas can form the core of a novel and effective basis for stock market analysis, the book is completed by an indication of possible and likely future expansions of the research in this area. 410 0$aLecture Notes in Control and Information Sciences,$x0170-8643 ;$v442 606 $aAutomatic control 606 $aEconomics, Mathematical 606 $aFinance 606 $aSystem theory 606 $aControl and Systems Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/T19010 606 $aQuantitative Finance$3https://scigraph.springernature.com/ontologies/product-market-codes/M13062 606 $aFinance, general$3https://scigraph.springernature.com/ontologies/product-market-codes/600000 606 $aSystems Theory, Control$3https://scigraph.springernature.com/ontologies/product-market-codes/M13070 615 0$aAutomatic control. 615 0$aEconomics, Mathematical. 615 0$aFinance. 615 0$aSystem theory. 615 14$aControl and Systems Theory. 615 24$aQuantitative Finance. 615 24$aFinance, general. 615 24$aSystems Theory, Control. 676 $a332.0415 700 $aZheng$b Xiaolian$4aut$4http://id.loc.gov/vocabulary/relators/aut$01059612 702 $aChen$b Ben M$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437909703321 996 $aStock Market Modeling and Forecasting$92507361 997 $aUNINA