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020 _a9781447151555
_9978-1-4471-5155-5
024 7 _a10.1007/978-1-4471-5155-5
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aZheng, Xiaolian.
_eauthor.
245 1 0 _aStock Market Modeling and Forecasting
_h[electronic resource] :
_bA System Adaptation Approach /
_cby Xiaolian Zheng, Ben M. Chen.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2013.
300 _aXII, 161 p. 92 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Control and Information Sciences,
_x0170-8643 ;
_v442
505 0 _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.
520 _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.
650 0 _aEngineering.
650 0 _aFinance.
650 0 _aEconomics, Mathematical.
650 0 _aSystem theory.
650 0 _aControl engineering.
650 1 4 _aEngineering.
650 2 4 _aControl.
650 2 4 _aQuantitative Finance.
650 2 4 _aFinance, general.
650 2 4 _aSystems Theory, Control.
700 1 _aChen, Ben M.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781447151548
830 0 _aLecture Notes in Control and Information Sciences,
_x0170-8643 ;
_v442
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4471-5155-5
912 _aZDB-2-ENG
942 _2Dewey Decimal Classification
_ceBooks
999 _c43756
_d43756