000 03614nam a22004935i 4500
001 978-3-642-23336-4
003 DE-He213
005 20140220083301.0
007 cr nn 008mamaa
008 111013s2012 gw | s |||| 0|eng d
020 _a9783642233364
_9978-3-642-23336-4
024 7 _a10.1007/978-3-642-23336-4
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aBrabazon, Anthony.
_eeditor.
245 1 0 _aNatural Computing in Computational Finance
_h[electronic resource] :
_bVolume 4 /
_cedited by Anthony Brabazon, Michael O’Neill, Dietmar Maringer.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2012.
300 _aX, 202p. 62 illus., 25 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 _aStudies in Computational Intelligence,
_x1860-949X ;
_v380
505 0 _a1 Natural Computing in Computational Finance (Volume 4): Introduction -- 2 Calibrating Option Pricing Models with Heuristics -- 3 A Comparison Between Nature-Inspired and Machine Learning Approaches to Detecting Trend Reversals in Financial Time Series -- 4 A soft computing approach to enhanced indexation -- 5 Parallel Evolutionary Algorithms for Stock Market Trading Rule Selection on Many-Core Graphics Processors -- 6 Regime-Switching Recurrent Reinforcement Learning in Automated Trading -- 7 An Evolutionary Algorithmic Investigation of US Corporate Payout Policy Determination -- 8 Tackling Overfitting in Evolutionary-driven Financial Model Induction -- 9 An Order-Driven Agent-Based Artificial Stock Market to Analyze Liquidity Costs of Market Orders in the Taiwan Stock Market -- 10 Market Microstructure: A Self-Organizing Map Approach to Investigate Behavior Dynamics under an Evolutionary Environment.
520 _aThis book follows on from Natural Computing in Computational Finance  Volumes I, II and III.   As in the previous volumes of this series, the  book consists of a series of  chapters each of  which was selected following a rigorous, peer-reviewed, selection process.  The chapters illustrate the application of a range of cutting-edge natural  computing and agent-based methodologies in computational finance and economics.  The applications explored include  option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading,  corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation.  While describing cutting edge applications, the chapters are  written so that they are accessible to a wide audience. Hence, they should be of interest  to academics, students and practitioners in the fields of computational finance and  economics.  
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aManagement information systems.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aBusiness Information Systems.
700 1 _aO’Neill, Michael.
_eeditor.
700 1 _aMaringer, Dietmar.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642233357
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v380
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-23336-4
912 _aZDB-2-ENG
999 _c102156
_d102156