MARC 主機 00000nam a2200517 i 4500 
001    978-3-319-52866-3 
003    DE-He213 
005    20171103154401.0 
006    m     o  d         
007    cr nn 008maaau 
008    170405s2017    gw      s         0 eng d 
020    9783319528663|q(electronic bk.) 
020    9783319528656|q(paper) 
024 7  10.1007/978-3-319-52866-3|2doi 
040    GP|cGP|erda|dAS 
041 0  eng 
050  4 HG176.7 
082 04 658.15|223 
100 1  Rigatos, Gerasimos G.,|eauthor 
245 10 State-space approaches for modelling and control in 
       financial engineering :|bsystems theory and machine 
       learning methods /|cby Gerasimos G. Rigatos 
264  1 Cham :|bSpringer International Publishing :|bImprint: 
       Springer,|c2017 
300    1 online resource (xxviii, 310 pages) :|billustrations 
       (some color), digital ;|c24 cm 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file|bPDF|2rda 
490 1  Intelligent systems reference library,|x1868-4394 ;
       |vvolume 125 
520    The book conclusively solves problems associated with the 
       control and estimation of nonlinear and chaotic dynamics 
       in financial systems when these are described in the form 
       of nonlinear ordinary differential equations. It then 
       addresses problems associated with the control and 
       estimation of financial systems governed by partial 
       differential equations (e.g. the Black-Scholes partial 
       differential equation (PDE) and its variants) Lastly it an
       offers optimal solution to the problem of statistical 
       validation of computational models and tools used to 
       support financial engineers in decision making. The 
       application of state-space models in financial engineering
       means that the heuristics and empirical methods currently 
       in use in decision-making procedures for finance can be 
       eliminated. It also allows methods of fault-free 
       performance and optimality in the management of assets and
       capitals and methods assuring stability in the functioning
       of financial systems to be established. Covering the 
       following key areas of financial engineering: (i) control 
       and stabilization of financial systems dynamics, (ii) 
       state estimation and forecasting, and (iii) statistical 
       validation of decision-making tools, the book can be used 
       for teaching undergraduate or postgraduate courses in 
       financial engineering. It is also a useful resource for 
       the engineering and computer science community 
650  0 Financial engineering|xMathematics 
650  0 Finance|xDecision making 
650  0 Kalman filtering 
650 14 Engineering 
650 24 Computational Intelligence 
650 24 Risk Management 
650 24 Applications of Nonlinear Dynamics and Chaos Theory 
650 24 Control 
650 24 Complexity 
650 24 Electronics and Microelectronics, Instrumentation 
710 2  SpringerLink (Online service) 
773 0  |tSpringer eBooks 
830  0 Intelligent systems reference library ;|vvolume 125 
856 40 |uhttp://dx.doi.org/10.1007/978-3-319-52866-3
       |zeBook(Springerlink)