000 05310nam a22006015i 4500
999 _c11770
_d11770
001 978-3-319-52866-3
003 DE-He213
005 20211210093138.0
008 170405s2017 gw | s |||| 0|eng d
020 _a9783319528663
040 _cAIKTC-KRRC
041 _aENG
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aRigatos, Gerasimos G.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aState-Space Approaches for Modelling and Control in Financial Engineering
_h[electronic resource] :
_bSystems theory and machine learning methods /
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXXVIII, 310 p. 114 illus., 88 illus. in color.
_bCard Paper
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v125
520 _aThe 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 _aMechanical Engineering
_94626
653 _aRisk Management, Complexity.
653 _aApplications of Nonlinear Dynamics and Chaos Theory.
653 _aElectronics and Microelectronics, Instrumentation.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319528656
776 0 8 _iPrinted edition:
_z9783319528670
776 0 8 _iPrinted edition:
_z9783319850047
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v125
856 4 0 _uhttps://doi.org/10.1007/978-3-319-52866-3
_zClick here to access eBook in Springer Nature platform. (Within Campus only.)
942 _cEBOOKS
_2ddc