Markov Decision Processes with Applications to Finance

The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research....

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Bäuerle, Nicole (Συγγραφέας), Rieder, Ulrich (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
Σειρά:Universitext,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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020 |a 9783642183249  |9 978-3-642-18324-9 
024 7 |a 10.1007/978-3-642-18324-9  |2 doi 
040 |d GrThAP 
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050 4 |a QA274-274.9 
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100 1 |a Bäuerle, Nicole.  |e author. 
245 1 0 |a Markov Decision Processes with Applications to Finance  |h [electronic resource] /  |c by Nicole Bäuerle, Ulrich Rieder. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2011. 
300 |a XVI, 388 p. 24 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Universitext,  |x 0172-5939 
505 0 |a Preface -- 1.Introduction and First Examples -- Part I Finite Horizon Optimization Problems and Financial Markets -- 2.Theory of Finite Horizon Markov Decision Processes -- 3.The Financial Markets -- 4.Financial Optimization Problems -- Part II Partially Observable Markov Decision Problems -- 5.Partially Observable Markov Decision Processes -- 6.Partially Observable Markov Decision Problems in Finance -- Part III Infinite Horizon Optimization Problems -- 7.Theory of Infinite Horizon Markov Decision Processes -- 8.Piecewise Deterministic Markov Decision Processes -- 9.Optimization Problems in Finance and Insurance -- Part IV Stopping Problems -- 10.Theory of Optimal Stopping Problems -- 11.Stopping Problems in Finance -- Part V Appendix -- A.Tools from Analysis -- B.Tools from Probability -- C.Tools from Mathematical Finance -- References -- Index. 
520 |a The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers  in both applied probability and finance, and provides exercises (without solutions).  . 
650 0 |a Mathematics. 
650 0 |a Applied mathematics. 
650 0 |a Engineering mathematics. 
650 0 |a Economics, Mathematical. 
650 0 |a Probabilities. 
650 1 4 |a Mathematics. 
650 2 4 |a Probability Theory and Stochastic Processes. 
650 2 4 |a Quantitative Finance. 
650 2 4 |a Applications of Mathematics. 
700 1 |a Rieder, Ulrich.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642183232 
830 0 |a Universitext,  |x 0172-5939 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-18324-9  |z Full Text via HEAL-Link 
912 |a ZDB-2-SMA 
950 |a Mathematics and Statistics (Springer-11649)