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Kategorie szczegółowe BISAC

Markov Decision Processes with Applications to Finance

ISBN-13: 9783642183232 / Angielski / Miękka / 2011 / 406 str.

Nicole Bauerle; Ulrich Rieder
Markov Decision Processes with Applications to Finance Nicole Bauerle Ulrich Rieder 9783642183232 Not Avail - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Markov Decision Processes with Applications to Finance

ISBN-13: 9783642183232 / Angielski / Miękka / 2011 / 406 str.

Nicole Bauerle; Ulrich Rieder
cena 281,76
(netto: 268,34 VAT:  5%)

Najniższa cena z 30 dni: 269,85
Termin realizacji zamówienia:
ok. 22 dni roboczych
Dostawa w 2026 r.

Darmowa dostawa!

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).

Kategorie:
Nauka, Matematyka
Kategorie BISAC:
Mathematics > Prawdopodobieństwo i statystyka
Mathematics > Matematyka stosowana
Business & Economics > Finance - General
Wydawca:
Not Avail
Seria wydawnicza:
Universitext
Język:
Angielski
ISBN-13:
9783642183232
Rok wydania:
2011
Numer serii:
000024642
Ilość stron:
406
Waga:
0.62 kg
Wymiary:
23.37 x 15.77 x 2.36
Oprawa:
Miękka
Wolumenów:
01
Dodatkowe informacje:
Bibliografia

From the reviews:

"This book presents Markov decision processes with general state and action spaces and includes various state-of-the-art applications that stem from finance and operations research. ... very helpful, not only for graduate students, but also for researchers working in the field of MDPs and finance. The authors do not focus only on discrete-time MDPs, but provide the description of different classes of Markov models ... . Each chapter ends with remarks, where the potential reader may find further hints concerning references." (Anna Jaskiewicz, Zentralblatt MATH, Vol. 1236, 2012)

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.

Nicole Bäuerle is full professor for Stochastics at the Karlsruhe Institute of Technology. Currently she is in the board of the Fachgruppe Stochastik and the DGVFM (Deutsche Gesellschaft für Versicherungs- und Finanzmathematik). She is editor of the journals "Stochastic Models" and "Mathematical Methods of Operations Research".

Ulrich Rieder is full professor for Optimization and Operations Research at the University of Ulm since 1980. He helped to establish a new program in applied mathematics at Ulm, called Wirtschaftsmathematik. From 1990-2008 he was editor-in-chief of "Mathematical Methods of Operations Research". He is editor of several journals in the areas of operations research and 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. 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).

 



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