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131214s2014 gw o 000 0 eng d |
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|a HG6024.A3
|b S55 2014 vol. 1
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|x 027000
|2 bisacsh
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|a 332.64/53
|2 23
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|a UAMI
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100 |
1 |
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|a Silʹvestrov, D. S.
|q (Dmitriĭ Sergeevich)
|1 https://id.oclc.org/worldcat/entity/E39PBJdrMrc6RKJV7VyYDWvmBP
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245 |
1 |
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|a American-type options.
|n Vol. 1,
|p Stochastic approximation methods /
|c Dmitrii S. Silverstrov.
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246 |
3 |
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|a Stochastic approximation methods
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260 |
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|a Berlin ;
|a Boston :
|b De Gruyter,
|c ©2014.
|
300 |
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|a 1 online resource
|
336 |
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|a text
|b txt
|2 rdacontent
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337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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490 |
1 |
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|a De Gruyter studies in mathematics ;
|v v. 56
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500 |
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|a Print version cataloged as a monographic set by Library of Congress.
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588 |
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|a Online resource; title from digital title page (viewed on Jan. 15, 2014).
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|a Preface; 1 Multivariate modulated Markov log-price processes (LPP); 1.1 Markov LPP; 1.2 LPP represented by random walks; 1.3 Autoregressive LPP; 1.4 Autoregressive stochastic volatility LPP; 2 American-type options; 2.1 American-type options; 2.2 Pay-off functions; 2.3 Reward and log-reward functions; 2.4 Optimal stopping times; 2.5 American-type knockout options; 3 Backward recurrence reward algorithms; 3.1 Binomial tree reward algorithms; 3.2 Trinomial tree reward algorithms; 3.3 Random walk reward algorithms; 3.4 Markov chain reward algorithms; 4 Upper bounds for option rewards.
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|a 4.1 Markov LPP with bounded characteristics4.2 LPP represented by random walks; 4.3 Markov LPP with unbounded characteristics; 4.4 Univariate Markov Gaussian LPP; 4.5 Multivariate modulated Markov Gaussian LPP; 5 Convergence of option rewards -- I; 5.1 Asymptotically uniform upper bounds for rewards -- I; 5.2 Modulated Markov LPP with bounded characteristics; 5.3 LPP represented by modulated random walks; 6 Convergence of option rewards -- II; 6.1 Asymptotically uniform upper bounds for rewards -- II; 6.2 Univariate modulated LPP with unbounded characteristics.
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|a 6.3 Asymptotically uniform upper bounds for rewards -- III6.4 Multivariate modulated LPP with unbounded characteristics; 6.5 Conditions of convergence for Markov price processes; 7 Space-skeleton reward approximations; 7.1 Atomic approximation models; 7.2 Univariate Markov LPP with bounded characteristics; 7.3 MultivariateMarkov LPP with bounded characteristics; 7.4 LPP represented by multivariate modulated random walks; 7.5 MultivariateMarkov LPP with unbounded characteristics; 8 Convergence of rewards for Markov Gaussian LPP; 8.1 Univariate Markov Gaussian LPP.
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|a 8.2 Multivariate modulated Markov Gaussian LPP8.3 Markov Gaussian LPP with estimated characteristics; 8.4 Skeleton reward approximations for Markov Gaussian LPP; 8.5 LPP represented by Gaussian random walks; 9 Tree-type approximations for Markov Gaussian LPP; 9.1 Univariate binomial tree approximations; 9.2 Multivariate binomial tree approximations; 9.3 Multivariate trinomial tree approximations; 9.4 Inhomogeneous in space binomial approximations; 9.5 Inhomogeneous in time and space trinomial approximations; 10 Convergence of tree-type reward approximations.
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|a 10.1 Univariate binomial tree approximation models10.2 Multivariate homogeneous in space tree models; 10.3 Univariate inhomogeneous in space tree models; 10.4 Multivariate inhomogeneous in space tree models; Bibliographical Remarks; Bibliography; Index.
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|a This book gives a systematical presentation of stochastic approximation methods for models of American-type options with general pay-off functions for discrete time Markov price processes. It is the first volume of the comprehensive two volumes monograph.
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590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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650 |
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|a Options (Finance)
|x Mathematical models.
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650 |
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|a Stochastic approximation.
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650 |
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|a Markov processes.
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650 |
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|a Markov Chains
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650 |
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|a Options (Finances)
|x Modèles mathématiques.
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650 |
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|a Approximation stochastique.
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650 |
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6 |
|a Processus de Markov.
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650 |
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7 |
|a Markov processes
|2 fast
|
650 |
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|a Options (Finance)
|x Mathematical models
|2 fast
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7 |
|a Stochastic approximation
|2 fast
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653 |
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|a American Option.
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653 |
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|a Approximation Algorithm.
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|a Convergence of Rewards.
|
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|a Markov Chain.
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|a Optimal Stopping.
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758 |
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|i has work:
|a American-type options (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGG8j7qxRcBfVHW3V9Gcrm
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
776 |
0 |
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|i Print version:
|a Silvestrov, Dmitrii S.
|t American-Type Options : Stochastic Approximation Methods, Volume 1.
|d Berlin : De Gruyter, ©2013
|z 9783110329674
|
830 |
|
0 |
|a De Gruyter studies in mathematics ;
|v 56.
|
856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1575440
|z Texto completo
|
938 |
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|a ProQuest Ebook Central
|b EBLB
|n EBL1575440
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|a YBP Library Services
|b YANK
|n 10818878
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