American-type options, Volume 1, Stochastic approximation methods:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin
De Gruyter
c2014
|
| Schriftenreihe: | De Gruyter studies in mathematics
56 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Print version cataloged as a monographic set by Library of Congress 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 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 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 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 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 |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9783110329827 3110329824 9783110329674 3110329670 |
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| 500 | |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 | ||
| 500 | |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 | ||
| 500 | |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 | ||
| 500 | |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 | ||
| 500 | |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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| author | Silʹvestrov, D. S., (Dmitriĭ Sergeevich) |
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| discipline | Wirtschaftswissenschaften |
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| spelling | Silʹvestrov, D. S., (Dmitriĭ Sergeevich) Verfasser aut American-type options, Volume 1, Stochastic approximation methods Dmitrii S. Silverstrov Stochastic approximation methods Berlin De Gruyter c2014 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier De Gruyter studies in mathematics 56 Print version cataloged as a monographic set by Library of Congress 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 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 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 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 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 BUSINESS & ECONOMICS / Finance bisacsh Markov processes fast Options (Finance) / Mathematical models fast Stochastic approximation fast Mathematisches Modell Wirtschaft Options (Finance) Mathematical models Stochastic approximation Markov processes http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=674415 Aggregator Volltext |
| spellingShingle | Silʹvestrov, D. S., (Dmitriĭ Sergeevich) American-type options, Volume 1, Stochastic approximation methods BUSINESS & ECONOMICS / Finance bisacsh Markov processes fast Options (Finance) / Mathematical models fast Stochastic approximation fast Mathematisches Modell Wirtschaft Options (Finance) Mathematical models Stochastic approximation Markov processes |
| title | American-type options, Volume 1, Stochastic approximation methods |
| title_alt | Stochastic approximation methods |
| title_auth | American-type options, Volume 1, Stochastic approximation methods |
| title_exact_search | American-type options, Volume 1, Stochastic approximation methods |
| title_full | American-type options, Volume 1, Stochastic approximation methods Dmitrii S. Silverstrov |
| title_fullStr | American-type options, Volume 1, Stochastic approximation methods Dmitrii S. Silverstrov |
| title_full_unstemmed | American-type options, Volume 1, Stochastic approximation methods Dmitrii S. Silverstrov |
| title_short | American-type options, Volume 1, Stochastic approximation methods |
| title_sort | american type options volume 1 stochastic approximation methods |
| topic | BUSINESS & ECONOMICS / Finance bisacsh Markov processes fast Options (Finance) / Mathematical models fast Stochastic approximation fast Mathematisches Modell Wirtschaft Options (Finance) Mathematical models Stochastic approximation Markov processes |
| topic_facet | BUSINESS & ECONOMICS / Finance Markov processes Options (Finance) / Mathematical models Stochastic approximation Mathematisches Modell Wirtschaft Options (Finance) Mathematical models |
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