American-Type Options : Stochastic Approximation Methods, Volume 2

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Year of publication:	2014
Authors:	Silvestrov, Dmitrii S
Publisher:	Berlin/Boston : De Gruyter, Inc.
Subject:	Theorie \| Theory \| Iteratives Verfahren \| Approximation method \| Optionsgeschäft \| Option trading \| Markov-Kette \| Markov chain \| Börsenkurs \| Share price \| Stochastischer Prozess \| Stochastic process
Description of contents:	Description [zbmath.org]

Extent:	1 online resource (559 pages)
Series:	De Gruyter Studies in Mathematics Ser ; v.57 De Gruyter Studies in Mathematics ; Volume 57
Type of publication:	Book / Working Paper
Language:	English
Notes:	Description based on publisher supplied metadata and other sources. Preface; Contents; 1 Reward approximations for autoregressive log-price processes (LPP); 1.1 Markov Gaussian LPP; 1.2 Autoregressive LPP; 1.3 Autoregressive moving average LPP; 1.4 Modulated Markov Gaussian LPP; 1.5 Modulated autoregressive LPP; 1.6 Modulated autoregressive moving average LPP; 2 Reward approximations for autoregressive stochastic volatility LPP; 2.1 Nonlinear autoregressive stochastic volatility LPP; 2.2 Autoregressive conditional heteroskedastic LPP; 2.3 Generalized autoregressive conditional heteroskedastic LPP 2.4 Modulated nonlinear autoregressive stochastic volatility LPP2.5 Modulated autoregressive conditional heteroskedastic LPP; 2.6 Modulated generalized autoregressive conditional heteroskedastic LPP; 3 American-type options for continuous time Markov LPP; 3.1 Markov LPP; 3.2 LPP with independent increments; 3.3 Diffusion LPP; 3.4 American-type options for Markov LPP; 4 Upper bounds for option rewards for Markov LPP; 4.1 Upper bounds for rewards for Markov LPP; 4.2 Asymptotically uniform conditions of compactness for Markov LPP; 4.3 Upper bounds for rewards for LPP with independent increments 4.4 Upper bounds for rewards for diffusion LPP4.5 Upper bounds for rewards for mean-reverse diffusion LPP; 5 Time-skeleton reward approximations for Markov LPP; 5.1 Lipschitz-type conditions for pay-off functions; 5.2 Time-skeleton approximations for optimal expected rewards; 5.3 Time-skeleton approximations for reward functions; 5.4 Time-skeleton reward approximations for LPP with independent increments; 5.5 Time-skeleton reward approximations for diffusion LPP; 6 Time-space-skeleton reward approximations for Markov LPP; 6.1 Time-space-skeleton reward approximations for Markov LPP 6.2 Time-space-skeleton reward approximations for LPP with independent increments6.3 Time-space-skeleton reward approximations for diffusion LPP; 7 Convergence of option rewards for continuous time Markov LPP; 7.1 Convergence of rewards for continuous time Markov LPP; 7.2 Convergence of rewards for LPP with independent increments; 7.3 Convergence of rewards for univariate Gaussian LPP with independent increments; 7.4 Convergence of rewards for multivariate Gaussian LPP with independent increments; 8 Convergence of option rewards for diffusion LPP 8.1 Convergence of rewards for time-skeleton approximations of diffusion LPP8.2 Convergence of rewards for martingale-type approximations of diffusion LPP; 8.3 Convergence of rewards for trinomial-tree approximations of diffusion LPP; 8.4 Rewards approximations for mean-reverse diffusion LPP; 9 European, knockout, reselling and random pay-off options; 9.1 Reward approximations for European-type options; 9.2 Reward approximations for knockout American-type options; 9.3 Reward approximations for reselling options; 9.4 Reward approximations for American-type options with random pay-off 10 Results of experimental studies
ISBN:	978-3-11-032984-1 ; 978-3-11-032968-1 ; 978-3-11-032968-1
Source:	ECONIS - Online Catalogue of the ZBW

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