Basic Stochastic Processes

By: Brzezniak, ZdzislawContributor(s): Zastawniak, ThomazMaterial type: TextTextSeries: Springer undergraduate mathematics seriesPublication details: London: Springer-Verlag, 1999Description: x, 225 pages : illustrationsISBN: 9783540761754; 3540761756 Subject(s): Stochastic processesDDC classification: 519.2
Contents:
1. Review of probability -- 2. Conditional expectation -- 3. Martingles in discrete time -- 4. Martingale inequalities and convergence -- 5. Markov chains -- 6. Stochastic processes in continuous time -- 7. Ito Stocahstic calculus.
Summary: "This book is a final year undergraduate text on stochastic processes, a tool used widely by statisticians and researchers working, for example, in the mathematics of finance. The book will give a detailed treatment of conditional expectation and probability, a topic which is essential as a tool for stochastic processes. Although the book is a final year text, the authors have chosen to use exercises as the main means of explanation for the various topics, hence the course has a strong self-study element. The authors have concentrated on major topics within stochastic analysis: martingales in discrete time and their convergence, Markov chains, stochastic processes in continuous time, with emphasis on the Poisson process and Brownian motion, as well as Ito stochastic calculus including stochastic differential equations."--Jacket.
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Reference 519.2 BRZ (Browse shelf(Opens below)) Available 008567
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Index

1. Review of probability --
2. Conditional expectation --
3. Martingles in discrete time --
4. Martingale inequalities and convergence --
5. Markov chains --
6. Stochastic processes in continuous time --
7. Ito Stocahstic calculus.


"This book is a final year undergraduate text on stochastic processes, a tool used widely by statisticians and researchers working, for example, in the mathematics of finance. The book will give a detailed treatment of conditional expectation and probability, a topic which is essential as a tool for stochastic processes. Although the book is a final year text, the authors have chosen to use exercises as the main means of explanation for the various topics, hence the course has a strong self-study element. The authors have concentrated on major topics within stochastic analysis: martingales in discrete time and their convergence, Markov chains, stochastic processes in continuous time, with emphasis on the Poisson process and Brownian motion, as well as Ito stochastic calculus including stochastic differential equations."--Jacket.

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