Stochastic Calculus for Finance II

Name: Stochastic Calculus for Finance II
Brand: Springer-Verlag New York Inc.
SKU: 9781441923110
Price: 374.94 RON
Availability: InStock

Continuous-Time Models

Autor: Steven E Shreve

Limbă:

Legare: Carte broșată

Editura: Springer-Verlag New York Inc.

Disponibilitate: În depozitul extern în cantități mici

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374.94 lei

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional...

Informații despre carte

Autor

Steven E Shreve

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2010

Pagini

550

EAN

9781441923110

ISBN

144192311X

Enbook ID

01343789

Editura

Springer-Verlag New York Inc.

Greutate

854

Dimensiuni

150 x 230 x 32

Descriere completă

Stochastic Calculus for Finance evolved from the first ten years of the Carnegie Mellon Professional Master's program in Computational Finance. The content of this book has been used successfully with students whose mathematics background consists of calculus and calculus-based probability. The text gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided. The book includes a self-contained treatment of the probability theory needed for stochastic calculus, including Brownian motion and its properties. Advanced topics include foreign exchange models, forward measures, and jump-diffusion processes.§This book is being published in two volumes. This second volume develops stochastic calculus, martingales, risk-neutral pricing, exotic options and term structure models, all in continuous time.§Masters level students and researchers in mathematical finance and financial engineering will find this book useful.§Steven E. Shreve is Co-Founder of the Carnegie Mellon MS Program in Computational Finance and winner of the Carnegie Mellon Doherty Prize for sustained contributions to education. "A wonderful display of the use of mathematical probability to derive a large set of results from a small set of assumptions. In summary, this is a well-written text that treats the key classical models of finance through an applied probability approach....It should serve as an excellent introduction for anyone studying the mathematics of the classical theory of finance." --SIAM This text has grown out of a two-semester course sequence in the Carnegie Mellon Master's program in Computational Finance. It contains numerous examples, exercises, and references. It assumes the reader is familiar with differential and integral calculus and basic concepts from calculus-based probability. It does not assume familiarity with measure-theoretic probability, but rather informally develops the necessary tools from this subject within the text.

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Stochastic Calculus for Finance II

Continuous-Time Models

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