Stochastic Calculus and Financial Applications [electronic resource] / by J. Michael Steele.
This book is designed for students who want to develop professional skills in stochastic calculus and its application to problems in finance. The Wharton School course on which the book is based is designed for energetic students who have had some experience with probability and statistics, but who...
Saved in:
| Online Access: |
Full Text (via Springer) |
|---|---|
| Main Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, NY :
Springer New York,
2001.
|
| Series: | Applications of Mathematics, Stochastic Modelling and Applied Probability ;
45. |
| Subjects: |
MARC
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| 245 | 1 | 0 | |a Stochastic Calculus and Financial Applications |h [electronic resource] / |c by J. Michael Steele. |
| 260 | |a New York, NY : |b Springer New York, |c 2001. | ||
| 300 | |a 1 online resource (ix, 300 pages 3 illustrations). | ||
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| 490 | 1 | |a Applications of Mathematics, Stochastic Modelling and Applied Probability, |x 0172-4568 ; |v 45 | |
| 505 | 0 | |a Random Walk and First Step Analysis -- First Martingale Steps -- Brownian Motion -- Martingale: The Next Steps -- Richness of Paths -- Itô Integration -- Localization and Itô's Integral -- Itô's Formula -- Stochastic Differential Equations -- Arbitrage and SDEs -- The Diffusion Equation -- Representation Theorem -- Girsanov Theory -- Arbitrage and Martingales -- The Feynman-Kac Connection -- Appendix I. Mathematical Tools -- Appendix II. Comments and Credits -- Bibliography -- Index. | |
| 520 | |a This book is designed for students who want to develop professional skills in stochastic calculus and its application to problems in finance. The Wharton School course on which the book is based is designed for energetic students who have had some experience with probability and statistics, but who have not had advanced courses in stochastic processes. Even though the course assumes only a modest background, it moves quickly and - in the end - students can expect to have the tools that are deep enough and rich enough to be relied upon throughout their professional careers. The course begins with simple random walk and the analysis of gambling games. This material is used to motivate the theory of martingales, and, after reaching a decent level of confidence with discrete processes, the course takes up the more demanding development of continuous time stochastic process, especially Brownian motion. The construction of Brownian motion is given in detail, and enough material on the subtle properties of Brownian paths is developed so that the student should sense of when intuition can be trusted and when it cannot. The course then takes up the Itô integral and aims to provide a development that is honest and complete without being pedantic. With the Itô integral in hand, the course focuses more on models. Stochastic processes of importance in Finance and Economics are developed in concert with the tools of stochastic calculus that are needed in order to solve problems of practical importance. The financial notion of replication is developed, and the Black-Scholes PDE is derived by three different methods. The course then introduces enough of the theory of the diffusion equation to be able to solve the Black-Scholes PDE and prove the uniqueness of the solution. | ||
| 504 | |a Includes bibliographical references (pages 294-295) and index. | ||
| 546 | |a English. | ||
| 650 | 0 | |a Mathematics. |0 http://id.loc.gov/authorities/subjects/sh85082139 | |
| 650 | 0 | |a Finance. |0 http://id.loc.gov/authorities/subjects/sh85048256 | |
| 650 | 0 | |a Distribution (Probability theory) |0 http://id.loc.gov/authorities/subjects/sh85038545 | |
| 650 | 0 | |a Mathematical statistics. |0 http://id.loc.gov/authorities/subjects/sh85082133 | |
| 650 | 7 | |a Distribution (Probability theory) |2 fast | |
| 650 | 7 | |a Finance. |2 fast | |
| 650 | 7 | |a Mathematical statistics. |2 fast | |
| 650 | 7 | |a Mathematics. |2 fast | |
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| 830 | 0 | |a Applications of Mathematics, Stochastic Modelling and Applied Probability ; |v 45. | |
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