Author: Paul Malliavin
Publisher: Springer Science & Business Media
ISBN: 3540307990
Category : Business & Economics
Languages : en
Pages : 148

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Book Description
Highly esteemed author Topics covered are relevant and timely

Author: Damien Lamberton
Publisher: CRC Press
ISBN: 9781032477817
Category :
Languages : en
Pages : 0

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Book Description
Maintaining the lucid style of its popular predecessor, this concise and accessible introduction covers the probabilistic techniques required to understand the most widely used financial models. Along with additional exercises, this edition presents fully updated material on stochastic volatility models and option pricing.

Author: Marek Capiński
Publisher: Cambridge University Press
ISBN: 1139560409
Category : Business & Economics
Languages : en
Pages : 187

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Book Description
This book focuses specifically on the key results in stochastic processes that have become essential for finance practitioners to understand. The authors study the Wiener process and Itô integrals in some detail, with a focus on results needed for the Black–Scholes option pricing model. After developing the required martingale properties of this process, the construction of the integral and the Itô formula (proved in detail) become the centrepiece, both for theory and applications, and to provide concrete examples of stochastic differential equations used in finance. Finally, proofs of the existence, uniqueness and the Markov property of solutions of (general) stochastic equations complete the book. Using careful exposition and detailed proofs, this book is a far more accessible introduction to Itô calculus than most texts. Students, practitioners and researchers will benefit from its rigorous, but unfussy, approach to technical issues. Solutions to the exercises are available online.

Author: Eric Chin
Publisher: John Wiley & Sons
ISBN: 1119965837
Category : Business & Economics
Languages : en
Pages : 404

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Book Description
Mathematical finance requires the use of advanced mathematical techniques drawn from the theory of probability, stochastic processes and stochastic differential equations. These areas are generally introduced and developed at an abstract level, making it problematic when applying these techniques to practical issues in finance. Problems and Solutions in Mathematical Finance Volume I: Stochastic Calculus is the first of a four-volume set of books focusing on problems and solutions in mathematical finance. This volume introduces the reader to the basic stochastic calculus concepts required for the study of this important subject, providing a large number of worked examples which enable the reader to build the necessary foundation for more practical orientated problems in the later volumes. Through this application and by working through the numerous examples, the reader will properly understand and appreciate the fundamentals that underpin mathematical finance. Written mainly for students, industry practitioners and those involved in teaching in this field of study, Stochastic Calculus provides a valuable reference book to complement one’s further understanding of mathematical finance.

Author: Yasushi Ishikawa
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110675323
Category : Mathematics
Languages : en
Pages : 392

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Book Description
This book is a concise introduction to the stochastic calculus of variations for processes with jumps. The author provides many results on this topic in a self-contained way for e.g., stochastic differential equations (SDEs) with jumps. The book also contains some applications of the stochastic calculus for processes with jumps to the control theory, mathematical finance and so. This third and entirely revised edition of the work is updated to reflect the latest developments in the theory and some applications with graphics.

Author: Alexander A Gushchin
Publisher: Elsevier
ISBN: 0081004761
Category : Mathematics
Languages : en
Pages : 210

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Book Description
In 1994 and 1998 F. Delbaen and W. Schachermayer published two breakthrough papers where they proved continuous-time versions of the Fundamental Theorem of Asset Pricing. This is one of the most remarkable achievements in modern Mathematical Finance which led to intensive investigations in many applications of the arbitrage theory on a mathematically rigorous basis of stochastic calculus. Mathematical Basis for Finance: Stochastic Calculus for Finance provides detailed knowledge of all necessary attributes in stochastic calculus that are required for applications of the theory of stochastic integration in Mathematical Finance, in particular, the arbitrage theory. The exposition follows the traditions of the Strasbourg school. This book covers the general theory of stochastic processes, local martingales and processes of bounded variation, the theory of stochastic integration, definition and properties of the stochastic exponential; a part of the theory of Lévy processes. Finally, the reader gets acquainted with some facts concerning stochastic differential equations. Contains the most popular applications of the theory of stochastic integration Details necessary facts from probability and analysis which are not included in many standard university courses such as theorems on monotone classes and uniform integrability Written by experts in the field of modern mathematical finance

Author: Steven Shreve
Publisher: Springer Science & Business Media
ISBN: 9780387249681
Category : Mathematics
Languages : en
Pages : 212

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Book Description
Developed for the professional Master's program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S. Has been tested in the classroom and revised over a period of several years Exercises conclude every chapter; some of these extend the theory while others are drawn from practical problems in quantitative finance

Author: Eric Chin
Publisher: John Wiley & Sons
ISBN: 1119966078
Category : Business & Economics
Languages : en
Pages : 400

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Book Description
Mathematical finance requires the use of advanced mathematicaltechniques drawn from the theory of probability, stochasticprocesses and stochastic differential equations. These areas aregenerally introduced and developed at an abstract level, making itproblematic when applying these techniques to practical issues infinance. Problems and Solutions in Mathematical Finance Volume I:Stochastic Calculus is the first of a four-volume set ofbooks focusing on problems and solutions in mathematicalfinance. This volume introduces the reader to the basic stochasticcalculus concepts required for the study of this important subject,providing a large number of worked examples which enable the readerto build the necessary foundation for more practical orientatedproblems in the later volumes. Through this application and byworking through the numerous examples, the reader will properlyunderstand and appreciate the fundamentals that underpinmathematical finance. Written mainly for students, industry practitioners and thoseinvolved in teaching in this field of study, StochasticCalculus provides a valuable reference book to complementone’s further understanding of mathematical finance.

Author: Robert James Elliott
Publisher: Springer
ISBN:
Category : Mathematics
Languages : en
Pages : 320

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Book Description

Author: Jiro Akahori
Publisher: World Scientific
ISBN: 9812387781
Category : Mathematics
Languages : en
Pages : 410

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Book Description
This book contains articles on stochastic processes (stochastic calculus and Malliavin calculus, functionals of Brownian motions and Levy processes, stochastic control and optimization problems, stochastic numerics, and so on) and their applications to problems in mathematical finance. Examples of topics are applications of Malliavin calculus and numerical analysis to a new simulation scheme for calculating the price of financial derivatives, applications of the asymptotic expansion method in Malliavin calculus to financial problems, semimartingale decompositions under an enlargement of filtrations in connection with insider problems, and the problem of transaction costs in connection with stochastic control and optimization problems.