Stochastic Calculus for Quantitative Finance

Author: Alexander A Gushchin
Publisher: Elsevier
ISBN: 0081004761
Category: Mathematics
Page: 208
View: 5821

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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

Stochastic Integrals

An Introduction
Author: Heinrich von Weizsäcker
Publisher: Springer-Verlag
ISBN: 3663139239
Category: Mathematics
Page: 332
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Theory and Applications of Stochastic Processes

An Analytical Approach
Author: Zeev Schuss
Publisher: Springer Science & Business Media
ISBN: 1441916059
Category: Mathematics
Page: 468
View: 591

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Stochastic processes and diffusion theory are the mathematical underpinnings of many scientific disciplines, including statistical physics, physical chemistry, molecular biophysics, communications theory and many more. Many books, reviews and research articles have been published on this topic, from the purely mathematical to the most practical. This book offers an analytical approach to stochastic processes that are most common in the physical and life sciences, as well as in optimal control and in the theory of filltering of signals from noisy measurements. Its aim is to make probability theory in function space readily accessible to scientists trained in the traditional methods of applied mathematics, such as integral, ordinary, and partial differential equations and asymptotic methods, rather than in probability and measure theory.

Numerical Integration of Stochastic Differential Equations

Author: G.N. Milstein
Publisher: Springer Science & Business Media
ISBN: 9401584559
Category: Computers
Page: 172
View: 2622

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This book is devoted to mean-square and weak approximations of solutions of stochastic differential equations (SDE). These approximations represent two fundamental aspects in the contemporary theory of SDE. Firstly, the construction of numerical methods for such systems is important as the solutions provided serve as characteristics for a number of mathematical physics problems. Secondly, the employment of probability representations together with a Monte Carlo method allows us to reduce the solution of complex multidimensional problems of mathematical physics to the integration of stochastic equations. Along with a general theory of numerical integrations of such systems, both in the mean-square and the weak sense, a number of concrete and sufficiently constructive numerical schemes are considered. Various applications and particularly the approximate calculation of Wiener integrals are also dealt with. This book is of interest to graduate students in the mathematical, physical and engineering sciences, and to specialists whose work involves differential equations, mathematical physics, numerical mathematics, the theory of random processes, estimation and control theory.

A Modern Theory of Random Variation

With Applications in Stochastic Calculus, Financial Mathematics, and Feynman Integration
Author: Patrick Muldowney
Publisher: John Wiley & Sons
ISBN: 1118345940
Category: Science
Page: 544
View: 3846

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A ground-breaking and practical treatment of probability andstochastic processes A Modern Theory of Random Variation is a new and radicalre-formulation of the mathematical underpinnings of subjects asdiverse as investment, communication engineering, and quantummechanics. Setting aside the classical theory of probabilitymeasure spaces, the book utilizes a mathematically rigorous versionof the theory of random variation that bases itself exclusively onfinitely additive probability distribution functions. In place of twentieth century Lebesgue integration and measuretheory, the author uses the simpler concept of Riemann sums, andthe non-absolute Riemann-type integration of Henstock. Readers aresupplied with an accessible approach to standard elements ofprobability theory such as the central limmit theorem and Brownianmotion as well as remarkable, new results on Feynman diagrams andstochastic integrals. Throughout the book, detailed numerical demonstrations accompanythe discussions of abstract mathematical theory, from the simplestelements of the subject to the most complex. In addition, an arrayof numerical examples and vivid illustrations showcase how thepresented methods and applications can be undertaken at variouslevels of complexity. A Modern Theory of Random Variation is a suitable bookfor courses on mathematical analysis, probability theory, andmathematical finance at the upper-undergraduate and graduatelevels. The book is also an indispensible resource for researchersand practitioners who are seeking new concepts, techniques andmethodologies in data analysis, numerical calculation, andfinancial asset valuation. Patrick Muldowney, PhD, served as lecturer at the Magee BusinessSchool of the UNiversity of Ulster for over twenty years. Dr.Muldowney has published extensively in his areas of research,including integration theory, financial mathematics, and randomvariation.

Stochastic Calculus

Applications in Science and Engineering
Author: Mircea Grigoriu
Publisher: Springer Science & Business Media
ISBN: 9780817642426
Category: Mathematics
Page: 774
View: 8086

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"This self-contained text may be used for several graduate courses and as an important reference resource for applied scientists interested in analytical and numerical methods for solving stochastic problems."--BOOK JACKET.

Introduction to Stochastic Integration

Author: K.L. Chung,R.J. Williams
Publisher: Springer Science & Business Media
ISBN: 1461495873
Category: Mathematics
Page: 276
View: 4311

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A highly readable introduction to stochastic integration and stochastic differential equations, this book combines developments of the basic theory with applications. It is written in a style suitable for the text of a graduate course in stochastic calculus, following a course in probability. Using the modern approach, the stochastic integral is defined for predictable integrands and local martingales; then It’s change of variable formula is developed for continuous martingales. Applications include a characterization of Brownian motion, Hermite polynomials of martingales, the Feynman–Kac functional and the Schrödinger equation. For Brownian motion, the topics of local time, reflected Brownian motion, and time change are discussed. New to the second edition are a discussion of the Cameron–Martin–Girsanov transformation and a final chapter which provides an introduction to stochastic differential equations, as well as many exercises for classroom use. This book will be a valuable resource to all mathematicians, statisticians, economists, and engineers employing the modern tools of stochastic analysis. The text also proves that stochastic integration has made an important impact on mathematical progress over the last decades and that stochastic calculus has become one of the most powerful tools in modern probability theory. —Journal of the American Statistical Association An attractive text...written in [a] lean and precise style...eminently readable. Especially pleasant are the care and attention devoted to details... A very fine book. —Mathematical Reviews

Vector Integration and Stochastic Integration in Banach Spaces

Author: Nicolae Dinculeanu
Publisher: John Wiley & Sons
ISBN: 1118031261
Category: Mathematics
Page: 448
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A breakthrough approach to the theory and applications of stochastic integration The theory of stochastic integration has become an intensely studied topic in recent years, owing to its extraordinarily successful application to financial mathematics, stochastic differential equations, and more. This book features a new measure theoretic approach to stochastic integration, opening up the field for researchers in measure and integration theory, functional analysis, probability theory, and stochastic processes. World-famous expert on vector and stochastic integration in Banach spaces Nicolae Dinculeanu compiles and consolidates information from disparate journal articles-including his own results-presenting a comprehensive, up-to-date treatment of the theory in two major parts. He first develops a general integration theory, discussing vector integration with respect to measures with finite semivariation, then applies the theory to stochastic integration in Banach spaces. Vector Integration and Stochastic Integration in Banach Spaces goes far beyond the typical treatment of the scalar case given in other books on the subject. Along with such applications of the vector integration as the Reisz representation theorem and the Stieltjes integral for functions of one or two variables with finite semivariation, it explores the emergence of new classes of summable processes that make applications possible, including square integrable martingales in Hilbert spaces and processes with integrable variation or integrable semivariation in Banach spaces. Numerous references to existing results supplement this exciting, breakthrough work.

Continuous Stochastic Calculus with Applications to Finance

Author: Michael Meyer
Publisher: CRC Press
ISBN: 1420035592
Category: Mathematics
Page: 336
View: 8623

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The prolonged boom in the US and European stock markets has led to increased interest in the mathematics of security markets, most notably in the theory of stochastic integration. This text gives a rigorous development of the theory of stochastic integration as it applies to the valuation of derivative securities. It includes all the tools necessary for readers to understand how the stochastic integral is constructed with respect to a general continuous martingale. The author develops the stochastic calculus from first principles, but at a relaxed pace that includes proofs that are detailed, but streamlined to applications to finance. The treatment requires minimal prerequisites-a basic knowledge of measure theoretic probability and Hilbert space theory-and devotes an entire chapter to application in finances, including the Black Scholes market, pricing contingent claims, the general market model, pricing of random payoffs, and interest rate derivatives. Continuous Stochastic Calculus with Application to Finance is your first opportunity to explore stochastic integration at a reasonable and practical mathematical level. It offers a treatment well balanced between aesthetic appeal, degree of generality, depth, and ease of reading.

Stochastic Integration with Jumps

Author: Klaus Bichteler
Publisher: Cambridge University Press
ISBN: 9780521811293
Category: Mathematics
Page: 501
View: 8689

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The complete theory of stochastic differential equations driven by jumps, their stability, and numerical approximation theories.

Stochastic Calculus for Fractional Brownian Motion and Applications

Author: Francesca Biagini,Yaozhong Hu,Bernt Øksendal,Tusheng Zhang
Publisher: Springer Science & Business Media
ISBN: 1846287979
Category: Mathematics
Page: 330
View: 7089

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The purpose of this book is to present a comprehensive account of the different definitions of stochastic integration for fBm, and to give applications of the resulting theory. Particular emphasis is placed on studying the relations between the different approaches. Readers are assumed to be familiar with probability theory and stochastic analysis, although the mathematical techniques used in the book are thoroughly exposed and some of the necessary prerequisites, such as classical white noise theory and fractional calculus, are recalled in the appendices. This book will be a valuable reference for graduate students and researchers in mathematics, biology, meteorology, physics, engineering and finance.

Stochastic Differential Equations

With Applications to Physics and Engineering
Author: K. Sobczyk
Publisher: Springer Science & Business Media
ISBN: 9401137129
Category: Mathematics
Page: 400
View: 9617

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'Et moi, ..~ si lavait su CO.llUlJalt en revc:nir, One acMcc matbcmatica bu JaIdcred the human rac:c. It bu put COIDIDOD _ beet je n'y serais point aBe.' Jules Verne wbac it bdoup, 0Jl!be~ IbcII _t to!be dusty cauialcr Iabc & d 'diMardod__ The series is divergent; thc:reforc we may be -'. I!.ticT. Bc:I1 able to do something with it. O. Hcavisidc Mathematics is a tool for thought. A highly necessary tool in a world when: both feedback and non linearities abound. Similarly. all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statcmalts as: 'One service topology has rendered mathematical physics ...-; 'One service logic has rendered c0m puter science ... '; 'One service category theory has rendered mathematics ... '. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series. This series, Mathematics and Its Applications. started in 19n. Now that over one hundred volumes have appeared it seems opportune to reexamine its scope. At the time I wrote "Growing specialization and diversification have brought a host of monographs and textbooks on increasingly specialized topics. However. the 'tree' of knowledge of mathematics and related fields does not grow only by putting forth new branc:hes. It also happens, quite often in fact, that branches which were thought to be completely.

Stochastic Calculus and Financial Applications

Author: J. Michael Steele
Publisher: Springer Science & Business Media
ISBN: 1468493051
Category: Mathematics
Page: 302
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Stochastic calculus has important applications to mathematical finance. This book will appeal to practitioners and students who want an elementary introduction to these areas. From the reviews: "As the preface says, ‘This is a text with an attitude, and it is designed to reflect, wherever possible and appropriate, a prejudice for the concrete over the abstract’. This is also reflected in the style of writing which is unusually lively for a mathematics book." --ZENTRALBLATT MATH

An Informal Introduction to Stochastic Calculus with Applications

Author: Ovidiu Calin
Publisher: World Scientific
ISBN: 9814678953
Category: Mathematics
Page: 332
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The goal of this book is to present Stochastic Calculus at an introductory level and not at its maximum mathematical detail. The author aims to capture as much as possible the spirit of elementary deterministic Calculus, at which students have been already exposed. This assumes a presentation that mimics similar properties of deterministic Calculus, which facilitates understanding of more complicated topics of Stochastic Calculus. Contents:A Few Introductory ProblemsBasic NotionsUseful Stochastic ProcessesProperties of Stochastic ProcessesStochastic IntegrationStochastic DifferentiationStochastic Integration TechniquesStochastic Differential EquationsApplications of Brownian MotionGirsanov's Theorem and Brownian MotionSome Applications of Stochastic CalculusHints and Solutions Readership: Undergraduate and graduate students interested in stochastic processes. Key Features:The book contains numerous problems with full solutions and plenty of worked out examples and figures, which facilitate material understandingThe material was tested on students at several universities around the world (Taiwan, Kuwait, USA); this led to a presentation form that balances both technicality and understandingThe presentation mimics as close as possible the same chapters as in deterministic calculus; former calculus students will find this chronology of ideas familiar to CalculusKeywords:Stochastic Processes;Probability Distribution;Brownian Motion;Filtering Theory;Martingale;Ito Calculus;Poisson Process;Bessel Process

Stochastic Integration Theory

Author: Peter Medvegyev
Publisher: Oxford University Press on Demand
ISBN: 0199215251
Category: Business & Economics
Page: 608
View: 6574

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This graduate level text covers the theory of stochastic integration, an important area of Mathematics that has a wide range of applications, including financial mathematics and signal processing. Aimed at graduate students in Mathematics, Statistics, Probability, Mathematical Finance, and Economics, the book not only covers the theory of the stochastic integral in great depth but also presents the associated theory (martingales, Levy processes) and important examples (Brownianmotion, Poisson process).

Stochastic Calculus and Applications

Author: Samuel N. Cohen,Robert J. Elliott
Publisher: Birkhäuser
ISBN: 1493928678
Category: Mathematics
Page: 666
View: 3519

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Completely revised and greatly expanded, the new edition of this text takes readers who have been exposed to only basic courses in analysis through the modern general theory of random processes and stochastic integrals as used by systems theorists, electronic engineers and, more recently, those working in quantitative and mathematical finance. Building upon the original release of this title, this text will be of great interest to research mathematicians and graduate students working in those fields, as well as quants in the finance industry. New features of this edition include: End of chapter exercises; New chapters on basic measure theory and Backward SDEs; Reworked proofs, examples and explanatory material; Increased focus on motivating the mathematics; Extensive topical index. "Such a self-contained and complete exposition of stochastic calculus and applications fills an existing gap in the literature. The book can be recommended for first-year graduate studies. It will be useful for all who intend to work with stochastic calculus as well as with its applications."–Zentralblatt (from review of the First Edition)

Stochastic Integration in Banach Spaces

Theory and Applications
Author: Vidyadhar Mandrekar,Barbara Rüdiger
Publisher: Springer
ISBN: 3319128531
Category: Mathematics
Page: 211
View: 1271

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Considering Poisson random measures as the driving sources for stochastic (partial) differential equations allows us to incorporate jumps and to model sudden, unexpected phenomena. By using such equations the present book introduces a new method for modeling the states of complex systems perturbed by random sources over time, such as interest rates in financial markets or temperature distributions in a specific region. It studies properties of the solutions of the stochastic equations, observing the long-term behavior and the sensitivity of the solutions to changes in the initial data. The authors consider an integration theory of measurable and adapted processes in appropriate Banach spaces as well as the non-Gaussian case, whereas most of the literature only focuses on predictable settings in Hilbert spaces. The book is intended for graduate students and researchers in stochastic (partial) differential equations, mathematical finance and non-linear filtering and assumes a knowledge of the required integration theory, existence and uniqueness results and stability theory. The results will be of particular interest to natural scientists and the finance community. Readers should ideally be familiar with stochastic processes and probability theory in general, as well as functional analysis and in particular the theory of operator semigroups. ​

Elementary Stochastic Calculus, with Finance in View

Author: Thomas Mikosch
Publisher: World Scientific Publishing Company
ISBN: 9813105291
Category: Mathematics
Page: 224
View: 7317

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Modelling with the Itô integral or stochastic differential equations has become increasingly important in various applied fields, including physics, biology, chemistry and finance. However, stochastic calculus is based on a deep mathematical theory. This book is suitable for the reader without a deep mathematical background. It gives an elementary introduction to that area of probability theory, without burdening the reader with a great deal of measure theory. Applications are taken from stochastic finance. In particular, the Black-Scholes option pricing formula is derived. The book can serve as a text for a course on stochastic calculus for non-mathematicians or as elementary reading material for anyone who wants to learn about Itô calculus and/or stochastic finance.