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Stochastic Calculus and Financial Applications (Stochastic Modelling and Applied Probability) Hardcover – October 12, 2000
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From the reviews: MATHEMATICAL REVIEWS "…on the whole, the results are presented carefully and thoroughly, and I expect that readers will find that this combination of a careful development of stochastic calculus with many details and examples is very useful and will enable them to apply the whole theory confidently." SHORT BOOK REVIEWS "This is a world of 'lovely exercises' that are 'very good good for the soul', 'honest martingales', 'bedrock approximations', portfolios that are 'born to lose', 'intuitive but bogus arguments', and 'embarrassingly crude insights'. In short, this is a book on stochastic calculus of a different flavour. Intuition is not sacrificed for rigour nor rigour for intuition.The main results are reinforced with simple special cases, and only when the intuitive foundations are laid does the auhtor resort to the formalism of probability. The coverage is limited to the essentials but nevertheless includes topics that will catch the eye of experts (such as the wavelet construction of Brownian motion). This is one of the most interesting and easiest reads in the discipline; a gem of a book." JOURNAL OF THE AMERICAN STOCHASTIC ASSOCIATION "The book is indeed well written, with many insightful comments. I certainly would recommend it to students wishing to learn stochastic calculus and its applications to the Black-Sholes option-pricing theory…I thoroughly enjoyed reading this book. The author is to be complimented for his efforts in providing many useful insights behind the various theories. It is a superb introduction to stochastic calculus and Brownian motion…An interesting feature in this book is its coverage of partial differential equations." "It is clear that this is a fairly comprehensive introduction to the tools of (classical) mathematical finance. … the text has much to offer. … In addition, the writing style is refreshingly informal and makes a book about a rather technical subject surprisingly enjoyable to read. In short, despite the recent deluge of textbooks in this area, I know of no better book for self-study." (Christian Kleiber, Statistical Papers, Vol. 46 (2), 2005) "Steele’s book is a sophisticated introduction to stochastic calculus with applications from basic Black-Scholes theory. … I highly recommend the book. His style is wonderful, and concepts really build on one another. … it offers one of the most elegant treatments of the subject that I know of." (www.riskbook.com, May, 2006) "As is clear from the title of this book, it is concerned with applications of stochastic calculus to finance. … one naturally judges the book by three criteria: topic selection, organization, and exposition. In all three domains the book succeeds. The topics selected are rich enough … he or she will benefit from the book. … there are innovations as well … from the pedagogic standpoint." (Philip Protter, SIAM Review, Vol. 43 (4), 2001) "This book offers rich information and a mathematically honest treatment of stochastic calculus and of its use in the theory of finance … . The author gradually builds the reader’s ability to grasp stochastic concepts and techniques … . the author’s presentation of stochastic models in finance and economy is precise and extensive … . Each chapter is accompanied by a collection of rather challenging exercises … ." (EMS Newsletter, December, 2002) "The present book ‘is designed for students who want to develop professional skill in stochastic calculus and its application to problems in finance’. … the textbook … retains a lovely lecture style focusing basic ideas and not formalities and technical details of stochastic processes needed for finance. I can strongly recommend this book to students of mathematics and physics as well as non-experts in probability theory who are interested in stochastic finance." (H. –J. Girlich, Zeitschrift für Analysis und ihre Anwendungen, Vol. 21 (4), 2002) "The last few years have been a fertile period for books on stochastic calculus and its financial implications, but this one differs from the many mainstream treatments … . The style of the book creates the atmosphere of a lively lecture … . Each chapter ends with a section of carefully chosen exercises, preceded by some motivating remarks. … I really liked the book." (R. Grübel, Statistics & Decisions, Vol. 20 (4), 2002) "This book gives an introduction to stochastic calculus … with applications in mathematical finance. … 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. … on the whole, the results are presented carefully and thoroughly … ." (Martin Schweizer, Zentralblatt MATH, Vol. 962, 2001) "This is a book on stochastic calculus of a different flavour. Intuition is not sacrificed for rigour nor rigour for intuition. The main results are reinforced with simple special cases … . This is one of the most interesting and easiest reads in the discipline; a gem of a book." (D. L. McLeish, Short Book Reviews, Vol. 21 (1), 2001)
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Mike Steele has used the material in this text to teach stochastic calculus to business students. The text presupposes knowledge of calculus and advanced probability. However the students are not expected to have had even a first course in stochastic processes. The book introduces the Ito calculus by first teaching about random walks and other discrete time processes. Steele uses a lecturing style and even brings in some humor and philosophy. He also presents results using more than one approach or proof. This can help the student get a deeper appreciation for the probabilitist concepts.
The gambler's ruin problem is one of the first problems that Steele tackles and he uses recursive equations as his way to introduce it.
Brownian Motion, Skorohod embedding and other advanced mathematics is introduced and emphasized. After motivating the stochastic calculus and developing martingales Steele covers arbitrage and stochastic differential equations leading up to the fundamental Black-Scholes theory that is important in financial applications. It is not fair to criticize this book for lack of applicability. It is strickly intended to develop a firm theoretical background for the students that will prepare them for a deep understanding of financial models important in applications.
I am not enough of an expert in this area to know if Professor McCauley's criticism in another amazon review of this book is valid, but I do think he is a little too harsh in criticizing the ideology that Steele presents. The ideology is what makes Steele's lectures stimulating and interesting to the students.
On that note, Steele's book is a MATH book. By contrast, the wonderful book by Baxter & Rennie emphasizes core ideas with emphasis on the relationship between the three primary tools of the discipline (Martingale Representation, Ito-Doeblin Calculus, and the Feynman-Kac formula) while Shreve's classic emphasizes actual development of key models and techniques. Even Oksendal, which is aimed at a slightly more sophisticated mathematical audience, emphasizes applications at the expense of elegance.
In contrast, Steele's book is a math book aimed at Wharton (read: finance and economics doctoral students, likely in their second year) students with varied interests. Students taking this course probably have already taken a rigorous course in asset pricing theory from the academic viewpoint and need to fill in the blanks with the continuous-time techniques to extend these techniques and to understand stochastic calculus at the level necessary for research in economics/finance.
With that in mind, the book is versatile enough to be appreciated by different audiences. Steele certainly takes care give a clear, well-motivated presentation which explains to the reader WHY he is giving a concept, proof, or problem, and breaks the book up into small, digestible chapters. The problems are neither overly difficult nor disconnected from the text, although doing them is not an essential part of understanding the overall view. Furthermore, Steele clearly takes delight in the beauty of stochastic calculus, as demonstrated by Chapter 5 - Richness of Paths, which discusses the "interesting" properties of Brownian motion. For anyone who sat through a difficult analysis class thinking the whole purpose of the course was to annoy and taunt the student with irrelevant counterexamples (remember constructing a continuous yet non-differentiable function using limits?), this chapter will be especially fun.
In the first part of the book, Steele covers the basics of the random walk and martingales, introducing important theorems such as the upcrossing (downcrossing) lemma, submartingales and the Doob Decomposition theorem, the basic martingale inequalities, stopping times, and conditional probability (for those who are familiar with Williams' Probability with Martingales, the treatment is similiar). He then covers Brownian motion from both the standard perspective (a Brownian motion is a process such that...) and more intuitively as a limit of random walks (i.e. the "wavelet" construction/proof), using this subject as an opportunity to extend the martingale concepts to continuous-time.
In what could roughly be called the "second" part of the book, Steele develops the Ito integral as a martingale and as a process. Steele provides a lot of detail to the subject, perhaps in mind with the view that readers using stochastic calculus with more general underlying processes will have to understand the difference between a martingale and "just" a local martingale. He then quickly but sufficiently covers the standard topics of Ito calculus - Ito's lemma, quadratic variation, and the basic SDE, although in the Picard-type existence/uniqueness proof of SDEs he shows why the careful description of the Ito integral is not simply technical.
The next part of the book covers the "standard" topics in financial mathematics that would appeal to quant finance students . The chapter on arbitrage covers the basic Black-Scholes-Merton equation and its generalization to arbitrage pricing, although Steele (appropriately) addresses Black and Scholes CAPM derivation of their options pricing formula, which gives the finance/economics reader a historical perspective. The chapter on diffusions is excellent and gives all of the necessary elements for handling "nice" parabolic second-order equations. He even sneaks in Green's functions, series expansions, and the Maximum Principle without making uninterested readers have to learn them to follow the presentation.
In the last few chapters, he covers Martingale Representation, Girsanov's Theorem and their applications to more advanced topics in pricing, such as forward measures. The problems in this part of the book are nice because they help the reader understand the intuition behind a particular mathematical principle but not necessarily its application to a well-recognized model. The final chapter on the Feynman-Kac formula gives a very intuitive proof of its topic which helps the reader understand what is meant by "killing" a process and hopefully how that translates into finance; other books often just do a coefficient-matching proof, which really doesn't capture what's really going on.
I emphasize again that while the book is designed to serve a different purpose than texts such as Shreve or Baxter & Rennie, it can help readers of different backgrounds understand the basic elements needed for more advanced stochastic analysis and gain an appreciation for both the beauty of the subject and the underlying intuition liking the math to the finance. The prerequisite, though, is at least a (rigorous undergrad) course in real analysis, probably some familiarity with measure theory, probability, and L(p) spaces (or at least L(1,2,inf) spaces), and at least basic familiarity with the elements of stochastic calculus (Ito's lemma and computations with "box calculus", for example). For readers seeking a more comprehensive treatment of quantitative finance, this book is reasonably good mathematical preparation to understand Musiela/Rutkowski, and for doctoral students, understanding most of the topics in this book with a brief introduction to dynamic programming in the continuous-time setting is sufficient background to read Merton's book (consumption-investment problems) as well as understand the basics of derivative pricing.
Steele, a Wharton Statistics professor, uses financial applications to motivate stochastic calculus from a particular perspective. I have no doubt that he sees stochastic calculus as a field that exists outside of finance and that he does not intend to teach the reader finance theory. His goal, I believe, is to offer a text that is more readable than the classic text of Karatzas and Shreve ("Brownian Motion and Stochastic Calculus"). In my opinion, he has accomplished this goal.
Protter ("Stochastic Integration and Differential Equations: a new approach") does an excellent job, as he is clear and develops the theory in greater generality (using semi-martingales). However, his text is highly theoretical and offers no finance applications. Duffie ("Dynamic Asset Pricing Theory") and Musiela and Rutkowski (above) do not offer the reader the necessary stochastic calculus background.
Lastly, this is a non-trivial subject. For people who do not sit down by themselves and put in the required hours, the outcome will be disappointing.