Book Description
Designed to form the basis of an undergraduate course in mathematical finance, this book builds on mathematical models of bond and stock prices and covers three major areas of mathematical finance that all have an enormous impact on the way modern financial markets operate, namely: Black-Scholes’ arbitrage pricing of options and other derivative securities; Markowitz portfolio optimization theory and the Capital Asset Pricing Model; and interest rates and their term structure. Assuming only a basic knowledge of probability and calculus, it covers the material in a mathematically rigorous and complete way at a level accessible to second or third year undergraduate students. The text is interspersed with a multitude of worked examples and exercises, so it is ideal for self-study and suitable not only for students of mathematics, but also students of business management, finance and economics, and anyone with an interest in finance who needs to understand the underlying theory.
Customer Reviews:
Mathematics for Finance: A useful tool for the unskillled investor.......2007-03-19
I enjoyed reading the book and solving exercises in it. I have a Ph.D.in chemistry and my wife and I did our his and her's MBA in the 1990s. I wanted to learn more concepts in finance and needed an easy entry, something I could enjoy, and without spending much money. The book by Capinski came recommended from a friend who teaches Economics at Cal State. I can speak for myself: I feel reasonably informed and I feel the book gave me concepts I can use to handle my own portfolio.
In the future, this text should be offered with an interactive CD that contains Xls, matrix, calculus, and graphing capabilities so one (I) can visualize the outcomes of proposed solutions.
Incoherent.......2007-01-18
Anyone can scribble a bunch of equations on paper and call it a book. Without sufficient context, they are useless.
Insufficient and disappointing. Not even a good introductury text........2006-05-15
As a graduate student in Financial Engineering I have found this book useless.
The title of the book is "Mathematics for Finance", but can you find in it even an elementary introduction to the stochastic processes? No. Ditto for the Ito's lemma and many other topics. The derivation of the Black Scholes formula is just sketched, and the insight that you can get from it is very limited.
Nevertheless, I wouldn't mind these limitations if this book provided a clear introduction to more advanced topics: unfortunately this book is not good even in that. In comparison to other textbooks the theorems and definitions are convoluted and do not go straight to the point. For example, in Shreve's "Stochastic Calculus for Finance" or Baxter & Rennie "Financial Calculus" the Fundamental Theorem of Asset Pricing is stated in this way: "In a market with risk neutral probability there is no arbitrage". Can you find such a simple and explanatory definition in Capinski's book? Not at all. The theorem at page 83 (you can see it yourself by searching inside the book) basically says the same thing using 8 lines of text and little financial intuition.
The only good thing that I can say about this book is that all exercises are resolved.
Overall, "Mathematics for Finance" has been a big disappointment: it doesn't have either the mathematical depth of Shreve's books or the conciseness in explaining financial concepts of Baxter & Rennie.
Whatever is the level of education that you are pursuing, graduate or undergraduate, I don't see any point in using it.
Great Book for Undergrad Quants.......2005-08-29
Mathematics for Finance (An Introduction to Financial Engineering) is a book intended for undergrad students "IN MATHEMATICS" or other discipline with a relative high mathematical content.
The book assumes some basic notion of Calculus and Probability Theory and it is focused more on the mathematics than in its theory and application of Finance. If you are looking to dwell into the mathematics (Proof of Equations) this is a great book, but if you are looking for a book that is rich in theory and in application then you should consider "Option, Future and Other Derivatives" or "Quantitative Methods for Finance" as an alternative. Both books are "a most" for any finance student and are of great help. Now if you want an introduction into the mathematics behind Finance then this book is a perfect purchase.
Important to state that all the problems presented in this book are solved meaning that it is great for self teaching. Marek Capinsi and Thomas Zastawniak have done a great job on this book.
I gave it four stars, because it has room for impovement.
Joining the chorus.......2005-08-03
I can only echo the other reviewers. As far as I can tell this book has no serious competition. This is an excellent introduction to mathematical finance for those with a solid undergraduate level understanding of higher math but without graduate level exposure. I agree that it is ideal for self study as that is exactly what I am using it for. The price is right especially in contrast with its overpriced brethren. Five stars!
Book Description
This introductory text provides a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice. M. Joshi covers the strengths and weaknesses of such models as stochastic volatility, jump diffusion, and variance gamma, as well as the Black-Scholes. Examples and exercises, with answers, as well as computer projects, challenge the mind and encourage learning how to become a good quantitative analyst.
Customer Reviews:
An excellent starting point. ... .......2007-01-24
This book is excellent for a deeper introductory look at mathematical
finance. It is well-written, and strikes a nice balance
between sophistication and accessiblity. Its companion volume on
C++ development in the context of quantitative finance is also well
worth examining. I look forward to seeing the follow up volume, which
will cover additional, more advanced topics.
Very Good.......2006-11-03
I'm totally satisfied. About the timing of the shipment, to me very quick and about the quality of the product, that was in good condition.
Very useful book.......2006-02-01
This is a great book for those who want to learn quantitative finance, but don't have the benefit of being enrolled in a financial engineering program. It has the advantage of being self-contained and begins instruction from the ground up: you can "cold start" on the subject with this book. Just a basic knowledge of differential equations (non-stochastic) is required.
It is natural to compare Joshi's book with Hull, but I would recommend reading them together as they have complementary strengths. Hull is over-simplified but provides financial intuition and descriptions of real-world practices. However it does not have modern notation. It also does not teach you how to solve actual pricing problems from the mathematical or computational point of view. Joshi's book does all of that and even helps you develop some mathematical intuition for the models. It also has some computing projects in c++ that a student could do.
The real comparison should be with Neftci's mathematical finance book and Baxter and Rennie. I think Joshi's book is much better than either of the two. I could barely read Neftci after a while because of the errors and bad organization. B&R is way too formal in my opinion for such an applied subject. Joshi's book has good notation and organization which builds confidence in the author, plus it is very applied so you feel you are learning something useful. It has none of that lemma-proof style which can be so unappealing to non-pure mathematicians.
If you already know the field.......2005-10-11
If you already know almost everything it is a very good book. No error and the guy knows what he is doing. However, if you know everything, why do you want to buy this book?
Unfortunately, if you do not know everything, the book is very difficult to understand. At a first lecture I never get the point. After reading some others books and implement the problem, I can indeed understand the chapter... but what is the use? Maybe we (the author and me) do not have the same way of thinking...
Another bad point is that there is no implementation. So if you are blocked somewhere you are dead.
Moreover the authors spend 16 chapter of 18 on equities and 2 on interest rate. But this last field correspond to 90% of the market! ...
Well,..., However,... not so bad ... so, 3 stars
This is a highly recommended work for any quant........2005-06-18
As I write this in June of 2005, quantitative finance has grown up. What was once a cross-over subfield of finance with a veneer of mathematics is now a field unto itself, and hence, in the past decade there have been an explosion of books which often replicate or restate what has been said before with little new to add. Also, there remains an unforgiving gap between introductory texts that are too superficial and specialists' mathematics books that are rigorous and difficult works beyond the commitment for mastery of the busy, intelligent, practical front-line quant. In addition, works that were once adequate are now simplistic and under serve their readers by lulling them into false confidence. Into this fray Dr. Mark S. Joshi's "The Concepts and Practice of Mathematical Finance" enters with a modern voice and delivers what previous texts have only promised and failed to. The work lives up to its title by presenting both concepts and practicalities, and makes other works that do neither well obsolete. Those familiar with my other reviews on quantitative finance texts know that I place a premium on clarity, and on this front Joshi deserves six stars, for he is a master of what William Strunk called "the plain style." I am always sensitive to the fact that many of the world's best quants come from nations where English is not the first language. Readers from China, France, Germany, Greece, Italy, Norway, Sweden, Russia and eastern Europe will enjoy Joshi's clarity and find his English easy to follow. It would be impossible to cover everything in quanfin in a single volume, however there is nothing horribly glossed over here and neither is there a single wasted word or equation.
I recommend Amazon review readers refer to the table of contents in the "Look Inside" feature to see what Joshi covers, but my own highlight is how welcome it is that Joshi focuses on risk from the very first word. Since Louis Bachelier risk measurement is what separates quantitative finance from "finance." Other books, including some quantitative finance works, start with cash flows, valuation, and discounting, and only add risk as an antecedent. Joshi correctly emphasizes risk first, last, and always, and for that elevation alone his work deserves five stars. From this foundation Joshi then covers very well pricing methods and arbitrage, simple and high dimensional trees, and the useful shortcuts of Ito calculus that makes tractable Zeno's paradox. Joshi also covers risk neutral and martingale methods, continuous barrier options, multi-look exotic options and incomplete markets and jump processes with an aim of showing these as typical problems for the working quant. Joshi's own references, index, and footnotes testify that by no means is he offering the first, nor the last, word on these knotty subjects, but his treatment is welcome just the same.
The target audience who would benefit from this text over others is four-fold. The primary audience is for first semester students in a graduate financial engineering program, for Joshi's "Concepts and Practice" will be handy throughout his or her studies and career. For those students unsure of their skills and with a limited budget considering between this and an introductory quantitative finance text I recommend Joshi over, say, Wilmott, for this work is more rigorous and in the long run will provide the better value as a practical companion. Within this audience I include professors looking for a high level foundational text for teaching practical risk management and derivatives pricing: this is the book to adopt, yes, even over Hull.
The second audience is for those trained in other science fields: pure mathematics, statistics, physics, etc. who are moving to finance jobs. This volume is an easy "one-stop shop" for you to re-tool your own background towards those topics and techniques used on a quant desk. While by no means covering everything, Joshi speaks your language and after digesting this work all else will fall into place and be understood and used with greater efficiency.
The third and broadest audience is one I am a member of: the already trained and practical "quant." Why should we need this book? My observation is that between reading (for example) Hull and Wilmott, Joshi's "Concepts" unavoidably covers many of the same topics, but also some things they do not and in ways they never could. Joshi is an expert practitioner at the top of his art, and that practical spirit is in every single page. For example, while Hull and Wilmott cover the concept and mathematics of stochastic volatility, Joshi writes from the point of view of the coding quant and discusses the issues of implementation. Joshi's "Concepts and Practice" serves a two fold purpose for a qaunt: it provides an additional voice and explanation of inescapably fundamental material, while bridging the gap of technical deployment for front line practitioners. This is not to say that Joshi offers us up a cookbook, for by no means is this such. Anyone who thinks they can simply buy this book and in a sleepy afternoon plug away code and technique and be done is missing the point: for this is a teaching text. Moreover, each house and set of problems and instruments and structured products to offer are different, to say nothing of the platforms one will be working on. That is why they call it "work." Therefore the practical quant should look to this text as a reference guidebook in a tool box.
As a fourth audience I cautiously recommend this book for those who are going into exotic product sales, but only those who have a good grounding in upper level calculus, linear and matrix algebra, time series analysis, and trees. Why? Simply put, you will be offering products built by quants who simply assume the knowledge in this book is a given. In addition, your better clients will (or should) have quants speaking this language, and the greater your own understanding of the concerns of your team and your clients the better your sales. If this work is too rigorous, then Wilmott's "Introduction to Quantitative Finance" quickly followed by Joshi's "Concepts and Techniques" is the course to follow.
Who is this work not for? Here are some tests. If you are a quant who can type at five lines of code a minute and can read Shreve and Karatzas drinking beer, then this work is too redundant for you. On my desk is a paper on a stochastic process with drift and viscosity under regime switching. If you are reading the same journal, then this work is too simple for you. If you have no idea what I've written about in the past three sentences, then this work is too hard for you.
In summary, Dr. Mark Joshi advances his excellent reputation as an intelligent, practical, and generous quant in offering "The Concepts and Practice of Mathematical Finance" and I recommend this book's wide adoption in graduate programs and its addition to reference libraries.
Book Description
Finance is one of the fastest growing areas in the modern banking and corporate world. This, together with the sophistication of modern financial products, provides a rapidly growing impetus for new mathematical models and modern mathematical methods. Indeed, the area is an expanding source for novel and relevant "real-world" mathematics. In this book, the authors describe the modeling of financial derivative products from an applied mathematician's viewpoint, from modeling to analysis to elementary computation. The authors present a unified approach to modeling derivative products as partial differential equations, using numerical solutions where appropriate. The authors assume some mathematical background, but provide clear explanations for material beyond elementary calculus, probability, and algebra. This volume will become the standard introduction for advanced undergraduate students to this exciting new field.
Customer Reviews:
Good Buy.......2007-08-29
maps one to one with many chapters in Hull. more elaborate derivations than Hull. Fixed income area treatment is very slim though. Good Buy for the Price.
Okay but not an introduction.......2006-07-31
If you want an introduction, read another book like Hull. If you want to learn how to apply Partial Differential Equations (PDEs) approach to finance then it is a useful book. However, it is better to read an elementary PDEs book before reading this book. At least, learn how to solve parabolic PDEs analytically because the technical notes in the book would not help much.
Introduction to partial differential equations in finance.......2005-10-13
This book treats only the partial differential equations
in Finance and how to treat them using Finite Differences
and Tree. For this purpose it is very well written and
understandable. A very good beginning for student. Even
undergraduate.
Now after reading it you should understand the martingales reading the baxter and how to implement Monte Carlo using, for example Glasserman (see my reviews)
A good introduction to the PDE approach.......2005-10-10
Contrary to what many readers believe, this book explains the pricing of derivatives much better than Hull. Hull gives an overview of the mechanics and properties of the derivative pricing industry, along with its pricing methodologies, and this book provides an in depth method to one of the pricing methods.
Financial derivatives can be priced by a wide range of methodologies, among some the elegant equivalent martingale measure approach (or risk-neutral pricing), replication, multinomial tree approximation, Monte Carlo simulation, partial differential equations etc etc.
This book gives an excellent introduction, and an insight to the PDE approach. Although being a big fan of the Girsanov-change-of-measure method myself, these analytical methods often fail in the valuation of highly complex derivatives like the exotics. Pricing americans prove to be hard and inefficient too, even with simulation and the risk-neutral approach.
This is where PDE methods come in. Since most derivatives (or term structures) have a PDE describing its evolution, solving the PDE seems to be a good (or sometimes the best) way, no matter how complex the derivative can get. PDEs on the other hand, have very robust and easy methods for solving. Therefore, this book brings the reader through basic PDE solving methods, analytical solutions, techniques for fast and efficient numerical approximations as well as rigorous technical explanations for some of the mathematics of partial differential equations (which arise in the financial industry).
The authors are famous for their research in the field of Industrial and Applied Mathematics, and this book continues to be a classic for undergraduates in mathematics in Oxford. If you want to have an overview of the pde approach to option valuation, without the hassle of learning up Radon-Nikodým and martingales, I highly recommend this book!
waste of time.......2005-03-10
This book is very bad, lacks almost everything you can think of, but if you don't know any better you probably won't care. It certainly needs to be supplemented by a respectable book if you want to learn derivatives (c.f. Hull's textbook, for example), and on the other hand, the math isn't rigorous at all, so you'll need a book on stochastic calculus (e.g. Michael Steele's, actually there are tons of better books out there, it's not hard to find better).
Book Description
Implementing Derivatives Models Les Clewlow and Chris Strickland Derivatives markets, particularly the over-the-counter market in complex or exotic options, are continuing to expand rapidly on a global scale, However, the availability of information regarding the theory and applications of the numerical techniques required to succeed in these markets is limited. This lack of information is extremely damaging to all kinds of financial institutions and consequently there is enormous demand for a source of sound numerical methods for pricing and hedging. Implementing Derivatives Models answers this demand, providing comprehensive coverage of practical pricing and hedging techniques for complex options. Highly accessible to practitioners seeking the latest methods and uses of models, including
* The Binomial Method
* Trinomial Trees and Finite Difference Methods
* Monte Carlo Simulation
* Implied Trees and Exotic Options
* Option Pricing, Hedging and Numerical Techniques for Pricing Interest Rate Derivatives
* Term Structure Consistent Short Rate Models
* The Heath, Jarrow and Morton Model
Implementing Derivatives Models is also a potent resource for financial academics who need to implement, compare, and empirically estimate the behaviour of various option pricing models. Finance/Investment
Customer Reviews:
Best book of implementing IR option models.......2007-09-18
Best book of implementing IR option models that I found while I was writing my masters thesis. It has full algorithms for most of the models presented and also simulations of the results. This book complemented with Interest-Rate Option Models: Understanding, Analysing, and Using Models for Exotic Interest-Rate Options (Wiley Series in Financial Engineering)is a good set to IR Option background.
Great book.......2007-01-31
Learnt a great deal from this book. I bought this because I had to learn some stuff for work, on a project. The book helped me learn the concept easily and understand the content.
good introduction.......2006-02-14
Very good introduction or summary for the most basic models that are used in the industry. However, it is not very detailed for more complicated models.
You can do it but you do not understand.......2005-10-11
This books is very valuable for equities derivatives. In particular the implementations are very clear even if it is only sketch and not real implementations.
Unfortunately it does not explain the real points behind (martingale, risk neutral). So you know how to do it but you do not know why you do it. For this you should read the Baxter.
Another bad point is that the interest rate derivatives are covered just for the single factor rate models and the HJM model and not the LIBOR-Market model which is the most useful model.
Fills a gap, but needs polish.......1999-10-13
Even more than Wilmott's book, C&S's book gets into the details of pricing derivatives. The choice of topics is truly excellent, and the copious source code included is a superb move. I am currently using this book (and others) to teach a class in Financial Programming.On the other hand, errors are frustratingly frequent. Not so much in the source code, but in the prose. It would be nice to see a floppy disk of code come with the book, a la Hull. There are no exercises in the text, which I consider to be an egregious error, because exercises are really the only way to learn the material.C&S try to make finite difference schemes seem less intimidating by expressing them in terms of probabilities (to stress the link between trees and more general lattices). This works OK for explicit schemes, but for the more important implicit and Crank Nicolson schemes is weird and unnatural. It fails to give the reader any clue as to how to do finite differencing on his own. (Their odd changes of variables don't help, either.) Wilmott's treatment of the subject of finite differencing is far superior.
Book Description
In the 2nd edition some sections of Part I are omitted for better readability, and a brand new chapter is devoted to volatility risk. As a consequence, hedging of plain-vanilla options and valuation of exotic options are no longer limited to the Black-Scholes framework with constant volatility.
The theme of stochastic volatility also reappears systematically in the second part of the book, which has been revised fundamentally, presenting much more detailed analyses of the various interest-rate models available: the authors' perspective throughout is that the choice of a model should be based on the reality of how a particular sector of the financial market functions, never neglecting to examine liquid primary and derivative assets and identifying the sources of trading risk associated. This long-awaited new edition of an outstandingly successful, well-established book, concentrating on the most pertinent and widely accepted modelling approaches, provides the reader with a text focused on practical rather than theoretical aspects of financial modelling.
Customer Reviews:
Excellent introductory book to financial math.......2006-11-03
This book takes you through the math of finance step-by-step, passing through very simple examples first and then slowly adding complexity to the models studied. It is written very clearly and the prerequisites to reading this book are only some basic notions of probabilities (sigma-fields, probability measures).
Sometimes, the problem with math books is that they are "dry" and contain only a succession of theorems and proofs. In this one, the authors make a point of explaining in detail how different theorems and models relate to each other, and make extensive comparisons between them so that you get a better feel for how they work in practice.
The book is primarily a math book and can be light on market specifics. Do not buy this book as a practical "howto" in derivatives trading.
At the Forefront of Modern Mathematical Finance.......2005-05-23
This advanced text provides an excellent account of the current state-of-the art of options pricing/hedging models and interest rate term structure models. The book is accessible to both advanced practitioners of mathematical finance as well as to pure researchers in the field.
The book is in written in a mathematical style and contains rigorous proofs of many results. However, the main focus of the text is to describe the frontier of knowledge in the subject. Each section contains copious references to the literature and is so current that several references are to working papers. Many sections detail open problems and other areas suitable for scholarly research.
In their second edition, the authors provide an extremely useful critique of each modeling paradigm that they investigate. They also provide evidence for their position in the form of literature references which instruct the reader as to the shortcomings/limitations of a particular model. This information should prove quite valuable to model practitioners and implementers.
The authors assume an advanced background from the field of stochastic analysis, although they do provide an appendix which summarizes key results needed from the field. For the stochastic calculus prerequisites, I recommend Rogers & Williams "Diffusions, Markov Processes and Martingales" volumes I and II. Suitable prerequisites are also covered by Karatzas and Shreve in "Brownian Motion and Stochastic Calculus" 2nd edition. A good foundation in arbitrage pricing theory is also needed. I recommend the nice treatment by Bjork in "Arbitrage Theory in Continuous Time" 2nd edition.
The book is divided into two parts. The first part deals with options pricing in equity markets. Chapter 1 sets premlinaries required for the arbitrage theoretic framework, while Chapter 2 has a very nice treatment of discrete time models and finite financial markets.
In Chapter 3, the authors develop the Black-Scholes model along with the Bachelier model using arbitrage techniques. The models are compared and used as benchmark continuous time models and form the basis for all subsequent analysis.
Chapter 4 provides a nice survey of techniques used to price/hedge options in foreign equity and currency markets. The authors assume familarity of the basic workings of foriegn markets.
Chapter 5 is a terrific chapter on valuing American-style options. The American call option is thoroughly studied and approximation techniques for the American put option are introduced. The explicit derivations of the formulas are referenced to the literature.
Chapter 6 provides an introduction to exotic options, although the authors vary their use of the term 'exotic' to meaning 'not a standard European-style or American-style' in this chapter to meaning 'no readily available liquid market' in Chapter 7. The descriptions are quite accessible and the basic properties of the options are described along with pricing formulas (assuming the Black-Scholes framework).
Chapter 7 provides as complete an accounting as I have ever seen of the generalizations of the Black-Scholes model and motivates this from the point of view of volatility surfaces. Many of the well-known models are studied in detail, such as CEV, local volatility, and mixture models. The strengths and weaknesses of each model are analyzed. The stochastic volatility models of Wiggins (via Orenstien-Uhlenbeck processes), Hull-White, and Heston are studied, as is the SABR model. The chapter wraps up with a study of the SIV models, describes how the stochastic volatility models can be obtained via limits of GARCH models and surveys Jump-diffusion processes and Levy processes.
The second part of the book is concerned with term structure models and interest rate derivatives. The authors are quite well-know for their many contributions to this study and their treatment is authoritative.
Martingales & Finance.......2003-04-12
I have used this book for two courses in my MSc degree in Financial Maths...well this book is hard to understand at first glance, but, once you are introduced with a good course on stochastic analysis and applied probability, this is an illuminating book...I particularly enjoyed the part on foreing equity derivatives and exotic derivatives.....Harmed with patience this is definitely the book by which you can effectively gain a sound a knowledge on modern mathematical finance theory....reading in conjunction with Bingham-Kiesel book, could help understanding the foundation of the subject.
yes, but ..........2000-03-17
I've been using this book on and off over the last year. At first I was very impressed with the level of detail in the mathematics, especially as it was the only book at the time focussing on risk-neutral methods and covering BGM. But I've become increasing disillusioned with it of late. It's difficult to explain, but although the whole book is written in traditional theorem-proof style, there are no real proofs! (I have a PhD in math and have done research for 10 years so I should know a little about proofs.) The only "proofs" provided are basically symbol shifting, but the heart of the math is strangely absent. This is especially strange given the Springer series in which it appears.
In short, if you want a catalogue of methods this book does the job, but if you want a deeper understanding try Lars Nielsens book.
excellent book for post-John-Hull readers.......1999-08-17
This book covers essentially everything needed for a serious financial math study. It captures the spirit of modern financial math. For people with math, physics or engineering background, when you feel comfortable woth John Hull's books, then this book is right one, and a must one.
Average customer rating:
- An excellent crash course in OOP
- Benchmark book on Computational Finance
- Full of OOP Wisdom!
- depends what you are looking at
- From particular to general: design patterns in c++
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C++ Design Patterns and Derivatives Pricing (Mathematics, Finance and Risk)
Mark S. Joshi
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ASIN: 0521832357 |
Book Description
Combining mathematical finance with C++ and object-oriented programming (00P), M. Joshi demonstrates the relevance and use of OOP in financial mathematics by describing how to use price derivatives to obtain reusable and extensible code. A large part of the book is devoted to designing reusable components which are then combined to build a Monte Carlo pricer for exotic equity derivatives. Readers knowing the basics of C++ and mathematical finance, but are unclear how to use OOP to implement models, will welcome this analysis.
Customer Reviews:
An excellent crash course in OOP.......2007-10-04
Do not be put off by the rich price/page-count multiple: it will take a lot of time and work to go through the book's 200 pages, and you won't regret the effort. You may be interested to know that Mark Joshi has devoted a section of his site to the book, complete with a forum for readers. Two warnings on what this book is not:
(1) It is not one's introduction to C++; you risk a brain aneurysm trying to learn C++ on the go.
(2) It's not a collection of ready-to-use code. (The reviewer complaining about lack of coverage of IR models misses the point completely).
Instead, it sets out to demonstrate why you need OOP, and does that in the context of a single, progressively expanding, exercise.
Benchmark book on Computational Finance.......2006-06-26
Mark has produced a marvel. The book introduces practical C++ programming with such spontaneity. The author sets the pitch beautifully with a step-by-step introduction of the need of advanced computing. It handholds reader as it expands from basic oops programming to designs and patterns in computing while mentioning rare tips on efficiency requirements when pricing derivatives versus robust programming.
The book is elegantly written with precise explanations and very concise (and very practical). It comes with the code as well.
As the other reviewer pointed out, the book has written for specific purpose and the focus is not diluted throughout (for example, it did not expand on quantitative issues which could have taken the book out of bounds which is a very big plus point). Even though the book is concise, it would require quite a lot of time to get the best out of it, because it is very dense on issues.
A must have book for anyone who is interested in Computational Finance (Quantitative Analyst/Developers, Financial Engineers, and Risk Managers). It filled a very big gap in this arena.
And this is written by a Practitioner Quant. Very well done Mark.
Full of OOP Wisdom!.......2005-10-15
In terms of programming concepts and OOP design for financial engineering, this book has no equals. We have Daniel Duffy's Financial Instrument Pricing Using C++, but it takes a different approach (i.e. generic programming based in STL). All through the book, the author introduces improvements sequentially and doesn't start from the best design from the outset in order to demonstrate the flaws of a less general/useful/reusable program. In this sense, this is mainly a conceptual book, not an example book. For example, it deals with and develops vanilla-option pricing using Monte Carlo simulation over the first five chapters. A reader looking for a cookbook that gives programs to implement a large number of financial-derivative models would be well-advised to look elsewhere (e.g. Justin London's Modeling Derivatives in C++). However, someone looking for OOP wisdom would be generously rewarded for buying this book.
depends what you are looking at.......2005-10-13
This small book (192 pages) is pretty expensive but if it brings you a lot it is OK.
It depends what you are looking at:
If you want a book "how to write a clean C++ program", this book is for you. The authors enhance the formal (and correct) writing you should have when coding.
If you are interested in understand and solve the various problems you encounter implementing derivatives with numerous examples, it is not the good book for you. There are few programs so few examples and solutions. Moreover I have to dig in his classes to understand them. I would have preferred static functions, even if I have to do a little work to implement them in my library.
However from my point of view, the biggest reproach to this book is that it does not treat the interest rate derivatives at all, which is really problematic.
So it was not really interesting. The Clewlow was much better for me.
From particular to general: design patterns in c++.......2005-08-23
In principle, it seems that this book is a very specialized one: design patterns in derivatives pricing. However, Mark Joshi has been able to give ideas that are generalizable to many other fields. For example, I have developed a trading simulator in c++ using several of the ideas of the book. The ideas in the book are so general, that very often one can do simply a copy and paste and just change the names of the classes and variables.
The only complaint to the writer is that he does not supply the answers to the questions of the book. This is standard practice in academia (and there is a good reason for it), but this book is designed mainly for practitioners, that probably do not have too much time to solve difficult questions.
The writer is widely known in forums like nuclearphynance and wilmott for his deep comments about derivatives pricing.
Disclosure: I only know Mark Joshi because I have sent him an email with some questions about the book. He very kindly has replied to me. I do not have any other kind of relation with him.
Book Description
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. The first volume presents the binomial asset-pricing model primarily as a vehicle for introducing in the simple setting the concepts needed for the continuous-time theory in the second volume.
Chapter summaries and detailed illustrations are included. Classroom tested exercises conclude every chapter. Some of these extend the theory and others are drawn from practical problems in quantitative finance.
Advanced undergraduates and Masters level students 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.
Customer Reviews:
Good book.......2007-10-01
I agree that most concepts are clearly explained....emphasis on *most*. OK, I'll nitpick. And I admit I'm nitpicking. For example, the proof of Jensen's inequality (which he oddly dives into without defining convex functions), is rather non-intuitive, and seems to be more an appeal to the accompanying picture rather than a proof. The proof given under the Wikipedia entry for "Jensen's Inequality" is much clearer, and makes much more sense, at least to my way of thinking. Other than the occassional gaffe such as this, it is a highly readable, informative, and dare I say enjoyable text!
Nice book.......2007-03-08
I think its a very good book for fundamental concepts in stocastic calculus.
Good for finanical mathematics graduates.......2007-01-10
clear explanations on binomial models for European and American options. Abstract concepts also included such as change of measures, martingales, stopping times. Proofs in book assumed no knowledge on sigma fields or measure theory.
Very good to understand the basics of pricing-theory........2006-03-04
This book is great book about theory. Using a simple binomial tree as asset evolution model, all key notions are introduced. Neutral-risk probabilities come up in a simple, natural way, and I never found such a clear explanation of the the change of measure and its meaning in finances. Examples help to understand every ussue.
The only case in which you should not buy it: if you are looking for real-market instruments and techniques.
Interesting Read.......2006-02-17
I found this book to be a very interesting and fun read. A very helpful introduction to binomimal models and basic stopping time principals. It also provides a great refresher to Martingale principals. If you are having trouble with Shreve's volume II then have a look at this book first.
Average customer rating:
- Most impressive extension of the term
- Integrated treatment
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Financial Engineering and Computation: Principles, Mathematics, and Algorithms
Yuh-Dauh Lyuu
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ASIN: 052178171X |
Book Description
Nowadays students and professionals intending to work in any area of finance must master not only advanced concepts and mathematical models but also learn how to implement these models computationally. This comprehensive text combines the theory and mathematics behind financial engineering with an emphasis on computation, in keeping with the way financial engineering is practiced in today's capital markets. Unlike most books on investments, financial engineering, or derivative securities, the book starts from very basic ideas in finance and gradually builds up the theory. It offers a thorough grounding in the subject for MBAs in finance, students of engineering and sciences who are pursuing a career in finance, researchers in computational finance, system analysts, and financial engineers. Along with the theory, the author presents numerous algorithms for pricing, risk management, and portfolio management. The emphasis is on pricing financial and derivative securities: bonds, options, futures, forwards, interest rate derivatives, mortgage-backed securities, bonds with embedded options, and more. Each instrument is treated in a short, self-contained chapter for ready reference use. Many of these algorithms are coded in Java as programs for the Web, available from the book's home page (www.csie.ntu.edu/~lyuu/Capitals/capitals.htm)
Customer Reviews:
Most impressive extension of the term.......2004-02-17
The term financial engineering is appearing increasingly in the title of various works. What it actually means remains nebulous, for even natural sciences and engineering remain irresolvable at their respective cores. This is evidently addressing another boon of the digital age, where equations and approximations can be done both automatically, and with extreme rapidity. It is only natural for the advantages of this to trickle into research of finance and economics, only now it is becoming a steady stream, and, with the inclusion of this work, a most sound one at that.
It is inferred that the author views this phrase, "financial engineering," as the level of control over precision of computation, and then the resulting accuracy of projected results (with an occasional forecast of unanticipated outcome). His credentials validate this as well.
The tools utilized include the complete discipline of algorithmics, and numerous branches of mathematics, along with tools assisting with and automating graphics and formatting, such as Latex and Mathematica, all channelled into this most profitable and competitive field of finance.
The approach for most sections begins with a brief discussion of motivation, typically condensed to one or a few paragraphs, followed by an equation representing an historical approach to the problem. This is followed by one or more expanded sections building algorithms, expressed in mathematics and pseudocode, as well as plots of typical results. The section then concludes with a broader discussion of how computation and finance become intertwined through this particular application. The author is extremely well versed in both. There are numerous exercises as well.
The book has the look and feel of an adept computer scientist, applying his honed skills to the financial realm. The typesetting is extremely well done, and even for sections initially unfamiliar, the reader feels confident and motivated to become fluent in time. Many of the exercises have solutions provided in an appendix.
At the time of its original publish date the book was unique in the field due to its approach and concise depth of mathematics, all available from a single resource. The author clearly exerted an extraordinary amount of time and energy to producing this work, and each section attests to this meticulous attention detail.
This work is highly-recommended as a reference, for a plethora of well-constructed algorithms in pseudocode are provided; Java examples are also provided via a website. Some considerable level of sophistication in topics typically relegated to computer science and mathematics are required, for which the intrepid reader can find additional resources. When time and motivation are sufficient, there is a wealth of mathematically sound information, providing depth of understanding and a mature foundation to build upon just what financial engineering means.
Integrated treatment.......2002-12-02
The text covers quite a broad range of topics. It assumes that the reader has a fairly good grasp of statistics and mathematics (senior undergraduate level). Introductory financial material reads ok. The algorithmic approach is useful and so are the answers to select problems. However, some could find the material too tightly packed.
Book Description
This book is intended for use in a rigorous introductory PhD level course in econometrics, or in a field course in econometric theory. It covers the measure-theoretical foundation of probability theory, the multivariate normal distribution with its application to classical linear regression analysis, various laws of large numbers, central limit theorems and related results for independent random variables as well as for stationary time series, with applications to asymptotic inference of M-estimators, and maximum likelihood theory. Some chapters have their own appendices containing the more advanced topics and/or difficult proofs. Moreover, there are three appendices with material that is supposed to be known. Appendix I contains a comprehensive review of linear algebra, including all the proofs. Appendix II reviews a variety of mathematical topics and concepts that are used throughout the main text, and Appendix III reviews complex analysis. Therefore, this book is uniquely self-contained.
Customer Reviews:
Highly recommended - a joy to read . . ........2005-01-07
If you are looking for an introduction to financial option valuation that is well-written and well-referenced than this book is for you. Prof. Higham is an excellent author (I highly recommend his other books Learning LaTeX and MATLAB Guide) and so anything he writes is a joy to read. His latest book is no exception. It is full of figures that help bring the equations and the ideas to life. Like many of his technical papers (which I also recommend you read - they are available at his website), he has incorporated MATLAB (a powerful matrix manipulation and numerical simulation tool) codes throughout the book (not only does he provide code listings but you can actually download the codes and run them assuming you own the software or have a license - I have!). The codes are a great way to see the equations in practice if you don't have MATLAB and experiment with some of the key parameters yourself if you do. Regarding the subject of the book itself, let me say that I am in the mechanical engineering field and can barely balance my checkbook - ok, my wife does it for me) but I am interested in all things mathematical and find the subject of option valuation (and the possibility of making some extra money) enticing. The book clearly introduces topics related to random numbers and stochastics, as well as finite-difference approximations for partial differential equations. The ultimate goal is the Black-Scholes PDE which is treated in the later half of the book. Monte Carlo simulation techniques as applied to finance are covered as well in several chapters. What I really enjoy about this book (and his other books) is the way he actually tries to teach and advise the reader - a good writer must be sensitive to his/her audience - and this is most appreciated by myself and others I am sure. The bottomline is that this is the first book to own if you want to get into the field of computational finance (his references tell you where to go next). I highly recommend it.
A good hands-on intro to option valuation.......2004-12-05
There are a lot of derivatives books out there - most of them follow the same approach. This one's different: no complicated measure-theoretic probability theory (of absolutely no use to practitioners), but lots of hands-on Matlab examples. A very reasonable price too. My only suggestion to the author would be to provide more appropriate names to his Matlab functions (instead of chapter numbers) - but this can easily be changed by the reader.
Book Description
In An Engine, Not a Camera, Donald MacKenzie argues that the emergence of modern economic theories of finance affected financial markets in fundamental ways. These new, Nobel Prize-winning theories, based on elegant mathematical models of markets, were not simply external analyses but intrinsic parts of economic processes.
Paraphrasing Milton Friedman, MacKenzie says that economic models are an engine of inquiry rather than a camera to reproduce empirical facts. More than that, the emergence of an authoritative theory of financial markets altered those markets fundamentally. For example, in 1970, there was almost no trading in financial derivatives such as "futures." By June of 2004, derivatives contracts totaling $273 trillion were outstanding worldwide. MacKenzie suggests that this growth could never have happened without the development of theories that gave derivatives legitimacy and explained their complexities.
MacKenzie examines the role played by finance theory in the two most serious crises to hit the world’s financial markets in recent years: the stock market crash of 1987 and the market turmoil that engulfed the hedge fund Long-Term Capital Management in 1998. He also looks at finance theory that is somewhat beyond the mainstream--chaos theorist Benoit Mandelbrot’s model of âwildâ randomness. MacKenzie’s pioneering work in the social studies of finance will interest anyone who wants to understand how America’s financial markets have grown into their current form.
Customer Reviews:
A plausible case.......2007-08-29
Many financial analysts and financial journalists have pointed to quantitative trading and the subprime mortgage markets as being the major cause behind the extreme volatility in the financial markets in the summer of 2007. This book therefore seems fitting for this particular time in financial history, if only at a bare minimum to educate the reader about the use of mathematical modeling in financial analysis and financial engineering. As the subtitle of the book indicates, the author's main thesis is that the use of mathematical models can actually change the dynamics of the markets themselves, moving them possibly to territories even more uncertain that they were invented to describe. Quantitative trading, now done by most of the major players in the financial markets, is dependent of course on mathematical modeling, some of which uses highly sophisticated reasoning patterns and artificial intelligence. Most of these models are proprietary, and therefore one cannot ascertain their efficacy in the acquisition of wealth for the organizations that deploy them. However, with a little pertinacity one can acquire a good understanding of their workings by studying the academic literature.
Some of the predominant models in the public domain are discussed in this book, mostly from an historical perspective but the author inserts some of the relevant mathematics in its appendices for the more mathematically sophisticated reader. In general the author makes a plausible case for his main thesis, but at times his conclusions are based on mere anecdotes, and he makes the typical mistake of imputing power and influence to individuals that is unsubstantiated. It is very tempting, especially among those individuals or institutions that are involved in trading, or even responsible for innovations in the same, to believe that they are the cause for some of volatility in the financial markets. But such claims, even if they seem reasonable or intuitively clear, must be substantiated with careful statistical analysis, which can be time-consuming and difficult, and few individuals it seems are willing to devote themselves to such a project. The author though is aware of this, for he states very early on in the book that historical sources may not be sufficient to allow one to decide if the influences are real. In addition, he cautions the reader to "look not just at what participants say and write but also at whether the processes in question involve procedures and material devices that incorporate economics."
The author labels the idea that economics as an academic project is actually part of economic processes the `performativity of economics', which he further breaks down into subclasses that serve to clarify the distinctions he wishes to make. One of these is more of a passive notion, called "generic" performativity, which is used to describe the participant's use of economic theories or data without emphasizing their effects on economic processes. If such effects take place, this is called "effective" performativity, which is then specialized to "Barnesian" performativity. The latter is used to describe the situations where the practical use of economic theory makes economic processes resemble what they are described to be by economic theory. Barnesian performativity is to be contrasted with `counterperformativity' where the actual use of economic models makes economic processes not resemble their description by these models. The author discusses how to detect Barnesian performativity, but warns of the difficulty in proving that movements in prices are following certain model predictions.
But aside from the qualitative/historical emphasis that the author makes in this book and the small number of unsubstantiated claims of model-market influence, the reader will take away a better understanding of such topics as the capital asset pricing model, the Black-Scholes-Merton model of option pricing, the Modigliani-Miller theory of capital structure, a description of Levy processes and their role in econometrics, and most interestingly, a different explanation for the demise of Long Term Capital Management. All of these topics, coupled with the intellectual honesty and literary skill of the author, make this book a highly interesting contribution to the financial literature.
An Insightful Look into Finance's Twin Roles.......2006-12-19
Both the science and the art and practice of finance have experienced phenomenal growth since the 1970s.
As a science, finance has evolved from a descriptive outpost on the economic frontiers to become of that discipline's cent
Introduction to the Mathematics of Financial Derivatives
Stochastic Calculus for Finance I: The Binomial Asset Pricing Model (Springer Finance)
Financial Calculus : An Introduction to Derivative Pricing
Interest Rate Models - Theory and Practice: With Smile, Inflation and Credit (Springer Finance)
