Rating: 
Summary: Not very clear on the subject just cute drawings...
Review: This book doesn't explain any "hard stff" very well.A goal of Wilmott's book is to "gently" introduce Quantitative finance, derivatives and their pricing, to non-math majors. Wilmott puts cute drawings to help the reader feel the subject matter is not so scary, but I need the simplest clearest
writting possible and many simple(as possible) examples, not just cute pictures. In his chapter that introduces PDE's , Wilmott starts talking "engineer ease" within the first few sentences, and I
assume Wilmott thinks he is being clear to the non-quant reader. Wrong! The chapter has too much jargon. The book doesn't go too deep into math, but it's still not
clear on the material it attempts to explain. However, the CD has some nice Excel examples on pricing,
provided you are already familiar with the pricing models used. Wilmott, has several books on Finance, but many of them are
just repeats of his earlier books but with some chapters taken out!...
Rating: 
Summary: Good set of books...but needs exercises
Review: This book is a lengthy overview of some modern techniques in financial engineering. If viewed from the standpoint of applications of partial differential equations to finance, then this book is a reasonably complete treatment. The author does spend a great deal of time on the more bread-and-butter topics of financial modeling and less on more specialized topics, as for example weather and energy derivatives, where the use of partial differential equations is of upmost importance. There are of course alternative approaches to financial modeling from the mathematical perspective, such as techniques from the theory of stochastic processes and martingales, but a consideration of such techniques would swell the book to over twice the size, and there are other good books that cover thses approaches in detail. The author uses Visual Basic and Excel spreadsheets to compute the relevant financial quantities, and given the popularity of spreadsheets in finance, this is appropriate. The numerical solution of partial differential equations is most efficiently done using C (or Fortran) and no doubt the author does recognize this, for he does mention translating existing code in C to Visual Basic. My only major objection to the book is the lack of exercises, which were a major selling point to me in the author's earlier book on derivatives. Having such exercises is indispensable in understanding results of this nature. The first few chapters of Volume 1 give an elementary introduction to the theory of derivatives and stochastic calculus. The author does remain concrete in his explanations, and he gives a fairly straightforward derivation of the Black-Scholes equation. This is followed by a very quick discussion of Green's function solutions of the equation and introduction to the Greeks. Generalizations of the Black-Scholes model are discussed later, in the context of dividends, foreign currency, and time-dependent parameters. The author does not give a critical analysis of the Black-Scholes equation in these chapters. This would have been useful to both the practitioner and a newcomer to the field. Also, the Black-Scholes can be derived in many different ways, and it would have been instructive to see some of these alternative derivations. There are derivations of the Black-Scholes equations based on concepts from information theory, and these shed light on the limitations of this equation. All of the concepts in these chapters can be found in the author's earlier book on derivatives. The second half of the first volume is an overview of the mathematical techniques used to deal with path-dependent and "exotic" options. Consultation of the references is mandatory for a complete understanding of the ideas in these chapters, for the author is a little lacking on details. In addition, more discussion is needed on case history validation of the many formulas given in these chapters: are these formulas useful in practice? The author also introduces some new concepts in this volume that are not in the derivatives book, one being stochastic control. Also, the author introduces a similarity reduction technique for partial differential equations that is very much like the techniques used in neutron reactor physics. Physicists-turned-financial-engineers will see the similarity between these two approaches. The last part of the first volume deals with extending Black-Scholes. The author discusses the problems with Black-Scholes but his treatment is too hurried. A better approach might have been to give (historical) examples of what might happen, from an investment/risk management perspective, if the assumptions of Black-Scholes are followed to the letter. He does give references though for a more in-depth discussion. Volatility surfaces, viz a viz the Fokker-Planck equation, are discussed here, and effectively. Again, the physicist reader will pick up on the dialog immediately. Information-theoretic techniques, via entropy minimization, are used, interestingly. It is refreshing to see in this part that the author gets down to an empirical analysis of some important issues (volatility for example). The second volume is somewhat more specialized that the first and outlines in the first chapters fixed income products, swaps, and interest rate derivatives. Phase plane analysis is employed in the discussion on multi-factor interest rate modeling. The treatment here is too curt and needs considerable expansion. The theory of stability of fixed points under the influence of noise is non-trivial and requires careful consideration. A departure from the framework of partial differential equations occurs in the discussion of the Heath, Jarrow, and Morton model. Noting that this model is non-Markovian, he introduces Monte Carlo simulation as a technique to calculate the expected present values. He remarks that the simulation time to carry this out is very long. The sluggishness of Monte Carlo simulations in this model and others in financial engineering has motivated many researchers and start-up firms to devise techniques to speed up the simulations. Indeed, a whole industry has grown in recent years offering packages and algorithms to speed up Monte Carlo. Risk and portfolio management are also discussed in this volume, beginning with modern portfolio theory. The most interesting and well-written part is on asset allocation in continuous time. Energy derivatives, an up-and-coming field are also discussed. The author is un-sure of himself in this chapter, but he does give a general but elementary introduction to the subject. This is an area that needs a lot more investigation and research given its importance. The last part of the book addresses numerical methods, and there is some source code in Visual Basic. Monte Carlo simulation is discussed again, along with an introduction to low-discrepancy sequences. These sequences have been used extensively in recent years to improve the efficacy of Monte Carlo simulations. The author's treatment is very terse but he does give many references. The author has done a fine job in these two volumes, and he spices up the reading with a litte humour, which does not detract at all from the seriousness of the topics, but instead makes for more enjoyable reading.
Rating: 
Summary: Well thought out and easy to follow
Review: This book is for those who like their finance applied. The pde approach to finance is far more powerful than the relatively useless martingale idea. If you don't believe me, then read this book. There are many models that a probability theorist wouldn't even understand never mind be able to solve but Wilmott takes them in his stride. The material is well thought out, and easy to digest. At every step Wilmott likes to share his worries about popular models. This is a result of his practitioner experience. (BTW His website rocks!)
Rating:
Summary: Quantitative Finance for Everyone
Review: This is a breakthrough book in quantitative finance: comprehensive, up-to-date, mathematically rigorous, fun and easy to read and eminently practical. It covers all aspects of quantitative finance, each area progresses from abstract mathematical theory to real application. The author has used sidebars, graphics and cartoons to ease the reader along. This is essential because most readers will be interested in only certain aspects: some will just want a formula, others want to understand the intuition behind a concept, still others will want to see a practical example. The arrangement makes it easy to locate what you need. It could be read from cover-to-cover by someone who wanted to teach themselves to be a quantitative finance expert, or as a reference book, or anything in between. It replaces a bookshelf full of quantitative finance books.
Rating:
Summary: Insufficient
Review: This is not as good as Wilmott's earlier work, and even that could have benefited from better definition of terms. Wilmott needs to brush up on the latest techniques and talk to some practitioners to learn how to apply math to real world examples. It seems there is a lack of depth of understanding evidenced by the writing. The sections of self-expose are an embarrassment.
Rating:
Summary: Old Material
Review: This is recycled Wilmott, but not even as good as earlier work. His first book was better, probably because his co-authors talked some sense into him. His personal anecdotes demonstrate a low emotional IQ. It is as if Wilmott thinks that if readers agree with the finance they must agree with his incessant and juvenile self-regard. My reaction to the inappropriate self-expose was: "Who cares? Get some friends, they might help on the financial aspects of this book". Wilmott's financial IQ is only average, if this book is to be the evidence. It seems Wilmott isn't up on the latest techniques, or can't be bothered to research them. Stochastic calculus for example. Lack of real world practical examples demonstrates lack of knowledge of how financial instruments work in practice.
Rating:
Summary: Throw all your other quant books away!
Review: This is the only quantitative finance book you will ever need, whether you are a student or a rocket scientist. This is an update of his book Derivatives. It is written so as to make finance easy and fun. Most books seem to want to make this subject as complicated as possible (why?). But if you read this you will realise how straightforward quantitative finance really is. One of the best things about it is that the author tells you what he thinks about different models. The book is not just another no brain copy of other text books. Wilmott's books are always easy to read with some jokes thrown in. A small percentage of people don't seem to appreciate this style, but that is more a bad reflection on them than on Wilmott!
Rating:
Summary: Wilmott is now the quant to beat
Review: Who should buy this book? The real question is who shouldn't buy this book. For the Phd Quant this book is a tour de force in how to explain technical topics clearly and concisely. For the newbie, this is simply the lowest barrier to entry available. Interestingly, QF does not "replace" a bookshelf of quant books -- rather it nicely compliments many that you're likely to have such as Taleb, Neftci etc. As sales of QF increase, it is likely that readers will be less likely to buy a derivatives book that is over their head. Volume 1 covers 37 chapters of the equities/currency derivatives world, While Volume 2 covers the Fixed Income World, Risk Measurement , Miscellaneous Topics and Numerical Methods. Chapter 10 has an excellent and all too rare discussion of Probability Density Functions and First Exit Times, whilst Chapter 14 has an outstanding Trading Game invented by one of Paul Wilmott's former students. Chapters 16 through 21 cover the Path Dependent world while the balance of the chapters cover extensions to Black Scholes. Its in these sections that Wilmott delivers some surprising thoughts and insights into Stochastic Volatility Surfaces that are currently the rage. Throughout both volumes I continue to be astonished at how clear, concise and effective his explanations are. The icons are not annoying at all -- rather I found myself skimming the icons to find out what was required to be committed to memory in each section versus what was background. As obvious as it sounds, a glaring weakness in Derivatives texts is the inability of authors to elucidate what must be memorized as rote for the student to make further progress. Paul's easy to follow icons lay out a precise plan of study. I can't say enough about what a leap this is over competing texts. In Volume 2, Chapters 38 through 50 cover models that Wilmott likes as well as ones that he doesn't [again, a rather novel approach] Some surprises in Chapters 51 and 52 are an excellent overview of Portfolio Management and a survey of Robert Merton's Asset Allocation in Continuous Time. Sprinkle in outstanding chapters on Derivatives Fiascos, Real Options, Energy Derivatives and 5 chapters on Numerical Methods and an astonishing survey of Quantitative Finance is complete. Throughout the books Paul's practical use of Term Sheets and quick and dirty VB code and spreadsheet tricks [you just have to see his Excel shortcut for approximating the Normal distribution] leave the reader constantly wanting to rev ahead. To round out a tremendous effort, Wilmott also pays homage to authors that he's found helpful and he's generous with suggestions on further reading. This builds sorely needed confidence when attempting new material. The comparison with Richard Feynman is apt but misses an important detail...Feynman was not noted for turning out hordes of talented understudies. Paul Wilmott has turned out enough talented graduate students that maybe he will be a bona fide cult leader someday.
Rating:
Summary: Superficial coverage...
Review: Wilmotts book is an incomplete treatment of a wide variety of financial problems. And most of problems are based on the PDE approach,
instead of the more powerful risk-neutral/martingale approach.
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