Paul Wilmott on Quantitative Finance, 2 Volume Set

Saw the book at a library and decided that it was worth owning as a reference. It more than met expectations.

I bough 20 books before this set. I was wondering if the older Derivatives book was really worth $450 used without the CD. This is the place to start. It is written with style and humor coupled with a pace that is simple to adjust to. I judge a book by how many equations it has - more is BETTER! This set strikes a balance. The exposition is solid. It covers many specialized topics like Energy Derivatives (just a taste, mind you, but it is there to get us thinking). I guess the bottom line is this book allowed me to start thinking like a Financial Quant and less like a mathematical physicist. I have gotten much more out of the other more mathematical works because I understand how the Quants think. I still like The Physics of Finance by Ilinsky. This is more than the past Derivatives book (that makes up the first 65% of volume 1) and sets a real tone to understanding - this is just what I was looking for as I re-tool. Buy this FIRST. Read the TOC. Get moving!

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.

Another overpriced useless book by Mr. Wilmott. This book does not have any useful information about the practical application of quantitative finance. It's not surprising since author never worked as a practitioner. The book spends too much time on Black Scholes framework for exotic options. Most of the problems and examples considered there have exactly zero practical and even academic value. It looks like the target audience for this book are people who want to enter finance. Spending time and money on reading this book will not get them any closer to their goal.

A lot of chapters, a lot of topics covered. Wilmott manages to cover just about everything you need to know about mathematical finance. However with 67 chapters squeezed into 1100 pages - he only _just_ manages to touch on everything. He is also trapped in the methodological past - he reduces everything down to the PDE and looks to solve that. The more recent methods, involving Martingale representations, are not only much simpler (no PDEs) but are also more powerful. Yet Wilmott continues to ignore these methods. Having said that, he does cover everything else you might ever want to know. Use this book as a good dictionary. If you see a term used that you do not know - look it up in Wilmott. Then if you need to know details about that topic, go elsewhere.

After reading the reviews by various readers, I bought the text. After reading it, I must commend Paul Wilmott for his work. The text reads well and the icons are particularly interesting, and yes, helpful in identifying critical matter. Some reviewers found his entertaining writing style to be distracting; I didn't. I believe it's okay to chuckle from time to time. Others found his use of different symbology confusing. Learning and applying derivatives is not about a particular symbol, rather it's about the equation form and meaning. The use of different symbols from that of other authors served to reinforce meaning and form to me. And still, others found the lack of examples to be unacceptable. I agree to some degree, but referring to texts and examples by other authors (e.g., Hull, Prisman, Kolb) helped me to appreciate the application as well as meaning and form. The text is designed for serious study and was not a "quick read" for me. Hope this helps you decide to buy this text. I think it is worth the investment...only if you have additional texts on your bookshelf.