Stochastic Simulation and Applications in Finance with MATLAB Programs 1st Edition

I wonder why Wiley editors decided to present a textbook for a master's course in math finance as an authority on Matlab or simulation.Use of Matlab is limited to matrix multiplication and inversion and simple within-matrix recursions. On simulation, discussion is adequate but nowhere near Glasserman or Iacus. The chapter on "solution of stochastic differential equations" has nothing of the kind. The one on fixed-income models shows simple simulations and closed-form calculations.On the other hand, you get a solid, thoroughly hands-on intermediate math-finance textbook, one that I would enthusiastically recommend alongside Lyuu (personal favorite) or Neftci.

I've read handful of books on quantitative finance over the years. Most of a few good books that focus on rigorous mathematical treatment often lack practicality. I've been looking for books that offer a rigorous and yet intuitive, practical way to gain an understanding into quantitative finance in general and MonteCarlo simulation in particular. Therefore I often browse Matlab website in search of good books that combine theory and computation. I have found only a good one so far (Higham). But it was written rather for beginners and/or students.Recently I found this one which is an excellent book for intermediate and advanced users, practitioners and academics alike. The book strikes a good balance between theory and practice; it presents a rigorous and yet intuitive treatment of quantitative finance, from fundamentals of probability theory and random processes, through the foundations of Monte-Carlo method and all the way to real-world applications. The book is up to date with latest research in computational finance. It contains not only simple, pedagogical Matlab programs but also more sophisticate methods such as quadratic resampling, dynamic programming technique of Barraquand and Martineau. The final chapters present the authors' own research, mostly on financial guarantees (credit derivatives) and Value at Risk.The book presents not only rigorous theory, but also practical, well-designed Matlab programs. The programs contain useful explanatory comments so they are very easy to follow. They can be used as is or adapted for your own purposes. Recently I had to price an exotic executive stock option, and I just chose a Matlab program from the book and modified it. The whole pricing process took just a couple of hours. That is, the programs are good for practitioners working in a high-pressure environment like myself. Academic researchers will also find the Matlab programs useful as the authors generously made codes of their own research on financial guarantees and Value at Risks available. These programs serve as a good starting point for other research projects.A drawback of this book is that you need Matlab which can be expensive if you don't qualify for an educational licence. However, it does not require other expensive add-ons. I think that interested readers can use open-source Matlab clones like Octave, Scilab etc.

I bought a copy of "Stochastic Simulation and applications in finance with MATLAB". There was supposed to be a CD with the book, with sample MATLAB codes etc, but in the opening pages of the book it says this has been converted to a URL on a companion website.However if one follows the URL link given, there is no mention of MATLAB material whatsoever .I would like a response from the publisher.

Unless you are a rocket scientist, you will not understand most of this book. Avoid.

This is my first reference in financial engineering. The book has grown me up greatly as a financial engineer and I use it so often in my daily work. It is really a MUST for those who wish to study financial engineering. Some of the remarkable features are:1) It consists of both theory and computer MATLAB programs. However, it does not simply repeat the theory that can be found elsewhere. Instead, it uses computer program examples to illustrate the theoretical problems. Hence the subjects which are considered difficult in other books are relatively easy to understand here. The MATLAB code is not long but it is the most important core part.2) The book discusses from the basic Monte Carlo methods (random number generation), fundamentals of options pricing theory and other important topics (e.g., interest-rate models and Value-at-Risk computations) to credit risk, financial guarantees. Both entry-level and experienced readers, professionals with financial and mathematical background will benefit from these subjects.3) Although it covers wide range of quantitative finance topics, the book explains the complicated subjects in a clear and precise way in only 354 pages. The authors have carefully selected useful materials and relevant references.

Excellent for programming Many applications in financeSuch as pricing options using monte carlo or the valuation or portfolios of financial guarantees or determining credit risk.Everything in finance you can model it with Matlab with This book.

The book presents in a quite concise manner the mathematical development with a focus on applications rather than on rigorous theory, each part accompanied by commented codes. Most of the added value and author's contribution is due to the Matlab code, rather than stricly fr the theory itself.It might be very useful if you are looking for a straight matlab implementations, but it may not necessarily meet your high theoretical needs.Overall my feedback is positive, since the exposition is clear, the book has a proper structure, the code is very useful and efficient and the main stochastic numerical methods are detailed.

An excellent and practical book on the subject of financial modelling. Gets you writing code and understanding models quickly. The style is informative and direct with just the right level of mathematical exposition. A great buy.

Très bien écrit et de bon niveau!