Monte Carlo Methods in Finance

Rating:
Summary: Solid gold
Review: Conflict of interest pervades the field of finance on every level including the intellectual level.

Often you might find books reviewed most favorably by
leading academic researchers to fall far short of the praise constituting a legal liability for the author's employer and
inducing a suspicion that the reviewer had material interests at stake.

For this reason we are grateful that Amazon has a liberal return policy. This book however you will not want to send back.

It hits the mark in several important aspects:

1. Level of detail.
The presentation is detailed enough for you to be able to translate the description into computer code but not so detailed that this step is immediate.
This allows an elegant and fluent style of writing.
Descriptions that are detailed enough to translate into code immediately almost certainly lack aesthetic qualities and one usually does not read them again them once the relevant information has been extracted. This is not the case here. I find myself browsing the material again after some algorithm has already been implemented and enjoying the experience.
The author has the ability to articulate complicated concepts clearly and without resort to heavy notation.

2. Mathematical rigour.

The mathematics is impeccable. In my own experience this can be said of fewer than 10% of the books in the field of finance.
The prerequisites are minimal. You have to know the most basic properties of Brownian motion (barely more than the definition)
and be familiar with the notion of a probability density.
Nonetheless several highly interesting subjects are treated in much detail (for example effective dimensionality reduction in conjunction with the application of low discrepancy sequences).

3. Choice of subject.

The techniques discussed are those used by leading investment banks. This is unsurprising since the author himself works at such an institution. The book is quite different from one devoted to Monte Carlo methods in physics, genetics or polymer science.

4. Physical appearance.

Page size, page layout, font selection and binding are all of high quality. The book has a wealth of diagrams communicating interesting information.

I love it and believe that you will too.

Rating:
Summary: for Quants only
Review: if you're a quant, you might really love this book

if you're a person who wants to have a "basic" understanding how to use MC for consulting or product pricing with examples, you got the wrong book (not mentioning that your maths must be pretty good).

if you're looking for an Excel example on how to price some basic options, i highly recommend Jackson & Staunton or Wilmott.

Rating:
Summary: for Quants only
Review: if you're a quant, you might really love this book

if you're a person who wants to have a "basic" understanding how to use MC for consulting or product pricing with examples, you got the wrong book (not mentioning that your maths must be pretty good).

if you're looking for an Excel example on how to price some basic options, i highly recommend Jackson & Staunton or Wilmott.

Rating:
Summary: Good book
Review: It is a book for mathematics lovers not financial oriented profesionals. I would not recomend this book for those looking to gain more practical knowledge on this subject.

Rating:
Summary: CD does not work
Review: It is a book for mathematics lovers not financial oriented profesionals. I would not recomend this book for those looking to gain more practical knowledge on this subject.

Rating:
Summary: Good book
Review: This book is pretty good as it covers lots of different areas of Monte Carlo simulation and some of the newer stuffs, such as copulae, etc. The math presentation is brief but to the point as application of the mathematics to Monte Carlo methods is the emphasis. Intuitive ideas behind the formula is explained pretty well as it tells you where certain formula can be used for. It would be helpful to have taken an advanced course in Monte Carlo methods in Finance to appreciate the book. I would personally suggest Glasserman's course at Columbia U. Prof Glasserman is also writing a book on the subject that he uses for lecture notes now. It would turn out to be an even better book to read.

Rating:
Summary: Competent Treatment of an Advanced Approach
Review: This is an excellent resource for anyone already familiar with Monte Carlo modelling. Scientists making the transition to Wall Street will find this a needed supplement to Hull and other good resources. Product descriptions are also needed, especially for areas in which growth is exploding and therefore jobs are available. "Credit Derivatives" (Second Edition) by Janet Tavakoli is a great resource for getting up to speed on these products and for highlighting some of the data and modelling issues one will encounter. Although it is a product book and an applications book that helps the modeller understand how to approach the problem.

Rating:
Summary: An advanced approach to math methods behind finance
Review: Very interesting and well written book reviewing more advanced mathematical concepts which might be relevant for finance engineering - not limited to Monte Carlo methods. The author seems to have a firm background in theoretical physics. Definitely not for simpletons.

Rating:
Summary: I can NOT follow the math and NO CODE!
Review: You better already know the basics of Monte Carlo Simulation
to get anything out of the book.

I STRONGLY disagree with one reviewer who thinks
all one needs to know is :
1) The definition of Brownian Motion and
2) What a Probability distribution is.
FAT chance.

The book requires knowing Linear Algebra, Probability,
PDEs, Stochastic Modelling, and SDEs to be of any use.

Where's the CODE, baby!
There are very few examples put into code!

One reviewer on Amazon.com, says the book is so
detailed you don't need code. Funny, I have never
seen anything "so detailed" that an example (code)
would make the explanation less clear!