» Monte Carlo Methods in Financial Engineering (Stochastic Modelling and Applied Probability) (v. 53)

Monte Carlo Methods in Financial Engineering (Stochastic Modelling and Applied Probability) (v. 53) Reviews

Customer Rating:
Summary: Very well written
Comment: I must admit it is magnificently written book. Not just the main thematical issues but also appendix, where, compared to other similar publications, Girsanov theorem is thoroughly explained. All in all it's
a very useful book for everyone who has some basic information about stochastic processes and wants to learn something more about it or deepen their's knowledges. Well done.

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Customer Rating:
Summary: Advanced analysis
Comment: Let me start by saying that I'm not a "quant." I am interested in the calculations that quants do, and in Monte Carlo techniques in general. As a result, I'm reviewing only about half of this book, the half on generally applicable Monte Carlo techniques, and skipping the finance-specific material that it alternates with.

As something of a novice to advanced Monte Carlo techniques, I find this book immensely useful. The chapter on "Generating Random Numbers" helps, even if the description of the basic uniform generators could be stronger. Given the uniform generator, its descriptions of generators for non-uniform distributions work well for me. The "Sample Path" material is where I came into this book, really, looking for more insight into generation Brownian bridges. The math certainly is not for the notation-shy, but suffices for the dedicated practitioner. The next few chapters on variance reduction, quasi-MC, discretization, and sensitivity analysis are all widely applicable - I don't have immediate use for the material, but now I know where to look when the need arises. The remaining two chapters cover specific financial applications, and I leave comment on them to other readers.

This book gave me what I wanted, and lots more besides. Much of what it offers really isn't for me, though - the financial instruments being analyzed border on abstract art. I also felt a little pain at having no background in stochastic calculus, but some determination and a willingness to skip over fine points got me through well enough. The successful reader has a working knowledge of basic calculus, linear algebra, and probability. That reader must have a real interest in MC techniques, and should care about the financial decision-making to which Glasserman applies those techniques - but, as I prove, even that isn't necessary for getting a lot of value from this text.

-- wiredweird

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Customer Rating:
Summary: Review for Monte Carlo Methods... by P. Glasserman
Comment: The book is just right for a reader who is looking for state-of-the-art techniques in Monte-Carlo methods in general. The fact that the book is specific to financial systems does not limit the usability of the book in the manner it is written. There are a lots of useful references one can get out of this book.
The book is for advanced readers in the sense that it requires rigorous mathematical ability to understand all the concepts. It is by no means for a novice reader and requires background in computational mathematics.

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Customer Rating:
Summary: Best financial engineering book on MC
Comment: This is like the bible of Monte Carlo methods in financing. Both a good read and a good reference book. Must have! for any quant on wall street.

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Customer Rating:
Summary: good book on Monte Carlo in Finance
Comment: But it seems the author is a little focused on selling his ideas, but not a very subjective overview of all topics in M-C method in finance.

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