Download Ebook Stochastic Simulation and Applications in Finance with MATLAB Programs
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Stochastic Simulation and Applications in Finance with MATLAB Programs
Download Ebook Stochastic Simulation and Applications in Finance with MATLAB Programs
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From the Inside Flap
“This book is a good companion to text books on theory, so if you want to get straight to the meat of implementing the classical quantitative finance models here's the answer.” —Paul Wilmott, wilmott.com “This powerful book is a comprehensive guide for Monte Carlo methods in finance. Every quant knows that one of the biggest issues in finance is to well understand the mathematical framework in order to translate it in programming code. Look at the chapter on Quasi Monte Carlo or the paragraph on variance reduction techniques and you will see that Huu Tue Huynh, Van Son Lai and Issouf Soumaré have done a very good job in order to provide a bridge between the complex mathematics used in finance and the programming implementation. Because it adopts both theoretical and practical point of views with a lot of applications, because it treats about some sophisticated financial problems (like Brownian bridges, jump processes, exotic options pricing or Longstaff-Schwartz methods) and because it is easy to understand, this handbook is valuable for academics, students and financial engineers who want to learn the computational aspects of simulations in finance.” —Thierry Roncalli, Head of Investment Products and Strategies, SGAM Alternative Investments & Professor of Finance, University of Evry
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From the Back Cover
Stochastic Simulation and Applications in Finance with MATLAB Programs explains the fundamentals of Monte Carlo simulation techniques, their use in the numerical resolution of stochastic differential equations and their current applications in finance. Building on an integrated approach, it provides a pedagogical treatment of the need-to-know materials in risk management and financial engineering. The book takes readers through the basic concepts, covering the most recent research and problems in the area, including: the quadratic re-sampling technique, the Least Squared Method, the dynamic programming and Stratified State Aggregation technique to price American options, the extreme value simulation technique to price exotic options and the retrieval of volatility method to estimate Greeks. The authors also present modern term structure of interest rate models and pricing swaptions with the BGM market model, and give a full explanation of corporate securities valuation and credit risk based on the structural approach of Merton. Case studies on financial guarantees illustrate how to implement the simulation techniques in pricing and hedging. NOTE TO READER: The CD has been converted to URL. Go to the following website www.wiley.com/go/huyhnstochastic which provides MATLAB programs for the practical examples and case studies, which will give the reader confidence in using and adapting specific ways to solve problems involving stochastic processes in finance.
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Product details
Hardcover: 356 pages
Publisher: Wiley; 1 edition (December 22, 2008)
Language: English
ISBN-10: 0470725389
ISBN-13: 978-0470725382
Product Dimensions:
6.9 x 1 x 9.9 inches
Shipping Weight: 1.7 pounds (View shipping rates and policies)
Average Customer Review:
2.8 out of 5 stars
5 customer reviews
Amazon Best Sellers Rank:
#319,625 in Books (See Top 100 in Books)
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.
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.
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.
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