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Numerical Methods and Optimization in Finance, by Manfred Gilli, Dietmar Maringer, Enrico Schumann
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This book�describes computational finance�tools. It covers fundamental numerical analysis and computational techniques, such as�option pricing, and gives�special attention to�simulation and optimization. Many chapters are organized as case studies around�portfolio insurance and risk estimation problems.� In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.
- Shows ways to build and implement tools that help test ideas
- Focuses on the application of heuristics; standard methods receive limited attention
- Presents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models
- Sales Rank: #1690090 in Books
- Published on: 2011-07-25
- Original language: English
- Number of items: 1
- Dimensions: 9.02" h x 1.31" w x 5.98" l, 2.05 pounds
- Binding: Hardcover
- 600 pages
Review
"This book aims at providing guidance which is practical and useful for practitioners in finance with emphasis on computational techniques which are manageable by modern day desktop personal computers’ processing power when building, testing, comparing and using mathematical and econometric models of finance in the pursuit of analysis of actual financial market data in day to day activities of financial analysts, be they students of courses in finance programs or analysts in financial institutions."--Zentralblatt MATH 2012-1236-91001 "With as much rigor as can be mastered by anyone in the still-developing field of computational finance and a sense of humor, the authors unravel its mysteries. The presentations are clear and the models are practical --- these are the two ingredients that make for a valuable book in this field. The book is both practical in scope and rigorous on its theoretical foundations. It� is a must for anyone who needs to apply quantitative methods for financial planning --- and who doesn’t need to in our days?"--Stavros A. Zenios, University of Cyprus and the Wharton Financial Institutions Center "Numerical Methods and Optimization in Finance is an excellent introduction to computational science. The combination of methodology, software, and examples allows the reader to quickly grasp and apply serious computational ideas."--Kenneth L. Judd, Hoover Institution, Stanford University
From the Back Cover
This book�describes computational finance�tools. It covers fundamental numerical analysis and computational techniques, such as�option pricing, and gives�special attention to�simulation and optimization. Many chapters are organized as case studies around�portfolio insurance and risk estimation problems.� In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.
About the Author
VIP Value Investment Professionals, Switzerland
Most helpful customer reviews
6 of 6 people found the following review helpful.
Highly recommended
By Finance practitioner
I read it from front to back and started over again. It is an excellent read on many finance topics with a special emphasis on experiments, implementation and heuristic methods. In spirit it is similar to Brandimarte but takes a somewhat more critical view on the usefullness of false exactitude in financial modelling. I appreciate the book because it does not provide even more - to a large extent intimidating - theory in finance (written for whom actually?). Two suggestions for a future edition:
1. please provide all the codes in Matlab and in R. As a practitioner in portfolio management I find it hard enough to do my programing in Matlab. Simply saying (as in the book) whoever can code in Matlab can also 'easily' translate it into the more obscure R language (and the other way around of course) seems asking too much. The true reason is more likely that one of the authors mostly codes in Matlab and the other in R.
2. some of the visualizations in the book are highly enjoying, some are difficult to read in the printed version of the book. Readers could benefit further if the scripts producing the figures would be available too rather than a library of pure functions.
All in all a must have for the quantitatively minded finance professional.
11 of 14 people found the following review helpful.
Avoid.
By EJ
As an e-book, the format is unreadable. Highlighted equations can't be read. Footnotes seem to be randomly placed amongst text. In parts, equation fonts are twice the size of text and determining if something is an exponent is a sad joke. The print version may be better, but for such an expensive book, we deserve better. I would like my money and time back. Disclosure, I have read about 10% of the book and it is unlikely I will read more.
1 of 1 people found the following review helpful.
Choke-full of examples
By GS
A great book that is choke-full of _implementable_ examples. As someone with a practical bend that likes to "learn by doing", I find that this book is one of those I'll be referring to constantly for a long time, whenever I'm studying a new concept that I'd like to apply. It saved me plenty of time by not hunting around from different sources since it's all in one place, it's got an extensive literature review for whichever topic I'm looking at and, most importantly, has the code to help me get started.
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