Average Reviews:
(More customer reviews)I am using this as a secondary reference for a half-semester Matlab and Optimization course and it has been invaluable. The writing is crystal clear, the examples and code are pretty close to perfect for every section. The author writes in a very intuitive fashion and of the sections I have covered I don't think I have been lost or confused once, which in this field is uncommon.
This is not really an introductory book for finance and if you read the preface, Brandimarte does explain that the book complements and does not replace more specific texts. I have been seen most of the material in this book covered in at least a cursory fashion in my Financial Engineering program and it makes a difference, so I would recommend that you are familiar with the material covered in Hull's "Options, Futures and Other Derivatives" or Neftci's "Principles of Financial Engineering" and Neftci's "Introduction to the Mathematics of Financial Derivatives" or similar texts.
You also won't be able to get away without having at least some intermediate level linear algebra. You don't have know it well but concept such as conditioning, LU and cholesky factorization should ring a bell. On the other hand some topics such as optimization I feel are covered very solidly. I am using "Optimization Methods in Finance" by Cornuejols and Tutuncu and although it is a great book I have to say that the examples in Brandimarte's book are much better and more intuitively explained, although clearly not in the same detail.
My only gripe with the book is that he tends to use code from the toolboxes, which can be inconvenient if you are student and only have the student version at home. Most of the time he builds the code from scratch but he uses toolbox code enough that it is annoying.
Click Here to see more reviews about: Numerical Methods in Finance and Economics: A MATLAB-Based Introduction (Statistics in Practice)
A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of financeThe use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB?--the powerful numerical computing environment--for financial applications.The author provides an essential foundation in finance and numerical analysis in addition to background material for students from both engineering and economics perspectives. A wide range of topics is covered, including standard numerical analysis methods, Monte Carlo methods to simulate systems affected by significant uncertainty, and optimization methods to find an optimal set of decisions.Among this book's most outstanding features is the integration of MATLAB?, which helps students and practitioners solve relevant problems in finance, such as portfolio management and derivatives pricing. This tutorial is useful in connecting theory with practice in the application of classical numerical methods and advanced methods, while illustrating underlying algorithmic concepts in concrete terms.Newly featured in the Second Edition:* In-depth treatment of Monte Carlo methods with due attention paid to variance reduction strategies* New appendix on AMPL in order to better illustrate the optimization models in Chapters 11 and 12* New chapter on binomial and trinomial lattices* Additional treatment of partial differential equations with two space dimensions* Expanded treatment within the chapter on financial theory to provide a more thorough background for engineers not familiar with finance* New coverage of advanced optimization methods and applications later in the textNumerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition presents basic treatments and more specialized literature, and it also uses algebraic languages, such as AMPL, to connect the pencil-and-paper statement of an optimization model with its solution by a software library. Offering computational practice in both financial engineering and economics fields, this book equips practitioners with the necessary techniques to measure and manage risk.
