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Mathematics and Statistics for Financial Risk Management is a practical guide to modern financial risk management for both practitioners and academics.
Now in its second edition with more topics, more sample problems and more real world examples, this popular guide to financial risk management introduces readers to practical quantitative techniques for analyzing and managing financial risk.
In a concise and easy-to-read style, each chapter introduces a different topic in mathematics or statistics.�As different techniques are introduced, sample problems and application sections demonstrate how these techniques can be applied to actual risk management problems. Exercises at the end of each chapter and the accompanying solutions at the end of the book allow readers to practice the techniques they are learning and monitor their progress.�A companion Web site includes interactive Excel spreadsheet examples and templates.
Mathematics and Statistics for Financial Risk Management is an indispensable reference for today’s financial risk professional.
- Sales Rank: #443012 in Books
- Published on: 2013-12-31
- Original language: English
- Number of items: 1
- Dimensions: 10.25" h x 1.10" w x 7.30" l, 1.60 pounds
- Binding: Hardcover
- 336 pages
Amazon.com Review
More to Explore: See More Risk Management Resources
�
� � Title Risk Management and
Financial Institutions Financial Risk Management Financial Risk Manager
Handbook Mathematics and Statistics
for Financial Risk Management � Guide Type Text Professional Professional Certification Advanced Professional � Pages 664 772 800 291 � List Price $95.00 $95.00 $175.00 $85.00 � Author(s) Hull Malz Jorion / GARP Miller � Publication Date May 2012 October 2011 December 2010 March 2012 � Imprint Wiley Wiley Wiley Wiley � Print Book 1118269039 0470481803 0470904011 1118170628 � Kindle Book B007U2ZQKU B005N8EY8I B004I6DDFG B0072LWTWC � Edition 3 1 6 1 � Brief Description Fundamental coverage after Dodd-Frank, Basel III, & other global developments from top teaching academic. Comprehensive book on cutting-edge tools and techniques to identify risks of all types, and manage them effectively. Core reference for GARP's FRM� Exam and risk professionals looking to stay current on best practices. A practitioners guide to quantitative risk management; many sample problems and application sections.
Review
"At every turn this book shows the relevance of mathematical and statistical concepts to risk management. They are no longer the desiccated notions found in most textbooks but assume a sense of vibrancy. So, if you're trying to hone your skills, this book is a great place to start." (SeekingAlpha, April 2012)
From the Inside Flap
Mathematics and Statistics for Financial Risk Management is a practical guide to modern financial risk management for both practitioners and academics.
The recent financial crisis and its impact on the broader economy underscore the importance of financial risk management in today's world. At the same time, financial products and investment strategies are becoming increasingly complex. Today, it is more important than ever that risk managers possess a sound understanding of mathematics and statistics.
In a concise and easy-to-read style, each chapter introduces a different topic in mathematics or statistics. As different techniques are introduced, sample problems and application sections demonstrate how these techniques can be applied to actual risk management problems. Exercises at the end of each chapter and the accompanying solutions at the end of the book allow readers to practice the techniques they are learning and monitor their progress. A companion web site includes interactive Excel spreadsheet examples and templates.
This comprehensive resource covers basic statistical concepts from standard deviation and correlation to regression analysis and hypothesis testing. Widely used risk models, including value at risk, factor analysis, Monte Carlo simulation, and stress testing are also explored. Time series analysis, interest rate modeling, optimal hedging, and many other financial topics are covered as well.
The Second Edition of this popular guide includes two new chapters. The first new chapter, on multivariate distributions, explores important concepts for measuring the risk of portfolios, including joint distributions and copulas. The other new chapter, on Bayesian analysis, explores an approach to statistical analysis that is particularly useful in dealing with the short, noisy data sets that risk managers often face in practice.
Mathematics and Statistics for Financial Risk Management is an indispensable reference for today's financial risk professional.
Most helpful customer reviews
34 of 35 people found the following review helpful.
An Important, Informed, and Practical Book
By C. Hobbs
In Mathematics and Statistics for Financial Risk Management ("MSFRM") Michael Miller has produced a very interesting effort that enjoys a unique position amongst the choices we have these days in risk management and the mathematics of risk management books. First, what this book is not: a foundational treatise brimming with abstraction and generalities. Proposition. Theorem. Lemma. Let there be a risky asset V such that... Let the price of the underlying asset follow the following process... &c. This book doesn't have the breadth of a bottom up treatment, with the exception of some appendix material and a couple of necessary diversions; rather, it assumes a certain level of sophistication from the reader, no more, and opts for practicality and depth. And this is a good thing! There are more than enough highly general treatments already in existence to choose from. Readers or autodidacts with a more mathematical or independent tilt can perhaps begin from a more general place, although the problems presented in MSFRM make the book potentially valuable to anyone. What level is assumed in MSFRM? Basic probability, calculus, and matrix algebra (although the former and latter is treated in chapters 3 and 6, respectively), perhaps consistent with an analyst or associate dealing with practical challenges. This book is not for a quant. What this book is: the stylized approach is top down instead of bottom up, obviating the need for excessive mathematical generalities, the very generalities that often leave an important readership frustrated, alienated, and confused about how to get from point A to point B. The author, on the back jacket, indicates he has "worked in risk management for more than ten years,..."; clearly, over this time, he's observed certain problems cropping up again and again, so much so that he decided to write a book on how to operate the tools to handle these problems. This is my inference since many of the ideas, problems, and tools discussed in the book have been a constant part of my professional life for over a decade. While impossible to be exhaustive, the material that made the cut is certainly well-informed and relevant, as Miller allocates some of the intellectual capital he has developed over the years and provides concrete problems that are interesting and unique. Subjects that I felt were presented well and supplemented with interesting problems for people to think about:
- Chapter 3 Basic Statistics: application to portfolio variance and hedging
- Chapter 5 Hypothesis Testing & Confidence Intervals: initially you expect a stock's vol to be 45%, but you have a estimated a different vol ex post from empirical data. Is this difference meaningful at a certain confidence level? How is VaR and Expected Shortfall related?
- Chapter 7 Vector Spaces: This chapter is interesting as it spends a bit of time on PCA and applications to yield curve decomposition and even cites current recent research in systemic risk measurement
- Chapter 9 Time Series Models: Spurious correlation, AR() processes and applications to rate models.
Stylistically I would classify MSFRM as a mixture of Carol Alexander's Quant Methods in Finance (cf chapters 6 or 9) and Euan Sinclair's Vol Trading (a book stemming from Sinclair's experience as an options' trader and hedger). It is very easy to comment on things that I would have liked to have seen more of or that I deem relevant. For example: applications of the materials covered to option markets or other asset classes in addition to stocks and bonds; the Cholesky decomposition, ubiquitous in our work, is introduced in chapter 6 but not really extended to, say, a multi-asset simulation or pricing and greek calculation (although I get the impression the author tried to stay away from potential coding problems). That being said, editing what stays and what goes is a thorny problem that can easily become impossible and for which there is no right answer and depends on one's perspective and experience. Judging MSFRM on its own merits I give it a solid 4 stars with the caveat that there is a select demographic out there that will find the book to be 5 stars. The people that will find this book the most useful will be able to immediately implement most of the material presented in a practical manner (note that I didn't download the excel examples provided by the publisher, but they are available). As someone that manages hedging and risk management teams myself, this is certainly a book that I would recommend to practitioners. Finally, it is clear that the author and the people he thanked in the acknowledgments spent quite a bit of time proofreading the final copy. The writing is clear, well-articulated, and thoughtful.
11 of 11 people found the following review helpful.
Excellent book
By Pri
This is an excellent book to grasp the basics of financial risk management. Everything in the book is explained from scratch and the concepts are very well exemplified with real life situations. This is the prescribed text book for my Risk Management class and is by far one of the best courses I have taken. As a matter of fact, the book's author conducts this course and I am highly impressed with the course material, thanks to this text book. I would totally recommend the book.
5 of 5 people found the following review helpful.
An Excellent foundation book
By kobby79
I gave this book five stars because, the book is easy to read and the author did a good job in explaining the concepts covered in the books. The problems at the end of the chapters were helpful for testing my understanding of concepts covered. I will recommend it to anyone interested in the mathematical and statistical foundations for computational finance.
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