Book description
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 easytoread style, each chapter of this book 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 website includes interactive Excel spreadsheet examples and templates.
This comprehensive resource covers basic statistical concepts from volatility and Bayes' Law to regression analysis and hypothesis testing. Widely used risk models, including ValueatRisk, factor analysis, Monte Carlo simulations, and stress testing are also explored. A chapter on time series analysis introduces interest rate modeling, GARCH, and jumpdiffusion models. Bond pricing, portfolio credit risk, optimal hedging, and many other financial risk topics are covered as well.
If you're looking for a book that will help you understand the mathematics and statistics of financial risk management, look no further.
Table of contents
 Cover
 Series
 Title Page
 Copyright
 Preface
 Acknowledgments
 CHAPTER 1: Some Basic Math
 CHAPTER 2: Probabilities
 CHAPTER 3: Basic Statistics

CHAPTER 4: Distributions
 PARAMETRIC DISTRIBUTIONS
 UNIFORM DISTRIBUTION
 BERNOULLI DISTRIBUTION
 BINOMIAL DISTRIBUTION
 POISSON DISTRIBUTION
 NORMAL DISTRIBUTION
 LOGNORMAL DISTRIBUTION
 CENTRAL LIMIT THEOREM
 APPLICATION: MONTE CARLO SIMULATIONS PART I: CREATING NORMAL RANDOM VARIABLES
 CHISQUARED DISTRIBUTION
 STUDENT'S T DISTRIBUTION
 FDISTRIBUTION
 MIXTURE DISTRIBUTIONS
 PROBLEMS
 CHAPTER 5: Hypothesis Testing & Confidence Intervals
 CHAPTER 6: Matrix Algebra
 CHAPTER 7: Vector Spaces
 CHAPTER 8: Linear Regression Analysis
 CHAPTER 9: Time Series Models
 CHAPTER 10: Decay Factors
 APPENDIX A: Binary Numbers
 APPENDIX B: Taylor Expansions
 APPENDIX C: Vector Spaces
 APPENDIX D: Greek Alphabet
 APPENDIX E: Common Abbreviations
 Answers
 References
 About the Author
 Index
Product information
 Title: Mathematics and Statistics for Financial Risk Management
 Author(s):
 Release date: March 2012
 Publisher(s): Wiley
 ISBN: 9781118170625
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