Mathematics and Statistics for Financial Risk Management Front Cover

Mathematics and Statistics for Financial Risk Management

  • Length: 291 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2012-03-06
  • ISBN-10: 1118170628
  • ISBN-13: 9781118170625
  • Sales Rank: #2951811 (See Top 100 Books)
Description

Mathematics and Statistics for Financial Risk Management (Wiley Finance)
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 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.

  • Covers basic statistical concepts from volatility and Bayes’ Law to regression analysis and hypothesis testing
  • Introduces risk models, including Value-at-Risk, factor analysis, Monte Carlo simulations, and stress testing
  • Explains time series analysis, including interest rate, GARCH, and jump-diffusion models
  • Explores bond pricing, portfolio credit risk, optimal hedging, and many other financial risk topics

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

CHAPTER 1 Some Basic Math
CHAPTER 2 Probabilities
CHAPTER 3 Basic Statistics
CHAPTER 4 Distributions
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
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