Praise for Mathematics and Statistics for Financial Risk Management "This is the best book to date on the basic mathematics needed for financial risk management: clear, comprehensive, and up to date. Extensive examples and problems make clear how these concepts are used in the worlds top financial institutions. The book is perfect for self-study or classroom use." -Aaron Brown, author of Red-Blooded Risk, A World of Chance, and The Poker Face of Wall Street "Risk managers have a need for relatively sophisticated mathematical tools in order to adequately describe and communicate the distributions of potential outcomes that they focus on every day. Michael Miller has provided a very nice, self-contained, practical introduction to the mathematics and statistics required for understanding the basic concepts of risk management." -Bob Litterman, Partner, Kepos Capital, and Executive Editor, Financial Analysts Journal Mathematics and Statistics for Financial Risk Management is a practical guide to modernfinancial risk management for bothpractitioners and academic. In a concise and easy-to-read style, eachchapter of this book introduces a different topic in mathematics or statistics.As different techniques are introduced,?sample problems and application sectionsdemonstrate how these techniques can beapplied to actual risk management problems. Exercises at the end of each chapter and the accompanying solutions at theend of the book allow readers to practicethe techniques they are learning and monitor their progress. A companion websiteincludes interactive Excel spreadsheet examples and templates.
This 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 todays world.
Michael B. Miller studied economics at the American University of Paris and the University of Oxford before starting a career in finance. He has worked in risk management for more than ten years, most recently as the chief risk officer for a hedge fund in New York City.
In chapter 1, there is a review three math topics -- logarithms, combinatorics, and geometric series - and one financial topic, discount factors. Emphasis will be given to the specific aspects of these topics that are most relevant to risk management. In chapter 2, the author explores the application of probabilities to risk management. There is also an introduction to basic terminology and notations that will be used throughout the rest of the book. In chapter 3, Miller teaches how to describe a collection of data in precise statistical terms. Many of the concepts will be familiar, but the notation and terminology might be new. This notation and terminology will be used throughout the rest of the book. In chapter 4, some of the most common probability distributions will be pointed out, followed by a chapter on two closely related topics, confidence intervals and hypothesis testing. For risk management, these are possibly the two most important concepts in statistics. Chapter 6 provides a basic introduction to linear regression models. At the end of the chapter, Miller explores two risk management applications, factor analysis and stress testing. The final chapter is on a class of estimators, which has become very popular in finance and risk management for analyzing historical data. These models hint at the limitations of the type of analysis that we have been explores in previous chapters. This book has a lot of charts and equations.
In chapter 1, there is a review three math topics -- logarithms, combinatorics, and geometric series and one financial topic, discount factors.?Emphasis will be given to the specific aspects of these topics that are most relevant to risk management. In chapter 2, the author explores the application of probabilities to risk management.?There is also an introduction to basic terminology and notations that will be used throughout the rest of the book. In chapter 3, Miller teaches how to describe a collection of data in precise statistical terms.?Many of the concepts will be familiar, but the notation and terminology might be new.?This notation and terminology will be used throughout the rest of the book. In chapter 4, some of the most common probability distributions will be pointed out, followed by a chapter on two closely related topics, confidence intervals and hypothesis testing.?For risk management, these are possibly the two most important concepts in statistics. Chapter 6 provides a basic introduction to linear regression models. At the end of the chapter, Miller explores two risk management applications, factor analysis and stress testing. The final chapter is on a class of estimators, which has become very popular in finance and risk management for analyzing historical data.?These models hint at the limitations of the type of analysis that we have been explores in previous chapters. This book has a lot of charts and equations.
In chapter 1, there is a review three math topics -- logarithms, combinatorics, and geometric series and one financial topic, discount factors. Emphasis will be given to the specific aspects of these topics that are most relevant to risk management. In chapter 2, the author explores the application of probabilities to risk management. There is also an introduction to basic terminology and notations that will be used throughout the rest of the book. In chapter 3, Miller teaches how to describe a collection of data in precise statistical terms. Many of the concepts will be familiar, but the notation and terminology might be new. This notation and terminology will be used throughout the rest of the book. In chapter 4, some of the most common probability distributions will be pointed out, followed by a chapter on two closely related topics, confidence intervals and hypothesis testing. For risk management, these are possibly the two most important concepts in statistics. Chapter 6 provides a basic introduction to linear regression models. At the end of the chapter, Miller explores two risk management applications, factor analysis and stress testing. The final chapter is on a class of estimators, which has become very popular in finance and risk management for analyzing historical data. These models hint at the limitations of the type of analysis that we have been explores in previous chapters. This book has a lot of charts and equations.
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 todays 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 youre looking for a book that will help you understand the mathematics and statistics of financial risk management, look no further.
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 todays 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. This comprehensive resource covers basic statistical concepts from volatility and Bayes Law to regression analysis and hypothesis testing. Widely used risk models, including Value-at-Risk, factor analysis, Monte Carlo simulations, and stress testing are also explored. A chapter on time series analysis introduces interest rate modeling, GARCH, and jump-diffusion models. Bond pricing, portfolio credit risk, optimal hedging, and many other financial risk topics are covered as well. If youre looking for a book that will help you understand the mathematics and statistics of financial risk management, look no further.
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 todays 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. This comprehensive resource covers basic statistical concepts from volatility and Bayes Law to regression analysis and hypothesis testing. Widely used risk models, including Value-at-Risk, factor analysis, Monte Carlo simulations, and stress testing are also explored. A chapter on time series analysis introduces interest rate modeling, GARCH, and jump-diffusion models. Bond pricing, portfolio credit risk, optimal hedging, and many other financial risk topics are covered as well. If youre looking for a book that will help you understand the mathematics and statistics of financial risk management, look no further.
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 todays world. At the same time, financial products and investment strategies are becoming increasingly complex.
A practical guide to modern financial risk management for both practitioners and academic The recent financial crisis and its impact on the broader economy underscore the importance of financial risk management in todays world. At the same time, financial products and investment strategies are becoming increasingly complex.
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 todays world.