book

Elements of Financial Risk Management, 2nd Edition

Name: Elements of Financial Risk Management, 2nd Edition
Author: Peter Christoffersen
ISBN: 9780080922430

by Peter Christoffersen

November 2011

Intermediate to advanced

344 pages

8h 40m

English

Academic Press

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Cover image
Table of Contents
Front Matter
Copyright
Dedication
Preface
Acknowledgments
1. Risk Management and Financial Returns
1. Chapter Outline2. Learning Objectives3. Risk Management and the Firm4. A Brief Taxonomy of Risks5. Asset Returns Definitions6. Stylized Facts of Asset Returns7. A Generic Model of Asset Returns8. From Asset Prices to Portfolio Returns9. Introducing the Value-at-Risk (VaR) Risk Measure10. Overview of the BookAppendix. Return VaR and $VaR
2. Historical Simulation, Value-at-Risk, and Expected Shortfall
1. Chapter Overview2. Historical Simulation3. Weighted Historical Simulation (WHS)4. Evidence from the 2008–2009 Crisis5. The True Probability of Breaching the HS VaR6. VaR with Extreme Coverage Rates7. Expected Shortfall8. Summary
3. A Primer on Financial Time Series Analysis
1. Chapter Overview2. Probability Distributions and Moments3. The Linear Model4. Univariate Time Series Models5. Multivariate Time Series Models6. Summary

4. Volatility Modeling Using Daily Data
1. Chapter Overview2. Simple Variance Forecasting3. The GARCH Variance Model4. Maximum Likelihood Estimation5. Extensions to the GARCH Model6. Variance Model Evaluation7. SummaryAppendix A. Component GARCH and GARCH(2,2)Appendix B. The HYGARCH Long-Memory Model
5. Volatility Modeling Using Intraday Data
1. Chapter Overview2. Realized Variance: Four Stylized Facts3. Forecasting Realized Variance4. Realized Variance Construction5. Data Issues6. Range-Based Volatility Modeling7. GARCH Variance Forecast Evaluation Revisited8. Summary
6. Nonnormal Distributions
1. Chapter Overview2. Learning Objectives3. Visualizing Nonnormality Using QQ Plots4. The Filtered Historical Simulation Approach5. The Cornish-Fisher Approximation to VaR6. The Standardized t Distribution7. The Asymmetric t Distribution8. Extreme Value Theory (EVT)9. SummaryAppendix A. ES for the Symmetric and Asymmetric t DistributionsAppendix B. Cornish-Fisher ESAppendix C. Extreme Value Theory ES
7. Covariance and Correlation Models
1. Chapter Overview2. Portfolio Variance and Covariance3. Dynamic Conditional Correlation (DCC)4. Estimating Daily Covariance from Intraday Data
8. Simulating the Term Structure of Risk
1. Chapter Overview2. The Risk Term Structure in Univariate Models3. The Risk Term Structure with Constant Correlations4. The Risk Term Structure with Dynamic Correlations5. Summary
9. Distributions and Copulas for Integrated Risk Management
1. Chapter Overview2. Threshold Correlations3. Multivariate Distributions4. The Copula Modeling Approach5. Risk Management Using Copula Models6. Summary
10. Option Pricing
1. Chapter Overview2. Basic Definitions3. Option Pricing Using Binomial Trees4. Option Pricing under the Normal Distribution5. Allowing for Skewness and Kurtosis6. Allowing for Dynamic Volatility7. Implied Volatility Function (IVF) Models8. SummaryAppendix. The CFG Option Pricing Formula
11. Option Risk Management
1. Chapter Overview2. The Option Delta3. Portfolio Risk Using Delta4. The Option Gamma5. Portfolio Risk Using Gamma6. Portfolio Risk Using Full Valuation7. A Simple Example8. Pitfall in the Delta and Gamma Approaches9. Summary
12. Credit Risk Management
1. Chapter Overview2. A Brief History of Corporate Defaults3. Modeling Corporate Default4. Portfolio Credit Risk5. Other Aspects of Credit Risk6. Summary
13. Backtesting and Stress Testing
1. Chapter Overview2. Backtesting VaRs3. Increasing the Information Set4. Backtesting Expected Shortfall5. Backtesting the Entire Distribution6. Stress Testing7. Summary
Index

Overview

The Second Edition of this best-selling book expands its advanced approach to financial risk models by covering market, credit, and integrated risk. With new data that cover the recent financial crisis, it combines Excel-based empirical exercises at the end of each chapter with online exercises so readers can use their own data. Its unified GARCH modeling approach, empirically sophisticated and relevant yet easy to implement, sets this book apart from others. Five new chapters and updated end-of-chapter questions and exercises, as well as Excel-solutions manual, support its step-by-step approach to choosing tools and solving problems.

Examines market risk, credit risk, and operational risk
Provides exceptional coverage of GARCH models
Features online Excel-based empirical exercises

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