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Elements of Financial Risk Management, 2nd Edition

Book Description

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

Table of Contents

  1. Cover image
  2. Table of Contents
  3. Front Matter
  4. Copyright
  5. Dedication
  6. Preface
  7. Acknowledgments
  8. 1. Risk Management and Financial Returns
    1. 1. Chapter Outline
    2. 2. Learning Objectives
    3. 3. Risk Management and the Firm
    4. 4. A Brief Taxonomy of Risks
    5. 5. Asset Returns Definitions
    6. 6. Stylized Facts of Asset Returns
    7. 7. A Generic Model of Asset Returns
    8. 8. From Asset Prices to Portfolio Returns
    9. 9. Introducing the Value-at-Risk (VaR) Risk Measure
    10. 10. Overview of the Book
    11. Appendix. Return VaR and $VaR
  9. 2. Historical Simulation, Value-at-Risk, and Expected Shortfall
    1. 1. Chapter Overview
    2. 2. Historical Simulation
    3. 3. Weighted Historical Simulation (WHS)
    4. 4. Evidence from the 2008–2009 Crisis
    5. 5. The True Probability of Breaching the HS VaR
    6. 6. VaR with Extreme Coverage Rates
    7. 7. Expected Shortfall
    8. 8. Summary
  10. 3. A Primer on Financial Time Series Analysis
    1. 1. Chapter Overview
    2. 2. Probability Distributions and Moments
    3. 3. The Linear Model
    4. 4. Univariate Time Series Models
    5. 5. Multivariate Time Series Models
    6. 6. Summary
  11. 4. Volatility Modeling Using Daily Data
    1. 1. Chapter Overview
    2. 2. Simple Variance Forecasting
    3. 3. The GARCH Variance Model
    4. 4. Maximum Likelihood Estimation
    5. 5. Extensions to the GARCH Model
    6. 6. Variance Model Evaluation
    7. 7. Summary
    8. Appendix A. Component GARCH and GARCH(2,2)
    9. Appendix B. The HYGARCH Long-Memory Model
  12. 5. Volatility Modeling Using Intraday Data
    1. 1. Chapter Overview
    2. 2. Realized Variance: Four Stylized Facts
    3. 3. Forecasting Realized Variance
    4. 4. Realized Variance Construction
    5. 5. Data Issues
    6. 6. Range-Based Volatility Modeling
    7. 7. GARCH Variance Forecast Evaluation Revisited
    8. 8. Summary
  13. 6. Nonnormal Distributions
    1. 1. Chapter Overview
    2. 2. Learning Objectives
    3. 3. Visualizing Nonnormality Using QQ Plots
    4. 4. The Filtered Historical Simulation Approach
    5. 5. The Cornish-Fisher Approximation to VaR
    6. 6. The Standardized t Distribution
    7. 7. The Asymmetric t Distribution
    8. 8. Extreme Value Theory (EVT)
    9. 9. Summary
    10. Appendix A. ES for the Symmetric and Asymmetric t Distributions
    11. Appendix B. Cornish-Fisher ES
    12. Appendix C. Extreme Value Theory ES
  14. 7. Covariance and Correlation Models
    1. 1. Chapter Overview
    2. 2. Portfolio Variance and Covariance
    3. 3. Dynamic Conditional Correlation (DCC)
    4. 4. Estimating Daily Covariance from Intraday Data
  15. 8. Simulating the Term Structure of Risk
    1. 1. Chapter Overview
    2. 2. The Risk Term Structure in Univariate Models
    3. 3. The Risk Term Structure with Constant Correlations
    4. 4. The Risk Term Structure with Dynamic Correlations
    5. 5. Summary
  16. 9. Distributions and Copulas for Integrated Risk Management
    1. 1. Chapter Overview
    2. 2. Threshold Correlations
    3. 3. Multivariate Distributions
    4. 4. The Copula Modeling Approach
    5. 5. Risk Management Using Copula Models
    6. 6. Summary
  17. 10. Option Pricing
    1. 1. Chapter Overview
    2. 2. Basic Definitions
    3. 3. Option Pricing Using Binomial Trees
    4. 4. Option Pricing under the Normal Distribution
    5. 5. Allowing for Skewness and Kurtosis
    6. 6. Allowing for Dynamic Volatility
    7. 7. Implied Volatility Function (IVF) Models
    8. 8. Summary
    9. Appendix. The CFG Option Pricing Formula
  18. 11. Option Risk Management
    1. 1. Chapter Overview
    2. 2. The Option Delta
    3. 3. Portfolio Risk Using Delta
    4. 4. The Option Gamma
    5. 5. Portfolio Risk Using Gamma
    6. 6. Portfolio Risk Using Full Valuation
    7. 7. A Simple Example
    8. 8. Pitfall in the Delta and Gamma Approaches
    9. 9. Summary
  19. 12. Credit Risk Management
    1. 1. Chapter Overview
    2. 2. A Brief History of Corporate Defaults
    3. 3. Modeling Corporate Default
    4. 4. Portfolio Credit Risk
    5. 5. Other Aspects of Credit Risk
    6. 6. Summary
  20. 13. Backtesting and Stress Testing
    1. 1. Chapter Overview
    2. 2. Backtesting VaRs
    3. 3. Increasing the Information Set
    4. 4. Backtesting Expected Shortfall
    5. 5. Backtesting the Entire Distribution
    6. 6. Stress Testing
    7. 7. Summary
  21. Index