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Quantitative Risk Management: A Practical Guide to Financial Risk, + Website

Book Description

State of the art risk management techniques and practices—supplemented with interactive analytics

All too often risk management books focus on risk measurement details without taking a broader view. Quantitative Risk Management delivers a synthesis of common sense management together with the cutting-edge tools of modern theory. This book presents a road map for tactical and strategic decision making designed to control risk and capitalize on opportunities. Most provocatively it challenges the conventional wisdom that "risk management" is or ever should be delegated to a separate department. Good managers have always known that managing risk is central to a financial firm and must be the responsibility of anyone who contributes to the profit of the firm.

A guide to risk management for financial firms and managers in the post-crisis world, Quantitative Risk Management updates the techniques and tools used to measure and monitor risk. These are often mathematical and specialized, but the ideas are simple. The book starts with how we think about risk and uncertainty, then turns to a practical explanation of how risk is measured in today's complex financial markets.

  • Covers everything from risk measures, probability, and regulatory issues to portfolio risk analytics and reporting

  • Includes interactive graphs and computer code for portfolio risk and analytics

  • Explains why tactical and strategic decisions must be made at every level of the firm and portfolio

Providing the models, tools, and techniques firms need to build the best risk management practices, Quantitative Risk Management is an essential volume from an experienced manager and quantitative analyst.

Table of Contents

  1. Cover
  2. Series Page
  3. Title Page
  4. Copyright
  5. Dedication
  6. Foreword
  7. Preface
  8. Acknowledgments
  9. Part One: Managing Risk
    1. Chapter 1: Risk Management versus Risk Measurement
      1. 1.1 Contrasting Risk Management and Risk Measurement
      2. 1.2 Redefinition and Refocus for Risk Management
      3. 1.3 Quantitative Measurement and a Consistent Framework
      4. 1.4 Systemic versus Idiosyncratic Risk
    2. Chapter 2: Risk, Uncertainty, Probability, and Luck
      1. 2.1 What Is Risk?
      2. 2.2 Risk Measures
      3. 2.3 Randomness and the Illusion of Certainty
      4. 2.4 Probability and Statistics
      5. 2.5 The Curse of Overconfidence
      6. 2.6 Luck
    3. Chapter 3: Managing Risk
      1. 3.1 Manage People
      2. 3.2 Manage Infrastructure—Process, Technology, Data
      3. 3.3 Understand the Business
      4. 3.4 Organizational Structure
      5. 3.5 Brief Overview of Regulatory Issues
      6. 3.6 Managing the Unanticipated
      7. 3.7 Conclusion
    4. Chapter 4: Financial Risk Events
      1. 4.1 Systemic versus Idiosyncratic Risk
      2. 4.2 Idiosyncratic Financial Events
      3. 4.3 Systemic Financial Events
      4. 4.4 Conclusion
    5. Chapter 5: Practical Risk Techniques
      1. 5.1 Value of Simple, Approximate Answers
      2. 5.2 Volatility and Value at Risk (VaR)
      3. 5.3 Extreme Events
      4. 5.4 Calculating Volatility and VaR
      5. 5.5 Summary for Volatility and VaR
      6. 5.6 Portfolio Tools
      7. 5.7 Conclusion
    6. Chapter 6: Uses and Limitations of Quantitative Techniques
      1. 6.1 Risk Measurement Limitations
  10. Part Two: Measuring Risk
    1. Chapter 7: Introduction to Quantitative Risk Measurement
      1. 7.1 Project Implementation
      2. 7.2 Typology of Financial Institution Risks
      3. 7.3 Conclusion
    2. Chapter 8: Risk and Summary Measures: Volatility and VaR
      1. 8.1 Risk and Summary Measures
      2. 8.2 Comments Regarding Quantitative Risk Measures
      3. 8.3 Methods for Estimating the P&L Distribution
      4. 8.4 Techniques and Tools for Tail Events
      5. 8.5 Estimating Risk Factor Distributions
      6. 8.6 Uncertainty and Randomness—the Illusion of Certainty
      7. 8.7 Conclusion
      8. Appendix 8.1: Small-Sample Distribution of VaR and Standard Errors
      9. Appendix 8.2: Second Derivatives and the Parametric Approach
    3. Chapter 9: Using Volatility and VaR
      1. 9.1 Simple Portfolio
      2. 9.2 Calculating P&L Distribution
      3. 9.3 Summary Measures to Standardize and Aggregate
      4. 9.4 Tail Risk or Extreme Events
      5. 9.5 Conclusion
      6. 9.6 Appendix 9.1: Parametric Estimation Using Second Derivatives
    4. Chapter 10: Portfolio Risk Analytics and Reporting
      1. 10.1 Volatility, Triangle Addition, and Risk Reduction
      2. 10.2 Contribution to Risk
      3. 10.3 Best Hedge
      4. 10.4 Replicating Portfolio
      5. 10.5 Principal Components and Risk Aggregation
      6. 10.6 Risk Reporting
      7. 10.7 Conclusion
      8. Appendix 10.1: Various Formulae for Marginal Contribution and Volatilities
      9. Appendix B: Stepwise Procedure for Replicating Portfolio
      10. Appendix C: Principal Components Overview
    5. Chapter 11: Credit Risk
      1. 11.1 Introduction
      2. 11.2 Credit Risk versus Market Risk
      3. 11.3 Stylized Credit Risk Model
      4. 11.4 Taxonomy of Credit Risk Models
      5. 11.5 Static Structural Models
      6. 11.6 Static Reduced Form Models—CreditRisk+
      7. 11.7 Static Models—Threshold and Mixture Frameworks
      8. 11.8 Actuarial versus Equivalent Martingale (Risk-Neutral) Pricing
      9. 11.9 Dynamic Reduced Form Models
      10. 11.10 Conclusion
      11. Appendix 11.1: Probability Distributions
    6. Chapter 12: Liquidity and Operational Risk
      1. 12.1 Liquidity Risk—Asset versus Funding Liquidity
      2. 12.2 Asset Liquidity Risk
      3. 12.3 Funding Liquidity Risk
      4. 12.4 Operational Risk
      5. 12.5 Conclusion
    7. Chapter 13: Conclusion
  11. About the Companion Web Site
  12. References
  13. About the Author
  14. Index