Elements of Financial Risk Management.
Title:
Elements of Financial Risk Management.
Author:
Christoffersen, Peter.
ISBN:
9780080472614
Personal Author:
Physical Description:
1 online resource (229 pages)
Contents:
Front Cover -- ELEMENTS OF FINANCIAL RISK MANAGEMENT -- Copyright Page -- CONTENTS -- PREFACE -- ACKNOWLEDGMENTS -- Chapter 1. Risk Management and Financial Returns -- 1.1. Chapter Outline -- 1.2. Learning Objectives -- 1.3. Risk Management and the Firm -- 1.4. A Brief Taxonomy of Risks -- 1.5. Stylized Facts of Asset Returns -- 1.6. Overview of the Book -- 1.7. Further Resources -- 1.8. Empirical Exercises on CD-ROM -- References -- Chapter 2. Volatility Modeling -- 2.1. Chapter Overview -- 2.2. Simple Variance Forecasting -- 2.3. The Garch Variance Model -- 2.4. Extensions to the Garch Model -- 2.5. Maximum Likelihood Estimation -- 2.6. Variance Model Evaluation -- 2.7. Using Intraday Information -- 2.8. Summary -- 2.9. Further Resources -- 2.10. Empirical Exercises on CD-ROM -- References -- Chapter 3. Correlation Modeling -- 3.1. Chapter Overview -- 3.2. Value at Risk for Simple Portfolios -- 3.3. Portfolio Variance -- 3.4. Modeling Conditional Covariances -- 3.5. Modeling Conditional Correlations -- 3.6. Quasi-Maximum Likelihood Estimation -- 3.7. Realized and Range-Based Covariance -- 3.8. Summary -- 3.9. Further Resources -- 3.10. Appendix: VaR from Logarithmic versus Arithmetic Returns -- 3.11. Empirical Exercises on CD-ROM -- References -- Chapter 4. Modeling the Conditional Distribution -- 4.1. Chapter Overview -- 4.2. Visualizing Non-Normality -- 4.3. The Standardized t(d) Distribution -- 4.4. The Cornish-Fisher Approximation to VaR -- 4.5. Extreme Value Theory (EVT) -- 4.6. The Expected Shortfall Risk Measure -- 4.7. Summary -- 4.8. Further Resources -- 4.9. Empirical Exercises on CD-ROM -- References -- Chapter 5. Simulation-Based Methods -- 5.1. Chapter Overview -- 5.2. Historical Simulation (HS) -- 5.3. Weighted Historical Simulation (WHS) -- 5.4. Multi-Period Risk Calculations -- 5.5. Monte Carlo Simulation (MCS).
5.6. Filtered Historical Simulation (FHS) -- 5.7. Summary -- 5.8. Further Resources -- 5.9. Empirical Exercises on CD-ROM -- References -- Chapter 6. Option Pricing -- 6.1. Chapter Overview -- 6.2. Basic Definitions -- 6.3. Option Pricing Under the Normal Distribution -- 6.4. Allowing for Skewness and Kurtosis -- 6.5. Garch Option Pricing Models -- 6.6. Implied Volatility Function (IVF) Models -- 6.7. Summary -- 6.8. Further Resources -- 6.9. Appendix: The CFG Option Pricing Formula -- 6.10. Empirical Exercises on CD-ROM -- References -- Chapter 7. Modeling Option Risk -- 7.1. Chapter Overview -- 7.2. The Option Delta -- 7.3. Portfolio Risk Using Delta -- 7.4. The Option Gamma -- 7.5. Portfolio Risk Using Gamma -- 7.6. Portfolio Risk Using Full Valuation -- 7.7. A Simple Example -- 7.8. Pitfall in the Delta and Gamma Approaches -- 7.9. Summary -- 7.10. Further Resources -- 7.11. Empirical Exercises on CD-ROM -- References -- Chapter 8. Backtesting and Stress Testing -- 8.1. Chapter Overview -- 8.2. Backtesting VaRs -- 8.3. Increasing the Information Set -- 8.4. Backtesting Expected Shortfall -- 8.5. Backtesting the Entire Distribution -- 8.6. Stress Testing -- 8.7. Summary -- 8.8. Further Resources -- 8.9. Empirical Exercises on CD-ROM -- References -- Index.
Abstract:
Value-at-Risk has emerged as the standard tool for measuring and reporting financial market risk. Currently, more than eighty commercial vendors offer enterprise or trading risk management systems that provide VAR-like measures. Risk managers are therefore often left with the daunting task of having to choose from this plethora of risk measures. While basic VAR textbooks describe average VAR situations, the vast majority of these situations are abnormal. Elements of Financial Risk Management focuses on implementation, especially recent techniques which facilitate "bridging the gap" between standard textbooks on risk and real-life risk management systems. This book will appeal to practitioners in the financial services and investment industries, as well as graduate students and advanced undergraduates who want exposure to these techniques. *Pinpoints key features of risk asset returns and captures them in tractable statistical models in the companion website *Presents step-by-step approaches as a means to solve problems *Visible patterns in the data motivate the choices of tools, and when tools fall short, it presents the next tool.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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Electronic Access:
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