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Correlation Risk Modeling and Management

Correlation Risk Modeling and Management An Applied Guide including the Basel III Correlation Framework - With Interactive Models in Excel / VBA

  • Author:
  • Publisher: John Wiley & Sons
  • ISBN: 9781118796900
  • Published In: January 2014
  • Format: Hardback , 350 pages
  • Jurisdiction: International ? Disclaimer:
    Countri(es) stated herein are used as reference only

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    A thorough guide to correlation risk and its growing importance in global financial markets

    Ideal for anyone studying for CFA, PRMIA, CAIA, or other certifications, Correlation Risk Modeling and Management is the first rigorous guide to the topic of correlation risk. A relatively overlooked type of risk until it caused major unexpected losses during the financial crisis of 2007 through 2009, correlation risk has become a major focus of the risk management departments in major financial institutions, particularly since Basel III specifically addressed correlation risk with new regulations. This offers a rigorous explanation of the topic, revealing new and updated approaches to modelling and risk managing correlation risk.

    • Offers comprehensive coverage of a topic of increasing importance in the financial world
    • Includes the Basel III correlation framework
    • Features interactive models in Excel/VBA, an accompanying website with further materials, and problems and questions at the end of each chapter
  • Preface xiii

    Acknowledgments xvii

    About the Author xix

    CHAPTER 1
    Some Correlation Basics: Properties, Motivation, Terminology 1

    1.1 What Are Financial Correlations? 1

    1.2 What Is Financial Correlation Risk? 2

    1.3 Motivation: Correlations and Correlation Risk Are Everywhere in Finance 5

    1.4 How Does Correlation Risk Fit into the Broader Picture of Risks in Finance? 24

    1.5 A Word on Terminology 33

    1.6 Summary 34

    Appendix 1A: Dependence and Correlation 35

    Dependence 35

    Correlation 36

    Independence and Uncorrelatedness 37

    Appendix 1B: On Percentage and Logarithmic Changes 38

    Practice Questions and Problems 39

    References and Suggested Readings 40

    CHAPTER 2
    Empirical Properties of Correlation: How Do Correlations Behave in the Real World? 43

    2.1 How Do Equity Correlations Behave in a Recession, Normal Economic Period, or Strong Expansion? 43

    2.2 Do Equity Correlations Exhibit Mean Reversion? 46

    2.3 Do Equity Correlations Exhibit Autocorrelation? 50

    2.4 How Are Equity Correlations Distributed? 51

    2.5 Is Equity Correlation Volatility an Indicator for Future Recessions? 52

    2.6 Properties of Bond Correlations and Default Probability Correlations 53

    2.7 Summary 54

    Practice Questions and Problems 55

    References and Suggested Readings 55

    CHAPTER 3
    Statistical Correlation Models—Can We Apply Them to Finance? 57

    3.1 AWord on Financial Models 57

    3.2 Statistical Correlation Measures 60

    3.3 Should We Apply Spearman’s Rank Correlation and Kendall’s t in Finance? 65

    3.4 Summary 66

    Practice Questions and Problems 67

    References and Suggested Readings 68

    CHAPTER 4
    Financial Correlation Modeling—Bottom-Up Approaches 69

    4.1 Correlating Brownian Motions (Heston 1993) 69

    4.2 The Binomial CorrelationMeasure 72

    4.3 Copula Correlations 74

    4.4 Contagion Correlation Models 88

    4.5 Summary 90

    Appendix 4A: Cholesky Decomposition 91

    Example: Cholesky Decomposition for Three Assets 92

    Appendix 4B: A Short Proof of the Gaussian Default

    Time Copula 93

    Practice Questions and Problems 93

    References and Suggested Readings 94

    CHAPTER 5
    Valuing CDOs with the Gaussian Copula—What Went Wrong? 101

    5.1 CDO Basics—What Is a CDO? Why CDOs? Types of CDOs 101

    5.2 Valuing CDOs 105

    5.3 Conclusion: The Gaussian Copula and CDOs—What Went Wrong? 113

    5.4 Summary 115

    Practice Questions and Problems 116

    References and Suggested Readings 117

    CHAPTER 6
    The One-Factor Gaussian Copula (OFGC) Model—Too Simplistic? 119

    6.1 The Original One-Factor Gaussian Copula (OFGC) Model 121

    6.2 Valuing Tranches of a CDO with the OFGC 122

    6.3 The Correlation Concept in the OFGC Model 128

    6.4 The Relationship between the OFGC and the Standard Copula 131

    6.5 Extensions of the OFGC 132

    6.6 Conclusion—Is the OFGC Too Simplistic to Evaluate Credit Risk in Portfolios? 135

    6.7 Summary 138

    Practice Questions and Problems 139

    References and Suggested Readings 140

    CHAPTER 7
    Financial Correlation Models—Top-Down Approaches 143

    7.1 Vasicek’s 1987 One-Factor Gaussian Copula (OFGC) Model Revisited 144

    7.2 Markov Chain Models 146

    7.2.1 Inducing Correlation via Transition Rate Volatilities 146

    7.3 Contagion Default Modeling in Top-Down Models 150

    7.4 Summary 153

    Practice Questions and Problems 154

    References and Suggested Readings 154

    CHAPTER 8
    Stochastic Correlation Models 157

    8.1 What Is a Stochastic Process? 157

    8.2 Sampling Correlation from a Distribution (Hull and White 2010) 159

    8.3 Dynamic Conditional Correlations (DCCs) (Engle 2002) 160

    8.4 Stochastic Correlation—Standard Models 162

    8.5 Extending the Heston Model with Stochastic Correlation (Buraschi et al. 2010; Da Fonseca et al. 2008) 168

    8.6 Stochastic Correlation, Stochastic Volatility, and Asset Modeling (Lu and Meissner 2012) 172

    8.7 Conclusion: Should We Model Financial Correlations with a Stochastic Process? 176

    8.8 Summary 177

    Practice Questions and Problems 177

    References and Suggested Readings 178

    CHAPTER 9
    Quantifying Market Correlation Risk 181

    9.1 The Correlation Risk Parameters Cora and Gora 182

    9.2 Examples of Cora in Financial Practice 184

    9.3 Cora and Gora in Investments 187

    9.4 Cora in Market Risk Management 189

    9.5 Gora in Market Risk Management 197

    9.6 Summary 198

    Practice Questions and Problems 199

    References and Suggested Readings 200

    CHAPTER 10
    Quantifying Credit Correlation Risk 201

    10.1 Credit Correlation Risk in a CDS 203

    10.2 Pricing CDSs, Including Reference Entity–Counterparty Credit Correlation 205

    10.3 Pricing CDSs, Including the Credit Correlation of All Three Entities 215

    10.4 Correlation Risk in a Collateralized Debt Obligation (CDO) 227

    10.5 Summary 231

    Practice Questions and Problems 232

    References and Suggested Readings 233

    CHAPTER 11
    Hedging Correlation Risk 235

    11.1 What Is Hedging? 235

    11.2 Why Is Hedging Financial Correlations Challenging? 238

    11.3 Two Examples to Hedge Correlation Risk 239

    11.4 When to Use Options and When to Use Futures to Hedge 247

    11.5 Summary 248

    Practice Questions and Problems 249

    References and Suggested Readings 249

    CHAPTER 12
    Correlation and Basel II and III 251

    12.1 What Are the Basel I, II, and III Accords? Why Do Most Sovereigns Implement The Accords? 251

    12.2 Basel II and III’s Credit Value at Risk (CVaR) Approach 252

    12.3 Basel II’s Required Capital (RC) for Credit Risk 258

    12.4 Credit Value Adjustment (CVA) Approach without Wrong-Way Risk (WWR) in The Basel Accord 261

    12.5 Credit Value Adjustment (CVA) with Wrong-Way Risk in the Basel Accord 264

    12.6 How Do the Basel Accords Treat Double Defaults? 269

    12.7 Debt Value Adjustment (DVA): If Something Sounds Too Good to Be True . . . 274

    12.8 Funding Value Adjustment (FVA) 276

    12.9 Summary 278

    Practice Questions and Problems 280

    References and Suggested Readings 280

    CHAPTER 13
    The Future of Correlation Modeling 283

    13.1 Numerical Finance: Solving Financial Problems Numerically with the Help of Graphical Processing Units (GPUs) 283

    13.2 New Developments in Artificial Intelligence and Financial Modeling 287

    13.3 Summary 298

    Practice Questions and Problems 300

    References and Suggested Readings 300

    Glossary 303

    Index 315

  • GUNTER MEISSNER, PH.D., heads Dersoft (www.dersoft.com), the software company behind TradeSmart, a software package that derives futures, options, and swaps prices and risk parameters. In addition, he runs a hedge fund (www. cassandracm.com), and is Adjunct Professor of Mathematical Finance at NYU.

    Dr. Meissner joined Deutsche Bank in 1990, where he traded interest rate futures, swaps, and options in Frankfurt and New York. He became Head of Product Development in 1994, responsible for originating algorithms for new derivatives products. In 1995/1996 Dr. Meissner became Head of Options at Deutsche Bank Tokyo. From 1997 to 2007, he was Professor of Finance at Hawaii Pacific University. From 2008 to 2013 he was Director of the Master in Financial Engineering program at the Shidler College of Business at the University of Hawaii. The author of numerous published papers on derivatives in international journals, Dr. Meissner also is a frequent speaker at international conferences and seminars and the author of four other books, including The Definitive Guide to CDOs: Application, Pricing, and Risk Management.

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