Edition 
1st ed 
Descript 
1 online resource (352 pages) 

text txt rdacontent 

computer c rdamedia 

online resource cr rdacarrier 
Series 
Wiley Finance Ser 

Wiley Finance Ser

Note 
Correlation Risk Modeling and Management: An Applied Guide Including the Basel III Correlation Frameworkwith Interactive Correlation Models in Excel®/VBA  Contents  Preface  Acknowledgments  About the Author  Chapter 1: Some Correlation Basics: Properties, Motivation, Terminology  1.1 What Are Financial Correlations?  1.2 What Is Financial Correlation Risk?  1.3 Motivation: Correlations and Correlation Risk Are Everywhere in Finance  1.3.1 Investments and Correlation  1.3.2 Trading and Correlation  1.3.3 Risk Management and Correlation  1.3.4 The Global Financial Crisis of 2007 to 2009 and Correlation  1.3.5 Regulation and Correlation  1.4 How Does Correlation Risk Fit into the Broader Picture of Risks in Finance?  1.4.1 Correlation Risk and Market Risk  1.4.2 Correlation Risk and Credit Risk  1.4.3 Correlation Risk and Systemic Risk  1.4.4 Correlation Risk and Concentration Risk  1.5 A Word on Terminology  1.6 Summary  Appendix 1A: Dependence and Correlation  Dependence  Correlation  Independence and Uncorrelatedness  Appendix 1B: On Percentage and Logarithmic Changes  Practice Questions and Problems  References and Suggested Readings  Chapter 2: Empirical Properties of Correlation: How Do Correlations Behave in the Real World?  2.1 How Do Equity Correlations Behave in a Recession, Normal Economic Period, or Strong Expansion?  2.2 Do Equity Correlations Exhibit Mean Reversion?  2.2.1 How Can We Quantify Mean Reversion?  2.3 Do Equity Correlations Exhibit Autocorrelation?  2.4 How Are Equity Correlations Distributed?  2.5 Is Equity Correlation Volatility an Indicator for Future Recessions?  2.6 Properties of Bond Correlations and Default Probability Correlations  2.7 Summary  Practice Questions and Problems  References and Suggested Readings 

Chapter 3: Statistical Correlation ModelsCan We Apply Them to Finance?  3.1 A Word on Financial Models  3.1.1 The Financial Model Itself  3.1.2 The Calibration of the Model  3.1.3 Mindfulness about Models  3.2 Statistical Correlation Measures  3.2.1 The Pearson Correlation Approach and Its Limitations for Finance  3.2.2 Spearman's Rank Correlation  3.2.3 Kendall's T  3.3 Should We Apply Spearman's Rank Correlation and Kendall's T in Finance?  3.4 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 4: Financial Correlation ModelingBottomUp Approaches  4.1 Correlating Brownian Motions (Heston 1993)  4.1.1 Applications of the Heston Model  4.2 The Binomial CorrelationMeasure  4.2.1 Application of the Binomial Correlation Measure  4.3 Copula Correlations  4.3.1 The Gaussian Copula  4.3.2 Simulating the Correlated Default Time for Multiple Assets  4.3.3 Finding the Correlated Default Time in a Continuous Time Framework Using Survival Probabilities  4.3.4 Copula Applications  4.3.5 Limitations of the Gaussian Copula  4.4 Contagion Correlation Models  4.5 Summary  Appendix 4A: Cholesky Decomposition  Example: Cholesky Decomposition for Three Assets  Appendix 4B: A Short Proof of the Gaussian Default Time Copula  Practice Questions and Problems  References and Suggested Readings  Chapter 5: Valuing CDOs with the Gaussian CopulaWhat Went Wrong?  5.1 CDO BasicsWhat Is a CDO? Why CDOs? Types of CDOs  5.1.1 What Is a CDO?  5.1.2 Why CDOs?  5.1.3 Types of CDOs  5.2 Valuing CDOs  5.2.1 Deriving the Default Probability for Each Asset in a CDO  5.2.2 Deriving the Default Correlation of the Assets in a CDO  5.2.3 Recovery Rate  5.3 Conclusion: The Gaussian Copula and CDOsWhat Went Wrong?  5.3.1 Complexity of CDOs 

5.3.2 The Gaussian Copula Model to Value CDOs  5.4 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 6: The OneFactor Gaussian Copula (OFGC) ModelToo Simplistic?  6.1 The Original OneFactor Gaussian Copula (OFGC) Model  6.2 Valuing Tranches of a CDO with the OFGC  6.2.1 Randomness in the OFGC Model  6.3 The Correlation Concept in the OFGC Model  6.3.1 The Loss Distribution of the OFGC Model  6.3.2 The Tranche SpreadCorrelation Relationship  6.4 The Relationship between the OFGC and the Standard Copula  6.5 Extensions of the OFGC  6.5.1 Further Extensions of the OFGC Model: Hybrid CIDContagion Modeling  6.6 ConclusionIs the OFGC Too Simplistic to Evaluate Credit Risk in Portfolios?  6.6.1 Benefits of the OFGC Model  6.6.2 Limitations of the OFGC Model  6.7 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 7: Financial Correlation ModelsTopDown Approaches  7.1 Vasicek's 1987 OneFactor Gaussian Copula (OFGC) Model Revisited  7.2 Markov Chain Models  7.2.1 Inducing Correlation via Transition Rate Volatilities  7.2.2 Inducing Correlation via Stochastic Time Change  7.3 Contagion Default Modeling in TopDown Models  7.4 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 8: Stochastic Correlation Models  8.1 What Is a Stochastic Process?  8.2 Sampling Correlation from a Distribution (Hull and White 2010)  8.3 Dynamic Conditional Correlations (DCCs) (Engle 2002)  8.4 Stochastic CorrelationStandard Models  8.4.1 The Geometric Brownian Motion (GBM)  8.4.2 The Vasicek 1977 Model  8.4.3 The Bounded Jacobi Process  8.5 Extending the Heston Model with Stochastic Correlation (Buraschi et al. 2010  Da Fonseca et al. 2008) 

8.5.1 Critical Appraisal of the Buraschi et al. (2010) and Da Fonseca et al. (2008) Model  8.6 Stochastic Correlation, Stochastic Volatility, and Asset Modeling (Lu and Meissner 2012)  8.6.1 Asset Modeling  8.7 Conclusion: Should We Model Financial Correlations with a Stochastic Process?  8.8 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 9: Quantifying Market Correlation Risk  9.1 The Correlation Risk Parameters Cora and Gora  9.2 Examples of Cora in Financial Practice  9.2.1 Option Vanna  9.2.2 Option Cora and Gora  9.3 Cora and Gora in Investments  9.4 Cora in Market Risk Management  9.4.1 GapCora  9.5 Gora in Market Risk Management  9.6 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 10: Quantifying Credit Correlation Risk  10.1 Credit Correlation Risk in a CDS  10.2 Pricing CDSs, Including Reference EntityCounterparty Credit Correlation  10.2.1 The Model  10.3 Pricing CDSs, Including the Credit Correlation of All Three Entities  10.3.1 The Model  10.3.2 Cora for CDSs  10.3.3 Gora for CDSs  10.4 Correlation Risk in a Collateralized Debt Obligation (CDO)  10.4.1 Types of Risk in a CDO  10.4.2 Cora of a CDO  10.4.3 Gora of a CDO  10.5 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 11: Hedging Correlation Risk  11.1 What Is Hedging?  11.2 Why Is Hedging Financial Correlations Challenging?  11.3 Two Examples to Hedge Correlation Risk  11.3.1 Hedging CDS Counterparty Risk with a CorrelationDependent Option  11.3.2 Hedging VaR Correlation Risk with a Correlation Swap  11.4 When to Use Options and When to Use Futures to Hedge  11.5 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 12: Correlation and Basel II and III 

12.1 What Are the Basel I, II, and III Accords? Why Do Most Sovereigns Implement The Accords?  12.2 Basel II and III's Credit Value at Risk (CVaR) Approach  12.2.1 Properties of Equation (12.7)  12.3 Basel II's Required Capital (RC) for Credit Risk  12.3.1 The Default ProbabilityDefault Correlation Relationship  12.4 Credit Value Adjustment (CVA) Approach without WrongWay Risk (WWR) in The Basel Accord  12.5 Credit Value Adjustment (CVA) with WrongWay Risk in the Basel Accord  12.5.1 How Do Basel II and III Quantify WrongWay Risk?  12.6 How Do the Basel Accords Treat Double Defaults?  12.6.1 Substitution Approach  12.6.2 Double Default Approach  12.7 Debt Value Adjustment (DVA): If Something Sounds Too Good to Be True . . .  12.8 Funding Value Adjustment (FVA)  12.9 Summary  Practice Questions and Problems  References and Suggested Readings  Chapter 13: The Future of Correlation Modeling  13.1 Numerical Finance: Solving Financial Problems Numerically with the Help of Graphical Processing Units (GPUs)  13.1.1 GPU Technology  13.1.2 A GPU Model for Valuing Portfolio Counterparty Risk  13.1.3 Benefits of GPUs  13.1.4 Limitations of GPUs  13.2 New Developments in Artificial Intelligence and Financial Modeling  13.2.1 Neural Networks  13.2.2 Fuzzy Logic  13.2.3 Genetic Algorithms  13.2.4 Chaos Theory  13.2.5 Bayesian Probabilities  13.3 Summary  Practice Questions and Problems  References and Suggested Readings  Glossary  Index 

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 

Description based on publisher supplied metadata and other sources 

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries 
Link 
Print version: Meissner, Gunter Correlation Risk Modeling and Management : An Applied Guide Including the Basel III Correlation Framework  with Interactive Models in Excel / VBA
New York : John Wiley & Sons, Incorporated,c2014 9781118796900

Subject 
Financial institutions  Risk management  Econometric models


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