Investment Risk and Uncertainty Advanced Risk Awareness Techniques for the Intelligent Investor Wiley Finance Series, Vol. 832

Valuable insights on the major methods used in today′s asset and risk management arena Risk management has moved to the forefront of asset management since the credit crisis. However, most coverage of this subject is overly complicated, misunderstood, and extremely hard to apply. That′s why Steven Greiner—a financial professional with over twenty years of quantitative and modeling experience—has written Investment Risk and Uncertainty. With this book, he skillfully reduces the complexity of risk management methodologies applied across many asset classes through practical examples of when to use what. Along the way, Greiner explores how particular methods can lower risk and mitigate losses. He also discusses how to stress test your portfolio and remove the exposure to regular risks and those from "Black Swan" events. More than just an explanation of specific risk issues, this reliable resource provides practical "off–the–shelf" applications that will allow the intelligent investor to understand their risks, their sources, and how to hedge those risks. Covers modern methods applied in risk management for many different asset classes Details the risk measurements of truly multi–asset class portfolios, while bridging the gap for managers in various disciplines—from equity and fixed income investors to currency and commodity investors Examines risk management algorithms for multi–asset class managers as well as risk managers, addressing new compliance issues and how to meet them The theory of risk management is hardly ever spelled out in practical applications that portfolio managers, pension fund advisors, and consultants can make use of. This book fills that void and will put you in a better position to confidently face the investment risks and uncertainties found in today′s dynamic markets.

Foreword xiii Preface xv Acknowledgments xvii Introduction Why Risk Management Is Mostly Misunderstood 1 Steven P. Greiner, PhD Quantitative Risk Management Beginnings 3 Quantitative Risk Management Successes 8 Quantitative Risk Management Failures 11 Warren Buffett’s Risk Management Strategy 14 Defining Risk Management 16 Fat Tails, Stationarity, Correlation, and Optimization 18 Managing the Risks of a Risk Management Strategy 23 The Risk Management Opportunity Set 25 Notes 29 Part One Chapter 1 Exposed versus Experienced Risk Revisited 33 Steven P. Greiner, PhD, and Andrew Geer, CFA, FRM Exposure Hedge versus Dollar Hedge 37 How the Credit Crisis Moved Risk Management to the Forefront 47 Risks beyond Volatility 49 What Risk Management Should Provide 51 Clarifying Expectations of Risk Management 54 An Example 55 Notes 58 Chapter 2 Definitions of Tractable Risk 59 Steven P. Greiner, PhD, and Andrew Geer, CFA, FRM The Effect of Uncertainty on Objectives 59 Identifying and Measuring Risks 63 Forecasting and Hedging Risks 71 Portfolio View versus Security–Level View 75 Total Risk View of Multi–Asset–Class (MAC) Portfolios 82 Stability and Accuracy 84 Note 86 Chapter 3 Introduction to Asset Class Specifics 87 Steven P. Greiner, PhD; Andrew Geer, CFA, FRM; and William F. McCoy, CFA, PRM Equities 87 Fixed Income 96 Conclusion 117 Notes 118 Chapter 4 Commodities and Currencies 121 Steven P. Greiner, PhD, and William F. McCoy, CFA, PRM Commodities 121 Introduction to Currency Risk 138 Conclusion 143 Notes 144 Chapter 5 Options and Interest Rate Derivatives 145 Steven P. Greiner, PhD; William F. McCoy, CFA, PRM; and Mido Shammaa, CFA, FRM Short History of Option Pricing 145 Volatility Smile 149 Implied Volatility Model 151 Baroni–Adesi Whaley (BAW) Option Pricing Methodology 161 Other Option Pricing Methods 162 Swaps, Swaptions, Forwards, and Futures 165 Conclusion 181 Notes 182 Chapter 6 Measuring Asset Association and Dependence 183 Steven P. Greiner, PhD; Andrew Geer, CFA, FRM; Christopher Carpentier, CFA, FRM; and Dan diBartolomeo The Sample Covariance Matrix 183 Estimation Error Maximization 184 Minimizing the Extremes 185 The Copula, the Most Comprehensive Dependent Structure Measure 193 The Model Covariance Matrix 196 Notes 197 Chapter 7 Risk Model Construction 199 Steven P. Greiner, PhD; Andrew Geer, CFA, FRM; Jason MacQueen; Laurence Wormald, PhD Multifactor Prespecified Risk Models 199 Principal Component (Statistical) Risk Models 205 Customized Hybrid Risk Models 212 Notes 229 Part Two Chapter 8 Fixed Income Issues 233 David Mieczkowski, PhD, and William F. McCoy, CFA, PRM Variety. Illiquidity. Size. 235 Empirical Evidence 240 Test Portfolios and Methodology 241 Test Metrics 242 Computational Efficiency 248 Conclusion 249 Notes 250 Chapter 9 Interest Rate Risk 251 David Mieczkowski, PhD, and Mido Shammaa, CFA, FRM The Term Structure 252 Term Structure Dynamics 258 Factor Models 258 Stochastic Differential Equations 267 Interest Rate Risk Exposures 273 Risk Forecasting 278 Conditional Duration and Expected Tail Duration 281 Conclusion 282 Notes 283 Chapter 10 Spread Risk 285 David Mieczkowski, PhD, and Sameer R. Patel Spread Basics 286 Reduced Form Approach 290 Structural Approach 292 Spread Exposure 295 Spread Volatility 296 Derived Spread Approach 297 Euro–Sovereign Spreads 308 Factor Model Approach 312 Conclusion 322 Notes 324 Chapter 11 Fixed Income Interest Rate Volatility, Idiosyncratic Risk, and Currency Risk 325 David Mieczkowski, PhD, and Steven P. Greiner, PhD Fixed Income Interest Rate Risk 325 Fixed Income Idiosyncratic Bond Risk 346 Fixed Income Currency Risk 352 Conclusion 367 Notes 368 Chapter 12 Portfolio Risk Measures 369 William F. McCoy, CFA, PRM, and Steven P. Greiner, PhD Coherent Risk Measures 370 Commonly Used Risk Measures 370 Marginal Contribution 375 Stress–Testing 377 Notes 399 Chapter 13 Risk for the Fundamental Investor 401 Richard Barrett, CFA, FRM; Roberto Isch, CFA, FRM; and Steven P. Greiner, PhD Fundamental Investing versus Other Approaches 401 Typical Risk Controls for Fundamental Investors 403 Implementing Risk Management Strategies into a Fundamental Process 405 Optimization 421 Conclusion 428 Chapter 14 Portfolio Optimization 429 Sebastian Ceria, PhD, and Kartik Sivaramakrishnan, PhD The Enhanced MVO Model 432 Constraints and Objectives in EMVO 434 Further Improvements to the Enhanced MVO Model 441 Factor Alignment Problems 443 Constraint Attribution 445 Specially Structured MVO Models 448 Extreme Tail Loss Optimization 450 Incorporating Nonlinear Instruments in the EMVO Model 452 Algorithms for Solving MVO Models 453 How to Choose an Optimizer 456 Notes 459 Part Three Chapter 15 The SunGard APT Risk Management System 465 Laurence Wormald, PhD Introduction to Statistical Factor Models 465 APT Factor Model Estimation—Equities Models 468 Selection of the Core Universe for Factor Modeling 469 Choosing the Number of APT Factors 470 Estimating the Risk Profiles in an APT Factor Model 471 APT Multi–Asset–Class Factor Model Estimation 474 Modeling Derivatives and Other Nonunderlying Securities 477 User–Defined Assets within APT Models 479 Conclusion 480 Notes 481 Chapter 16 Axioma Risk Models 483 Bill Wynne; Melissa Brown, CFA; and Sebastian Ceria, PhD Background 483 Risk Model–Based Reporting 484 Role of Risk Models in Investment Decisions 485 Axioma Value at a High Level 486 Daily Risk Models, Delivered Daily 487 Multiple Risk Models 488 Empirical Results 489 Details of Axioma Innovations 492 Conclusion 506 Notes 506 Chapter 17 Distinguishing Risk Models 507 Steven P. Greiner, PhD, and Richard Barrett, CFA, FRM History 507 Risk Model Details 508 Risk Model–Based Reporting 510 Conclusion 520 Notes 521 Chapter 18 Northfield’s Integration of Risk Assessments across Multiple Asset Classes 523 Dan diBartolomeo, PRM, and Joseph J. Importico, CFA, FRM A Unified Framework 524 Interest Rate Risk 526 Credit Risk 527 Equity Factor Representation of Corporate Credit Risk 528 Default Correlation 529 Complex Instruments and Derivatives 531 Private Equity 532 Direct Real Estate and Geographically Localized Assets 536 Concluding Example 540 Conclusion 543 References 544 Chapter 19 R–Squared 547 Jason MacQueen Why Build Stock Risk Models? 547 Generic Risk Modeling 548 Practical Risk Modeling 551 Statistical Factor Models 552 Defined Factor Models 554 Estimate Factors or Estimate Betas? 555 Practical Consequences at the Stock Level 557 Practical Consequences at the Portfolio Level 557 A Short Digression 558 Hybrid Risk Models 559 The R–Squared Short–Term Hybrid Risk Model for Global Equities 560 Summary 565 Note 565 Chapter 20 The Future of Risk Management and Analytics 567 Steven P. Greiner, PhD; David Mieczkowski, PhD; William F. McCoy, CFA, PRM; Andrew Geer, CFA, FRM; Daniel S. Mathon, PhD, CFA; Viviana Vieli; Christopher Carpentier, CFA, FRM; Mido Shammaa, CFA, FRM; and Sameer R. Patel The Increasing Regulatory Environment 569 The Impact of Regulations with Technology 571 The Future View 572 New Types of Risk Models 573 Stress–Testing Your Way to Event Risk Preparedness 577 Index 579

STEVEN GREINER is currently the head of Risk Research for FactSet Research Systems. He has served as the senior quantitative strategist and portfolio manager for Allegiant Asset Management (now wholly owned by PNC Capital Advisors) and was a member of its investment committee. Prior to this, Greiner was a senior quantitative strategist for large capitalization investments at Harris Investment Management. He has more than twenty years of quantitative and modeling experience. Greiner received his BS in mathematics and chemistry from the University at Buffalo, his MS and PhD in physical chemistry from the University of Rochester, and attained postdoctoral experience from the Free University Berlin, Department of Physics. Greiner has published numerous papers and is the author of the Wiley book Ben Graham Was a Quant.