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- Wiley
More About This Title Investment Risk and Uncertainty: Advanced Risk Awareness Techniques for the Intelligent Investor
English
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.
English
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.
English
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
