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Investment Risk and Uncertainty: Advanced Risk Awareness Techniques for the Intelligent Investor

Book Description

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.

Table of Contents

  1. Cover
  2. series
  3. Title Page
  4. Copyright
  5. Foreword
  6. Preface
    1. HOW THE BOOK IS ORGANIZED
  7. Acknowledgments
  8. Introduction: Why Risk Management Is Mostly Misunderstood
    1. QUANTITATIVE RISK MANAGEMENT BEGINNINGS
    2. QUANTITATIVE RISK MANAGEMENT SUCCESSES
    3. QUANTITATIVE RISK MANAGEMENT FAILURES
    4. WARREN BUFFETT’S RISK MANAGEMENT STRATEGY
    5. DEFINING RISK MANAGEMENT
    6. FAT TAILS, STATIONARITY, CORRELATION, AND OPTIMIZATION
    7. MANAGING THE RISKS OF A RISK MANAGEMENT STRATEGY
    8. THE RISK MANAGEMENT OPPORTUNITY SET
    9. NOTES
  9. Part One
    1. Chapter 1: Exposed versus Experienced Risk Revisited
      1. EXPOSURE HEDGE VERSUS DOLLAR HEDGE
      2. HOW THE CREDIT CRISIS MOVED RISK MANAGEMENT TO THE FOREFRONT
      3. RISKS BEYOND VOLATILITY
      4. WHAT RISK MANAGEMENT SHOULD PROVIDE
      5. CLARIFYING EXPECTATIONS OF RISK MANAGEMENT
      6. AN EXAMPLE
      7. NOTES
    2. CHAPTER 2: Definitions of Tractable Risk
      1. THE EFFECT OF UNCERTAINTY ON OBJECTIVES
      2. IDENTIFYING AND MEASURING RISKS
      3. FORECASTING AND HEDGING RISKS
      4. PORTFOLIO VIEW VERSUS SECURITY-LEVEL VIEW
      5. TOTAL RISK VIEW OF MULTI-ASSET-CLASS (MAC) PORTFOLIOS
      6. STABILITY AND ACCURACY
      7. NOTE
    3. CHAPTER 3: Introduction to Asset Class Specifics
      1. EQUITIES
      2. FIXED INCOME
      3. CONCLUSION
      4. NOTES
    4. CHAPTER 4: Commodities and Currencies
      1. COMMODITIES
      2. INTRODUCTION TO CURRENCY RISK
      3. CONCLUSION
      4. NOTES
    5. CHAPTER 5: Options and Interest Rate Derivatives
      1. SHORT HISTORY OF OPTION PRICING
      2. VOLATILITY SMILE
      3. IMPLIED VOLATILITY MODEL
      4. BARONI-ADESI WHALEY (BAW) OPTION PRICING METHODOLOGY
      5. OTHER OPTION PRICING METHODS
      6. SWAPS, SWAPTIONS, FORWARDS, AND FUTURES
      7. CONCLUSION
      8. NOTES
    6. CHAPTER 6: Measuring Asset Association and Dependence
      1. THE SAMPLE COVARIANCE MATRIX
      2. ESTIMATION ERROR MAXIMIZATION
      3. MINIMIZING THE EXTREMES
      4. THE COPULA, THE MOST COMPREHENSIVE DEPENDENT STRUCTURE MEASURE
      5. THE MODEL COVARIANCE MATRIX
      6. NOTES
    7. CHAPTER 7: Risk Model Construction
      1. MULTIFACTOR PRESPECIFIED RISK MODELS
      2. PRINCIPAL COMPONENT (STATISTICAL) RISK MODELS
      3. CUSTOMIZED HYBRID RISK MODELS
      4. NOTES
  10. Part Two
    1. CHAPTER 8: Fixed Income Issues
      1. VARIETY. ILLIQUIDITY. SIZE.
      2. EMPIRICAL EVIDENCE
      3. TEST PORTFOLIOS AND METHODOLOGY
      4. TEST METRICS
      5. COMPUTATIONAL EFFICIENCY
      6. CONCLUSION
      7. NOTES
    2. CHAPTER 9: Interest Rate Risk
      1. THE TERM STRUCTURE
      2. TERM STRUCTURE DYNAMICS
      3. FACTOR MODELS
      4. STOCHASTIC DIFFERENTIAL EQUATIONS
      5. INTEREST RATE RISK EXPOSURES
      6. RISK FORECASTING
      7. CONDITIONAL DURATION AND EXPECTED TAIL DURATION
      8. CONCLUSION
      9. NOTES
    3. CHAPTER 10: Spread Risk
      1. SPREAD BASICS
      2. REDUCED FORM APPROACH
      3. STRUCTURAL APPROACH
      4. SPREAD EXPOSURE
      5. SPREAD VOLATILITY
      6. DERIVED SPREAD APPROACH
      7. EURO-SOVEREIGN SPREADS
      8. FACTOR MODEL APPROACH
      9. CONCLUSION
      10. NOTES
    4. CHAPTER 11: Fixed Income Interest Rate Volatility, Idiosyncratic Risk, and Currency Risk
      1. FIXED INCOME INTEREST RATE RISK
      2. FIXED INCOME IDIOSYNCRATIC BOND RISK
      3. FIXED INCOME CURRENCY RISK
      4. CONCLUSION
      5. NOTES
    5. CHAPTER 12: Portfolio Risk Measures
      1. COHERENT RISK MEASURES
      2. COMMONLY USED RISK MEASURES
      3. MARGINAL CONTRIBUTION
      4. STRESS-TESTING
      5. NOTES
    6. Chapter 13: Risk for the Fundamental Investor
      1. FUNDAMENTAL INVESTING VERSUS OTHER APPROACHES
      2. TYPICAL RISK CONTROLS FOR FUNDAMENTAL INVESTORS
      3. IMPLEMENTING RISK MANAGEMENT STRATEGIES INTO A FUNDAMENTAL PROCESS
      4. OPTIMIZATION
      5. CONCLUSION
    7. Chapter 14: Portfolio Optimization
      1. THE ENHANCED MVO MODEL
      2. CONSTRAINTS AND OBJECTIVES IN EMVO
      3. FURTHER IMPROVEMENTS TO THE ENHANCED MVO MODEL
      4. FACTOR ALIGNMENT PROBLEMS
      5. CONSTRAINT ATTRIBUTION
      6. SPECIALLY STRUCTURED MVO MODELS
      7. EXTREME TAIL LOSS OPTIMIZATION
      8. INCORPORATING NONLINEAR INSTRUMENTS IN THE EMVO MODEL
      9. ALGORITHMS FOR SOLVING MVO MODELS
      10. HOW TO CHOOSE AN OPTIMIZER
      11. NOTES
  11. Part Three
    1. Chapter 15: The SunGard APT Risk Management System
      1. INTRODUCTION TO STATISTICAL FACTOR MODELS
      2. APT FACTOR MODEL ESTIMATION—EQUITIES MODELS
      3. SELECTION OF THE CORE UNIVERSE FOR FACTOR MODELING
      4. CHOOSING THE NUMBER OF APT FACTORS
      5. ESTIMATING THE RISK PROFILES IN AN APT FACTOR MODEL
      6. APT MULTI-ASSET-CLASS FACTOR MODEL ESTIMATION
      7. MODELING DERIVATIVES AND OTHER NONUNDERLYING SECURITIES
      8. USER-DEFINED ASSETS WITHIN APT MODELS
      9. CONCLUSION
      10. NOTES
    2. Chapter 16: Axioma Risk Models
      1. BACKGROUND
      2. RISK MODEL–BASED REPORTING
      3. ROLE OF RISK MODELS IN INVESTMENT DECISIONS
      4. AXIOMA VALUE AT A HIGH LEVEL
      5. DAILY RISK MODELS, DELIVERED DAILY
      6. MULTIPLE RISK MODELS
      7. EMPIRICAL RESULTS
      8. DETAILS OF AXIOMA INNOVATIONS
      9. CONCLUSION
      10. NOTES
    3. Chapter 17: Distinguishing Risk Models
      1. HISTORY
      2. RISK MODEL DETAILS
      3. RISK MODEL–BASED REPORTING
      4. CONCLUSION
      5. NOTES
    4. Chapter 18: Northfield’s Integration of Risk Assessments across Multiple Asset Classes
      1. A UNIFIED FRAMEWORK
      2. INTEREST RATE RISK
      3. CREDIT RISK
      4. EQUITY FACTOR REPRESENTATION OF CORPORATE CREDIT RISK
      5. DEFAULT CORRELATION
      6. COMPLEX INSTRUMENTS AND DERIVATIVES
      7. PRIVATE EQUITY
      8. DIRECT REAL ESTATE AND GEOGRAPHICALLY LOCALIZED ASSETS
      9. CONCLUDING EXAMPLE
      10. CONCLUSION
      11. REFERENCES
    5. Chapter 19: R-Squared
      1. WHY BUILD STOCK RISK MODELS?
      2. GENERIC RISK MODELING
      3. PRACTICAL RISK MODELING
      4. STATISTICAL FACTOR MODELS
      5. DEFINED FACTOR MODELS
      6. ESTIMATE FACTORS OR ESTIMATE BETAS?
      7. PRACTICAL CONSEQUENCES AT THE STOCK LEVEL
      8. PRACTICAL CONSEQUENCES AT THE PORTFOLIO LEVEL
      9. A SHORT DIGRESSION
      10. HYBRID RISK MODELS
      11. THE R-SQUARED SHORT-TERM HYBRID RISK MODEL FOR GLOBAL EQUITIES
      12. SUMMARY
      13. NOTE
    6. Chapter 20: The Future of Risk Management and Analytics
      1. THE INCREASING REGULATORY ENVIRONMENT
      2. THE IMPACT OF REGULATIONS WITH TECHNOLOGY
      3. THE FUTURE VIEW
      4. NEW TYPES OF RISK MODELS
      5. STRESS-TESTING YOUR WAY TO EVENT RISK PREPAREDNESS
  12. Index