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
- Cover
- series
- Title Page
- Copyright
- Foreword
- Preface
- Acknowledgments
-
Introduction: Why Risk Management Is Mostly Misunderstood
- QUANTITATIVE RISK MANAGEMENT BEGINNINGS
- QUANTITATIVE RISK MANAGEMENT SUCCESSES
- QUANTITATIVE RISK MANAGEMENT FAILURES
- WARREN BUFFETT’S RISK MANAGEMENT STRATEGY
- DEFINING RISK MANAGEMENT
- FAT TAILS, STATIONARITY, CORRELATION, AND OPTIMIZATION
- MANAGING THE RISKS OF A RISK MANAGEMENT STRATEGY
- THE RISK MANAGEMENT OPPORTUNITY SET
- NOTES
-
Part One
- Chapter 1: Exposed versus Experienced Risk Revisited
- CHAPTER 2: Definitions of Tractable Risk
- CHAPTER 3: Introduction to Asset Class Specifics
- CHAPTER 4: Commodities and Currencies
- CHAPTER 5: Options and Interest Rate Derivatives
- CHAPTER 6: Measuring Asset Association and Dependence
- CHAPTER 7: Risk Model Construction
-
Part Two
- CHAPTER 8: Fixed Income Issues
- CHAPTER 9: Interest Rate Risk
- CHAPTER 10: Spread Risk
- CHAPTER 11: Fixed Income Interest Rate Volatility, Idiosyncratic Risk, and Currency Risk
- CHAPTER 12: Portfolio Risk Measures
- Chapter 13: Risk for the Fundamental Investor
-
Chapter 14: Portfolio Optimization
- THE ENHANCED MVO MODEL
- CONSTRAINTS AND OBJECTIVES IN EMVO
- FURTHER IMPROVEMENTS TO THE ENHANCED MVO MODEL
- FACTOR ALIGNMENT PROBLEMS
- CONSTRAINT ATTRIBUTION
- SPECIALLY STRUCTURED MVO MODELS
- EXTREME TAIL LOSS OPTIMIZATION
- INCORPORATING NONLINEAR INSTRUMENTS IN THE EMVO MODEL
- ALGORITHMS FOR SOLVING MVO MODELS
- HOW TO CHOOSE AN OPTIMIZER
- NOTES
-
Part Three
-
Chapter 15: The SunGard APT Risk Management System
- INTRODUCTION TO STATISTICAL FACTOR MODELS
- APT FACTOR MODEL ESTIMATION—EQUITIES MODELS
- SELECTION OF THE CORE UNIVERSE FOR FACTOR MODELING
- CHOOSING THE NUMBER OF APT FACTORS
- ESTIMATING THE RISK PROFILES IN AN APT FACTOR MODEL
- APT MULTI-ASSET-CLASS FACTOR MODEL ESTIMATION
- MODELING DERIVATIVES AND OTHER NONUNDERLYING SECURITIES
- USER-DEFINED ASSETS WITHIN APT MODELS
- CONCLUSION
- NOTES
- Chapter 16: Axioma Risk Models
- Chapter 17: Distinguishing Risk Models
- Chapter 18: Northfield’s Integration of Risk Assessments across Multiple Asset Classes
-
Chapter 19: R-Squared
- WHY BUILD STOCK RISK MODELS?
- GENERIC RISK MODELING
- PRACTICAL RISK MODELING
- STATISTICAL FACTOR MODELS
- DEFINED FACTOR MODELS
- ESTIMATE FACTORS OR ESTIMATE BETAS?
- PRACTICAL CONSEQUENCES AT THE STOCK LEVEL
- PRACTICAL CONSEQUENCES AT THE PORTFOLIO LEVEL
- A SHORT DIGRESSION
- HYBRID RISK MODELS
- THE R-SQUARED SHORT-TERM HYBRID RISK MODEL FOR GLOBAL EQUITIES
- SUMMARY
- NOTE
- Chapter 20: The Future of Risk Management and Analytics
-
Chapter 15: The SunGard APT Risk Management System
- Index
Product information
- Title: Investment Risk and Uncertainty: Advanced Risk Awareness Techniques for the Intelligent Investor
- Author(s):
- Release date: March 2013
- Publisher(s): Wiley
- ISBN: 9781118300183
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