Hedge Funds
An Analytic Perspective - Updated Edition
1st Edition
Published on 1. July 2010
400 pages
978-1-4008-3581-2 (ISBN)
Description
The hedge fund industry has grown dramatically over the last two decades, with more than eight thousand funds now controlling close to two trillion dollars. Originally intended for the wealthy, these private investments have now attracted a much broader following that includes pension funds and retail investors. Because hedge funds are largely unregulated and shrouded in secrecy, they have developed a mystique and allure that can beguile even the most experienced investor. In Hedge Funds, Andrew Lo--one of the world's most respected financial economists--addresses the pressing need for a systematic framework for managing hedge fund investments.
Arguing that hedge funds have very different risk and return characteristics than traditional investments, Lo constructs new tools for analyzing their dynamics, including measures of illiquidity exposure and performance smoothing, linear and nonlinear risk models that capture alternative betas, econometric models of hedge fund failure rates, and integrated investment processes for alternative investments. In a new chapter, he looks at how the strategies for and regulation of hedge funds have changed in the aftermath of the financial crisis.
Arguing that hedge funds have very different risk and return characteristics than traditional investments, Lo constructs new tools for analyzing their dynamics, including measures of illiquidity exposure and performance smoothing, linear and nonlinear risk models that capture alternative betas, econometric models of hedge fund failure rates, and integrated investment processes for alternative investments. In a new chapter, he looks at how the strategies for and regulation of hedge funds have changed in the aftermath of the financial crisis.
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07/2010
Princeton University Press
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Person
Andrew W. Lo is the Harris & Harris Group Professor at the MIT Sloan School of Management, and director of the MIT Laboratory for Financial Engineering. He is the coauthor of A Non-Random Walk Down Wall Street and The Econometrics of Financial Markets (both Princeton).
Content
List of Tables xi
List of Figures xvii
List of Color Plates xxi
Acknowledgments xxiii
Chapter 1: Introduction 1
1.1 Tail Risk 7
1.2 Nonlinear Risks 13
1.3 Illiquidity and Serial Correlation 25
1.4 Literature Review 30
Chapter 2: Basic Properties of Hedge Fund Returns 34
2.1 CS/Tremont Indexes 37
2.2 Lipper TASS Data 40
2.3 Attrition Rates 43
Chapter 3: Serial Correlation, Smoothed Returns, and Illiquidity 64
3.1 An Econometric Model of Smoothed Returns 66
3.2 Implications for Performance Statistics 70
3.3 Estimation of Smoothing Profiles 75
3.4 Smoothing-Adjusted Sharpe Ratios 79
3.5 Empirical Analysis of Smoothing and Illiquidity 83
Chapter 4: Optimal Liquidity 97
4.1 Liquidity Metrics 98
4.2 Liquidity-Optimized Portfolios 105
4.3 Empirical Examples 107
4.4 Summary and Extensions 117
Chapter 5: Hedge Fund Beta Replication 121
5.1 Literature Review 123
5.2 Two Examples 124
5.3 Linear Regression Analysis 126
5.4 Linear Clones 138
5.5 Summary and Extensions 164
Chapter 6: A New Measure of Active Investment Management 168
6.1 Literature Review 170
6.2 The AP Decomposition 172
6.3 Some Analytical Examples 181
6.4 Implementing the AP Decomposition 186
6.5 An Empirical Application 193
6.6 Summary and Extensions 197
Chapter 7: Hedge Funds and Systemic Risk 198
7.1 Measuring Illiquidity Risk 200
7.2 Hedge Fund Liquidations 203
7.3 Regime-Switching Models 211
7.4 The Current Outlook 215
Chapter 8: An Integrated Hedge Fund Investment Process 217
8.1 Define Asset Classes by Strategy 221
8.2 Set Portfolio Target Expected Returns 222
8.3 Set Asset-Class Target Expected Returns and Risks 222
8.4 Estimate Asset-Class Covariance Matrix 223
8.5 Compute Minimum-Variance Asset Allocations 224
8.6 Determine Manager Allocations within Each Asset Class 225
8.7 Monitor Performance and Risk Budgets 227
8.8 The Final Specification 227
8.9 Risk Limits and Risk Capital 229
8.10 Summary and Extensions 235
Chapter 9: Practical Considerations 237
9.1 Risk Management as a Source of Alpha 237
9.2 Risk Preferences 239
9.3 Hedge Funds and the Efficient Markets Hypothesis 242
9.4 Regulating Hedge Funds 250
Chapter 10: What Happened to the Quants in August 2007? 255
10.1 Terminology 260
10.2 Anatomy of a Long/Short Equity Strategy 261
10.3 What Happened in August 2007? 269
10.4 Comparing August 2007 with August 1998 273
10.5 Total Assets, Expected Returns, and Leverage 276
10.6 The Unwind Hypothesis 281
10.7 Illiquidity Exposure 284
10.8 A Network View of the Hedge Fund Industry 286
10.9 Did Quant Fail? 292
10.10 Qualifications and Extensions 298
10.11 The Current Outlook 300
Chapter 11: Jumping the Gates 303
11.1 Linear Risk Models 305
11.2 Beta Overlays 308
11.3 Hedging Long/Short Equity Managers 310
11.4 Dynamic Implementations of Beta Overlays 317
11.5 Conclusion 319
Appendix 323
A.1 Lipper TASS Category Definitions 323
A.2 CS/Tremont Category Definitions 325
A.3 Matlab Loeb Function tloeb 328
A.4 GMM Estimators for the AP Decomposition 330
A.5 Constrained Optimization 332
A.6 A Contrarian Trading Strategy 333
A.7 Statistical Significance of Aggregate Autocorrelations 334
A.8 Beta-Blocker and Beta-Repositioning Strategies 335
A.9 Tracking Error 339
References 341
Index 355
List of Figures xvii
List of Color Plates xxi
Acknowledgments xxiii
Chapter 1: Introduction 1
1.1 Tail Risk 7
1.2 Nonlinear Risks 13
1.3 Illiquidity and Serial Correlation 25
1.4 Literature Review 30
Chapter 2: Basic Properties of Hedge Fund Returns 34
2.1 CS/Tremont Indexes 37
2.2 Lipper TASS Data 40
2.3 Attrition Rates 43
Chapter 3: Serial Correlation, Smoothed Returns, and Illiquidity 64
3.1 An Econometric Model of Smoothed Returns 66
3.2 Implications for Performance Statistics 70
3.3 Estimation of Smoothing Profiles 75
3.4 Smoothing-Adjusted Sharpe Ratios 79
3.5 Empirical Analysis of Smoothing and Illiquidity 83
Chapter 4: Optimal Liquidity 97
4.1 Liquidity Metrics 98
4.2 Liquidity-Optimized Portfolios 105
4.3 Empirical Examples 107
4.4 Summary and Extensions 117
Chapter 5: Hedge Fund Beta Replication 121
5.1 Literature Review 123
5.2 Two Examples 124
5.3 Linear Regression Analysis 126
5.4 Linear Clones 138
5.5 Summary and Extensions 164
Chapter 6: A New Measure of Active Investment Management 168
6.1 Literature Review 170
6.2 The AP Decomposition 172
6.3 Some Analytical Examples 181
6.4 Implementing the AP Decomposition 186
6.5 An Empirical Application 193
6.6 Summary and Extensions 197
Chapter 7: Hedge Funds and Systemic Risk 198
7.1 Measuring Illiquidity Risk 200
7.2 Hedge Fund Liquidations 203
7.3 Regime-Switching Models 211
7.4 The Current Outlook 215
Chapter 8: An Integrated Hedge Fund Investment Process 217
8.1 Define Asset Classes by Strategy 221
8.2 Set Portfolio Target Expected Returns 222
8.3 Set Asset-Class Target Expected Returns and Risks 222
8.4 Estimate Asset-Class Covariance Matrix 223
8.5 Compute Minimum-Variance Asset Allocations 224
8.6 Determine Manager Allocations within Each Asset Class 225
8.7 Monitor Performance and Risk Budgets 227
8.8 The Final Specification 227
8.9 Risk Limits and Risk Capital 229
8.10 Summary and Extensions 235
Chapter 9: Practical Considerations 237
9.1 Risk Management as a Source of Alpha 237
9.2 Risk Preferences 239
9.3 Hedge Funds and the Efficient Markets Hypothesis 242
9.4 Regulating Hedge Funds 250
Chapter 10: What Happened to the Quants in August 2007? 255
10.1 Terminology 260
10.2 Anatomy of a Long/Short Equity Strategy 261
10.3 What Happened in August 2007? 269
10.4 Comparing August 2007 with August 1998 273
10.5 Total Assets, Expected Returns, and Leverage 276
10.6 The Unwind Hypothesis 281
10.7 Illiquidity Exposure 284
10.8 A Network View of the Hedge Fund Industry 286
10.9 Did Quant Fail? 292
10.10 Qualifications and Extensions 298
10.11 The Current Outlook 300
Chapter 11: Jumping the Gates 303
11.1 Linear Risk Models 305
11.2 Beta Overlays 308
11.3 Hedging Long/Short Equity Managers 310
11.4 Dynamic Implementations of Beta Overlays 317
11.5 Conclusion 319
Appendix 323
A.1 Lipper TASS Category Definitions 323
A.2 CS/Tremont Category Definitions 325
A.3 Matlab Loeb Function tloeb 328
A.4 GMM Estimators for the AP Decomposition 330
A.5 Constrained Optimization 332
A.6 A Contrarian Trading Strategy 333
A.7 Statistical Significance of Aggregate Autocorrelations 334
A.8 Beta-Blocker and Beta-Repositioning Strategies 335
A.9 Tracking Error 339
References 341
Index 355
