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).

"Andrew Lo is a major figure in finance so his new book on the fast-moving world of hedge funds ought to be in the 'must read' category... The book is the authoritative distillation into an accessible form of a huge amount of academic research and practical experience... Professor Lo gives a masterful illustration of the problems in gauging hedge fund performance with his famous fantasy fund Capital Decimation Partners."--Steven Bell, The Business Economist "Anyone who is considering investing in hedge funds, or is involved in regulating the financial-services industry, should give it a go."--The Economist "Finally a serious book on hedge funds based on real data, written by a leading financial economist."--Tyler Cowen, Marginal Revolution "For scholars already familiar with the concepts of modern portfolio theory, the book is a good start in a quest to expand their knowledge of hedge funds strategies... As one of the leading researchers in the field, Lo sets the standard by establishing key concepts for the industry with this book."--Marcel Mollenbeck, Financial Markets and Portfolio Management

• 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

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).

"Andrew Lo is a major figure in finance so his new book on the fast-moving world of hedge funds ought to be in the 'must read' category... The book is the authoritative distillation into an accessible form of a huge amount of academic research and practical experience... Professor Lo gives a masterful illustration of the problems in gauging hedge fund performance with his famous fantasy fund Capital Decimation Partners."--Steven Bell, The Business Economist "Anyone who is considering investing in hedge funds, or is involved in regulating the financial-services industry, should give it a go."--The Economist "Finally a serious book on hedge funds based on real data, written by a leading financial economist."--Tyler Cowen, Marginal Revolution "For scholars already familiar with the concepts of modern portfolio theory, the book is a good start in a quest to expand their knowledge of hedge funds strategies... As one of the leading researchers in the field, Lo sets the standard by establishing key concepts for the industry with this book."--Marcel Mollenbeck, Financial Markets and Portfolio Management

• 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