Alternative Investments: An Allocator's Approach

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Whether you are a seasoned professional looking to explore new areas within the alternative investment arena or a new industry participant seeking to establish a solid understanding of alternative investments, Alternative Investments: An Allocator's Approach, Fourth Edition (CAIA Level II curriculum official text) is the best way to achieve these goals. In recent years, capital formation has shifted dramatically away from public markets as issuers pursue better financial and value alignment with ownership, less onerous and expensive regulatory requirements, market and information dislocation, and liberation from the short-term challenges that undergird the public capital markets. The careful and informed use of alternative investments in a diversified portfolio can reduce risk, lower volatility, and improve returns over the long-term, enhancing investors' ability to meet their investment outcomes. Alternative Investments: An Allocator's Approach (CAIA Level II curriculum official text) is a key resource that can be used to improve the sophistication of asset owners and those who work with them. This text comprises the curriculum, when combined with supplemental materials available at caia.org, for the CAIA Level II exam. "Over the course of my long career one tenet has held true, 'Continuing Education'. Since CalSTRS is a teachers' pension plan, it is no surprise that continuing education is a core attribute of our Investment Office culture. Overseeing one of the largest institutional pools of capital in the world requires a cohesive knowledge and understanding of both public and private market investments and strategies. We must understand how these opportunities might contribute to delivering on investment outcomes for our beneficiaries. Alternative Investments: An Allocator's Approach is the definitive core instruction manual for an institutional investor, and it puts you in the captain's chair of the asset owner." —Christopher J. Ailman, Chief Investment Officer, California State Teachers’ Retirement System "Given their diversified cash flow streams and returns, private markets continue to be a growing fixture of patient, long-term portfolios. As such, the need to have proficiency across these sophisticated strategies, asset classes, and instruments is critical for today's capital allocator. As a proud CAIA charterholder, I have seen the practical benefits in building a strong private markets foundation, allowing me to better assist my clients." —Jayne Bok, CAIA, CFA, Head of Investments, Asia, Willis Tower Watson Cover Title Page Copyright Contents Preface Acknowlegements About the Authors PART 1 Ethics Regulations and ESG CHAPTER 1 Asset Manager Code 1.1 General Principles of Conduct 1.2 Asset Manager Code 1.3 Notification of Compliance 1.4 Additional Guidance for the Asset Manager Code 1.4.1 Defining a Firm 1.4.2 Claiming Compliance 1.4.3 Suitability 1.4.4 Protecting Client Interests 1.4.5 Best Execution 1.4.6 Third-Party Confirmation of Client Information 1.4.7 Risk Management 1.4.8 Valuation of Assets 1.4.9 Disclosures 1.4.10 Soft Dollars 1.4.11 Investment Process 1.4.12 Additional Q&As CHAPTER 2 Recommendations and Guidance CHAPTER 3 Global Regulation 3.1 OVERVIEW OF FINANCIAL MARKET REGULATION 3.1.1 Theories of Regulation 3.1.2 Principles of Securities Economic Regulation 3.1.3 Importance of Regulation to Some Trading Strategies 3.2 REGULATION OF ALTERNATIVE INVESTMENTS WITHIN THE UNITED STATES 3.2.1 Overview of Regulatory Bodies in the US 3.2.2 Regulatory Framework 3.2.3 Regulation of Private Funds: Registration as an Investment Adviser 3.2.4 Regulation of Private Funds: Investment Adviser Obligations 3.2.5 Hedge Fund Registration in the United States 3.2.6 Public Securities, Private Securities, and Securities Act Registration 3.2.7 Investment Company Act Registration 3.2.8 Compliance Culture and the Role of the Chief Compliance Officer 3.2.9 Review of Marketing Materials 3.2.10 SEC Exams 3.2.11 Reporting Requirements 3.3 ALTERNATIVE INVESTMENT REGULATION IN EUROPE 3.3.1 An Overview of the Supervisory Framework 3.3.2 The European Regulatory Framework 3.3.3 Registration and Exemptions in European Regulation 3.3.4 Disclosures and Marketing 3.3.5 Formal Risk Management 3.3.6 Required Reporting in European Regulation 3.3.7 Legal Structures 3.3.8 Enforcement of European Regulation 3.3.9 Non-EU Managers in Europe 3.4 HEDGE FUND REGULATION IN ASIA 3.4.1 Hong Kong 3.4.2 Singapore 3.4.3 South Korea 3.4.4 Japan CHAPTER 4 ESG and Alternative Investments 4.1 BACKGROUND ON ESG AND ALTERNATIVE INVESTING 4.1.1 Growth in Alternatives Assets 4.1.2 ESG and Institutional Investors 4.1.3 ESG Challenges 4.2 ESG AND REAL ASSETS: NATURAL RESOURCES 4.2.1 Natural Resources and Environmental Issues 4.2.2 Natural Resources and Social Issues 4.2.3 Natural Resources and Governance Issues 4.3 ESG AND REAL ASSETS: COMMODITIES 4.3.1 Commodity Derivatives and Speculation 4.3.2 Commodity Speculation and Volatility 4.3.3 Physical Commodities and ESG 4.4 ESG AND REAL ASSETS: REAL ESTATE 4.4.1 Real Estate Development and ESG 4.4.2 Real Estate Use and ESG 4.4.3 ESG Issues in the Treatment of Tenants, Community, and Workers 4.4.4 ESG Issues in Recovery and Disposal 4.4.5 ESG Issues in Refurbishment and Retro-fitting 4.4.6 Waste Management, Resource Conservation, and Recycling During Demolition 4.4.7 Land Recovery and Rehabilitation 4.5 ESG AND HEDGE FUNDS 4.5.1 Hedge Fund Investment Strategies and ESG 4.5.2 Hedge Fund Governance and ESG 4.5.3 Hedge Fund Transparency and ESG 4.5.4 Hedge Fund Investment Techniques and Instruments and ESG 4.5.5 Hedge Fund Strategies and Underlying Investments 4.5.6 Hedge Fund Strategies and Activism 4.5.7 Hedge Fund Strategies and Avoidance 4.6 ESG AND PRIVATE EQUITY 4.6.1 ESG within a Partnership Organization and the GP-LP Relationship 4.6.2 ESG and the Private Equity Investment Process 4.6.3 ESG and the Monitoring Process References CHAPTER 5 ESG Analysis and Application 5.1 BACKGROUND ON ESG 5.1.1 History of ESG 5.1.2 The Global Reporting Initiative (GRI) Standards 5.1.3 Social Responsibility, ESG, and Evidence Regarding Stakeholder Wealth 5.2 ESG RATINGS AND SCORES 5.3 ESG MATERIALITY AND DISCLOSURE 5.3.1 ESG Materiality, ESG Disclosure, and the Global Reporting Initiative 5.3.2 A Framework for ESG Materiality Assessment 5.3.3 ESG Materiality Maps 5.3.4 ESG Materiality Measurement 5.4 THE UNITED NATIONS ROLE IN ESG ISSUES 5.4.1 The Six Principles for Responsible Investment (PRI) 5.4.2 The Sustainable Development Goals (SDGs) 5.5 ESG FIDUCIARY RESPONSIBILITIES AND REGULATION 5.5.1 ESG and Fiduciary Responsibilities in the US 5.5.2 ESG and Fiduciary Responsibilities in Europe 5.5.3 ESG and Fiduciary Responsibilities in Asia 5.5.4 ESG Compliance and Risk Management for Asset Managers 5.6 METHODS OF ESG INVESTING 5.6.1 Negative versus Positive Screening 5.6.2 Engagement and Proxy Voting 5.6.3 Impact Investing 5.6.3.1 Two Categories Of Impact Investments 5.6.3.2 The Five Steps of Implementing Impact Investing 5.6.3.3 Evidence from Research on Impact Investing in Illiquid Investments 5.7 MARKET-BASED METHODS OF ADDRESSING ESG ISSUES 5.7.1 Background on Externalities and Markets 5.7.2 The Coase Theorem 5.7.3 Cap and Trade Programs 5.8 ESG AND SPECIAL INVESTMENT CONSIDERATION 5.8.1 Special Consideration, Cash Flows, Returns, and Risk 5.8.2 The Case for Special Consideration of ESG Issues 5.8.3 The Case Against Special Consideration of ESG Issues REFERENCES PART 2 Models CHAPTER 6 Modeling Overview and Interest Rate Models 6.1 Types of Models Underlying Investment Strategies 6.1.1 Normative Strategies versus Positive Strategies 6.1.2 Theoretical versus Empirical Approaches 6.1.3 Applied versus Abstract Approaches 6.1.4 Cross-Sectional versus Time-Series Approaches 6.1.5 Importance of Methodology 6.2 Equilibrium Fixed-Income Models 6.2.1 Vasicek's Short-Term Interest Rate Process 6.2.2 Vasicek's Model and Expected Interest Rates 6.2.3 Vasicek's Model and the Term Structure of Interest Rates 6.2.4 Robustness of Vasicek's Model of the Term Structure of Interest Rates 6.2.5 The Cox, Ingersoll, and Ross Model of Interest Rates 6.3 Arbitrage-Free Models of the Term Structure 6.3.1 Overview of Arbitrage-Free Interest Rate Models 6.3.2 A Single-Factor Arbitrage-Free Model of Interest Rates 6.3.3 The Ho and Lee Model in a Binomial Framework 6.3.4 Evaluation of the Ho and Lee Model of Interest Rates 6.4 The Black-Derman-Toy Model 6.4.1 Evolution of a Binomial BDT Tree 6.4.2 Calibrating the Level of Rates Based on Average Returns 6.4.3 Calibrating the Spread of Rates Based on Volatilities 6.4.4 Summary of BDT Calibration 6.5 P-Measures and Q-Measures References CHAPTER 7 Credit Risk Models 7.1 The Economics of Credit Risk 7.1.1 Adverse Selection and Credit Risk 7.1.2 Moral Hazard and Credit Risk 7.1.3 Probability of Default 7.1.4 Expected Credit Loss 7.2 Overview of Credit Risk Modeling 7.3 The Merton Model 7.3.1 Capital Structure in the Merton Model 7.3.2 The Merton Model and the Black-Scholes Option Pricing Model 7.3.3 The Role of the Credit Spread in the Structural Model 7.3.4 Evaluation of the Merton Model 7.3.5 Four Important Properties of the Merton Model 7.4 Other Structural Models: KMV 7.4.1 Overview of the KMV Credit Risk Model 7.4.2 Using the KMV Model to Estimate a Credit Score 7.4.3 Using the KMV Model to Estimate an Expected Default Frequency 7.5 Reduced-Form Models 7.5.1 Default Intensity in Reduced-Form Models 7.5.2 Default Intensity and the Probabilities of Default 7.5.3 Valuing Risky Debt with Default Intensity 7.5.4 Relating the Credit Spread to Default Intensity and the Recovery Rate 7.5.5 The Two Predominant Reduced-Form Credit Models 7.6 Empirical Credit Models 7.6.1 Two Features of Empirical Credit Models 7.6.2 The Purpose of Altman's Z-Score Model 7.6.3 The Five Determinants of Altman's Z-Scores 7.6.4 Solving for the Z-Score in Altman's Credit Scoring Model 7.6.5 Interpreting Z-Scores in Altman's Credit Scoring Model References CHAPTER 8 Multi-Factor Equity Pricing Models 8.1 Multi-Factor Asset Pricing Models 8.2 FAMA-French Models 8.3 Three Challenges of Empirical Multi-Factor Models 8.4 Factor Investing 8.5 The Adaptive Markets Hypothesis 8.6 Time-Varying Volatility 8.7 Stochastic Discount Factors 8.8 Summary of Multiple-Factor Asset Allocation References CHAPTER 9 Asset Allocation Processes and the Mean-Variance Model 9.1 Asset Allocation Processes and the Mean-Variance Model 9.1.1 Origin of Mean-Variance Optimization 9.1.2 The Tradeoff Between Expected Return and Volatility 9.1.3 Evaluating Risk and Return with Utility 9.1.4 Risk Aversion and the Shape of the Utility Function 9.1.5 Expressing Utility Functions in Terms of Expected Return and Variance 9.1.6 Expressing Utility Functions with Higher Moments 9.1.7 Expressing Utility Functions with Value at Risk 9.1.8 Finding Investor Risk Aversion from the Asset Allocation Decision 9.1.9 Managing Assets with Risk Aversion and Growing Liabilities 9.2 Implementation of Mean-Variance Optimization 9.2.1 Mean-Variance Optimization 9.2.2 Mean-Variance Optimization with a Risky and Riskless Asset 9.2.3 Mean-Variance Optimization with Growing Liabilities 9.2.4 Mean-Variance Optimization and 𝝀 9.3 Mean-Variance Optimization with Multiple Risky Assets 9.3.1 A Riskless Asset and the Linearity of Efficient Frontier 9.3.2 A Riskless Asset with Multiple Risky Assets 9.3.3 Unconstrained Optimization and Unrealistic Weights 9.4 Mean-Variance Optimization and Hurdle Rates 9.5 Issues in Using Optimization for Portfolio Selection 9.5.1 Optimizers as Error Maximizers 9.5.2 Portfolio Optimization and Smoothing of Illiquid Returns 9.5.3 Data Issues for Large-Scale Optimization 9.5.4 Mean-Variance Ignores Higher Moments 9.5.5 Three Ways to Address Skewness and Kurtosis 9.6 Adjustment of the Mean-Variance Approach for Illiquidity 9.6.1 The Liquidity Penalty Function 9.6.2 Examples of Adjusting for Illiquidity 9.6.3 Takeaway Points on Illiquidity Adjustments 9.7 Adjustment of the Mean-Variance Approach for Factor Exposure 9.8 Mitigating Estimation Error Risk in Mean-Variance Optimization 9.8.1 Estimation Error Risk Reduction through Objective Measures of Estimation Error Risk 9.8.2 Resampling to Reduce the Effect of Estimation Error 9.8.3 Shrinkage to Reduce the Effect of Estimation Error 9.8.4 Mean-Variance Optimization and the Black-Litterman Approach 9.8.5 Mean-Variance Optimization and the Use Of Constraints References CHAPTER 10 Other Asset Allocation Approaches 10.1 The Core-Satellite Approach 10.2 Top-Down and Bottom-Up Asset Allocation Approaches 10.3 Risk Budgeting 10.4 A Factor-Based Example of Implementing A Risk Budgeting Approach 10.5 Risk Parity 10.6 Other Quantitative Portfolio Allocation Strategies 10.7 The New Investment Model References PART 3 Institutional Asset Owners and Investment Policies CHAPTER 11 Types of Asset Owners and the Investment Policy Statement 11.1 Endowments and Foundations 11.2 Pension Funds 11.3 Sovereign Wealth Funds 11.4 Family Offices 11.5 Strategic Asset Allocation: Risk and Return 11.5.1 Basing Strategic Asset Allocations on Observation and Reasoning 11.5.2 Reasons That Alternative Assets Raise Return Estimation Challenges 11.5.3 Reasons for Placing Caps and Floors on Asset Allocations 11.6 Asset Allocation Objectives 11.7 Investment Policy Constraints 11.7.1 Internal and External Constraints 11.7.2 Three Types of Internal Constraints 11.7.3 Two Types of External Constraints 11.8 Investment Policy Statements for Institutional Asset Owners 11.8.1 Six Benefits to a Thoughtfully Developed IPS 11.8.2 Introduction, Scope, and Purpose 11.8.3 Roles and Responsibilities 11.8.4 Investment Objectives 11.8.5 Time Horizon 11.8.6 Risk Tolerance 11.8.7 Spending Policy 11.8.8 Asset Allocation Guidelines 11.8.9 Selection and Retention Criteria for Investment Managers or Funds 11.8.10 Strategic Investment Guidelines 11.8.11 Performance Measurement and Evaluation 11.8.12 Additional Considerations 11.8.13 Conclusion Reference CHAPTER 12 Foundations and the Endowment Model 12.1 Defining Endowments and Foundations 12.2 Intergenerational Equity, Inflation, and Spending Challenges 12.3 The Endowment Model 12.3.1 Asset Allocation in the Endowment Model 12.3.2 The Endowment Model's Case Against Bonds 12.3.3 Alternative Investments in the Endowment Models 12.4 Why Might Large Endowments Outperform? 12.4.1 Six Attributes of the Endowment Model 12.4.2 An Aggressive Asset Allocation 12.4.3 Effective Investment Manager Research 12.4.4 First-Mover Advantage 12.4.5 Access to a Network of Talented Alumni 12.4.6 Acceptance of Liquidity Risk 12.4.7 Sophisticated Investment Staff and Board Oversight 12.4.8 Outsourced CIO Model 12.5 Risks of the Endowment Model 12.5.1 Spending Rates and Spending Rules 12.5.2 Spending Rates and Inflation 12.5.3 Spending Rates and Liquidity Issues 12.5.4 Spending Rates and Liquidity-Driven Investors 12.5.5 Avoiding Liquidity Losses from a Financial Crisis 12.5.6 Leverage Risk and the Endowment Model 12.6 Liquidity Rebalancing and Tactical Asset Allocation 12.7 Tail Risk 12.8 Conclusion References CHAPTER 13 Pension Fund Portfolio Management 13.1 Development, Motivations, and Types of Pension Plans 13.1.1 Development of Pension Plans 13.1.2 Motivations for Using Pension Plans 13.1.3 Three Basic Types of Pension Plans 13.2 Risk Tolerance and Asset Allocation 13.2.1 Three Approaches to Managing the Assets of Defined Benefit Plans 13.2.2 Four Factors Driving the Impact of Liabilities on a Plan's Risk 13.2.3 Five Major Factors Affecting the Risk Tolerance of the Plan Sponsor 13.2.4 Strategic Asset Allocation of a Pension Plan Using Two Buckets 13.3 Defined Benefit Plans 13.3.1 Pension Plan Portability and Job Mobility 13.3.2 Defining Liabilities: Accumulated Benefit Obligation and Projected Benefit Obligation 13.3.3 Funded Status and Surplus Risk 13.3.4 Why Defined Benefit Plans Are Withering 13.3.5 Asset Allocation and Liability-Driven Investing 13.3.6 Liability-Driven Pension Investing 13.4 Governmental Social Security Plans 13.5 Contrasting Defined Benefit and Contribution Plans 13.5.1 Defined Contribution Plans 13.5.2 Plan Differences in Portability, Longevity Risk, and Investment Options 13.5.3 Asset Allocation in Defined Contribution Plans 13.5.4 Target-Date Funds and Alternative Investments within Pension Plans 13.6 Annuities for Retirement Income 13.6.1 Financial Phases Relative to Retirement 13.6.2 Three Important Risks to Retirees 13.6.3 Estimating Exposure to Longevity Risk 13.6.4 Two Major Types of Annuities 13.6.5 Analysis of the Value of a Growth Annuity 13.7 Conclusion References CHAPTER 14 Sovereign Wealth Funds 14.1 Sources of Sovereign Wealth 14.1.1 Accounting for Changes in the Reserve Account 14.1.2 Changes in the Reserve Account and Five Drivers of Currency Exchange Rates 14.1.3 Fixed versus Floating Rule Policies 14.1.4 Commodity Exports and the Reserve Account 14.2 Four Types of Sovereign Wealth Funds 14.2.1 Stabilization Funds 14.2.2 Savings Funds 14.2.3 Reserve Funds 14.2.4 Development Funds 14.3 Establishment and Management of Sovereign Wealth Funds 14.3.1 Four Common Motivations to Establishing a Sovereign Wealth Fund 14.3.2 Investment Management of Sovereign Wealth Funds 14.3.3 Dutch Disease and Sterilization Policies 14.3.4 Managing the Size of a Sovereign Wealth Fund 14.4 Governance and Political Risks of SWFs 14.4.1 Governance of SWFs 14.4.2 Impact of SWF Investments on Portfolio Companies 14.4.3 Ten Principles of the Linaburg-Maduell Transparency Index 14.4.4 Santiago Principles 14.5 Analysis of Three Sovereign Wealth Funds 14.5.1 Government Pension Fund Global (Norway) 14.5.2 China Investment Corporation 14.5.3 Temasek Holdings (Singapore) 14.6 Conclusion REFERENCES CHAPTER 15 Family Offices and the Family Office Model 15.1 Identifying Family Offices 15.2 Goals, Benefits, and Business Models of Family Offices 15.2.1 General Goals of the Family Office 15.2.2 Benefits of the Family Office 15.2.3 Models and Structure of the Family Office 15.3 Family Office Goals by Generations 15.3.1 First-Generation Wealth 15.3.2 Risk Management of First-Generation Wealth 15.3.3 Benchmarking First-Generation Wealth 15.3.4 Goals of the Second Generation and Beyond 15.4 Macroeconomic Exposures of Family Offices 15.5 Income Taxes of Family Offices 15.5.1 Tax Efficiency and Wealth Management 15.5.2 Taxability of Short-Term and Long-Term Capital Gains 15.5.3 Tax Efficiency and Hedge Fund Investment Strategies 15.6 Lifestyle Assets of Family Offices 15.6.1 Art as a Lifestyle Asset 15.6.2 Lifestyle Wealth Storage and Other Costs 15.6.3 Lifestyle Assets and Portfolio Management 15.6.4 Concierge Services 15.7 Family Office Governance 15.7.1 Governance Structures of Family Offices 15.7.2 The Challenges of Family Wealth Sustainability 15.7.3 Strategies to Maintain Family Wealth 15.7.4 Family Office Inheritance and Succession Strategies 15.8 Charity, Philanthropy, and Impact Investing 15.8.1 Charity and Philanthropy 15.8.2 Impact Investing 15.9 Ten Competitive Advantages of Family Offices References PART 4 Risk and Risk Management CHAPTER 16 Cases in Tail Risk 16.1 PROBLEMS DRIVEN BY MARKET LOSSES 16.1.1 Amaranth Advisors, LLC 16.1.2 Long-Term Capital Management 16.1.3 Carlyle Capital Corporation 16.1.4 Declining Investment Opportunities and Leverage 16.1.5 Behavioral Biases and Risk Taking 16.1.6 Volatility of Volatility Derivatives in February 2018 16.2 TRADING TECHNOLOGY AND FINANCIAL CRISES 16.2.1 Quant Crisis, August 2007 16.2.2 The Flash Crash of 2010 16.2.3 Knight Capital Group 16.3 FAILURES DRIVEN BY FRAUD 16.3.1 Bayou Management 16.3.2 Bernie Madoff 16.3.3 Lancer Group 16.3.4 Venture Capital Startup: Theranos 16.4 FOUR MAJOR LESSONS FROM CASES IN TAIL EVENTS REFERENCES CHAPTER 17 Benchmarking and Performance Attribution 17.1 BENCHMARKING AND PERFORMANCE ATTRIBUTION OVERVIEW 17.1.1 Active Return in Benchmarking 17.1.2 The Bailey Criteria for a Useful Benchmark 17.1.3 Selecting a Benchmark for Alternative Investments 17.1.4 Benchmarking Liquid Alternative Investments 17.2 SINGLE-FACTOR BENCHMARKING AND PERFORMANCE ATTRIBUTION 17.2.1 An Example of Single-Factor Benchmarking 17.2.2 Three Considerations in Benchmarking 17.2.3 Single-Factor Market Model Performance Attribution 17.2.4 Examining Time-Series Returns with a Single-Factor Market-Based Regression Model 17.2.5 Application of Single-Factor Benchmarking 17.3 MULTI-FACTOR BENCHMARKING 17.3.1 An Example of Multi-factor Benchmarking 17.3.2 The Bias from Omitted Factors in Benchmarking 17.3.3 Multi-factor versus Single-factor Methods 17.4 DISTINCTIONS REGARDING ALTERNATIVE ASSET BENCHMARKING 17.4.1 Why Not Apply the CAPM to Alternative Assets? 17.4.2 Reason 1: Multi-period Issues 17.4.3 Reason 2: Nonnormality 17.4.4 Reason 3: Illiquidity of Returns and Other Barriers to Diversification 17.4.5 Reason 4: Investor-Specific Assets or Liabilities 17.4.6 Summary of Why Multiple-Factor Models May be Preferable 17.5 BENCHMARKING OF COMMODITIES 17.5.1 Weighting All Positions on Value versus Quantity 17.5.2 The Three Schemes Used to Weight Commodities Sectors and Components 17.5.3 Total Return versus Excess Return 17.5.4 Roll Method 17.5.5 Three Generations of Commodity Indices 17.6 THREE APPROACHES TO BENCHMARKING MANAGED FUTURES FUNDS 17.6.1 Benchmarking with Long-Only Futures Contracts 17.6.2 Benchmarking CTAs with Peer Groups 17.6.3 Benchmarking CTAs with Algorithmic Indices 17.6.4 Five Conclusions from Evidence on CTA Benchmarking 17.7 BENCHMARKING PRIVATE EQUITY FUNDS 17.7.1 Listed Asset-Based Benchmarks 17.7.2 Public Equity Indices and the Public Market Equivalent (PME) Method 17.7.3 Key Computations in the Public Market Equivalent (PME) Method 17.7.4 Extensions to the PME Method and Other Related Performance Metrics 17.8 GROUP PEER RETURNS AS BENCHMARKS 17.9 BENCHMARKING REAL ESTATE 17.9.1 Benchmarking Core Real Estate with Cap Rates 17.9.2 Benchmarking Core Real Estate with a Risk Premium Formula 17.9.3 Three Approaches to Benchmarking Noncore Real Estate 17.9.4 Examples of Benchmark Return Estimates for Noncore Style Assets References CHAPTER 18 Liquidity and Funding Risks 18.1 Margin Accounts and Collateral Management 18.1.1 Three Specialized Terms for Futures Account Levels 18.1.2 Collateral and Margin for Futures Portfolios 18.1.3 Margin Across Multiple Clearinghouses 18.1.4 Capital at Risk for Managed Futures 18.2 Value at Risk for Managed Futures 18.2.1 Value at Risk for a Portfolio as a Quantile 18.2.2 VaR Using a Parametric Approach with Variance Based on Equal Return Weighting 18.2.3 Parametric VaR Using a Variance based on Unequal Return Weighting 18.2.4 Confidence Intervals with Parametric VaR 18.3 Other Methods of Estimating Liquidity Needs 18.3.1 Simulation Analysis and Potential Managed Futures Losses 18.3.2 Omega Ratio and Managed Futures 18.3.3 Interpreting the Omega Ratio 18.4 Smoothed Returns on Illiquid Funds 18.4.1 Smoothed Asset Returns and Unsmoothing 18.4.2 Price Smoothing and Arbitrage in a Perfect Market 18.4.3 Persistence in Price Smoothing 18.4.4 Problems Resulting from Price Smoothing 18.5 Modeling Price and Return Smoothing 18.5.1 Reported Prices as Lags of True Prices 18.5.2 Modeling True Returns from Smoothed Returns 18.5.3 Four Reasons for Smoothed Prices and Delayed Price Changes in an Index 18.6 Unsmoothing a Hypothetical Return Series 18.6.1 Unsmoothing Returns Based on First-Order Autocorrelation 18.6.2 The Three Steps of Unsmoothing 18.6.3 An Example of Unsmoothing with the Three Steps 18.7 Unsmoothing Actual Real Estate Return Data 18.7.1 The Smoothed Data and the Market Data 18.7.2 Estimating the First-Order Autocorrelation Coefficient 18.7.3 Unsmoothing the Smoothed Return Series 18.7.4 The Relation between the Variances of True and Reported Returns 18.7.5 The Relation between the Betas of True and Reported Returns 18.7.6 Interpreting the Results of Unsmoothing References CHAPTER 19 Hedging, Rebalancing, and Monitoring 19.1 Managing Alpha and Systematic Risk 19.1.1 Separating Alpha and Beta 19.1.2 Hedging Systematic Risk 19.1.3 Porting Alpha 19.2 Managing the Risk of a Portfolio with Options 19.2.1 Put-Call Parity as a Foundation for Risk Analysis 19.2.2 Option Sensitivities 19.2.3 Delta of a Simple Call Option and Put Option 19.2.4 Viewing Options as Volatility Bets 19.3 Delta-Hedging of Option Positions 19.3.1 Construction of a Binomial Stock and Call Option Tree in a Risk-Neutral World 19.3.2 Performing Arbitrage on a Properly Priced Option 19.3.3 Performing Arbitrage on a Mispriced Option 19.3.4 Geometric Motion and Delta-Hedging 19.4 Three Key Observations on Delta-Hedging 19.5 Three Observations on Rebalancing Delta-Neutral Option Portfolios 19.6 Rebalancing Portfolios with Directional Exposures 19.6.1 Rebalancing, Mean-Reversion, Trending, and Randomness 19.6.2 Rebalancing When Assets Follow a Random Walk 19.6.3 Rebalancing When Individual Assets Trend 19.6.4 Rebalancing When Individual Asset Prices Mean-Revert 19.6.5 Empirical Evidence on the Effect of Rebalancing on Return 19.6.6 The Effects of Rebalancing When Prices Do Not Mean-Revert 19.7 Mean-Reversion and Diversification Return 19.7.1 Benefits of Mean-Reversion in Commodity Investing 19.7.2 Benefiting from Mean-Reversion through Portfolio Rebalancing 19.7.3 Volatility Reduction Enhances Geometric Mean Returns, Not Expected Values 19.7.4 Summary of Rebalancing 19.8 Investment Monitoring 19.8.1 Portfolio and Individual Asset Monitoring 19.8.2 Six Activities of Monitoring Private Partnerships 19.8.3 Monitoring Objectives 19.8.4 Forms of Active Involvement in the Fund's Governance Process 19.8.5 Forms of Active Involvement Outside the Fund's Governance Process 19.8.6 Three Ways to Create Value through Monitoring 19.8.7 Two Limits to the Detail and Extent of Information Available from Monitoring References CHAPTER 20 Risk Measurement, Risk Management, and Risk Systems 20.1 OVERVIEW OF RISK MEASUREMENT AND AGGREGATION 20.1.1 Risk and the Investment Mandate 20.1.2 The Five Components of Risk Measurement 20.1.3 Risk Measurement at the Investment/Position Level 20.1.4 Risk Measurement and Frequency of Data Collection 20.1.5 Risk Aggregation and Systems Development 20.1.6 Risk Measurement and Dimensions of Risk 20.1.7 An Example of Dimensions of Risk Reporting for an Alternative Investment 20.2 CATEGORIES OF INFORMATION TO BE CONSIDERED 20.2.1 Quantitative Information Categories and Associated Statistics 20.2.2 Due Diligence Tracking Matrices 20.2.3 Qualitative Information Categories 20.3 RISK MEASUREMENT WITH DAILY FREQUENCY OF DATA COLLECTION 20.4 RISK MEASUREMENT WITH WEEKLY FREQUENCY OF DATA COLLECTION 20.5 RISK MEASUREMENT WITH MONTHLY FREQUENCY OF DATA COLLECTION 20.6 RISK MEASUREMENT WITH QUARTERLY FREQUENCY OF DATA COLLECTION 20.7 RISK MEASUREMENT WITH ANNUAL FREQUENCY OF DATA COLLECTION OR ROLLING TIME PERIODS 20.8 CYBERSECURITY FOR FUND MANAGERS 20.8.1 Vulnerability of Investment Organizations to Cybersecurity Issues 20.8.2 Achieving a State of Preparedness Regarding Cybersecurity 20.8.3 Evidence on Regularity with Which Cybersecurity Functions Were Observed 20.8.4 Evidence on Areas Requiring Improved Policies 20.8.5 Evidence on Robust Policies and Procedures Worth Emulating 20.8.6 Cybersecurity and EU Regulation 20.8.7 Cybersecurity and Asian Regulation 20.9 RISK MANAGEMENT STRUCTURE AND PROCESS 20.9.1 Three Models of Risk Management Structure 20.9.2 The Investment Process as Primarily a Risk Process 20.9.3 The Evolution of Risk Reporting PART 5 Methods for Alternative Investing CHAPTER 21 Valuation and Hedging Using Binomial Trees 21.1 A ONE-PERIOD BINOMIAL TREE AND RISK-NEUTRAL MODELING 21.1.1 A One-Period Model of Default Risk with Risk-Neutrality 21.1.2 A One-Period Model With A Risk Premium For Default 21.1.3 P-measures, Q-measures, and the Power of Risk-Neutral Modeling 21.1.4 Four Key Concepts of Risk-Neutral Modeling 21.2 MULTI-PERIOD BINOMIAL TREES, VALUES, AND MEAN RATES 21.2.1 A Trinomial Tree Model Based on Prices 21.2.2 Two-Period Binomial Tree Model with Compounded Returns 21.2.3 Three Fallacies Generated by Averaging Compounded Rates of Return 21.3 VALUATION OF CONVERTIBLE SECURITIES WITH A BINOMIAL TREE MODEL 21.3.1 Forming a Tree of Stock Prices 21.3.2 The Tree of Prices for a Call Option on an Equity 21.3.3 The Tree of Prices for the Bond's Underlying Stock 21.3.4 The Tree of Prices for the Convertible Bond's Underlying Stock 21.3.5 Valuing the Convertible Bond One Period Prior to Its Maturity 21.3.6 Determining the Current Value of the Convertible Bond 21.4 VALUING CALLABLE BONDS WITH A TREE MODEL 21.4.1 A Two-Period Binomial Tree 21.4.2 Modeling the Spread Between Upward and Downward Shifting Rates 21.4.3 Calculating a Two-Period Straight Bond Price with a Binomial Tree 21.4.4 Calculating a Two-Period Callable Bond Price with a Binomial Tree 21.5 TREE MODELS, VISUALIZATION, AND TWO BENEFITS TO SPREADSHEETS Reference CHAPTER 22 Directional Strategies and Methods 22.1 EFFICIENTLY INEFFICIENT MARKETS 22.2 TECHNICAL DIRECTIONAL STRATEGIES OVERVIEW 22.2.1 Metrics of Technical Analysis 22.2.2 Trend-Following or Momentum Models 22.2.3 Market Divergence 22.2.4 Measuring Market Divergence of an Individual Asset 22.2.5 Interpreting Market Divergence 22.2.6 Measuring Market Divergence 22.2.7 Technical Strategies Based on Machine Learning 22.2.8 Risks of Directional Technical Strategies 22.3 FUNDAMENTAL DIRECTIONAL STRATEGIES 22.3.1 Overview of Fundamental Directional Strategies 22.3.2 The Bottom-Up Approach of Fundamental Analysis 22.3.3 Fundamental Bottom-Up Equity Valuation Models 22.3.4 Four Procedures within the Fundamental Investment Process 22.3.5 Four Mechanics of Fundamental Strategies 22.3.6 The Top-Down Approach of Fundamental Analysis 22.3.7 Top-Down Managers and Schools of Thought 22.3.8 Two Risks of Directional Fundamental Strategies 22.4 DIRECTIONAL STRATEGIES AND BEHAVIORAL FINANCE 22.4.1 Sentiment Sensitivity 22.4.2 Overconfidence 22.4.3 Behavioral Biases From Over-Reliance on the Past 22.4.4 Other Potential Sources of Pricing Anomalies 22.5 DIRECTIONAL TRADING AND FACTORS 22.5.1 Emphasis on Value versus Growth Investing 22.5.2 Directional Trading Based on Momentum 22.5.3 Emphasis on Illiquidity Premiums 22.5 References CHAPTER 23 Multivariate Empirical Methods and Performance Persistence 23.1 STATISTICAL FACTORS AND PRINCIPAL COMPONENT ANALYSIS 23.1.1 Principal Component Analysis and Types of Factors 23.1.2 The Basics of Principal Component Analysis 23.1.3 The Two Primary Outputs of Principal Component Analysis 23.1.4 An Example of Applying and Interpreting a Principal Component Analysis 23.1.5 Three Key Differences Between Principal Component Analysis and Factor Analysis 23.2 MULTI-FACTOR MODELS AND REGRESSION 23.2.1 Selecting Factors for Multi-factor Regression 23.2.2 Multicollinearity 23.2.3 Selecting the Number of Factors and Overfitting 23.3 PARTIAL AUTOCORRELATIONS AND REGRESSION 23.3.1 Intuition of Partial Autocorrelations 23.3.2 Estimation of Partial Autocorrelations 23.3.3 Partial Autocorrelations of a Return Series Based on Appraisals 23.4 THREE DYNAMIC RISK EXPOSURE MODELS 23.4.1 The Nonlinear Exposure of Perfect Market-Timing Foresight 23.4.2 The Dummy Variable Approach to Dynamic Risk Exposures 23.4.3 The Separate Regression Approach to Dynamic Risk Exposures 23.4.4 The Quadratic Approach to Dynamic Risk Exposures 23.5 Two Approaches to Modeling Changing Correlation 23.5.1 Conditional Correlation Modeling Approach 23.5.2 Interpreting an Example of Conditional Correlations 23.5.3 Variations on Conditional Empirical Analyses 23.5.4 Rolling Window Modeling Approach 23.6 FOUR MULTI-FACTOR APPROACHES TO UNDERSTANDING RETURNS 23.6.1 Understanding Style Analysis and Fund Groupings Based on Asset Classes 23.6.2 Understanding Funds Based on Strategies 23.6.3 Understanding Funds Based on Market-wide Factors 23.6.4 Understanding Funds Based on Specialized Market Factors 23.7 EVIDENCE ON FUND PERFORMANCE PERSISTENCE 23.7.1 Performance Persistence Based on Return Correlations 23.7.2 Performance Persistence Based on Risk-Adjusted Returns 23.7.3 Performance Persistence Based on Portfolio Returns References CHAPTER 24 Relative Value Methods 24.1 OVERVIEW OF RELATIVE VALUE METHODS 24.1.1 Arbitrage and Risks in Relative Value Strategies 24.1.2 Pure Arbitrage and Risk Arbitrage 24.1.3 Limits to Arbitrage 24.1.4 Two Examples of Nearly Pure Arbitrage 24.1.5 Two Examples of Risk Arbitrage 24.2 TYPES OF PAIRS TRADING AND THE FOUR TYPICAL STEPS 24.3 STATISTICAL PAIRS TRADING OF EQUITIES 24.3.1 Statistical Pairing using the Co-Integration Approach 24.3.2 Identification and Timing of Trade Entry Opportunities 24.3.3 The Nature and Performance of Pairs-Trading Strategies 24.4 Pairs Trading in Commodity Markets Based on Spreads 24.4.1 Commodity Derivatives Calendar Spreads 24.4.2 Estimating the Profitability of Calendar Spread Trading 24.4.3 Processing Spreads 24.4.4 The Economics of Processing Spreads to Producers and Speculators 24.4.5 Substitution Commodity Spreads 24.4.6 Quality and Location Spreads 24.4.7 Intramarket Relative Value Strategies 24.5 PAIRS TRADING IN RATES FROM FIXED INCOME AND CURRENCY MARKETS 24.6 Relative Value Market-Neutral Strategies and Portfolio Risks 24.6.1 Risks of Pairs-Trading Strategies 24.6.2 Equity Market-Neutral Strategy 24.6.3 Risks Related to Equity Market Neutrality References CHAPTER 25 Valuation Methods for Private Assets: The Case of Real Estate 25.1 DEPRECIATION TAX SHIELDS 25.1.1 Valuation of the Depreciation Tax Shield 25.1.2 Computation of the Depreciation Tax Shield 25.1.3 Viewing Depreciation as Generating an Interest-Free Loan 25.2 DEFERRAL OF TAXATION OF GAINS 25.2.1 Return with Annual Taxation of Gains 25.2.2 Return with Deferred Taxation of Gains 25.2.3 Depreciation, Deferral, and Leverage Combined 25.3 COMPARING AFTER-TAX RETURNS FOR VARIOUS TAXATION SCENARIOS 25.3.1 Real Estate Example without Taxation 25.3.2 After-Tax Returns When Depreciation Is Not Allowed 25.3.3 Return When Accounting Depreciation Equals Economic Depreciation 25.3.4 Return When Accounting Depreciation Is Accelerated 25.3.5 Return When Capital Expenditures Can Be Expensed 25.3.6 Depreciation and Heterogenous Marginal Tax Rates Among Investors 25.4 TRANSACTION-BASED INDICES: REPEAT-SALES 25.4.1 Overview and Example of the Repeat-Sales Method 25.4.2 Two Advantages of the Repeat-Sales Method 25.4.3 Three Disadvantages of the Repeat-Sales Method 25.5 TRANSACTION-BASED INDICES: HEDONIC 25.5.1 Overview of the Hedonic-Pricing Method 25.5.2 Three Steps to Calculating a Hedonic Price Index 25.5.3 A Simplified Example of the Hedonic-Pricing Approach 25.5.4 Three Primary Advantages of the Hedonic-Pricing Model 25.5.5 Three Primary Disadvantages of the Hedonic-Pricing Model 25.6 SAMPLE BIAS AND THE REPEAT-SALES AND HEDONIC-PRICE METHODS 25.7 APPRAISAL-BASED INDICES 25.7.1 Approaches to Appraisals 25.7.2 Two Advantages of Appraisal-Based Models 25.7.3 Three Disadvantages of Appraisal-Based Models 25.8 NOISY PRICING 25.8.1 Random Pricing Errors and Reservation Prices 25.8.2 Appraisals and Appraisal Error 25.8.3 The Square Root of N Rule References PART 6 Accessing Alternative Investments CHAPTER 26 Hedge Fund Replication 26.1 AN OVERVIEW OF REPLICATION PRODUCTS 26.2 POTENTIAL BENEFITS OF REPLICATION PRODUCTS 26.3 THE CASE FOR HEDGE FUND REPLICATION 26.3.1 Estimating the Risk and Return of Funds of Funds 26.3.2 Three Theories for Increased Beta and Decreased Alpha in Hedge Fund Returns 26.3.3 The Aggregate Alpha of the Hedge Fund Industry 26.3.4 Replication Products as a Source of Alpha 26.3.5 Replication Products as a Source of Alternative Beta 26.4 UNIQUE BENEFITS OF REPLICATION PRODUCTS 26.4.1 Two Reasons to Use Replication Products 26.4.2 Two Key Issues Regarding Fund Replication Benefits 26.4.3 Eight Potential Unique Benefits from Hedge Fund Replication 26.5 FACTOR-BASED APPROACH TO REPLICATION 26.5.1 Four Primary Issues in Constructing a Factor-Based Replication Product 26.5.2 Three Steps to Factor-Based Replication 26.5.3 Two Key Concepts Regarding Factor-Based Replication 26.5.4 Research on Factor-Based Replication 26.5.5 Comparison of Factor-Based Approaches to Payoff-Distribution Approaches 26.6 THE ALGORITHMIC (BOTTOM-UP) APPROACH 26.7 THREE ILLUSTRATIONS OF THE ALGORITHMIC (BOTTOM-UP) APPROACH 26.7.1 An Illustration of the Algorithmic Approach: Merger Arbitrage 26.7.2 An Illustration of the Algorithmic Approach: Convertible Arbitrage 26.7.3 An Illustration of the Algorithmic Approach: Momentum Strategies References CHAPTER 27 Diversified Access to Hedge Funds 27.1 Evidence Regarding Hedge Fund Risk and Returns 27.1.1 Evidence Regarding Performance of Hedge Funds by Strategies 27.1.2 Evidence Regarding the Systematic and Total Risk of Hedge Funds 27.1.3 Evidence Regarding Correlations and Diversification of Hedge Funds 27.2 Approaches to Accessing Hedge Funds 27.2.1 The Direct Approach and Its Three Advantages 27.2.2 The Delegated Approach and Its Five Services 27.2.3 The Indexed Approach 27.3 Characteristics of Funds of Hedge Funds 27.3.1 Approach to Manager Selection 27.3.2 Four Types of Funds of Hedge Funds Based on Diversification 27.3.3 Exposure of Funds of Hedge Funds Returns to Four Potential Biases 27.3.4 Four Key Issues Comparing Funds of Hedge Funds and Multi-strategy Funds 27.4 Fund of Hedge Funds Portfolio Construction 27.4.1 Assets-Under-Management Weighted Approach and its Three Challenges 27.4.2 Equally Weighted Approach 27.4.3 Equal Risk-Weighted Approach 27.4.4 Mean-Variance (Unconstrained and Constrained) Approach 27.4.5 Mean-Variance Approach with Constraints on Higher-Moments 27.4.6 Personal Allocation Biases Approach 27.5 Ways that Funds of Hedge Funds Can Add Value 27.5.1 Evidence on the Three Levels at Which Funds of Hedge Funds Can Add Value 27.5.2 General Evidence on the Performance of Funds of Hedge Funds 27.6 Investable Hedge Fund Indices 27.7 Alternative Mutual Funds 27.7.1 Three Potential Benefits of Offering Alternative Mutual Funds 27.7.2 Three Benefits of Alternative Mutual Funds to Investors 27.7.3 Three Risks of Alternative Mutual Funds 27.7.4 Three Advantages of Exchange-Traded Alternative Funds References CHAPTER 28 Access to Real Estate and Commodities 28.1 UNLISTED REAL ESTATE FUNDS 28.1.1 Open-End Funds 28.1.2 Closed-End Real Estate Funds 28.1.3 Real Estate Funds of Funds 28.1.4 Nontraded REITs 28.1.5 Four Potential Advantages of Unlisted Real Estate Funds 28.1.6 Three Potential Disadvantages of Unlisted Real Estate Funds 28.2 LISTED REAL ESTATE FUNDS 28.2.1 REITs and REOCs 28.2.2 Exchange-Traded Funds Based on Real Estate Indices 28.2.3 Four Potential Advantages of Listed Real Estate Funds 28.2.4 Two Potential Disadvantages of Listed Real Estate Funds 28.2.5 Global REITs 28.3 COMMODITIES 28.3.1 Direct Physical Ownership of Commodities 28.3.2 Indirect Ownership of Commodities 28.3.3 Commodity Index Swaps 28.3.4 Public Commodity-Based Equities 28.3.5 Bonds Issued by Commodity Firms 28.3.6 Commodity-Based Mutual Funds and Exchange-Traded Products 28.3.7 Public and Private Commodity Partnerships 28.3.8 Commodity-Linked Investments 28.3.9 Commodity-Based Hedge Funds 28.4 COMMODITY TRADE FINANCING AND PRODUCTION FINANCING 28.5 LEVERAGED AND OPTION-BASED STRUCTURED COMMODITY EXPOSURES 28.5.1 Leveraged and Inverse Commodity Index-Based Products 28.5.2 Leveraged Notes 28.5.3 Principal-Guaranteed Notes 28.6 KEY CONCEPTS IN MANAGING COMMODITY EXPOSURE 28.6.1 Roll Return 28.6.2 Commodity Prices and Cycles 28.6.3 Commodity Prices and Key Economic Variables References CHAPTER 29 Access Through Private Structures 29.1 OVERVIEW OF ISSUES IN PRIVATE VERSUS LISTED INVESTMENT ACCESS 29.1.1 Financial Market Segmentation 29.1.2 Major Potential Advantages of Listed Assets 29.1.3 Major Potential Advantages of Privately Organized Assets 29.1.4 Rational Investing with High Fees 29.1.5 Private Structures as a Superior Governance Paradigm 29.2 UNLISTED MANAGER-INVESTOR RELATIONSHIPS 29.2.1 GP and Fund Economics 29.2.2 Fund Term and Structure 29.2.3 Key Person 29.2.4 Fund Governance 29.2.5 Financial Disclosures 29.2.6 Notification and Policy Disclosures 29.3 SIDE LETTERS TO LIMITED PARTNERSHIP AGREEMENTS 29.4 CO-INVESTMENTS 29.4.1 Overview of Co-Investing 29.4.2 Investment Processes for Co-Investing 29.4.3 Evidence on the Performance of Co-Investments 29.4.4 Potential Advantages of Co-Investing 29.4.5 Potential Expected Disadvantages of Co-Investing 29.5 CASH COMMITMENTS AND ILLIQUIDITY 29.5.1 The Costs of Excess Liquidity 29.5.2 The Costs of Illiquidity 29.5.3 Overcommitment Strategies 29.5.4 The Challenge of Identifying Illiquidity and Managing Cash Flows 29.5.5 Four Benefits of Private Equity Cash Flow Models 29.5.6 The Overcommitment Ratio 29.5.7 The Optimal Overcommitment Ratio 29.5.8 Commitments, the Global Financial Crisis, and Liquidity 29.6 THE SECONDARY MARKET FOR PE PARTNERSHIPS 29.6.1 Secondary PE Market Development 29.6.2 PE Secondary Market Size 29.6.3 PE Buyer Motivations 29.6.4 PE Seller Motivations 29.6.5 The Secondary Market PE Investment Process 29.6.6 Sourcing PE Secondary Opportunities 29.6.7 Valuing Secondary PE Stakes 29.6.8 Limitations of the PE Secondary Market References CHAPTER 30 The Risk and Performance of Private and Listed Assets 30.1 EVIDENCE ON AN ILLIQUIDITY PREMIUM FROM LISTED ASSETS 30.1.1 A Factor-Pricing-Based Explanation for an Illiquidity Premium 30.1.2 Empirical Evidence of an Illiquidity Premium in US Treasuries 30.1.3 Empirical Evidence of an Illiquidity Premium in US Equities 30.2 PRIVATE VERSUS LISTED REAL PERFORMANCE: THE CASE OF REAL ESTATE 30.2.1 The Case Against Unlisted Real Estate Pools based on Historical Performance 30.2.2 Listing: Increased Risk or the Appearance of Increased Risk? 30.2.3 The Case Against Unlisted Real Estate Pools Based on Risk-Adjusted Performance 30.3 CHALLENGES WITH THE PME METHOD TO EVALUATING PRIVATE ASSET PERFORMANCE 30.3.1 The Interim Internal Rate of Return (IIRR) and Multiple Solutions 30.3.2 The IRRs under the PME Method Cannot be Calculated in Some Cases 30.3.3 IRR Does not Adjust for Scale and Timing 30.3.4 The PME Method Can be Effective in Evaluating Performance 30.3.5 The PME Method Can be Manipulated 30.4 MULTIPLE EVALUATION TOOLS 30.4.1 Simple Cash Flow Multiples 30.4.2 Multiples based on the PME Method 30.4.3 Private Equity Fund Benchmark Analysis 30.4.4 Applying a PME Analysis to the Example PE Funds 30.4.5 Summary of Results Using Multiple Evaluation Tools 30.5 IRR AGGREGATION PROBLEMS FOR PORTFOLIOS 30.5.1 Equally Weighting IRRs or IIRRs 30.5.2 Commitment-Weighting IRRs or IIRRs 30.5.3 Pooled Cash Flows for Weighting IRRs or IIRRs 30.5.4 Time-Zero-Based Pooling 30.5.5 Contrasting the Weighting Approaches for IRR and IIRR 30.6 THE CASE AGAINST PRIVATE EQUITY 30.7 TWO PROPOSITIONS REGARDING ACCESS THROUGH PRIVATE VERSUS LISTED STRUCTURES References PART 7 Due Diligence & Selecting Managers CHAPTER 31 Active Management and New Investments 31.1 TACTICAL ASSET ALLOCATION 31.2 THE FUNDAMENTAL LAW OF ACTIVE MANAGEMENT 31.2.1 The Central Relation of the FLOAM 31.2.2 The FLOAM and the Transfer Coefficient 31.2.3 The Tradeoff Between the Information Coefficient and Breadth and Its Key Driver 31.3 COSTS OF ACTIVELY REALLOCATING ACROSS ALTERNATIVE INVESTMENTS 31.3.1 Incentive Fees and Forgone Loss Carryforward 31.3.2 Two Potential Costs of Staying with a Manager Below its High-Water Mark 31.3.3 Two Types of Potential Costs of Replacing Managers Unrelated to Incentive Fees 31.4 KEYS TO A SUCCESSFUL TACTICAL ASSET ALLOCATION PROCESS 31.4.1 The TAA Process and Return Predictability 31.4.2 The TAA Process and Model-based Return Prediction 31.4.3 Three Important Characteristics of Sound TAA Model Development 31.4.4 SAA Models and Unconditional Analyses 31.4.5 TAA Models Based on Conditional Analyses 31.4.6 Technical Analysis Underlying TAA Models 31.5 ADJUSTING EXPOSURES TO ILLIQUID PARTNERSHIPS 31.5.1 The Primary Markets for PE Funds 31.5.2 PE Funds as Intermediaries 31.5.3 PE Fund Incentives and Terms 31.6 THE SECONDARY MARKET FOR PE LP INTERESTS 31.6.1 Secondary PE Market Emergence and Development 31.6.2 PE Secondary Market Size and Overview 31.6.3 PE LP Seller Motivations 31.6.4 PE LP Buyer Motivations 31.6.5 Sourcing Secondary PE Fund Opportunities 31.6.6 Valuing Secondary Stakes 31.6.7 Limitations of the Secondary Market for PE Interests References CHAPTER 32 Selection of a Fund Manager 32.1 THE IMPORTANCE OF FUND SELECTION ACROSS MANAGERS THROUGH TIME 32.2 THE RELATIONSHIP LIFE CYCLE BETWEEN LPs AND GPs 32.2.1 The Relationship Between PE GPs and LPs 32.2.2 Adverse Selection and GP-LP Relationships 32.2.3 Overview of the Life Cycle Aspect of the GP-LP Relationship 32.2.4 The Entry and Establish Phase 32.2.5 The Build and Harvest Phase 32.2.6 The Decline or Exit Phase 32.3 FUND RETURN PERSISTENCE 32.3.1 The Fund Performance Persistence Hypothesis 32.3.2 Evidence Regarding Fund Performance Persistence 32.3.3 Transition Matrices and Return Persistence in PE Funds 32.3.4 Persistence of Return Persistence in PE Funds 32.3.5 Six Challenges to the Performance Persistence Hypothesis 32.3.6 Performance Persistence Implementation Issues 32.4 MORAL HAZARD, ADVERSE SELECTION, AND THE HOLDUP PROBLEM IN FUND MANAGEMENT 32.5 SCREENING WITH FUNDAMENTAL QUESTIONS 32.5.1 Three Fundamental Questions Regarding the Nature of a Fund's Investment Program 32.5.2 Three Detailed Questions Regarding the Investment Objective 32.5.3 Four Detailed Questions Regarding the Investment Process 32.5.4 Two Detailed Questions Regarding the Value Added by the Fund Manager 32.6 HISTORICAL PERFORMANCE REVIEW 32.6.1 Two Critical Decisions Regarding A Performance Review 32.6.2 Reliance on Past Performance 32.6.3 Comprehensive Listing of Current and Past Assets under Management 32.6.4 Drawdowns 32.6.5 Statistical Return Data and Five Classic Issues 32.6.6 Statistical Return Analysis, Computation Horizons, and Intervals 32.7 MANAGER SELECTION AND DEAL SOURCING 32.7.1 Determination of the Wish List of Fund Characteristics 32.7.2 Classifying Management Teams 32.7.3 Deal Sourcing 32.8 FUND CULTURE 32.9 DECISION-MAKING AND COMMITMENT AND MANAGER SELECTION References CHAPTER 33 Investment Process Due Diligence 33.1 OVERVIEW OF INVESTMENT DUE DILIGENCE 33.1.1 Due Diligence Approaches 33.1.2 Importance of Investment Due Diligence 33.1.3 Three Internal Fund Functions 33.1.4 Differentiating Between Investment Process and Operational Due Diligence 33.1.5 Costs and Importance of Due Diligence 33.1.6 Due Diligence Checklists and Questionnaires 33.2 THE INVESTMENT STRATEGY OR MANDATE 33.2.1 Details on Components of the Investment Strategy 33.2.2 The Investment Mandate and Strategy Drift 33.2.3 Strategy Drift and Leverage 33.2.4 Investment Markets and Securities 33.2.5 Competitive Advantage and Source of Investment Ideas 33.2.6 Fund Assets Under Management Capacity for Effective Management 33.2.7 Key Persons and Investment Strategy 33.3 THE INVESTMENT IMPLEMENTATION PROCESS AND ITS RISKS 33.3.1 Implementing the Investment Strategy 33.3.2 Investment Process Risk 33.3.3 Detecting Investment Process Risk 33.4 ASSET CUSTODY AND VALUATION 33.4.1 Custody of Fund Assets 33.4.2 Current Portfolio Position 33.4.3 Principles of Fund Asset Valuation 33.4.4 Four Implications of Conflicts of Interest in Fund Asset Valuation 33.4.5 Challenges in Listed Asset Valuation 33.4.6 Valuation of Illiquid Assets and Level 1, 2, and 3 Assets 33.4.7 Internal Valuation of Assets 33.5 RISK ALERT'S ONE ADVANTAGE AND SIX OBSERVATIONS ON THIRD-PARTY INFORMATION 33.5.1 Advantages of Portfolio Information Aggregators 33.5.2 The Risk Alert Made Two Observations on Third Party Information Regarding Asset Values 33.5.3 The Risk Alert Made Four Observations on Four Trends in Due Diligence 33.6 PORTFOLIO RISK REVIEW 33.6.1 Risk Review Overview 33.6.2 Chief Risk Officer 33.6.3 Three General Questions of a Risk Review 33.6.4 Key Risks of Special Concern in a Risk Review 33.6.5 Risk Reviews and Leverage 33.6.6 How Leverage Magnifies Losses and Probabilities of Various Loss Levels 33.6.7 Subscription and Redemption Risks 33.7 FOUR WARNING INDICATORS AND AWARENESS SIGNALS REGARDING INVESTMENTS 33.8 FOUR WARNING INDICATORS AND AWARENESS SIGNALS REGARDING RISK MANAGEMENT References CHAPTER 34 Operational Due Diligence 34.1 OPERATIONS: OVERVIEW, RISKS, AND REMEDIES 34.1.1 Operational Errors, Agency Conflicts, and Operational Fraud 34.1.2 Operational Due Diligence is Driven by Operational Risk 34.1.3 Prevention, Detection, and Mitigation of Operational Risk by Asset Managers 34.1.4 Mitigation of Operational Risk by Investors 34.1.5 Perverse Incentives and Internal Control Procedures 34.1.6 Oversight of the Trade Life Cycle 34.1.7 Potential Veto Power of Due Diligence Teams 34.2 FOUR KEY OPERATIONAL ACTIVITIES 34.2.1 Overview of Due Diligence Regarding Execution 34.2.2 Overview of Due Diligence Regarding Posting 34.2.3 Overview of Due Diligence Regarding Trade Allocation 34.2.4 Overview of Due Diligence Regarding Reconciliation 34.3 ANALYZING FUND CASH MANAGEMENT AND MOVEMENT 34.3.1 Four Primary Purposes of Fund Cash 34.3.2 Analyzing Cash for Fund Expenses 34.3.3 Analyzing Cash to Facilitate Trading 34.3.4 Four Reasons for Analyzing Cash to And From Investors 34.3.5 Analyzing Unencumbered Cash 34.4 ANALYZING EXTERNAL PARTIES AND CHECKING PRINCIPALS 34.4.1 Analyzing Fund Prime Brokers 34.4.2 Analyzing Fund Administrators 34.4.3 Overview of Investigative Due Diligence 34.4.4 Three Models of Selecting Personnel for Investigation 34.4.5 Five Areas of Background Investigation 34.4.6 Organizing and Interpreting Information from Background and Other Investigations 34.4.7 Independent Service Provider Verification of Fund Operational Data 34.4.8 Checks with Other Investors 34.5 ANALYZING FUND COMPLIANCE 34.5.1 Personal Trading Compliance of Fund Employees 34.5.2 Common Compliance Risks Regarding Personal Trading 34.5.3 Compliance Risks Regarding Nonpublic and Inside Information 34.5.4 Electronic Communication Monitoring 34.5.5 Analyzing the Work of Third-Party Compliance Consultants 34.6 ONSITE MANAGER VISITS 34.6.1 Selection of Visit Location 34.6.2 Desk Reviews Are Not Best Practice 34.6.3 Risk Alert's Three Tasks on Desk versus Onsite Reviews 34.7 ELEMENTS AND KEY CONCERNS OF THE ODD PROCESS 34.7.1 Eight Core Elements of The ODD Process 34.7.2 Five Explanations for the Expanding Scope of Operational Due Diligence 34.7.3 External Sources of Review and Confirmation 34.8 INFORMATION TECHNOLOGY AND META RISKS 34.8.1 Information Technology 34.8.2 Five Key Questions Regarding Information Technology 34.8.3 Evaluating Meta Risk 34.9 FUNDING, APPLYING, AND CONCLUDING ODD 34.9.1 Four Approaches to Resource Allocation for Operational Due Diligence 34.9.2 Documenting the Operational Due Diligence Process 34.9.3 Operational Decision-Making and Allocation Considerations References CHAPTER 35 Due Diligence of Terms and Business Activities 35.1 DUE DILIGENCE DOCUMENT COLLECTION PROCESS 35.2 FUND GOVERNANCE 35.2.1 Fund Governance through Internal Committees 35.2.2 Fund Governance through Boards of Directors 35.2.3 Limited Partner Control and Communication 35.3 STRUCTURAL REVIEW OF THE FUND AND FUND MANAGER 35.3.1 Fund Organization 35.3.2 Master-Feeder Trusts 35.3.3 Side Pocket Arrangements 35.3.4 Registrations 35.3.5 Fund Manager Organization and Ownership 35.4 TERMS FOR LIQUID PRIVATE FUNDS 35.4.1 Redemptions 35.4.2 Lockups and Their Two Potential Benefits 35.4.3 Gates 35.5 TERMS FOR ILLIQUID PRIVATE FUNDS 35.5.1 The LPA, Fund Term, and Distributions 35.5.2 Advisory Committee 35.5.3 Termination and Divorce 35.6 GENERAL TERMS FOR PRIVATE FUNDS 35.6.1 Type of Investment and Liability Limits 35.6.2 Subscription Amount 35.6.3 Investor Relations 35.7 PRIVATE PLACEMENT MEMORANDUM (PPM) 35.7.1 Four Key Functions of the OM/PPM 35.7.2 Side Letters 35.7.3 Different Purposes of Legal Counsel Reviews and ODD Document Reviews 35.7.4 Analyzing Other Common Private Placement Memorandum Terms 35.8 FUND FEES AND EXPENSES 35.8.1 Timing of Fee Collection 35.8.2 Fee Offsets 35.8.3 Details Regarding Incentive Fees 35.8.4 GP's Contribution 35.9 PRIVATE FUND AUDITED FINANCIAL STATEMENT REVIEW 35.9.1 Valuation Policies 35.10 BUSINESS ACTIVITIES, CONTINUITY PLANNING, DISASTER RECOVERY, AND INSURANCE 35.10.1 Business Continuity Planning and Disaster Recovery 35.10.1.1 Focus on Information Technology 35.10.1.2 Fund Insurance Reference PART 8 Volatility and Complex Strategies CHAPTER 36 Volatility as a Factor Exposure 36.1 Measures of Volatility 36.1.1 Implied Volatility and Realized Volatility 36.1.2 Three Limitations of Realized Volatility as a Measure of Dispersion 36.1.3 Six Properties of Realized Volatility 36.2 Volatility and the Vegas, Gammas, and Thetas of Options 36.2.1 Option Vegas 36.2.2 Scaling of the Vega of an Option 36.2.3 Vega as an Approximation for Finite Shifts 36.2.4 Four Observations on Option Vegas 36.2.5 Option Gammas 36.2.6 Putting Option Vegas, Gammas, and Thetas Together 36.3 Exposures to Volatility as a Factor 36.3.1 Long and Short Volatility 36.3.2 Distinctions between Positive Vega and Long Volatility Exposures 36.3.3 Using Volatility Derivatives to Hedge Market Risk 36.3.4 Volatility as an Unobservable but Unique Risk Factor 36.3.5 The Volatility Factor Has a Negative Risk Premium 36.3.6 Evidence That Short Volatility Earns a Positive Risk Premium 36.4 Modeling Volatility Processes 36.4.1 Volatility Processes with Jump Risk 36.4.2 Volatility Processes and Regime Changes 36.4.3 Two Reasons Why Volatility Strategies Tend to Recover Quickly 36.4.4 Reasons Why Volatility Mean-Reversion Cannot Arbitraged 36.5 Implied Volatility Structures 36.5.1 Methods of Computing Implied Volatility 36.5.2 Implied Volatility Structures and Moneyness 36.5.3 Implied Volatility Surfaces 36.5.4 Four Key Reasons for Implied Volatility Structures and Surfaces 36.5.5 Two Explanations for High Implied Volatilities of Out-of-The-Money Puts References CHAPTER 37 Volatility, Correlation, and Dispersion Products and Strategies 37.1 Common Option Strategies and their Volatility Exposures 37.1.1 Option Writing, Theta, and Time Decay 37.1.2 Writing Option Straddles and Strangles as a Short Volatility Strategy 37.1.3 Writing Option Butterflies and Condors as Volatility Strategies 37.2 Volatility and Delta-Neutral Portfolios with Options 37.2.1 General Performance Drivers of Delta-Neutral Portfolios with Options 37.2.2 Four Key Points Regarding Delta-Neutral Option Portfolios 37.2.3 Delta Normalization and Exposure to Volatility 37.3 Advanced Option-Based Volatility Strategies 37.3.1 Vertical Intra-Asset (Skew) Option Spreads 37.3.2 Vertical Spreads with Delta-Hedging 37.3.3 Horizontal Intra-Asset (Skew) Spreads 37.3.4 Inter-Asset Option Spreads 37.4 Variance-Based and Volatility-Based Derivative Products 37.4.1 Variance Swaps and Variance Futures on Realized Variance 37.4.2 Implied Volatility Indices 37.4.3 Computation of the CBOE Volatility Index (VIX) 37.4.4 Futures Contracts on the CBOE Volatility Index (VIX) 37.4.5 The S&P 500 VIX Short-Term Futures Index 37.4.6 Options, Exchange-Traded Notes, and Other VIX-Related Products 37.4.7 The VIX Term Structure and Its Slope as a Proxy for Portfolio Insurance 37.5 Correlation Swaps 37.5.1 Mechanics of a Correlation Swap 37.5.2 Modeling the Relation between Correlations, Security Volatility, and Portfolio Volatility 37.5.3 Motivations to Correlation Trading 37.6 Dispersion Trades 37.7 Summary and Common Themes of Volatility, Correlation, and Dispersion Trading 37.8 Volatility Hedge Funds and their Strategies 37.8.1 Four Subcategories of Volatility Hedge Funds 37.8.2 Relative Value Volatility Funds 37.8.3 Short Volatility Funds 37.8.4 Long Volatility and Tail Risk Funds 37.8.5 Returns of the Four Volatility Fund Indices References CHAPTER 38 Complexity and Structured Products 38.1 UNCERTAINTY, AMBIGUITY, AND OPACITY 38.1.1 Knightian Uncertainty 38.1.2 Ambiguity 38.1.3 Opacity and the Theoretical Incentive to Create Complexity 38.2 ASSET AND STRATEGY COMPLEXITY 38.2.1 Complexity, Passive Indexation, and Active Management 38.2.2 Complexity Crashes 38.2.3 The Complexity Risk Premium 38.2.4 Complexity as a Return Characteristic or Factor 38.3 CASES IN COMPLEXITY AND PERVERSE INCENTIVES 38.3.1 Treasury Strips in the 1980s 38.3.2 Collateralized Mortgage Obligations in the 1990s 38.3.3 Residential Mortgage-Backed Securities in the 2000s 38.3.4 Five Key Takeaways from the Three Fixed Income Cases 38.4 ASSET-BASED LENDING 38.4.1 A Typical Borrower in Asset-Based Lending 38.4.2 Why Borrowers Select Asset-Based Lending 38.4.3 Features of Asset-Based Lending 38.4.4 Discount Rates for Various Assets in Asset-Based Lending 38.4.5 Use of Asset-Based Lending Proceeds 38.4.6 Asset-Based Loan Structures and Collateral 38.4.7 Asset-Based Lender Protection and Covenants 38.5 RISKS OF ASSET-BASED LOANS 38.5.1 Collateral Valuation Risk of Asset-Based Loans and Lender Remedies 38.5.2 Risks Regarding Process and People in Asset-Based Loans 38.5.3 Risks Regarding Hedging of Asset-Based Loans 38.5.4 Legal Risks of Asset-Based Loans 38.5.5 Risks Regarding Timing of Exits from Asset-Based Loans 38.6 ASSET-BACKED SECURITIES 38.6.1 The Creation of Asset-Backed Securities 38.6.2 Growth of Various Types of Asset-Backed Securities 38.6.3 Auto Loan-Backed Securities 38.6.4 Auto Loan-Backed Securities and Prepayments 38.6.5 Credit Card Receivables 38.6.6 Credit Card Receivables Credit Enhancements References CHAPTER 39 Insurance-Linked Products and Hybrid Securities 39.1 Nonlife ILS: Catastrophe Bonds 39.1.1 Overview of Catastrophe Bonds 39.1.2 Mechanics of Catastrophe Bonds 39.1.3 Risks and Returns of Catastrophe Bonds 39.1.4 Role of Catastrophe Bonds in Managing Risks to Insurers 39.2 Four Trigger Types of Cat Bonds 39.2.1 Indemnity Triggers 39.2.2 Industry Loss Triggers 39.2.3 Parametric Triggers 39.2.4 Modeled Triggers 39.3 Cat Bond Valuation, Performance, and Drawbacks 39.3.1 Establishing The Coupon Rate To Investors In Cat Bonds 39.3.2 Cat Bond Index Returns 39.3.3 Potential Drawbacks and Alpha of Investing in Cat Bonds 39.3.4 Catastrophe-related Derivative Securities 39.4 Longevity and Mortality Risk-Related Products 39.4.1 Longevity Risk 39.4.2 Hedging Longevity Risk 39.4.3 Four Longevity Hedging Risks 39.4.4 Mortality Risk 39.4.5 Mortality Risk and Structured Products 39.4.6 Main Risks of Catastrophic Mortality Bonds 39.5 Life Insurance Settlements 39.5.1 Mechanics and Details of Life Insurance Settlements 39.5.2 Path of Life Insurance Policy Values Through Time 39.5.3 Modeling Life Insurance Settlements 39.6 Overview of Viatical Settlements 39.6.1 Viatical Settlements, Life Settlements, and Secondary Markets 39.6.2 Investment Benefits, Risks, and Drawbacks of Viatical Settlements 39.6.3 Returns on Life Insurance Settlements 39.7 Hybrid Products: Mezzanine Debt 39.7.1 Subordinated Debt with Step-Up Rates 39.7.2 Subordinated Debt with PIK Interest 39.7.3 Subordinated Debt with Profit Participation 39.7.4 Subordinated Debt with Warrants 39.7.5 Project Finance and Public-Private Partnerships References CHAPTER 40 Complexity and the Case of Cross-Border Real Estate Investing 40.1 TRADITIONAL VIEW OF CURRENCY-HEDGING FOR CROSS-BORDER REAL ESTATE INVESTING 40.1.1 Cross-Border Return as a Function of Rates 40.1.2 The Key Traditional Currency Risk Assumption of Cross-Border Investing 40.1.3 Currency Risks and Return Variances 40.1.4 Risk when Domestic Investment Returns Fully Adjust for Currency Devaluation 40.1.5 Risk and a Focus on Single Currency Risk Measures 40.2 FUNDAMENTALS OF CURRENCY RISK AND HEDGING IN PERFECT MARKETS 40.2.1 Currency Risk and the Law of One Price 40.2.2 Example of No Currency-Hedging Needed 40.2.3 Currency Risk and the Law of One Price with Currency-Hedging 40.2.4 Currency Risk and Currency-Hedging of Fixed Income Securities 40.3 CURRENCY RISK AND HEDGING OF ALTERNATIVE INVESTMENTS 40.3.1 Price Stickiness, Asset Values, and Expected Future Cash Flows 40.3.2 Price Stickiness, Currency Risk, and Unlevered Corporate Assets 40.3.3 Currency Risk and Levered Assets 40.4 ACCESSING FOREIGN ASSETS WITH FUTURES AND QUANTO FUTURES 40.4.1 Quanto Financial Derivatives 40.4.2 Quanto Futures Contracts 40.4.3 Futures-based Strategies versus Direct Cash Investment in Foreign Assets 40.5 OVERVIEW OF INTERNATIONAL REAL ESTATE INVESTING 40.5.1 Characteristics of International Real Estate Markets 40.5.2 Global Real Estate Taxes and Transaction Costs 40.5.3 Benefits Of International Real Estate Investing 40.6 HETEROGENOUS INVESTMENT TAXATION ACROSS JURISDICTIONS 40.7 CHALLENGES TO INTERNATIONAL REAL ESTATE INVESTING 40.7.1 Three Reasons Why Agency Relationships Are Important 40.7.2 Relative Inefficiency of Global Real Estate Markets 40.7.3 Information Asymmetries 40.7.4 Liquidity and Transaction Costs 40.7.5 Political, Economic, and Legal Risks References Index 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