Thomas Meyer (Luxembourg European Investment Fund)

The Art of Commitment Pacing

Engineering Allocations to Private Capital

• Gebundenes Buch

Produktbeschreibung

Advanced guidance for institutional investors, academics, and researchers on how to construct portfolios of private capital funds.   The Art of Commitment Pacing: Engineering Allocations to Private Capital provides a much-needed analysis of the issues that face investors as they incorporate closed ended-funds targeting illiquid private assets (such as private equity, private debt, infrastructure, real estate) into their portfolios. These private capital funds, once considered 'alternative' and viewed as experimental, are becoming an increasingly standard component of institutional asset allocations.   However, many investors still follow management approaches that remain anchored in the portfolio theory for liquid assets but that often lead to disappointing results when applied to portfolios of private capital funds where practically investors remain committed over nearly a decade.   The Art of Commitment Pacing offers a systematic approach for building up and controlling allocations to such investments.

Produktdetails

• The Wiley Finance Series
• Verlag: John Wiley & Sons Inc
• Seitenzahl: 320
• Erscheinungstermin: 4. Juni 2024
• Englisch
• Abmessung: 245mm x 175mm x 22mm
• Gewicht: 728g
• ISBN-13: 9781394159604
• ISBN-10: 1394159609
• Artikelnr.: 69720610

Autorenporträt

THOMAS MEYER, is the co-author of Beyond the J Curve (translated into Chinese, Japanese, and Vietnamese), J Curve Exposure, Mastering Illiquidity (all by Wiley), and two CAIA books, which are required reading for Level II of the Chartered Alternative Investment Analyst (r) Program. He authored Private Equity Unchained (by Palgrave MacMillan).

Inhaltsangabe

Acknowledgments xiii Chapter 1 Introduction 1 Scope of the book 1 Quick
glossary 2 The challenge of private capital 2 Risk and uncertainty 3 Why do
we need commitment pacing? 4 Illiquidity 4 The siren song of the secondary
market 4 How does commitment pacing work? 5 Significant allocations needed
7 Multi-asset-class allocations 8 Intra-asset-class diversification 8
Engineering a resilient portfolio 9 Organisation of the book 10 Chapter 2
Institutional Investing in Private Capital 15 Limited partnerships 15
Structure 16 Criticism 18 Costs of intermediation 18 Inefficient fund
raising 18 Addressing uncertainty 19 Conclusion 19 Chapter 3 Exposure 21
Exposure definition 21 Layers of investment 23 Net asset value 23 Undrawn
commitments 24 Commitment risk 24 Timing 24 Classification 25 Exposure
measures - LP's perspective 25 Commitment 26 Commitment minus capital
repaid 26 Repayment-age-adjusted commitment 27 Exposure measures - fund
manager's perspective 28 Ipev Nav 28 IPEV NAV plus uncalled commitments 29
Repayment-age-adjusted accumulated contributions 30 Summary and conclusion
31 Chapter 4 Forecasting Models 37 Bootstrapping 37 Machine learning 38
Takahashi-Alexander model 40 Model dynamics 40 Strengths and weaknesses 46
Variations and extensions 47 Stochastic models 49 Stochastic modelling of
contributions, distributions, and NAVs 49 Comparison 50 Conclusion 51
Chapter 5 Private Market Data 53 Fund peer groups 53 Organisation of
benchmarking data 53 Bailey criteria 54 Data providers 55 Business model 55
Public route 55 Voluntary provision 56 Problem areas 56 Biases 57
Survivorship bias 57 Survivorship bias in private markets 58 Impact 58
Conclusion 59 Chapter 6 Augmented TAM - Outcome Model 61 From TAM to
stochastic forecasts 61 Use cases for stochastic cash-flow forecasts 62
Funding risk 62 Market risk 65 Liquidity risk 65 Capital risk 66 Model
architecture 66 Outcome model 67 Pattern model 67 Portfolio model 68 System
considerations 68 Semi-deterministic TAM 68 Adjusting ranges for lifetime
and TVPI 70 Ranges for fund lifetimes 71 Ranges for fund TVPIs 73 Picking
samples 76 Constructing PDF for TVPI based on private market data 78 A1*TAM
results 82 Chapter 7 Augmented TAM - Pattern Model 85 A2*tam 86
Reactiveness of model 86 Model overview 87 Changing granularity 89
Injecting randomness 89 Setting frequency of cash flows 90 Setting
volatility for contributions 92 Setting volatility for distributions 94
Scaling and re- picking cash- flow samples 94 Convergence A2*TAM to TAM 95
Split cash flows in components 97 Fees 98 Fixed returns 102 Cash- flow-
consistent NAV 103 Principal approach 103 First contributions, then
distributions 103 Forward pass 104 Backward pass 104 Combination 104
Summary 105 Chapter 8 Modelling Avenues into Private Capital 109 Primary
commitments 109 Modelling fund strategies 110 Parameter as suggested by
Takahashi and Alexander (2002) 110 Further findings on parameters 113
Basing parameters on comparable situations 113 Funds of funds 114 Secondary
buys 114 Secondary FOFs 116 Co-investments 118 Basic approach 118
Co-investment funds 119 Syndication 119 Side funds 119 Impact on portfolio
120 Chapter 9 Modelling Diversification for Portfolios of Limited
Partnership Funds 123 The LP diversification measurement problem 123 Fund
investments 124 Diversification or skills? 124 Aspects of diversification
125 A (non-ESG-compliant) analogy 125 Commitment efficiency 126 Exposure
efficiency 126 Outcome assessment 126 Diversifying commitments 127
Assigning funds to clusters 127 Diversification dimensions 128
Self-proclaimed definitions 128 Market practices 128 The importance of
diversification over vintage years 129 Other dimensions and their impact on
risks 129 Include currencies? 130 Definitions 131 Styles 131 Classification
groups 132 Style drifts 133 Robustness of classification schemes 133
Modelling vintage year impact 134 Commitment efficiency 135 Importance of
clusters 135 Partitioning into clusters 136 Measurement approach 137
Remarks 139 Mobility barriers 139 Similarity is a measure for barriers to
switching between classes 140 Similarity is not correlation 140 Is there an
optimum diversification? 141 How many funds? 141 Costs of diversification
141 How to set a 'satisficing' number of funds? 143 Portfolio impact 143
Commitment efficiency timeline 143 Portfolio-level forecasts 143 Appendix A
- Determining similarities 145 Appendix B - Geographical similarities 146
Geographical diversification for private capital 146 Regional groups 146
Trade blocs 147 Transport way connection 148 Language barriers 148 Limits
to geography as diversifier 148 Appendix C - Multi-strategies and others
149 Appendix D - Industry sector similarities 149 Appendix E - Strategy
similarities 149 Appendix F - Fund management firm similarities 150
Appendix G - Investment stage similarities 151 Appendix H - Fund size
similarities 152 Chapter 10 Model Input Data 155 Categorical input data 155
Perceptions 156 Regulation 156 Risk managers 157 Can data be objective? 157
Moving from weak to strong data 158 Chapter 11 Fund Rating/Grading 161
Private capital funds and ratings 161 Fiduciary ratings 161 Fund rankings
162 Internal rating systems 162 Further literature 163 Private capital fund
gradings 163 Scope and limitations 163 Selection skill model 164
Assumptions for grading 165 Prototype fund grading system 165 Ex-ante
weights 166 Expectation grades 166 Risk grades 169 Quantification 171
Chapter 12 Qualitative Scoring 173 Objectives and scope 173 Relevant
dimensions 174 Investment style 175 Management team 176 Fund terms 177
Liquidity and exits 178 Incentive structure 178 Alignment and conflicts of
interest 180 Independence of decision-making 181 Viability 181 Confirmation
182 Scoring method 183 Tallying 183 Researching practices 184 Ex-post
monitoring 184 Assigning grades 185 Appendix - Search across several
private market data providers 186 Interoperability 186 Matching 187 Chapter
13 Quantification Based on Fund Grades 191 Grading process 191 Quartiling
191 Quantiles 192 Quartiling 193 Approach 194 Example - how tall will she
be? 195 Probabilistic statement 196 Controlling convergence 196 LP
selection skills 198 Impact of risk grade 201 TVPI sampling 203 Chapter 14
Bottom- up Approach to Forecasting 205 Look- through 205 Regulation 205
Fund ratings 206 Look- through in practice 206 Bottom- up 207 Stochastic
bottom- up models 207 Machine- learning- based bottom- up models 207
Overrides 208 Investment intelligence 208 Advantages and restrictions 208
Treatment as exceptions 209 Integration of overrides in forecasts by a top-
down model 209 Probabilistic bottom- up 211 Expert knowledge for
probability density functions? 212 Estimating ranges 212 Combining top-
down with bottom- up 214 Chapter 15 Commitment Pacing 217 Defining a pacing
plan 217 Pacing phases 218 Ramp-up phase 219 Maintenance phase 219
Ramp-down phase 220 Controlling allocations 221 Simulating the pacing plan
221 Ratio-based commitment rules 222 Dynamic commitments 222 Pacing plan
outcomes 222 'Slow and steady' 223 Accelerated pacing plan 223 Liquidity
constraints 224 Impact on cash-flow profile 224 Impact of commitment types
225 Maintenance phase 228 Recommitments 229 Target NAV 229 Cash-flow
matching 230 Additional objectives and constraints 231 Commit to
high-quality funds 231 Achieve intra-asset diversification 231 Minimise
opportunity costs 233 Satisficing portfolios 233 Conclusion 234 Chapter 16
Stress Scenarios 235 Make forecasts more robust 235 Communication 235
Specific to portfolio 236 Impact of 'Black Swans' 236 Interest rates and
inflationary periods 237 Modelling crises 238 Delay of new commitments 238
Changes in contribution rates 238 Changes in distributions 239 NAV impact
and secondary transactions 240 Lessons 240 Building stress scenarios 241
Market replay 241 Varying outcomes 242 Foreign exchange rates 244 Varying
portfolio dependencies 244 Increasing and decreasing outcome dependencies
244 Increasing and decreasing cash-flow dependencies 247 Blanking out
periods of distributions 247 Varying patterns 248 Stressing commitments 249
Extending and shortening of fund lifetimes 250 Front-loading and
back-loading of cash flows 251 Foreign exchange rates and funding risk 251
Increasing and decreasing frequency of cash flows 253 Increasing and
decreasing volatility of cash flows 254 Conclusion 256 Chapter 17 The Art
of Commitment Pacing 259 Improved information technology 259 Direct
investments 260 Use of artificial intelligence 260 Risk of private equity
261 Securitisations 261 Judgement, engineering, and art 262 Abbreviations
263 Glossary 267 Biography 275 Bibliography 277 Index 289