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More About This Title J Curve Exposure - Managing a Portfolio of Venture Capital and Private Equity Funds
English
Factors that can sometimes cause institutions to shy away from venture capital are the industry’s opaque track record, unclear valuations and risks, perceived lack of transparency as well as the significant entry barriers to overcome before tangible results show. These issues are all addressed in details with practical solutions to the problems. Among other topics J-Curve Exposure includes discussions of:
- Experiences with the adoption of the International Private Equity and Venture Capital Valuation Guidelines to address fair value under IFRS.
- Approaches for splitting and prioritizing distributions from private equity funds.
- Techniques for track record analysis and other tools to help limited partners in their due diligence.
- Approaches to dealing with uncertainty, the relevance of real options, and co-investments and side funds as advanced portfolio management techniques.
- Questions related to limited partner decision making fallacies and how to manage portfolios of VC funds.
- Securitization backed by portfolios of investments in private equity funds.
Real life case studies illustrate the issues relevant for the practitioner.
English
Dr THOMAS MEYER heads up the risk management division of the European Investment Fund. Over the last few years he has been responsible for the creation of the European Investment Fund’s risk management function. The focus of his work is the development of valuation and risk management models and investment strategies for venture capital fund-of-funds. Thomas studied computer science at the Bundeswehr Universität in Munich followed by doctoral studies at the University of Trier. He holds an MBA from the London Business School and an MA in Japanese Language and Society from the University of Sheffield. After 12 years in the German Air Force he worked for the German insurance group Allianz AG in corporate finance and as the regional Chief Financial Officer of Allianz Asia Pacific in Singapore. He was a Visiting Research Fellow at Hitotsubashi University in Tokyo and is a member of the private equity subcommittee of the Chartered Alternative Investment Analyst® (CAIA) Program.
Together, as risk managers, the authors are responsible for one of the largest European private equity portfolio’s with of more than 250 funds and over €6 billion under management.
English
Foreword.
Acknowledgments.
Abbreviations.
Disclaimer.
PART I. PRIVATE EQUITY LANDSCAPE.
1. Introduction.
1.1 Barbarians, pirates and privateers.
1.2 A difficult world to conquer.
2. Institutional Investing in Private Equity.
2.1 Limited partnership.
2.2 Funds-of-funds.
2.3 Private equity funds investment program.
3. Private Equity Environment.
3.1 The informal VC market.
3.2 Private equity as part of alternative assets.
3.3 Mezzanine financing.
3.4 Overlap with public market.
3.5 Conclusion.
4. Risk Management Lessons from a Listed Private Equity Fund-of-Funds.
4.1 Relevance of the Private Equity Holding case.
4.2 The Swiss private equity funds-of-funds industry.
4.3 Commitments and investments.
4.4 The rise and (near) fall of Private Equity Holding.
4.5 Definition and analysis of ratios.
4.6 Lessons and epilogue.
Appendix 4A. Adjusted current ratio methodology.
PART II. THE ECONOMICS OF PRIVATE EQUITY FUNDS.
5. Venture Capital Fund Fair Value.
5.1 Valuation Guidelines.
5.2 Motivation.
5.3 Current practices.
5.4 Problem areas.
5.5 Conceptual questions.
5.6 Can one do without judgment?
5.7 Is there a pragmatic way forward?
6. Model-Based Approach to VC Fund Valuation.
6.1 Why model?
6.2 The private equity data market.
7. Private Equity Fund Valuation Approaches.
7.1 Determining the economic value of a private equity fund.
7.2 Accounting valuation of a fund’s portfolio of investee companies.
7.3 Conclusion.
8. Distribution Waterfall.
8.1 Introduction.
8.2 Basic waterfall model.
8.3 Impact of carried interest distribution approaches.
8.4 Clawback.
9. Break-even Analysis.
9.1 Objective of break-even analysis.
9.2 Methodology.
9.3 Scenarios and sensitivity analysis.
9.4 Additional analysis.
9.4.3 IRR distributions.
10. Track Record Analysis.
10.1 Due diligence.
10.2 Benchmarking.
10.3 Track record analysis tools.
10.4 Limitations.
10.5 Conclusion.
Appendix 10A. Performance spread between best and worst manager.
PART III. MANAGING UNDER UNCERTAINTY.
11. Grading and Fitness Landscapes.
11.1 Fitness landscapes.
11.2 Grading-based evaluation of private equity funds.
11.3 Grading as portfolio management tool.
11.4 VC market dynamics – power laws.
11.5 Searching landscapes.
11.6 Conclusion.
12. Private Equity Funds and Real Options.
12.1 Agency problems and contracting.
12.2 Changes in limited partnership agreements.
12.3 Braiding.
12.4 Summary.
13. Co-investing.
13.1 Motivation.
13.2 Co-investment risk and rewards.
13.3 Potential issues related to co-investments.
13.4 Implementation issues.
13.5 Portfolio management.
13.6 Conclusion.
14. Side Funds
14.1 ‘Classical’ side funds.
14.2 Side funds – similar structures.
14.3 LPs structure or how to increase flexibilty.
14.4 Conclusion.
15. Limited Partner Decision-Making Fallacies.
15.1 Decision-making with poor data.
15.2 Herding as a response to uncertainty.
15.3 Decision-making biases.
15.4 Conclusion.
PART IV. MANAGING PORTFOLIOS OF PRIVATE EQUITY FUNDS.
16. Portfolio Construction Principles.
16.1 Private equity and modern portfolio theory.
16.2 Creating a portfolio of private equity funds.
16.3 The risk profile of private equity assets.
16.4 Risk dimensions.
17. Portfolio Construction Rules of Thumb.
17.1 What we know.
17.2 What we think we know or simply don’t know.
17.3 Exploitation vs. Exploration.
18. Guidelines, Monitoring and Corrective Actions.
18.1 Investment guidelines as framework.
18.2 Implementation of investment policies.
18.3 Monitoring investment restrictions.
18.4 Monitoring strategy implementation.
18.5 Corrective actions.
19. Securitization.
19.1 Structure of private equity CFO.
19.2 Which private equity assets?
19.3 Parties involved and their objectives.
19.4 Modeling the transaction – simulating the performance of the assets.
19.5 Modeling the transaction – structural features.
19.6 External rating.
20. J Curve Exposure.
20.1 Cultural influences.
20.2 Blurred boundaries.
20.3 Limited scalability.
20.4 End-game?
References.
Index.
