Valuation, Returns and Disclosure

1. Valuation, Returns and Disclosure Cumming and Johan (2013 Chapter 22) 1

2. Chapter Objectives • Review the mechanics underlying the venture capital valuation method • Present evidence on venture capital fund returns to show ways in which the discount rate or cash flows considered in valuations might be adjusted depending on the characteristics of the venture capital fund, characteristics of the entrepreneurial firm, structure of investment, market conditions, and legal conditions; and • Present evidence that show how returns are disclosed to institutional investors prior to an exit event. 2

3. Venture Capital Valuation Equations 3

4. Example • Suppose you are employed at the Soprano Venture Capital Fund, a hypothetical venture capital fund in New Jersey. Your first assignment is to value the price per share for a $10 million investment in a start-up green technology venture, and to decide on what share of the firm you should demand. You project the firm will have Net Income in Year 6 of $40 million. Similar profitable green ventures listed on stock exchanges are trading at an average Price-Earning Ratio of 15. The firm currently has 400,000 shares outstanding. Tony, your Boss, tells you that the Soprano Venture Capital Fund requires a target rate of return of 80%. What is the appropriate price per share, and how many shares do you require? 4

5. Example (Continued) 5

6. Example (Continued) • Suppose further that you are of the opinion that three more senior staff will need to be hired by this green technology venture, and this number of top caliber recruits will probably require options amounting to 15% of this venture’s common stock outstanding. Additionally, you believe that, at the time the venture goes public, additional shares equivalent to 20% of the common stock will be sold to the public. As such, you would perform the following adjustments to your calculations: (next slide) 6

7. Example (Continued) 7

8. Some Lessons • Valuation is an art, not a science • VC Valuation technique somewhat arbitrary, particularly in the discount rate • Other methods (Comparables, NPV, APV, IRR, Options Pricing) involve assumptions which might be equally problematic • Here in the subsequent slides provide evidence showing valuations internationally 8

9. Now: Worldwide Evidence on Returns and Disclosure Evidence from 39 countries! 9

10. Motivation: Worldwide Policy Debate • 2002 CALPERS disclosure lawsuit • Public pension funds must disclose venture capital and private equity returns, even on unexited investments • Implications for understanding determinants of, and reporting of, returns • Do we need mandated disclosure standards for VC and PE funds? • Biggest issue for VC/PE markets since collapse of Internet bubble • Regulation of VC and PE funds one of the biggest issues in UK Financial Times last week • See also Chapter 4 10

11. Research Questions • What are the determinants of VC and private equity returns across countries? • Are unexited investment values over-reported to institutional investors? • Are biases in reporting unexited investments related to legal conditions? • Relative merits of alternative approaches to stimulating VC markets 11

12. New Contributions • First look at project-specific returns to VC and private equity across countries • Innovative application of econometric selection methods to measure VC returns • First look at biases in unexited returns and relations to fundraising • Policy implications: Reporting Standards needed in VC? 12

13. Theory and Hypotheses Data Econometric Tests Policy Implications Theory and Hypotheses 13

14. Venture Capital Cycle Pension Plan Members (you and I) E.g., CALPERS California Public Pension Fund Institutional and Other Investors Why care? Distorted asset allocations, less overall fundraising Returns $ Reporting bias of unexited returns in annual reports? Venture Capital Funds • Chapter 7 CD Howe Institute, AEI Sciences Po, Brookings, PWC, EVCA, NVCA, etc. They all care a lot! This Paper $ Returns (realized vs ‘expected’) 2-7 years before exit event (IPO, Acquisition, Write-off) Entrepreneurial Firms 14

15. Theory and Hypotheses Data Econometric Tests Policy Implications 1. Advice, Monitoring & Returns • Monitoring/advice activities of VC are responsible for return of VC • Main focus on VC characteristic • Model with asymmetric information • Advice is not contractible • IRR must be sufficiently large to induce VC to undertake optimal level of advice/monitoring • The more productive the VC is, the higher the optimal advice/monitoring level  the lower the price of shares for the VC  the higher the VC returns 15

16. Theory and Hypotheses Data Econometric Tests Policy Implications 1. Advice, Monitoring & Returns (Continued) • The higher the intensity of monitoring and advice the higher the expected IRR of the VC • Convertible securities, syndication  higher expected rate of return • Co-investment:  lower returns • Smaller portfolios (# investments) / manager  higher returns • Better legal environment  more efficient advice and less information asymmetries upon exit  the higher expected returns 16

17. Theory and Hypotheses Data Econometric Tests Policy Implications 2. Biases in Reporting Un-Exited Investments • Valuation take place against trade-off between • Fundraising concerns (higher valuations potentially facilitate fundraising in next round) • Reputational concerns (overvaluation damages long-run reputation) • Pooling equilibria may emerge (bad projects are overstated) 17

18. Theory and Hypotheses Data Econometric Tests Policy Implications 2. Biases in Reporting Un-Exited Investments (Continued) Hypotheses: • Expected Fundraising Benefit > Expected Reputation Cost • Inexperienced VCs: overstate • Earlier stage and high tech: overstate • Syndicated investment: less likely to overstate • Co-investment: more likely to overstate • Legal environment increases costs of overstatement • Less stringent accounting rules: overstate • Sarbanes Oxley: less likely to overstate 18

19. Theory and Hypotheses Data Econometric Tests Policy Implications 2. Biases in Reporting Un-Exited Investments (Continued) Formal Hypotheses Tested: • H1:Unexited PE investments are less likely to be overvalued in countries that have superior accounting and legal standards. • H2:Unexited PE investments are more likely to be overvalued at times of poor market conditions. • H3:Inexperienced PE managers and younger funds are more likely to overvalue unexited investments. • H4:Unexited earlier stage PE investments and high-tech investments are more likely to be overvalued. 19

20. Theory and Hypotheses Data Econometric Tests Policy Implications Data 20

21. Theory and Hypotheses Data Econometric Tests Policy Implications CEPRES Dataset • 221 venture capital and private equity funds • 72 venture capital and private equity firms • 5117 entrepreneurial firms (3826 venture capital and 1214 private equity) • 33years (1971 – 2003) • 39 countries (North and South America, Europe and Asia) • Table 1 (see paper) defines the variables 21

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26. Theory and Hypotheses Data Econometric Tests Policy Implications “Realized Returns Econometrics” • Multi-step Heckman correction to measure the returns to VC and private equity investment • Heckman selection corrections for • Unexited / Exited Investments • Partial / Full Exits • Statistical problems associated with OLS on a subsample of fully realized IRRs 26

27. Theory and Hypotheses Data Econometric Tests Policy Implications 3-Step Heckman Correction • Probit: Exit / No Exit • Selection Corrected Probit: Full / Partial Exit, accounting for the selection effects associated with an actual exit (step 1) • Heckman Linear Regression IRR, accounting for both steps # 1 and 2 27

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30. Theory and Hypotheses Data Econometric Tests Policy Implications Unexited Reported IRRs (2000 – 2003) versusPredicted IRRs • Contrast reported unexited IRRs (as reported to the institutional investors) with predicted IRRs for unexited investments • Log(1+IRR Reported)-Log(1+IRR Expected) = Log((1+Reported IRR)/(1+Predicted IRR) = 143% • Regression evidence: quite remarkably(!) consistent with the proposition that more informational asymmetry is associated with more ‘lying’! • Table 4: full sample • Table 5 (see paper): same results with European-only subsample 30

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32. Theory and Hypotheses Data Econometric Tests Policy Implications Unexited Reported IRRs (2000 – 2003) versus Actual IRRs • Subsample of 80 observations (investee firms) from 11 countries for which both the realized and unrealized reported IRR are known (Canada, Finland, France, Germany, Israel, Norway, Spain, Sweden, the Netherlands, the UK, and the US) • The correlation between out-of-sample average realized IRRs and our predicted IRRs is 0.45 32

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35. Theory and Hypotheses Data Econometric Tests Policy Implications Overstatement of Unexited IRRs and Fundraising • Not possible to assess causality • but there is evidence of positive correlations between overstatement of unexited reported IRRs and fundraising 35

36. Theory and Hypotheses Data Econometric Tests Policy Implications Correlations: Overstatement of Unexited IRRs and Fundraising 36

37. Theory and Hypotheses Data Econometric Tests Policy Implications Graphical Illustration of these Results (2 plots in next 2 slides) Cumming and Walz 2013 Journal of International Business Studies 37

38. Better Legal Conditions are Associated with Higher Fully Realized IRRs 38

39. Worse Legal Conditions are Associated with Higher Reported Unrealized (Unexited) Returns 39

40. Theory and Hypotheses Data Econometric Tests Policy Implications Policy Implications 40

41. Theory and Hypotheses Data Econometric Tests Policy Implications Measuring VC Returns • Heckman selection effects are crucial • Misspecification of model without selection effects • Multidimensional selection effects are a useful new component introduced in this paper • VC value-added is crucial • E.g., portfolio size / manager • Enables us to explain up to 36% of the variation in returns • Legality is crucial for cross-country differences 41

42. Theory and Hypotheses Data Econometric Tests Policy Implications Unexited IRRs Reported to Institutional Investors • Findings are quite consistent with the proposition that more informational asymmetry is associated with more ‘lying’! • for smaller ENTs, tech companies, higher earnings aggressiveness index, lower disclosure index • Positive correlation between fundraising and lying 42