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Style Drift

Style Drift. Cumming & Johan (2013, Chapter 7). 1. Introduction Theory Data Tests Conclusion. M otivation (1 / 2). Funds have stated objectives Private Equity (PE) memoranda include covenants and investment specifications

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Style Drift

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  1. Style Drift Cumming & Johan (2013, Chapter 7) 1

  2. Introduction Theory Data Tests Conclusion Motivation (1 / 2) • Funds have stated objectives • Private Equity (PE) memoranda include covenants and investment specifications • Definition of “Style” for PE: the VC fund’s stated investment focus on stage of entrepreneurial development at the time of investment (active style drift) • “Style Investing”: institutional investors increasingly categorize their investments in asset classes (Wermers, 2002, Brown and Harlow, 2004, Barberis and Shleifer, 2003, and Chan, Chen and Lakonishok, 2002 ) • Benefits: simplifies processing of information, increases control of overall risk for institutional investors, better assessment of portfolio managers’ performance • Style drift may potentially make private equity less attractive as it makes it more difficult for LPs to manage their risk/return profile. 2

  3. Introduction Theory Data Tests Conclusion Motivation (2 / 2) • Also other fund providers (banks, corporations) often have a preference for a specific stage. • Some have looked at drifts by mutual funds. However, there are important differences with private equity on that topic. • Little is known about style drift in Private Equity • Potential benefits/costs for the GP: • increased pool of projects, greater diversification, potentially quicker exit, managerial hybris (Shephard-Zacharis-Baron, 2003) … • potential litigation for breach of LP contract, reputational costs, changed risk-return profile 3

  4. Intermediation Implies Concern with Style Drift Pension Plan Members (you and I) • Different Types: • Pension • Insurance • Bank • And Different • Countries Institutional Investor 2 Institutional Investor 1 Regulated (FTK, IFRS, BASEL II) (helps different types & from different regions) Returns Fundraising Venture Capital Funds Scantly Regulated: Can market fund one way at time of fundraising then invest differently over fund 10 year life Supply of Investments Demand for Investments Entrepreneurial Firms 4

  5. Introduction Theory Data Tests Conclusion Objectives => Focus will be on VC manager’s trade-off for drifting, and not directly the effect on LPs risk/return. • How important is style drift in private equity? • Which VCs are more likely to style drift? How is it affected by VC fund characteristics, especially by how well established the VC firm is? • What is the impact on performance (from VC fund perspective)? 5

  6. Introduction Theory Data Tests Conclusion Main Results • Style drifts in Private Equity are extremely common • in 30%-50% of investments in our sample, depending on definition of style drift • Suggesting potentially significant benefits associated with style drift for VC managers (e.g. managerial hubris, diversification, better investments) • Style drifts are less common by less established VC firms • Style drifting is more likely once follow-up fund is secured • Market conditions have an important impact • The effect on performance is positive (measured as Prob(IPO)) 6

  7. Introduction Theory Data Tests Conclusion Related Literature • Recent studies on Style Investing (Wermers, 2002, Brown and Harlow, 2004, Barberis and Shleifer, 2003, and Chan, Chen and Lakonishok, 2002) • VC Partnership agreements (Lerner-Schoar, 2002, Gompers-Lerner, 1996, Ljungqvist-Richardson, 2003) • Grandstanding (Gompers, 1996) • Fund-raising (Gompers-Lerner, 1998, Kaplan-Schoar, 2003) • Importance of reputation-building (Barry et al., 1990, Megginson-Weiss, 1991, Neus-Walz, 2004, and many others) 7

  8. Introduction Theory Data Tests Conclusion A Theory of Signaling (1 / 3) • Consider a simple “two-fund” model (as Lerner and Schoar, 2002) • Opportunities: 2 pools of projects, both with good and bad projects • Fund Providers: Preference for Pool 1, o/w discount  • Venture Capitalists: • Raise two funds • Fund size I > 0 enough for 1 project • Managerial hubris: benefits  > 0 from investing in a good project in pool 2 • Compensation: fraction  of total fund profits • 50% of VCs are good (skilled), 50% bad (less skilled) • Good VCs are better are identifying good projects in Pool 1 8

  9. Introduction Theory Data Tests Conclusion A Theory of Signaling (2 / 3) • If no good project: “next best” one is in pool 1 with NPV = 0 • Time line: • t = 0: VCs raise their first fund VCs screen projects, then invest in one project • t = 1/2: VCs raise their second fund VCs screen projects, then invest in one project • t = 1: VCs divest the companies from their first fund • t = 3/2: VCs divest the companies from their second fund 9

  10. Introduction Theory Data Tests Conclusion A Theory of Signaling (3 / 3) • Then, skilled VCs may choose to prefer pool 1 project (provided they have the choice) if it improves their signal to fund providers • Fund providers then offer better conditions in 2nd fund to VCs who did not drift in their first fund • Gains from not drifting: getting better terms in the second fund (worth less to bad VCs, given difference in skills) • Costs from not drifting: losing benefits in the first fund • Main Empirical Prediction: “Younger VC firms style drift less often, since good VCs want to signal their screening skills to fund providers.” • We also control for changes in market conditions between the time funds are raised and funds are invested. 10

  11. Introduction Theory Data Tests Conclusion An Alternative Explanation • Learning Story: • Younger VCs are less capable in identifying valuable projects outside their (narrow) area of expertise. • This limits VCs in their first fund to style drift. • In empirical analysis (robustness), we include a control variable that aims at distinguishing between both rationales. 11

  12. Introduction Theory Data Tests Conclusion Changes in Market Conditions • Investment opportunities may have changed between the time the fund was raised and the time the money is invested. • This may also lead to style drift. • Assumption: improvements in market conditions leads to a greater increase in ES investment profits than LS investment profits. • Based on earlier work we have done. • Then, improvements in market conditions make style drifts by ES funds less likely. • LS funds may also drift less but may at the same time be tempted to drift more (if ES investments become particularly more attractive). 12

  13. Introduction Theory Data Tests Conclusion Data • Our analysis is on active style drift (Wermer, 2002) • Deal initiation only (first-round investments) • Drift dimension: stage of development • Data: • US VC-backed companies from Venture Economics Database • Investment by non-generalist funds • Period 1/1/1985 to 12/31/2003 • Total: 11,871 first-round investments by independent VC firms • Measures of Style Drift: • Stage Drift: dummy variable equal to 1 if the VC fund did not invest in the committed stage of development • Large Stage Drift: dummy variable equal to 1 if the VC fund drifted more than one stage of development 13

  14. Introduction Theory Data Tests Conclusion Definition of Variables • VC Fund / Firm Characteristics: • Fund Age • Fund Size • (*) Fund Sequence • (*) Firm Age • (*) New Fund Raised • Investment / Company Characteristics: • Amount of Investment (million US$) • Company Age • Industry Dummies • Market Conditions: • Bubble Dummy, log(NASDAQ) • % NASDAQ Change • 0 • 1 Fund 1 Fund 2 14

  15. Introduction Theory Data Tests Conclusion Descriptive Statistics: Table 7.2 • Up drifts: 14.9 % • No drifts: 41.3 % • Down drifts: 43.9 % 15

  16. Introduction Theory Data Tests Conclusion Summary Statistics • Overall, 56% of all investments are style drifts, 32% are large style drifts. • Drifts occurs less often in “good times” than in other times (29% versus 36% for bubble period). • Drifts are more likely in more mature portfolio companies (5.1 for drifts versus 2.7 years for no drifts). • Drifts are more often done by older VC funds (3.6 versus 2.8 years) and older and larger VC firms (11.4 versus 10.4 years). • There is no difference between US funds and non-US funds. 16

  17. Introduction Theory Data Tests Conclusion Multivariate Analysis • Effect of VC Firm Experience/Age on Style Drift • Effect of Style Drifts on Performance 17

  18. Introduction Theory Data Tests Conclusion Table 7.5. Dependent Variable: Stage Drift Also included in all the regressions: stage dummies, industry dummies, investment size, and company age. 18

  19. Introduction Theory Data Tests Conclusion Table 7.5 (Continued) Dependent Variable: Stage Drift Also included in all the regressions: stage dummies, industry dummies, investment size, and company age. 19

  20. Introduction Theory Data Tests Conclusion Table 7.6. Dependent Variable: Large Stage Drift Also included in all the regressions: stage dummies, industry dummies, investment size, and company age. 20

  21. Introduction Theory Data Tests Conclusion Table 7.6. (Continued) Dependent Variable: Large Stage Drift Also included in all the regressions: stage dummies, industry dummies, investment size, and company age. 21

  22. Introduction Theory Data Tests Conclusion Effect on Style Drift: Summary • Less established VC firms drift less (5 years difference => 1% increase). • VC funds drift more often after having secured follow-up funds, which is in line with the signaling story (3% increase). • Market conditions are an important reason (20% increase in Nasdaq => 4% reduction by ES funds, 5% increase by non-ES funds). • Given the simultaneous effect of both types of funds, the overall impact on the provision of ES capital is large. • While investment amount generally is not significant, company age has a significantly positive coefficient. 22

  23. Introduction Theory Data Tests Conclusion Table 7.7: Performance Implications 23

  24. Introduction Theory Data Tests Conclusion Effect on Performance: Summary • Fund Stage Drift is positively related to the probability of an IPO, but not Fund Large Stage Drift. • Fund Stage Drift leads to a 4% increase in IPO probability. • It suggests that style drift is associated with higher returns and (in our sample) higher risk. • It also suggests that, due to potential reputation costs, style drifts are more common for investments that are more likely to yield favorable realizations. 24

  25. Introduction Theory Data Tests Conclusion Concluding Remarks • Main Research Question Addressed: • How important is style drift in private equity? • Do younger VC firms style drift less than more established firms? • Results seems in line with the signaling story • Changes in market conditions are an important reason for drifting • There is still much to be explained, e.g. regarding other dimensions (industry, geography), VC firm types, drifts in follow-up rounds … => More theory is needed!! • Another important question is about the ultimate effect on LPs. 25

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