Investment-Based Underperformance Following Seasoned Equity Offering Evgeny Lyandres Rice University Le Sun University of Rochester Lu Zhang University of Rochester and NBER University of Texas at Austin December 9, 2005
Theme Optimal investment is an important driving force of the SEO underperformance Outline Question The investment hypothesis Tests Exploring alternative hypotheses 1
Question Seasoned-equity issuers underperform matching nonissuers in the long run Existing explanations References Underreaction to market timing Ritter (1991), Loughran and Ritter (1995), Spiess and Affleck Graves (1995), Baker and Wurgler (2000), Ritter (2003) Underreaction to overinvestment Titman, Wei, and Xie (2004), Richardson and Sloan (2003) Leverage Eckbo, Masulis, and Norli (2000) Liquidity Eckbo, Masulis, and Norli (2000), Eckbo and Norli (2005) Pervasive return pattern Brav and Gompers (1997), (small growth) Brav, Geczy, and Gompers (2000) 2
The Investment Hypothesis Issuers should earn lower expected returns than matching nonissuers Expected return Zhang (2005, Anomalies ) Low investment-to-asset firms Nonissuing firms High payout firms 0 High investment-to-asset firms Issuing firms Low payout firms Investment-to-asset 3
Covariances vs. Characteristics Only covariances matter in rational markets. Barberis and Thaler (2003) Surprise! Characteristics are sufficient statistics of expected returns Risk Expected returns Characteristics r ft + β Mt λ Mt = E t [r S t+1] = E t [r I t+1] Consumption-based asset pricing Investment-based asset pricing β Mt = E t[r I t+1] r ft λ Mt = 1 λ Mt [ Et [Π 1 (K t+1,x t+1 )] + 1 δ 1+a(I t /K t ) r ft ] 4
Tests How much of the SEO underperformance can the investment hypothesis explain? A return factor based on capital investment Augmented factor regressions Do issuers invest more than matching nonissuers? Simple, descriptive tests in calendar time and in event time 5
Data SEOs from SDC, stock returns from CRSP, accounting variables from Compustat Standard sample selection criteria Brav, Geczy, and Gompers (2000); Eckbo, Masulis, and Norli (2000) Sample period from 1970 to 2003, 11,092 SEOs, 8,126 with stock return data 6
The Investment Factor Investment-to-asset = annual change in PPE/lagged book assets A triple 3 3 3 sort on size, book-to-market, and investment-to-asset INV = the average low-minus-high investment-to-asset portfolio Captures cross-sectional variations independent of other common factors ι CAPM Fama French Carhart Eckbo Masulis Norli Intercept 0.37 0.40 0.27 0.18 0.28 (4.35) (4.88) (3.33) (2.21) (3.06) R 2 1.09% 12.44% 16.87% 8.89% 7
Factor Regressions Adding the investment factor into standard factor models makes SEO underperformance largely insignificant and reduces its magnitude by about 40% Prior 36-month SEO portfolios Equally weighted returns Value weighted returns CAPM Fama French CAPM Fama French α 0.28 0.15 0.29 0.17 0.36 0.20 0.28 0.18 ( 1.91) ( 0.94) ( 2.89) ( 1.62) ( 3.56) ( 2.12) ( 2.92) ( 1.90) β INV 0.32 0.47 0.41 0.39 ( 2.51) ( 5.84) ( 5.36) ( 5.91) α / α 45.9% 43.0% 45.2% 36.8% Equally-weighted vs. value-weighted underperformance 8
Prior 60-month SEO portfolios Equally weighted returns Value weighted returns CAPM Fama French CAPM Fama French α 0.11 0.07 0.21 0.12 0.25 0.14 0.21 0.13 ( 0.79) ( 0.41) ( 2.29) ( 1.27) ( 2.84) ( 1.46) ( 2.56) ( 1.65) β INV 0.12 0.32 0.28 0.28 ( 0.96) ( 4.25) ( 4.30) ( 4.85) α / α 42.1% 41.4% 45.0% 36.1% 9
Issuer-Purged Factor Regressions Loughran and Ritter (2000): traditional factor models constructed in part with data on issuers have low power in detecting SEO underperformance Prior 36 month SEOs Prior 60 month SEOs Equally weighted Value weighted Equally weighted Value weighted α 0.39 0.25 0.33 0.26 0.28 0.17 0.23 0.18 ( 3.28) ( 2.11) ( 2.85) ( 2.26) ( 2.50) ( 1.50) ( 2.39) ( 1.89) β pinv 0.48 0.27 0.35 0.18 ( 5.54) ( 3.27) ( 4.24) ( 2.53) α / α 35.6% 23.4% 37.0% 22.6% pinv: average return 0.35% (t = 3.76); Corr(INV, pinv) = 90.3% 10
Capital investment is a priced risk factor in equilibrium: Q-theory: Cochrane (1991, 1996), Cooper (2005), Zhang (2005a, b), Belo (2005), Gomes, Yaron, and Zhang (2006). Real options theory: Berk, Green, and Naik (1999); Carlson, Fisher, and Giammarino (2004, 2005). General equilibrium: Gomes, Kogan, and Zhang (2003), Kogan (2004), Gala (2005) Factor regressions (purged size and value factors, unpurged investment factor) Prior 36 month SEOs Prior 60 month SEOs Equally weighted Value weighted Equally weighted Value weighted α 0.39 0.20 0.33 0.19 0.28 0.14 0.23 0.13 ( 3.28) ( 1.74) ( 2.85) ( 1.74) ( 2.50) ( 1.21) ( 2.39) ( 1.38) β pinv 0.62 0.47 0.45 0.34 ( 7.72) ( 6.47) ( 5.77) ( 5.39) α / α 48.9% 43.1% 50.4% 45.2% 11
Investment Issuers invest much more than nonissuers before and after equity issuance Do not include R&D; differing from Loughran and Ritter (1997) Empirical design: Matching each issuer with nonissuers based on size and book-to-market Event-time and calendar-time investment behavior of issuers and nonissuers Report the Z-statistics from the Wilcoxon matched-pair signed-rank tests 12
Investment-to-asset and profitability in the fiscal yearend before SEOs, 1970 2003 Investment to asset Profitability non non issuers issuers Z issuers issuers Z 0.090 0.054 36.09 0.129 0.128 1.96 Issuers persistently invest more than nonissuers after SEOs Investment/asset Z 0.10 40 0.09 35 Investment-to-Assets 0.08 0.07 0.06 0.05 0.04 0.03 0.02 Z(Investment-to-Assets) 30 25 20 15 10 0.01 5 0.00 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 Post-even month 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 Post-event month 13
Frequency distribution of SEO firms across investment-to-asset deciles 1600 1400 1200 Number of SEOs 1000 800 600 400 200 0 1 2 3 4 5 6 7 8 9 10 Investment-to-Assets Deciles 14
The Overinvestment Hypothesis The negative investment-return relation should be stronger among firms more vulnerable to empire-building (weaker shareholder rights/less entrenchment) Split the 1990 2003 sample on Gompers-Ishii-Metrick s (2003) Governance-index Strong shareholder rights (G 9) log(me) log(be/me) Investment/asset Weak shareholder rights (G 10) log(me) log(be/me) Investment/asset 1.31 0.79 ( 3.03) ( 2.83) 0.18 0.06 0.94 0.13 0.04 0.44 ( 1.90) ( 0.35) ( 2.41) ( 1.52) ( 0.26) ( 1.56) 15
Bebchuk, Cohen, and Ferrell (2005): the Entrenchment-index fully drives the relation between the G-index and firm value (and stock returns) Six provisions: (i) Staggered boards, (ii) limits to shareholder bylaw amendments, (iii, iv) supermajority requirements for mergers and for charter amendments, (v) poison pills, (vi) golden parachutes Split the 1991-2003 sample on Bebchuk-Cohen-Ferrell s (2005) E-index Low entrenchment (E 2) High entrenchment (E 3) log(me) log(be/me) Investment/asset log(me) log(be/me) Investment/asset 0.91 0.73 ( 2.32) ( 1.86) 0.19 0.15 0.60 0.15 0.12 0.20 ( 1.96) ( 0.85) ( 1.73) ( 1.68) (0.83) ( 0.55) 16
Issuers are less vulnerable to empire-building (stronger shareholder rights) Median G-Index Z, Median G-Index 9.2 9 0-1 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 8.8-2 Governance Index 8.6 8.4 8.2 8 7.8 7.6 Z(Governance Index) -3-4 -5-6 -7-8 7.4 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59-9 Post-event month Post-event month Mean G-Index t, Mean G-Index 9.8 9.6 0.0-0.5 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 9.4-1.0 Governance Index 9.2 9.0 8.8 8.6 t(governance Index) -1.5-2.0-2.5-3.0-3.5 8.4-4.0 8.2 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 Post-event month -4.5 Post-even month 17
Issuers are less vulnerable to empire-building (lower entrenchment index) Median E-Index Z, Median E-Index 2.5 0.0 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 2-1.0 Median E-Index 1.5 1 0.5 Z(E-Index) -2.0-3.0-4.0-5.0 0 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 Event-time -6.0 Event-time Mean E-Index t, Mean E-Index 2.4 2.4 0.0-0.5 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 2.3-1.0 Mean E-Index 2.3 2.2 2.2 t(e-index) -1.5-2.0-2.5 2.1-3.0 2.1 2.0 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 Event-time -3.5-4.0-4.5 Event-time 18
The Leverage Hypothesis Issuers have lower loadings on macro risk factors because new equity lowers their leverage ratios, and hence equity risk and expected returns Contradicts underperformance following debt offerings Issuers should have lower leverage ratios than matching issuers Market and book leverage ratios in the fiscal yearend following SEOs, 1970 2003 Market leverage Book leverage non non issuers issuers Z issuers issuers Z 0.220 0.193 16.96 0.358 0.208 38.89 19
Issuers have persistently higher leverage ratios than nonissuers after SEOs Market Leverage Z, Market Leverage 0.30 45 0.25 40 35 Market Leverage 0.20 0.15 0.10 Z(Market Leverage) 30 25 20 15 0.05 10 5 0.00 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 Post-event month 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 Post-event month Book Leverage Z, Book Leverage 0.40 45 0.35 40 0.30 35 Book Leverage 0.25 0.20 0.15 Z(Book Leverage) 30 25 20 15 0.10 10 0.05 5 0.00 1 3 5 7 9 11131517192123252729313335373941434547495153555759 Post-event month 0 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 Post-event month 20
Pervasive Return Pattern Small-growth firms issue more seasoned equity Number of SEOs by ME and BE/ME Quintiles New Equity-to-Asset by ME and BE/ME Quintiles Issue Rate Number of SEOs 900 800 700 600 500 400 300 200 1.20 1.00 0.80 0.60 0.40 0.20 100 0 5 4 ME 3 2 1 5 4 3 2 1 BE/ME 0.00 5 4 ME 3 2 1 5 4 3 2 1 BE/ME 21
Small-growth firms also invest more Investment-to-Asset by ME and BE/ME Quintiles 0.450 0.400 0.350 0.300 0.250 0.200 I/K 0.150 0.100 0.050 0.000 5 1 4 2 ME 3 3 BM 2 4 1 5 Controlling for real investment reduces the magnitude of the small-growth anomaly, see Anderson and Garcia-Feijóo (2005) and Xing (2005) 22
Contribution Adding the investment factor into standard factor models makes the underperformance largely insignificant and reduces its magnitude by around 40% Evidence is suggestive of the role of optimal investment Evidence supporting the pervasive-return-pattern explanation Evidence inconsistent with the leverage explanation 23
Future Investment policy should be a first-order determinant of expected returns Testing the investment hypothesis for other external financing anomalies: Underperformance following debt offerings (in progress) Underperformance following initial public offerings Underperformance following private placements of equity Underperformance following loan announcements Positive long-term stock price drift following open market share repurchases Long-term stock price drift following dividend initiations/omissions 24