Strategic IPO underpricing, information momentum, and lockup ...

More documents

Recommendations

Info

y estimating a Heckman two-stage model. The first stage is designed to explain why First Call has no research coverage for some firms (i.e., why the data are missing). It is estimated as a probit model with the dependent variable, FirstCall, equal to one if the firm is ever mentioned on First Call from the time of the IPO through one month following the lockup expiration and zero otherwise. The second stage examines the impact of underpricing on the level of research coverage, controlling for firm-specific characteristics. We measure the dependent variable, Research, in three ways. First, we define Research as the total number of mentions of the stock on First Call from the IPO through one month after the lockup expiration date. Second, we define Research as the number of recommendations made by non-lead underwriter analysts from the time of the IPO through one month following the lockup expiration. Third, we define Research as the number of recommendations made by lead underwriter analysts from the time of the IPO through one month following the lockup expiration. The estimation takes the form: Stage 1: FirstCall = α + β 1 log(MktCap) + β 2 LUR + β 3 Internet + β 4 VC + β 5 3MoRet + µ t + e; (15) Stage 2: Research = α + β 1 log(MktCap) + β 2 LUR + β 3 Internet + β 4 Turnover + β 5 Co-Mgrs + β 6 UP + β 7 UP 2 + β 8 Lambda + e. (16) In the first stage, the independent variables are: the log of the firm’s market value of equity measured four weeks following the IPO in millions (Log(MktCap)), the lead underwriter rank (LUR), the three-month buy-and-hold raw return beginning on the day following the IPO (3MoRet), indicator variables for venture capital backed (VC) and internet firms, and calendar year indicators (µ t ). In the second stage, we include a variable for the average amount of trading volume in the first month as a percent of the shares offered (Turnover) to control for the possibility that greater volume leads to greater research coverage. We also control for the number of co-managers (Co- 23
Mgrs) at the IPO. We expect that there is more research coverage when there are more underwriters involved at the IPO. The independent variables of interest are the level of underpricing (UP) measured as the offer to open return and underpricing squared (UP 2 ). We include the squared term to test for concavity in the relationship between information momentum and underpricing, which we assumed in Section 2. We estimate the first stage using the full sample of 618 firms. The second-stage includes only the 519 firms with any level of research coverage on First Call. The results are in Table 5. Focusing on the second stage estimates, the first two columns show that the number of mentions by research analysts following the stock on First Call and the number of non-lead analyst recommendations are significantly related to the level of underpricing. However, the third column shows that the number of lead analyst recommendations is unrelated to the level of underpricing, suggesting that underpricing the IPO is not necessary to attract the attention of the lead underwriters’ analysts. This is consistent with the view that lead analyst recommendations are simply part of the service provided by the underwriter to firms going public. Another implication of the results in the third column is that lead underwriter analyst recommendations are not a mechanism through which information momentum operates. For the number of mentions on First Call and the number of non-lead recommendations, the relationship between underpricing and research coverage is concave, as evidenced by the positive and significant coefficient on underpricing and the negative and significant coefficient on underpricing squared. This is consistent with the assumed concavity of the momentum generating function from the model. For non-lead analyst recommendations, greater underpricing (up to 852%) leads to greater research coverage. The number of non-lead analyst recommendations is maximized at underpricing of 426%. In our sample, the average level of underpricing is 50%. Underpricing an IPO by 50% yields an additional 1.44 (= 0.0307*50 – 0.000036*50 2 ) non-lead 24
Page 1 and 2: Journal of Financial Economics 00 (
Page 3 and 4: We argue that substantial underpric
Page 5 and 6: analysts providing earnings estimat
Page 7 and 8: epresents the momentum effect. Mome
Page 9 and 10: max ( A + g( ∆P) − k( Q0 + Q2))
Page 11 and 12: The key implication of the Proposit
Page 13 and 14: There are several additional points
Page 15 and 16: the owner-manager for underpricing
Page 17 and 18: number of recommendations made spec
Page 19 and 20: The median firm in both subsamples
Page 21 and 22: III. Increased research coverage le
Page 23: IPOs (51) are defined as having und
Page 27 and 28: We also control for the level of un
Page 29 and 30: The final implication of the model
Page 31 and 32: Our empirical results are that mana
Page 33 and 34: References Beatty, R.P., Welch, I.,
Page 35 and 36: Price D 2 g(P 1 - P 0 ) Underpricin
Page 37 and 38: Table 1 Sample statistics, internet
Page 39 and 40: Table 3 OLS regressions of IPO unde
Page 41 and 42: Table 5 IPO research coverage using
Page 43 and 44: Table 7 Robustness of IPO research

Strategic IPO underpricing, information momentum, and lockup ...

Create successful ePaper yourself

Delete template?

Save as template?