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5 years ago

IPO performance and earnings expectations: some French evidence

IPO performance and earnings expectations: some French evidence

few years after their

few years after their creation, but this is a new phenomenon. It might be that young companies going public still suffer from old investor prejudices. In such a case, they would be priced at a discount in the IPO, and we would expect their long-run performance to be abnormally positive: the coefficient on age would be negative. Alternatively, the recent wave of startup IPOs may be the product of investor infatuation. In such a case, they would have been priced at a premium at the IPO, and their subsequent performance should have been disappointing. We would then expect the coefficient on age to be positive. � % of shares created is equal to the ratio of shares created at the date of the IPO to the total number of shares issued. If companies waste the proceeds of the sale of new shares in a manner not anticipated by investors, we would expect a negative coefficient on this variable. � Reasons for IPO: IPO prospectuses often mention reasons for going public, such as a planned acquisition, repayment of debt, or a shareholder's wish to sell out. Unwarranted investor enthusiasm (or skepticism) for such motives would result in a negative (positive) coefficient on such variables. � Book-to-market and size: we introduced these as control variables. Based on previous studies (Brav and Gompers (1997)), we would expect the coefficient on book-to-market to be positive, and the coefficient on size to be positive. � long-term debt: if debt improves managerial incentives, we would expect a positive coefficient on this variable. � Ownership structure (k-ventur, k-bank and k-perso): Brav and Gompers (1997) find a positive coefficient on a venture capitalist variable. � Stock exchange (Nouveau Marché, NM, or Second Marché, SM): we have no prior hypothesis on what coefficients to expect on these variables. performance results we present use the whole sample of IPOs for months 1 to 29 only. 12

� Underpricing/conditions: this variable is constructed using the Initial return (10-day underpricing) and Market conditions variables defined previously. Both variables are divided into quartiles, and Underpricing/conditions is equal, for a given IPO, to its 10-day initial return quartile minus its Market conditions quartile. Thus, we consider initial returns not in absolute terms but relative to the market conditions prevailing at IPO date. This allows us to take into account the fact that initial returns are highly linked to market conditions. � IPO procedure (book-building, PG, or auction, OPM): it is sometimes argued that the book building procedure gives investment bankers the incentives and the means to lower the IPO price. Book building IPOs should then subsequently outperform others. � Underwriter rank: first-tier underwriters may have a stronger incentive to maintain a reputation with investors than second-tier firms 7 . Their pricing should be more conservative, and investors should expect fewer disappointments. We would expect a negative coefficient on underwriter rank. Table 3 reports our regression results. Our dependent variable is IPO adjusted performance, computed as CARs, using comparison portfolios as the benchmark 8 . We report the results for 6, 12, 18, 24, 30 and 36-month performances. Overall, no ex ante factor seems to have been clearly over- or underpriced in our sample. However, a few variables exhibit significant coefficients. Bank-backed IPO firms have statistically and economically good performance between 6 and 30 months following their offerings. On the other hand, and surprisingly, venture-backed IPOs do not perform better (and even perform worse at some horizons) than average. In line with our hypothesis, the Underpricing/conditions variable has a positive impact on performance up to 24 months after the 7 Booth and Smith (1986) also suggest that choosing a high-quality underwriter can be a way for a firm conducting an IPO to guarantee its quality to potential investors, where quality can be defined as the fairness of its pricing. 8 We choose this method of calculation because previous articles (for instance Brav and Gompers (1997)) suggest that it is the most robust. Moreover, our previous results suggest that this measure is a mid-term between other more extreme measures. However, we ran the same regressions with those other measures, which did not change the results qualitatively. 13

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