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# IPO performance and earnings expectations: some French evidence

IPO performance and earnings expectations: some French evidence

## Table 4 Forecast errors:

Table 4 Forecast errors: descriptive statistics Panel A: Earnings forecasts come from pre-IPO prospectuses. Actual earnings per share are taken from the I/B/E/S consensus database. Prospectus Forecast Errors (PFE) are calculated using the following formula: PFE = (actual EPS – Prospectus EPS forecast) / IPO price Panels B and C: Earnings forecasts come the I/B/E/S analyst-by-analyst historical earnings estimate database. In Panel B, for each IPO firm, we take every analyst’s first earning forecast issued before the offering or within the 12month subsequent period if no earnings announcement has taken place between the IPO and the forecast. For both panels, actual earnings per share are taken from the I/B/E/S consensus database. Analyst Forecast Errors (AFE) are calculated using the following formula: AFE = (actual EPS – analyst EPS forecast) / Stock price at forecast date In the “All observations” tables, all observations are given the same weight. In the “By firm” tables, each firm is assigned one AFE value by firm / period, equal to the mean of analyst-by-analyst individual AFEs. In all panels, year 1 (and respectively, year 2, year 3), is the next (and respectively, second next, third next) fiscal year for which earnings per share are announced. * (and, respectively, **, ***) indicates that the coefficient is significantly different from 0 at a 10% (and, respectively, 5%, 1%) level. Panel A: IPO firms – Prospectus Forecast Errors (PFE) All years 1 st fiscal year following IPO 34 Year for which forecast is made 2 nd fiscal year following IPO 3 rd fiscal year following IPO # of forecasts 286 137 105 44 Average forecast error -0.0208*** -0.0036 -0.0254** -0.0630*** Median forecast error -0.0109 -0.0028 -0.0191 -0.0298 Panel B: IPO firms – Analyst Forecast Errors (AFE) All observations All years 1 st fiscal year following IPO Year for which forecast is made 2 nd fiscal year following IPO 3 rd fiscal year following IPO # of forecasts 2130 945 802 383 Average forecast error -0.0163*** -0.0053*** -0.0227*** -0.0299*** Median forecast error -0.0009 0.0000 -0.0037 -0.0068 By firm # of forecasts 432 185 156 91 Average forecast error -0.0236*** -0.0080*** -0.0312*** -0.0424*** Median forecast error -0.0060 -0.0007 -0.0119 -0.0187 Panel C: Non-IPO firms – Analyst Forecast Errors (AFE) All observations All years 1 st fiscal year following IPO Year for which forecast is made 2 nd fiscal year following IPO 3 rd fiscal year following IPO # of forecasts 266,622 129,649 110,360 26,613 Average forecast error -0.0191*** -0.0135*** -0.0255*** -0.0201*** Median forecast error -0.0038 -0.0018 -0.0072 -0.0091 By firm # of forecasts 1744 734 597 413 Average forecast error -0.0212*** -0.0132*** -0.0281*** -0.0255*** Median forecast error -0.0084 -0.0042 -0.0139 -0.0135

Table 5 The determinants of Analyst Optimism Analyst Forecast Errors (AFE), are calculated using the following formula: AFE = (actual EPS – analyst EPS forecast) / Stock price at forecast date where analyst EPS forecasts come from the I/B/E/S analyst-by-analyst historical earnings estimate database and actual EPS come from the I/B/E/S consensus database. For each IPO firm, we take every analyst’s first earning forecast issued before the offering or within the 12-month subsequent period if no earnings announcement has taken place between the IPO and the forecast. For non-IPO firms, we take all analyst forecasts that were issued in the 1991-1998 period. For both samples, we calculate “by-firm” AFE, i.e. for every firm and every forecast period, we take the average of the forecasts issued by the analysts following the firm. Panel A: IPO firms vs. non-IPO firms The equation we estimate in the regression is given by the following formula: AFE = α+β1*ipo+β2*value+β3*log(market capitalization)+ β4*number of month+ε Ipo is a dummy variable equal to 1 for IPO firms, 0 for non-IPO firms. Value is equal to the average of EPS forecasts for the firm / period, in French Francs. Number of months is equal to the average number of months between the date of the forecasts and the EPS announcement plus one month. There are 2,121 observations. Panel B: IPO firms only The dependent variables are prospectus forecast errors (PFE) and analyst forecast errors (AFE) in columns 1 and 2 respectively. Log(market capitalization), Value and Number of months are the same variables as in Panel A. OPM (resp. PG) is a dummy variable equal to 1 when the IPO used the OPM (resp. PG) procedure. Book-to-market is the book-to-market value of the company as at IPO date. Age is the age of the company, in years, as at IPO date. Exchange is a dummy variable equal to 1 for firms going public on the Second Marché, 0 for IPOs on the Nouveau Marché. Underpricing/conditions is constructed using the Initial return (10-day underpricing) and Market conditions variables used in the previous tables. Both variables are divided into quartiles, and Underpricing/conditions is equal, for a given IPO, to its Initial return (10-day underpricing) quartile minus its Market conditions quartile. Thus, Underpricing/conditions reflects the initial aftermarket performance of the offering relative to the market conditions prevailing at IPO date. White-consistent t-statistics are in parentheses. * (and, respectively, **, ***) indicates that the coefficient is significantly different from 0 at a 10% (and, respectively, 5%, 1%) level. Panel A: IPO firms vs. non-IPO firms (dependent variable : Analyst Forecast Error) IPO 0.0039 (1.326) Value 0.0000 (0.001) Log(market capitalization) 0.0066*** (4.144) Number of months -0.0013*** (-5.393) Constant term -0.0377*** (-3.435) R square 0.0162 35

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