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Market Reactions to Quarterly Earnings Surprises: The Impact of Market Reactions to Quarterly Earnings Surprises: The Impact of Document Transcript

  • Market Reactions to Quarterly Earnings Surprises: The Impact of Financial Statements’ Data Disclosed with Earnings Eli Amir London Business School Sussex Place, Regent’s Park London NW1 4SA United Kingdom Tel: +44 (0)20 7000 7000 (ext. 3182) eamir@london.edu And Joshua Livnat Department of Accounting Leonard N. Stern School of Business New York University 40 W. 4th St. NY, NY 10012 (212) 998 – 0022 jlivnat@stern.nyu.edu Current Draft: August 2006 The authors gratefully acknowledge Charter Oak Investment Systems Inc. for providing the preliminary and original Compustat quarterly data used in this study. The authors also gratefully acknowledge Standard and Poors’ Compustat for providing the SEC filing dates data. We thank seminar participants at Tel Aviv University for comments and suggestions.
  • Market Reactions to Quarterly Earnings Surprises: The Impact of Financial Statements’ Data Disclosed with Earnings Abstract This study focuses on market reactions to earnings and other financial statement information that is concurrently disclosed in preliminary earnings press releases. We use a large sample of heterogeneous companies and investigate whether market reactions to earnings surprises vary systematically with the amount of financial statement detail that is included in earnings press releases, after controlling for the timing of announcements and factors related to firms’ information environments. We observe a dramatic increase in the amount of detail disclosed concurrently with quarterly earnings in the years following Regulation Fair Disclosure. We find that level of financial statement detail is positively associated with the magnitude of the earnings surprise (and more so for negative surprises), firm size, volume of trade, likelihood of raising new capital and analysts' coverage. Conversely, it is negatively associated with the timing of press releases. Turning to the market-based analysis, we find that absolute abnormal returns are higher the more detail is disclosed in the preliminary earnings release, and that the level of detail is more strongly associated with unexpected returns when earnings surprises are extreme. We also find that market reactions to earnings surprises decline over time, but increase with the level of financial statement detail in preliminary earnings releases. However, the importance of detail to the interpretation of extreme earnings surprises has declined over time.
  • Market Reactions to Quarterly Earnings Surprises: The Impact of Financial Statements’ Data Disclosed with Earnings 1. Introduction Since Ball and Brown (1968), Beaver (1968) and as reviewed by Lev (1989) and Kothari (2001), numerous studies have consistently documented a positive and statistically significant association between excess stock returns and unexpected earnings during the short windows around preliminary earnings press releases.1 These findings imply that market participants obtain, process, and react to new earnings information, setting security prices according to the earnings news. Still, there has been some concern about the role of earnings news in explaining the total variability of stock prices around preliminary earnings announcements (Lev, 1989), and the potential deterioration over the years in the association between earnings news and short- window returns around them (Collins et al., 1997; Francis and Schipper, 1999; Lev and Zarowin, 1999). Preliminary earnings press releases often convey additional information beyond earnings, including other financial statements’ data that may be value-relevant for market participants (Chen et al., 2002). Because preliminary earnings press releases are not mandatory, companies select the level of detail they wish to disclose concurrently with preliminary earnings. There exists considerable variation in level of detail across preliminary earnings press releases. Some of these voluntary additional data are in fact used by market participants to set prices, incrementally to the effects of the earnings news. For example, Ertimur et al. (2003) provide evidence that investors react and properly utilize revenue data that are contained in preliminary 1 Most studies used excess stock return and signed unexpected earnings as dependent and independent variables, respectively. Beaver (1968), on the other hand, was the first study to include absolute excess returns and volume of trade as dependent variables and absolute unexpected earnings as independent variables.
  • earnings announcements. Many companies now include detailed income statements, some include condensed balance sheets (or balance sheet line items), and far fewer include any cash flow line items in their earnings press releases2. In a recent study, Francis et al. (2002) randomly selected 30 companies and examined 2,190 earnings press releases over the period 1980-1999. They provide evidence that the amount of information in press releases (including additional financial statement data) has increased significantly over time and show that the increased market reaction to earnings press releases over time is associated with the increase in the amount of information in these disclosures. Lo and Lys (2001) argue that the disclosure of concurrent information in earnings press releases may explain the disparity between an increased information content of earnings announcements and the decrease in the value-relevance of earnings per se; while the increase in concurrent information causes stronger market reactions around the preliminary earnings press releases over time. The reaction to the earnings signal alone in fact declines over time. Until recently it was prohibitively costly to examine the effect of concurrent disclosures on the market reactions to preliminary earnings press releases using large samples, because data from press releases had to be manually collected, read and coded. This is why the results in Francis et al. (2002) are obtained using a small sample of 30 companies randomly selected from their sample of large and stable 426 companies with complete quarterly financial data over 20 years. In contrast, our study employs the preliminary earnings database available from Compustat and Charter Oak through WRDS, together with the SEC filing dates supplied to us by Compustat. These databases allow an investigation of earnings and concurrent information 2 At the time of this draft, IBM preliminary earnings releases contain income statement and balance sheet information, but not cash flow data. See, e.g., IBM’s 2007 Q1’s release on April 17, 2007 at: http://www.ibm.com/investor/1q07/1q07earnings.phtml 2
  • disclosed during preliminary press releases using a very large sample of heterogeneous companies with substantially different information environments. The purpose of our study is to examine (i) whether market reactions to earnings are affected by other financial statements information concurrently disclosed in preliminary earnings announcements; (ii) whether the trend of stronger market reactions to earnings information over time is associated with the increasing level of other financial statement detail in preliminary earnings announcements; and (iii) whether the information environment plays a role in the level of detail provided in preliminary earnings releases, and if so, whether market reactions to preliminary earnings announcements are affected by the level of other financial statement detail in preliminary earnings announcements after controlling for the differential effects of the information environment. As we explore the association between earnings news, level of detail in preliminary earnings announcements and market reactions, we also control for the timing of the earnings press release relative to the quarter-end, a factor omitted by Francis et al. (2002), likely because of their small sample. As Chambers and Penman (1984) and Kross and Schroeder (1984) show, firms with good (unfavorable) earnings news tend to report earlier (later) than their expected reporting dates, with market reactions that are in the same direction as the prompt (delayed) reporting. As we show below, large companies tend to issue preliminary earnings announcements earlier than small companies, and their announcements usually contain more financial statement detail than those of small companies. Thus, with the large sample available to us, we can adequately control for the timing of the earnings release as well as for cross sectional differences in firms’ information environment and their effects on the association between detail level and market reactions. 3
  • The contribution of this study to the literature is along several dimensions. First, it sheds additional light on the voluntary activity of preliminary earnings announcements, and more specifically on the level of financial statement detail firms choose to include along earnings in these announcements. Second, it explains the cross-sectional variation in the amount of financial statement detail concurrently disclosed with quarterly earnings. Third, it examines whether market reactions to the preliminary earnings releases are sensitive to the level of detail for a large sample of firms and for different sub-samples depending on the information environment of firms. Fourth, it controls for the interaction between the timing of the preliminary earnings announcements and the level of financial statement detail in measuring market reactions to the announcements. Finally, it provides additional evidence about the role that financial statement detail in preliminary earnings announcements plays in explaining the trend of increasing market reactions to earnings announcements over time. To facilitate the empirical testing, we design and implement three scoring mechanisms that measure the amount of financial detail in earnings press releases. The first is based on a simple tally of the items included in our analysis from the income statement, balance sheet and the statement of cash flows. The second subjectively assigns weights to each financial statement item based on the relative importance of the item as depicted by prior studies. The third is based on “market” weights, which are obtained by regressing the market reaction to earnings on earnings surprises and an indicator variable that represents whether the financial statement data item was included in the preliminary earnings announcement. We show that the amount of financial detail in press releases has increased dramatically following Regulation Fair Disclosure in late 2000. 4
  • We find that the level of detail score is positively associated with positive earnings surprises, but significantly more so with negative earnings surprises. This result suggests that the likelihood of more disclosure is higher when earnings news is bad, consistent with the argument that companies increase disclosure to reduce litigation costs.3 We also find that the level of financial statement detail is positively associated with firm size, earnings volatility, volume of trade, the likelihood of raising new capital and analysts' coverage, and negatively associated with the timing of the press release. Turning to the market-based analysis, we show that, consistent with Francis et al. (2002), market reactions are stronger the more information is disclosed in preliminary earnings releases. However, we also show that these additional financial statement details are used more strongly by market participants when earnings are extreme, i.e., that the absolute unexpected earnings are more strongly associated with absolute unexpected returns the larger the amount of financial statement detail concurrently disclosed with earnings. This result generalizes that of Francis et al. (2002), who apparently due to their small sample size did not investigate this interaction effects. We also find that while the coefficient on absolute unexpected earnings in explaining absolute unexpected returns declines over time, the coefficient on the association between detail score and absolute unexpected returns actually increases over time, even after controlling for variables that affected by the firm’s information environment. We also find that the coefficient that measures the interaction between absolute unexpected earnings and level of detail and its association with absolute abnormal returns has decreased over time. This result explains the disparity between the decline in the value relevance of earnings and the increasing overall reaction to press releases, as suggested by Lo and Lys (2001). 3 This argument is consistent with the findings in Skinner (1994) and Kasznik and Lev (1995). 5
  • Our study continues as follows: Section 2 discusses the research design. Sample selection and data requirements are discussed in Section 3. The results of our analyses are provided in section 4, and section 5 provides concluding remarks. 2. Research Design 2.1 Institutional Setting The majority of companies voluntarily announce their operating results for the preceding quarter before filing the required 10-Q or 10-K Form with the SEC. The median company announces preliminary earnings about 27 days after quarter-end, as shown by Easton and Zmijewski (1993). Most companies actually file their 10-Q or 10-K Form with the SEC on the last day or two of the allowed period, as is shown by Griffin (2003). Since the preliminary earnings release is a voluntary activity, each company can choose the level of financial statement detail it wishes to disclose in the preliminary earnings release. About 95% of companies include sales along with earnings (Jegadeesh and Livnat, 2006). About 40% of the companies in the sample of Chen et al. (2002) provide balance sheet data that can be used to estimate current accruals. As we show below (Table 2), fewer than 10% of our sample observations have line items from the statement of cash flows. When a company issues a preliminary earnings report, Compustat extracts as many line items as it can from the preliminary earnings release and incorporates it in its quarterly database with an update code of "2". After the company files its 10-Q (or 10-K) Form with the SEC, Compustat extracts the line items again from the official filing and overwrites the preliminary figures, denoting them with an update code of "3". The process of extracting data from the preliminary earnings releases is quite fast, and is usually completed within 48 hours from the 6
  • press release. The process of extracting the information from the 10-Q and 10-K Forms is much longer, and in some cases of smaller companies it can take more than a month or two after the SEC filing for the final data to be included in the Compustat database. The initial research design problem that we need to tackle is the identification of those observations where a preliminary earnings release is issued prior to the SEC filing, as some companies may issue an earnings press release together or after the SEC filing.4 Compustat includes the preliminary earnings release date in its quarterly database, and I/B/E/S includes it for firms covered by analysts. However, the preliminary earnings release date in Compustat may actually be the SEC filing date subsequent to 1999. Until some time in year 2000, Compustat used to insert a missing value code if a firm had not issued a preliminary earnings release. Afterwards, Compustat revised its methodology and began including the SEC filing date for the earnings report date. Furthermore, to ascertain what market participants obtained in the preliminary earnings releases rather than the subsequent SEC filings, we require that the preliminary earnings release date be at least three days prior to the SEC filing date. This requires us to be able to identify the SEC filing dates for each firm; information that is typically unavailable in Compustat. However, Compustat provided us with the SEC filing dates for 10-Q and 10-K Forms for many firms in its database beginning in 1991. Thus, we are able to determine which companies issued preliminary earnings announcements at least three days prior to their SEC filings. To identify the line items that were included in the preliminary earnings release, we use another database provided to us by Charter Oak, which is also available for purchase through Compustat in WRDS. Charter Oak has collected the weekly CD-ROMs that were sent to 4 See Stice (2001). After 2002, less than 0.1% of our sample companies issue press release subsequent to the SEC filing. 7
  • Compustat clients over the years, where some data are designated with an update code of "2" and others with an update code of "3". Using the update codes of "2", Charter Oak is capable of constructing a database that includes the preliminary line items reported by companies in their preliminary earnings press releases. Thus, we can identify which financial statement line items were included by each company in its preliminary earnings press release. This enables us to use a very large sample in our study without the need to read and code actual earnings press releases, as in Francis et al. (2002). We should, however, point out two potential shortcomings of our research design. Because the Charter Oak database includes only financial statement data, we limit our study to the effects of financial statement line items rather than the other potentially useful non-financial and forward-looking information contained in the preliminary earnings releases, as do Francis et al (2002). On the other hand, coding such information in preliminary earnings releases may suffer from subjective assignments and classifications of information. The second shortcoming of our design relates to conference calls and the potential disclosure of information to selected parties prior to the issuance of Regulation Fair disclosure in October 2000 (REG FD). It is commonly assumed that prior to REG FD some companies disclosed financial statement line items to a select group of analysts and investors in conference calls and closed meetings. After REG FD, these items are broadcasted to all investors in the open conference calls. Kohlbeck and Magilke (2002) argue that additional information provided by conference calls combined with an increased conference call activity is the source of the increase in information content of earnings. They find that after controlling for conference calls, the information content of earnings has not increased during 1995-2000, and for small companies 8
  • has even decreased. This is consistent with additional information beyond earnings being released in conference calls. Kimbrough (2005) finds that the initiation of conference calls is associated with a significant reduction in the serial correlation in analyst forecast errors and post-earnings announcement drift. He also finds that the reduction in post-earnings announcement drift surrounding conference call initiation is concentrated in companies with the most significant drift, particularly small and least heavily traded companies, indicating the potential importance of controlling for the firm’s information environment. Bushee et al. (2004) examine the effect of REG FD on managers' decisions regarding the timing and content of conference calls. Their results suggest that the new rule had a negative impact on managers' decisions to continue hosting conference calls. Contrary to views expressed by critics of REG FD, they do not find evidence that the new rule decreased the amount of information disclosed during the call period. They also find that REG FD increased price volatility for firms that previously restricted access to their conference calls relative to companies that prior to the new rule held open conference calls, indicating that additional new information beyond earnings is likely disclosed in the conference calls. To the extent that limited-access conference calls and closed meetings are actually the instrument that is used by investors to learn new value-relevant information that is unavailable in the preliminary earnings announcements, and to the extent that conference calls are conducted within the three-day window centered on the preliminary earnings release date, our study will be biased against finding any effects of the additional disclosures in preliminary earnings releases beyond earnings on market reactions to earnings surprises prior to 2001. This bias is unlikely to exist subsequent to REG FD when all investors are supposed to obtain the same material 9
  • information simultaneously, so we include separate results for the periods prior and after REG FD. Our study is the first to examine the effects of concurrent disclosures in preliminary press releases before and after REG FD. 2.2 Detail Scoring Mechanism and its Determinants To measure the amount of information in the preliminary press release we design and implement three scoring mechanisms based on the number and relative importance of financial elements included in each quarterly press release. Initially, we identify 10 income statement items, 13 balance sheet items and 4 cash flow items to be included in the scoring mechanism. Second, we assign weights based on three distinct methods – "Equal", "Subjective" and "Market" Scoring. The Equal Scoring method is the simplest: the score is based on the number of items included in the quarterly press release. The “Subjective” scoring method is based on assigning subjective weights of "1", "2" or "3", where "3" denotes higher importance than "2", which, in turn, is assumed to be more important than "1". We assign the weights based on prior studies. For example, given the importance of revenues in prior studies (Ertimur et al., 2003) we assign a weight of "3" to "Sales." We assign a weight of "2" to "Inventory", which can be used to estimate current accruals, and a weight of "1" to "Depreciation Expense", which typically does not change much from one quarter to another. Weights for the “Market” scoring methods are based on the relative coefficients obtained by regressing absolute excess return around earnings announcements on absolute unexpected earnings, control variables (described below) and an indicator variable that is equal to "1" if the line item is available in the press release. We explain and demonstrate the use of the three scoring methods in the Appendix. We report results based on the Equal Scoring method and conduct sensitivity analysis using the other two methods. 10
  • The amount of detail in an earnings press release should depend on benefits accruing to the company from supplying additional information (voluntarily), on disclosure costs, and on capital market participants' demand for information. Companies may disclose more information in preliminary earnings press releases to support and interpret good earnings news or to provide mitigating explanations in cases of bad earnings news. As the propensity to disclose more information may be different in good and bad news, we examine the association between the detail score and positive and negative unexpected earnings. Similarly, companies with more volatile earnings are more likely to increase the amount of detail in earnings press releases to mitigate the effects of earnings variability on share prices. Investors' demand for additional financial information may also drive companies to include more detail in their quarterly earnings press releases. For example, it is expected that larger firms will disclose additional detail due to their more complex structure of operations than smaller companies, and also because shares of larger companies are likely to be held by professional investors with higher demand for more timely financial information. Similarly, the demand for additional financial information is likely to be higher for firms with larger trading volume, for firms that seek to raise new capital and for firms that are followed by analysts as these companies are more visible in the market. Also, more visible companies are more likely to reduce the cost of capital through supplying more information in a timely manner (Botosan 1997).5 The company also faces direct costs of providing more detail in preliminary earnings releases. These costs include more timely review of the press release by the company's auditor before it is disclosed, the firm’s ability to produce other financial statement data with sufficient 5 Regarding trading volume and analysts' coverage, the arguments could be reversed: Companies have higher trading volume and are followed more closely by analysts because they provide more information. As these variables are not the focus of our study, we consider them as control variables in our study and ignore the direction of causality. 11
  • reliability before finalizing the data for SEC filings, and the potential that some items will have to be revised by the SEC filing if errors are subsequently discovered (Hollie et al, 2005). A reasonable proxy for disclosure costs is the timing of earnings announcement. Controlling for the information itself, companies that release information relatively early are likely to have lower direct disclosure costs. We therefore include a variable that captures the relative timing of earnings announcements and expect that, ceteris paribus, early press releases include more financial detail than late press releases. We therefore estimate the following model to explain the level of detail score: SCOREit = α0t + α1tUEit + α2tNEGit x UEit + α3tLOGMKTit + α4tEARNVOLit+ α5tVOLUMEit + α6tFINAit + α7tANALYSTit + α8tTIMINGit + εit (1) The variables are defined as follows: LOGMKTit is the logarithm of market value of equity (in million of dollars) at quarter-end; UEit is the difference between quarterly earnings at time t and quarterly earnings at time t-4 scaled by market value of equity at quarter-end; EARNVOLit is the standard deviation of (earnings per share divided by share price), measured over the last eight quarters, and divided by the mean of that variable during the same period; VOLUMEit is the quarterly number of shares traded as a percentage of shares outstanding at quarter end; FINAit is an indicator variable that obtains the value of “1” if the average free cash flow (net operating cash flow minus capital expenditures) over the prior three years is negative or if the firm issued stock in the current or subsequent year, and “0” otherwise; ANALYSTit is the number of analysts that had forecasts of quarterly earnings on the summary IBES file in the month just before the preliminary earnings announcement; and TIMINGit is an indicator variable 12
  • that obtains the values of "1", "2" or "3" depending on the number of days between quarter-end and the preliminary earnings release. Specifically, TIMINGit is "1" if the number of days from quarter-end to earnings announcement is in the lower quartile of firms for that quarter, "2" if in the middle two quartiles, and "3" if in the upper quartile (we construct this variable separately for firms with fiscal quarters 1-3 and quarter 4). We expect positive coefficients on all variables except TIMING. The coefficient on TIMING is expected to be negative as early press releases are expected to include more financial detail due to lower disclosure costs. 2.3 The Market Reaction to Preliminary Earnings as a Function of Detail Score Our market-based tests draw on Francis et al. (2002). Similar to their study, we estimate the association between the absolute value of excess stock returns in the three-day window centered on the preliminary earnings announcements and the absolute value of unexpected earnings. The null hypothesis is that the association between absolute excess returns and absolute unexpected earnings is not affected by the amount of detail in press releases. The alternative hypothesis is that the market reaction to earnings increases with the amount of detail in earnings press releases. Since our sample is large and heterogeneous, we can control for various factors that are expected to affect the absolute value of excess stock returns. We use the following model: ABSRETPit = β0t + β1tABSUEit + β2tSCOREit + β3t ABSUEit x SCOREit + β4tTIMINGit + β5tLOGMKTit + β6tEARNVOLit+ β7tVOLUMEit + β8tFINAit +β9tANALYSTit + νit (2) The dependent variable – ABSRETPit – is the absolute value of excess stock returns in the three-day window centered on firm i's preliminary earnings announcement for quarter t, minus 13
  • the absolute value of excess returns in the three-day window around day -7, where day 0 is the preliminary earnings announcement date. ABSUEit is the absolute value of quarterly earnings changes between earnings in quarter t and earnings in quarter t-4, scaled by market value of equity at quarter-end. All other variables are as defined for Equation (1). 3. Sample and Descriptive Statistics The initial sample contains all companies covered by Compustat with a market value in excess of $10 million at quarter-end, beginning with the fourth quarter of 1990 and ending in the third quarter of 2005, or 514,435 firm/quarter observations. We then delete the following observations: (i) net income before extraordinary items (item 8 on quarterly Compustat) is missing, (ii) total assets is equal to zero, (iii) total sales for the quarter is below $1 million, and (iv) foreign-incorporated firms. This yields 334,573 observations. At this point, we rank all firm/quarters by the preliminary unexpected earnings (preliminary earnings minus earnings four quarters before, scaled by market value of equity at quarter-end) and match to CRSP using the WRDS CRSP-Compustat Merged file, leaving 323,107 observations. We delete all observations where the preliminary report date is not at least three days prior to the SEC filing date, or where the preliminary announcement date is in excess of 120 days after quarter-end, which are either very late announcers or data entry errors, leaving us with 223,272 observations. For the remaining observations, we compute Buy-and-hold excess returns around preliminary earnings announcements using CRSP and the Fama-French size and book-to- market 6-group portfolios, ending in a sample with 216,029 observations. This becomes our sample, although for some tests additional variables will cause elimination of observations with missing data on these variables. 14
  • Excess returns are measured in the three-day period (-1,+1) centered on the release of preliminary earnings (day 0) or day -7. Excess Buy-and-hold returns are calculated as the Buy- and-hold return from CRSP minus the Buy-and-hold return on the equally-weighted portfolio of firms with the same size (market value of equity) and book-to-market (B/M) ratio. Daily returns and cut-off points on the size and B/M portfolios are obtained from Prof. Kenneth French’s data library, based on classification of the population into six (two size and three B/M) portfolios. Observations in the top and bottom 0.5% of excess return are deleted from the sample to ensure that our results are not driven by outlying returns. Portfolio returns are computed each quarter. Table 1 presents the number of firm/quarter observations per year, median firm size (market value of equity), percentage of loss-reporting companies and median annual detail score. Consistent with prior studies, the percentage of loss-reporting companies reached its highest level in 2001 (34.1%) and decreased afterwards. Median detail score increased over the study period, reaching 0.69 in 2005, with a dramatic shift in 2000. (Table 1 about here) Figure 1 presents mean and median detail score for each quarter during the sample period (Q4 1990 – Q3 2005). The pattern of detail score has changed considerably during the sample period. From 1990 to 1996, mean and median detail scores were stable (mean around 0.25 and median around 0.15). From 1997 to 1999, mean and median scores vary significantly.6 Since 2000, we observe a monotonic increase in scores, primarily because of the disclosure of balance sheet and cash flow information in press releases. This may be related to Regulation Fair disclosure (REG FD) in October of 2000, which required firms to disclose material financial 6 Discussions with Compustat executives indicated that there were fewer employees to collect and enter data during the dot.com period, which may have resulted in a smaller number of preliminary line items that entered the Compustat database with the update code of “2”, although those items might in fact have been available in the preliminary earnings releases. Instead, Compustat may have entered the final data with an update code of “3” for these line items. In sensitivity analysis, we repeat the tests without the affected quarters. 15
  • information to all investors simultaneously. Thus, firms that had previously disclosed balance sheet and cash flow information to analysts in closed conference calls may have begun including these additional details in preliminary earnings press releases. Currently, detail scores are close to 0.70.7 (Figure 1 about here) Table 2 presents the percentage of companies that include each financial statement item in their preliminary earnings press releases for selected years. The table demonstrates a significant increase in reporting detail following REG FD, mostly with respect to balance sheet and cash flow information. Sales and summary figures such as Income from Continuing Operations, Total Assets and Total Liabilities have been traditionally the most frequently disclosed items. An interesting pattern is observed for cash flow items. In 1991, about 6% of companies included cash flow items in press releases. This percentage decreased during the 1990s (potentially due to inclusion of many additional smaller firms in the Compustat database), but started to increase following REG FD. In 2005, about 20% of companies included cash flow items in their press releases. (Table 2 about here) In untabulated analysis, we examine whether firms choose the level of financial statement disclosure and maintain it across adjacent quarters. Out of 183,374 observations (firm-quarters where adjacent quarter’s data are available), our Score variable (measured between 0 and 1, with a mean of 0.456 for this sub-sample) has changed by less than 0.01 in 106,391 cases, by less than 0.05 in 140,106 cases and by less than 0.10 in less than 157,663 cases. Thus, firms that choose a 7 We also observe a change in the skewness of the detail score. Prior to 2000, median score was below the mean suggesting that a small subset of observation exhibits high scores pulling the mean upwards. After 2000, median score is generally above the mean suggesting that a relatively small subset of companies exhibits low scores pulling the mean down. This phenomenon demonstrates a fundamental shift in disclosure policy and may be attributed to an external shock such as REG FD. 16
  • disclosure level tend to maintain it consistently, and seldom make changes in that chosen level of disclosure. 4. Results 4.1 The Determinants of Detail Score Table 3 presents median annual detail scores by size levels, timing of earnings announcements and analysts' coverage. We form three size levels based on market value of equity at quarter-end, where the group of 'small' and 'large' firms contains the lower and upper quartiles, respectively, and the 'medium' group contains the middle two quartiles. We also assign observations into three groups according to earnings announcement timing (25%, 50%, and 25%) as explained above. Regarding analysts coverage, a firm/quarter observation is considered covered by analysts if at least one analyst had an earnings forecast for that quarter. The table shows that detail scores were higher for large firms than for medium firms between 1990 and 1996. Since 2000, detail scores for medium and large firms are similar and even slightly larger in some cases for medium size companies. Also, in all quarters, detail scores for medium size companies are larger than those of small companies, although the difference in scores decreases after 2001. For example, in 1990 the median score was 0.115 for small firms, 0.148 for medium size companies and 0.269 for large firms. In contrast, in 2005, small firms had a median score of 0.731, below the score for medium size firms, 0.800, which, in turn, is almost equal to that of large firms, 0.808. The timing of earnings announcements (the number of days between quarter-end and the preliminary earnings announcement date) is also associated with detail score. The table shows that firms that announce early have a higher score than firms that disclose in the middle 50%, 17
  • which, in turn, have higher scores than 'late' firms. This behavior is consistent over the entire sample period. Detail scores also vary significantly by analyst coverage. Companies that are followed by analysts have higher detail scores than companies that are not followed by analysts. The difference in scores is attributed in part to differences in firm size as small firms are more likely not followed by analysts, and firms “neglected” by sophisticated investors may not find it in their best interest to provide additional detail in preliminary earnings announcements due to less investors’ pressure or the lower likelihood of accessing the capital markets. (Table 3 about here) Table 4 provides the results of estimating Equation (1). We estimate this equation separately for each quarter and report average coefficients and standard errors similar to Fama and MacBeth (1973). First, we estimate Equation (1) using the entire sample. The coefficient on unexpected earnings is 0.293 (significant at the 0.01 level, t = 13.02) when unexpected earnings are positive. This coefficient is 0.026 higher when unexpected earnings are negative and the difference between the coefficients is significant at the 0.01 level (t = 12.35). This result is consistent with the argument that the propensity to disclose more information in preliminary earnings announcements is higher when the earnings news is negative than when it is positive. Possible explanations for this behavior are the desire to reduce litigation costs by providing additional explanatory information when earnings changes are negative, or the desire to provide supplementary information that will help investors react less negatively to the earnings news. The volatility of earnings over the last eight quarters is also positively associated with detail score, as reflected by the positive coefficient on EARNVOL (0.007, t = 14.06, significant at the 0.01 level). This result suggests that companies with more volatile earnings provide more detailed earnings press releases, as this information is useful for investors in interpreting the 18
  • earnings changes. As expected, the coefficient on LOGMKT (firm size) is positive and significant at the 0.01 level, suggesting that, on average, large companies provide more information in earnings press releases than small companies, likely in response to higher demand for information by professional investors that tend to be more concentrated in large companies. Furthermore, companies with higher volume of trade disclose more information in their press releases, as reflected by the positive and significant coefficient on VOLUME. However, in this case it is difficult to say whether higher volume translates to more demand for information or that more information induces higher trading volume. Companies that are more likely to raise capital in the market have, on average, higher detail score, as reflected by the positive coefficient on FINA (0.031, t = 8.99). This result supports the argument that companies that need access to the capital markets respond to a higher demand for financial information by providing more detailed earnings press releases, attempting to reduce their cost of capital. Furthermore, as demand for financial information increases with analysts' coverage, companies that are followed by analysts respond to this higher demand by providing more detailed earnings press releases. This is reflected in the positive coefficient on ANALYST (0.003, t = 10.38). Finally, the coefficient on TIMING is negative, as expected, and highly significant suggesting that, ceteris paribus, early earnings announcements are more detailed than late announcements due to lower direct disclosure costs.8 We also estimate Equation (1) for three size levels and three levels of timing. Specifically, we report results for the lower size quartile (denoted as "small"), the middle two quartiles 8 This result may seem counter-intuitive because to have more financial statement detail available for the earnings announcement may require more time after quarter-end. However, as reported in Table 3, larger companies tend to both announce their preliminary earnings earlier than smaller companies, and also tend to have more details in their announcements. 19
  • ("medium") and for the upper size quartile ("large"). Several points are worth noting: (i) The intercept increases with size, consistent with the results reported in Table 3 that larger companies provide more information in their earnings press releases. (ii) The association between positive earnings changes and detail score is stronger in large companies than in small companies. However, the tendency to disclose more information when earnings changes are negative is stronger in small companies than in large companies, although this phenomenon exists in all three size levels. A possible explanation for this result is that the probability of negative earnings is lower for larger companies and consequently the propensity to disclose more information when earnings are negative is diminished. (iii) The strength of the association between Detail score and earnings volatility decreases with size. This is expected as earnings volatility decreases with firm size as well. (iv) The association between analysts' coverage and detail score is strongest for small companies. This is because the number of "neglected" companies is relatively large in small companies. (v) The coefficient on TIMINGit becomes more negative with firm size. This is primarily because there is much less variation in earnings announcement timing of small companies, as many of them announce earnings late. To complete the analysis in Table 3, we estimate Equation (1) separately for three levels of announcement timing. Consistent with our prior findings, late earnings announcements include less detail than early announcements, as reflected by the lower intercept for the 'late' group relative to the 'early' group. The association between earnings changes and detail score is consistent across different levels of announcement timing. In particular, detail score is higher in 20
  • negative earnings changes than in positive earnings changes in all three timing levels, and the difference in detail score between positive and negative earnings changes is significant at the 0.01 level in all cases. All other variables exhibit similar behavior and are not sensitive to different timing levels.9 (Table 4 about here) 4.2 Detail Score and the Market Reactions to Earnings Announcements Before we turn to analyzing the effect of detail score on absolute excess stock returns, we estimate the earnings response coefficients using the following model: RETPit =γ0t + γ1tUEit + ηit (3) RETPit is excess Buy-and-hold stock return in the three days centered on the preliminary earnings announcements of firm i in quarter t; and UEit is the change in quarterly earnings from quarter t-4 to quarter t scaled by market value of equity at quarter-end. The model is estimated cross-sectionally each quarter for 60 quarters. The regression coefficients as well as standard errors are obtained using the Fama and MacBeth (1973) approach. The results, which are reported in Table 5, are consistent with prior studies. The earnings response coefficient is positive and statistically significant, 0.022 (t = 10.72), and the average quarterly R2 is very low (0.003). We also estimate the model for the three size groups (small, medium and large companies), and obtain results consistent with prior studies; the earnings response coefficients decrease with size. Thus, we feel that our sample is not different from samples used in previous 9 We regressed each of the quarterly coefficients in Equation (1) on a time counter. The results (not tabulated) indicate that most coefficients are quite stable over time. An exception is the coefficient on unexpected earnings, which increases steadily and significantly over time, suggesting that firms increasingly tend to provide additional detail when earnings surprises are larger. We also repeated the analysis with Subjective and Market Scoring obtaining similar results. 21
  • market reactions studies so the influence of detail on the association between market reactions and earnings surprises is not due to a unique sample peculiarities. (Table 5 about here) Table 6 presents the results of estimating Equation (2). We also present results for two distinct time periods – Pre REG FD (40 quarters from Q4 1990 to Q3 2000) and Post REG FD (20 quarters from Q4 2000 to Q3 2005). Consider first the results for all quarters. The coefficient on absolute unexpected earnings (ABSUEit) is positive, as expected from prior studies, and significant at the 0.05 level (0.004, t = 2.17) for the entire sample period. This coefficient is larger in the Post REG FD period than in the Pre REG FD period, where the latter is insignificantly different from zero. The coefficient on SCOREit is positive and significant (0.003, t = 3.63), in line with Francis et al (2000), suggesting that absolute excess stock returns around preliminary earnings announcements increase with the amount of financial statement information disclosed concurrently with earnings. Moreover, the coefficient on the interaction variable between detail score and absolute unexpected earnings (ABSUEit x SCOREit) is also positive and significant at the 0.01 level (0.030, t = 4.48), suggesting that additional financial statement detail is used more strongly by investors when earnings surprises are extreme. The coefficient on the detail score is significant and larger in the Post REG FD period than in the Pre REG FD period, where the latter is insignificantly different from zero. In contrast, the interaction between score and absolute unexpected earnings is significantly different from zero for the Pre REG FD period, but insignificantly different from zero in the Post REG FD period. These results are new to the literature and provide further contribution beyond Francis et al. (2002), using a much larger and heterogeneous sample and controlling for the information and 22
  • regulatory environment of companies as well as the timing of the preliminary earnings announcements. Turning to the control variables in the model, the coefficient on TIMING is insignificantly different from zero, once we control for other dimensions such as size and analyst following. As expected, the coefficient on firm size (LOGMKTit) is negative (-0.003, t = -15.33) suggesting that absolute excess returns around earnings announcements decrease with firm size, likely because larger firms have more informative environments, so earnings affect prices less strongly. Also, the positive coefficient on earnings volatility (0.001, t = 9.09) suggests that firms with more volatile earnings are likely to have stronger market reactions when their earnings are announced. Similarly, the coefficient on VOLUMEit is positive, as expected (0.010, t = 10.88), suggesting that firms with higher share turnover are likely to also have stronger market reactions around earnings announcements, likely because they are followed more closely by market participants. Finally, the coefficients on FINAit and ANALYSTit are both positive, although the first is insignificantly different from zero, suggesting that companies that are more likely to raise new capital and companies that are followed by analysts are paid greater attention by market participants when their earnings are announced, hence their larger absolute excess returns around earnings press releases. These coefficients are not materially different before and after REG FD. (Table 6 about here) Since the timing of the preliminary earnings announcement is correlated with the level of detail in the press announcements and firms’ size, we estimate Equation (2) separately for three timing groups (early, middle, and late) and three size levels (small, medium, and large). The results are reported in Table 7. Referring to the timing groups, the regression intercepts increase with timing suggesting that excess stock returns are more volatile as earnings are released 23
  • relatively late, although this may also be related to the smaller size of late firms. Also, the coefficients on absolute unexpected earnings (ABSUEit) are positive, but significant at the 0.05 level or better just for the early group. The coefficient on SCOREit is significantly different from zero only for the early and middle group. Lastly, the coefficient on the interaction variable ABSUEit x SCOREit is significant only for the 'middle' group – the 50% of the observations that are neither early nor late. These results suggest that detail score provides more explanatory power for extreme earnings when the timing of the press release is not extreme. In early or late announcements, the timing of information release likely reveals additional information to the market as well as information transfer between companies in the same industry, reducing the explanatory power of SCOREit. Turning to the size levels, several results are worth noting: (i) The regression intercepts indicate that earnings news are more informative for smaller companies with weaker information environments. Also, the coefficient on absolute unexpected earnings is larger for small companies than for large companies, indicating the larger role earnings news play for smaller firms. (ii) The coefficient on SCOREit is significant only for medium size companies, suggesting that the richer information environment of larger firms makes the additional level of detail in the preliminary earnings announcement less relevant for investors, who may have obtained that information from other sources. (iii) The coefficient on ABSUEit x SCOREit is significant only for small companies. This result suggests that absolute stock returns depend much less on the release of concurrent information with earnings for large firms with richer information environments. 24
  • Overall, the results in Table 7 suggest that both timing of press releases and firm size are major factors in explaining the association between absolute unexpected earnings and absolute excess stock returns. The Table identifies sub-samples in which the detail score is a significant contributor to the explanatory power of the association between earnings news and absolute excess returns incrementally to timing and size. In particular, detail score is incrementally significant in companies that are neither late in releasing preliminary earnings nor large. Recall that large companies typically announce early and for those that provide more detail in their preliminary announcements we expect a stronger market reaction. Small companies that report late should have weaker market reactions. (Table 7 about here) As Francis et al. (2002) and Lo and Lys (2001) point out, there have been significant changes over time in the association between absolute excess returns and absolute unexpected earnings. These findings motivate us to examine the time series behavior of the coefficients obtained from Equation (2). We estimate the following models using the 60 coefficients from the quarterly cross-sectional regressions: β1t = δ0 + δ1COUNTERt +λt (4a) β2t = δ0 + δ1COUNTERt +λt (4b) β3t = δ0 + δ1COUNTERt +λt (4c) The dependent variables in Equation (4) are the regression coefficients obtained from Equation (2) and COUNTER is a time variable from 1 (the first quarter in our data, Q4 1990) to 60 (the 25
  • last quarter of our data, Q3 2005). Recall that the cross-sectional regressions control for the other variables (earnings volatility, analyst following, etc. The results, which are reported in Table 8, show that the association between absolute excess returns and absolute unexpected earnings has changed significantly over time, and also that this association has changed significantly over time according to the level of financial statement detail disclosed in the preliminary earnings announcements. Specifically, the coefficient on unexpected earnings, ABSUE, has decreased during the sample period (-0.006, t = -2.85) suggesting that the contribution of absolute unexpected earnings alone to the explanation of absolute returns has deteriorated over time. In contrast, the role of information provided concurrently with earnings has increased over time, as reflected by the increase in the coefficient on SCORE (0.005, t = 2.81). However, the interaction between concurrent information and earnings news has also decreased over time (-0.028, t = -2.21), suggesting that the additional effects of financial statement detail on stock returns is for extreme earnings is decreasing over time. Overall, the results in Table 8 highlight the increasing importance of concurrent information in press releases over time and its effects on market reactions. These results also support the argument in Lo and Lys (2001) that the value relevance of earnings has decreased over time, but that the quantity and relevance of concurrent information in preliminary earnings announcements have increased over time. (Table 8 about here) Our final analysis, provided in Table 9, focuses on matched samples rather than on linear regressions. We identify companies with detail score in the upper quartile of the distribution and match them with similar companies whose detail scores are in the bottom quartile during the 26
  • same quarter. We then compute average excess returns and average absolute excess returns around the preliminary earnings announcements for the high and low detail samples. In the first matching, we identify companies with high detail score and companies with low detail score that are similar in size (where the absolute size difference is capped at 10% of the high detail score company). The average excess return is larger for companies with high detail score than for companies with low detail score (at the 0.05 level). Furthermore, the average absolute excess returns are larger for companies with high detail score by 0.88% (t = 22.69). This result is consistent with our prior analysis and with Francis et al. (2002). The second match is performed by firm size and the decile of unexpected earnings. The difference in average excess returns is close to zero, but the difference in average absolute excess returns increases to 1.12% (t = 29.14). The third matching adds the number of analysts as another factor while the fourth matching takes into account all of the above and the timing of press releases. The results remain consistent – no difference in average excess returns but significant differences in absolute excess returns. The results in Table 9 clearly show that increasing the amount of financial statement detail disclosed concurrently with earnings is associated with stronger market reactions around the earnings press release dates. (Table 9 about here) 4.3 Sensitivity Analysis All our analyses are performed using the subjective and market weighting to determine the detail score. The results are insensitive to the alternative scoring method. We estimated Equation (2) separately for negative and positive unexpected earnings. The results about the effects of detail on the association between absolute excess returns and absolute 27
  • unexpected earnings are stronger for negative unexpected earnings changes than for positive ones, indicating that market participants incorporate more of the non-earnings information when earnings decline. To assess the effect of survivorship on our analysis and to facilitate better comparison with the results obtained by Francis et al. (2002), we estimated Equation (2) using companies with at least 55 quarters of data. We find that the coefficients on detail score (SCOREit) and the interaction between detail score and absolute unexpected earnings (ABSUEit x SCOREit) are larger and statistically more significant than those reported in Table 6. We repeated the market reaction tests with an additional dummy variable indicating whether the firm reported a loss during the quarter or not. The results on the detail score coefficients were qualitatively the same. We also repeated the analysis without the first two quarters of 1999, when Compustat may have been unable to record all the preliminary information in a timely manner due to staff shortages. The market reactions results are a bit stronger than those reported in Table 6 with respect to the effects of the detail score, and we obtain the same conclusions as those in Table 8 about the evolution of the coefficients on earnings, detail score and the interaction between the two over time. 5. Summary and Conclusions This study investigates the effects of additional financial statement disclosure in preliminary earnings announcements on the association between absolute unexpected earnings and absolute excess returns in the three-day window centered on the preliminary earnings announcements. It shows that market reactions to unexpected earnings increases with the amount 28
  • of financial statement detail concurrently disclosed with earnings, after controlling for variables that affect the firm's information environment. The study is based on a very large sample of firms and uses a unique database to study the effects of additional financial statement disclosure in preliminary earnings announcements. This extensive sample allows us to investigate the determinants of the level of detail in preliminary earnings announcements, their evolution over time, and control for the effects of the information environment on the relationship between earnings surprises, excess returns and the level of additional financial statement detail in preliminary earnings announcements. We find that the level of financial statement detail in preliminary earnings releases has increased over time and in particular after the enactment of Regulation Fair Disclosure in 2000. Typically, there is a positive relationship between the level of additional financial statement detail in preliminary announcements and size, investors’ interest in the company, the company’s earning volatility and firms’ likelihood to access the capital markets. There is an inverse relationship between the announcement timing and the level of detail in the announcement; larger firms tend to announce early and to have more financial statement detail in their preliminary earnings announcements than smaller firms. We also find that the association between market reactions and unexpected earnings is affected positively and significantly by the level of additional financial statement detail in preliminary earnings announcements. These effects are stronger for smaller firms and for firms that announce early. Extending Francis et al. (2000), we find significant explanation for the interaction between the level of financial statement detail and earnings surprises as it relates to market reactions; this indicates that more extreme earnings surprises which are accompanied by greater detail tend to be more strongly associated with greater market reactions. This implies that 29
  • investors likely seek and utilize other than earnings information when earnings surprises are extreme, probably attempting to better assess the persistence of the earnings surprises. The results of this study have implications for academics, managers and investors. They highlight the determinants and effects of additional (to earnings) voluntary disclosures, and how they are utilized by market participants. The results can be used by management to assess the likely effects of a decision to increase or decrease the level of additional financial statement detail in preliminary earnings announcements. Finally, investors should pay close attention to firms that decide to increase or decrease the level of financial statement detail in their preliminary earnings announcements. Such decisions are likely driven by the firms’ intention to attract more active and sophisticated investors in cases of increasing the level of detail, or to “fly under the radar screen” in cases of decreasing the level of detail. These actions have implications beyond the additional information that is provided or withheld. 30
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  • Table 1 Sample and Descriptive Statistics* Year N Median % Mean Size Loss Equal SCORE 1990 2,197 126.3 18.5 0.311 1991 9,910 146.1 18.3 0.303 1992 10,803 148.2 17.0 0.291 1993 11,664 165.2 18.2 0.296 1994 14,079 144.1 14.9 0.282 1995 15,247 165.3 15.8 0.292 1996 16,241 194.7 18.0 0.337 1997 18,036 217.1 19.5 0.384 1998 17,840 215.2 23.3 0.452 1999 17,117 220.9 24.0 0.379 2000 16,766 239.1 28.9 0.524 2001 16,020 249.5 34.1 0.579 2002 13,871 272.2 29.0 0.605 2003 13,166 293.5 25.1 0.643 2004 13,643 433.0 20.1 0.653 2005 9,429 476.9 19.8 0.690 All 216,029 219.5 22.0 0.444 *Notes: 1. N – The number of firm/quarter observations in each year during the sample period (Q4 1990 – Q3 2005). The sample includes all quarter/year observations that issued preliminary earnings reports and for which return data is available. We use only preliminary earnings reports that were issued 3 or more days prior to SEC filing. 2. Size - Market value of equity in millions of dollars. 3. %Loss – the percentage of companies that reported negative earnings during the quarter. 4. SCORE - A variable between zero and one that captures the amount of financial statement detail in earnings press releases. The computation of detail scores is demonstrated in the Appendix. 34
  • Figure 1 Detail Score over time (Q4 1990 – Q3 2005) Detail over Time 1 5000 0.8 4000 0.6 3000 0.4 2000 0.2 1000 0 0 19904 19914 19924 19934 19944 19954 19964 19974 19984 19994 20004 20014 20024 20034 20044 Mean Quarter Median N The Figure presents mean Score, median Score and the number of observations (N) per each quarter. Score is a variable between zero and one that captures the amount of financial detail in earnings press releases. The computation of detail scores is demonstrated in the Appendix. 35
  • Table 2 Reporting Frequency by Financial Statement Item and Year* 1991 1993 1995 1997 1999 2001 2003 2005 Income statement (10 items): Sales 0.955 0.958 0.881 0.896 0.903 0.900 0.880 0.894 Cost of goods sold 0.148 0.162 0.285 0.551 0.528 0.796 0.820 0.858 SG&A expenses 0.285 0.293 0.303 0.427 0.401 0.606 0.653 0.687 Interest expense 0.275 0.282 0.235 0.319 0.307 0.435 0.464 0.491 Special items 0.277 0.324 0.385 0.542 0.533 0.752 0.772 0.805 Depreciation expenses 0.127 0.130 0.114 0.128 0.181 0.220 0.258 0.328 Non-operating income 0.327 0.327 0.325 0.462 0.428 0.654 0.681 0.713 Income tax expense 0.605 0.589 0.494 0.635 0.656 0.885 0.893 0.912 Net income from continuing operations 0.990 0.990 0.992 0.982 0.964 0.970 0.946 0.947 Extraordinary items 0.079 0.099 0.041 0.052 0.057 0.075 0.109 0.114 Balance sheet (13 items) Cash (and equivalents) 0.240 0.229 0.227 0.337 0.327 0.600 0.683 0.735 Accounts receivable 0.191 0.182 0.200 0.299 0.318 0.570 0.658 0.692 Inventory 0.193 0.183 0.193 0.289 0.290 0.525 0.608 0.657 Current assets 0.233 0.218 0.198 0.308 0.279 0.490 0.539 0.542 Property Plant and Equipment 0.278 0.248 0.227 0.327 0.310 0.557 0.627 0.659 Total assets 0.320 0.299 0.279 0.421 0.430 0.728 0.798 0.833 Short-term debt 0.194 0.175 0.171 0.243 0.249 0.446 0.535 0.575 Accounts payable 0.166 0.152 0.172 0.255 0.293 0.523 0.606 0.655 Current liabilities 0.235 0.220 0.200 0.311 0.280 0.491 0.542 0.544 Long-term debt 0.280 0.255 0.232 0.339 0.328 0.566 0.656 0.714 Other liabilities 0.228 0.212 0.208 0.304 0.291 0.533 0.619 0.670 Total liabilities 0.296 0.287 0.274 0.415 0.421 0.713 0.785 0.826 Stockholders equity, total 0.248 0.273 0.247 0.372 0.338 0.688 0.760 0.815 Cash flow (4 items) Net operating cash flow 0.066 0.043 0.028 0.034 0.013 0.073 0.170 0.222 Capital expenditures 0.062 0.041 0.025 0.031 0.013 0.067 0.158 0.207 Total investing cash flows 0.064 0.042 0.026 0.032 0.013 0.071 0.166 0.218 Total financing cash flows 0.064 0.042 0.027 0.032 0.013 0.071 0.165 0.218 *Note: The table presents percentage of companies that include each financial statement item in their preliminary earnings press releases. Frequencies are reported for odd years. 36
  • Table 3 Median Annual Detail Score (Equal Scoring) by size levels and analysts coverage* Detail Score by Firm Size Detail Score by Timing of Detail Score by Earnings Announcements Analyst Coverage Year Small Medium Large Early Middle Late Yes No 1990 0.115 0.148 0.269 0.269 0.167 0.115 0.115 0.200 1991 0.115 0.148 0.269 0.269 0.154 0.115 0.115 0.200 1992 0.115 0.136 0.250 0.240 0.154 0.115 0.115 0.190 1993 0.115 0.154 0.269 0.250 0.154 0.115 0.115 0.208 1994 0.100 0.120 0.200 0.154 0.120 0.115 0.100 0.154 1995 0.105 0.120 0.154 0.136 0.115 0.115 0.105 0.148 1996 0.115 0.250 0.280 0.250 0.263 0.115 0.115 0.280 1997 0.231 0.318 0.308 0.346 0.308 0.192 0.154 0.333 1998 0.333 0.455 0.385 0.560 0.450 0.308 0.308 0.476 1999 0.120 0.308 0.381 0.412 0.308 0.143 0.125 0.333 2000 0.391 0.615 0.632 0.680 0.600 0.417 0.368 0.654 2001 0.578 0.692 0.654 0.722 0.692 0.500 0.476 0.720 2002 0.615 0.731 0.714 0.731 0.731 0.538 0.538 0.731 2003 0.654 0.769 0.769 0.789 0.762 0.565 0.615 0.769 2004 0.680 0.769 0.800 0.800 0.769 0.579 0.615 0.789 2005 0.731 0.800 0.808 0.808 0.800 0.714 0.667 0.800 *Notes: 1. The Table presents median detail scores for each year during the sample period (Q4 1990 – Q3 2005) for three size levels (small, medium, large), three levels of earnings announcement timing (early, middle, late) and by analyst coverage (Yes, No). 2. The sample includes all quarter/year observations that issued preliminary earnings reports and for which return data is available. We use only preliminary earnings reports that were issued 3 or more days prior to SEC filing. 3. Detail Score - A variable between zero and one that captures the amount of financial statement detail in earnings press releases. The computation of detail scores is demonstrated in the Appendix. The Table presents statistics using the Equal Scoring method. 4. Size levels - Formed every quarter based on market value of equity. The small and large levels include the lower and upper quartiles, respectively, and the medium level includes the middle two quartiles. 5. Timing levels - Measured every quarter based on the number of days from quarter-end to earnings announcement. Early and late levels include the lower and upper quartiles, respectively, and the middle level includes the middle two quartiles. 6. Analyst Coverage - A firm/quarter observation is considered as covered by analysts if at least one analyst is covering the firm during that quarter. 37
  • Table 4 Determinants of Detail Score for the Total Sample, by Size Levels and by Timing Levels Total Size Levels Timing Levels Sample Small Medium Large Early Medium Late Variable Sign Mean Mean Mean Mean Mean Mean Mean Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. INTERCEPT + 0.363 0.323 0.433 0.461 0.353 0.337 0.253 t-value 13.67 17.42 19.35 26.11 13.19 10.98 10.84 UE + 0.293 0.222 0.319 0.401 0.327 0.288 0.274 t-value 13.02 9.15 13.30 23.06 14.06 12.82 10.48 UE x NEG ? 0.026 0.031 0.025 0.014 0.024 0.026 0.029 t-value 12.35 9.29 11.24 3.44 7.02 8.21 11.70 LOGMKT + 0.010 -- -- -- 0.011 0.010 0.009 t-value 5.63 -- -- -- 5.82 4.02 6.54 EARNVOL + 0.007 0.010 0.008 0.003 0.007 0.007 0.007 t-value 14.06 12.16 11.64 3.83 5.98 9.74 9.96 VOLUME + 0.056 0.062 0.036 0.044 0.050 0.062 0.045 t-value 11.06 7.90 6.28 6.09 6.15 11.89 8.22 FINA + 0.031 0.040 0.013 0.032 0.039 0.024 0.032 t-value 8.99 7.73 3.96 5.89 5.57 5.79 7.06 ANALYST + 0.003 0.035 0.010 0.002 0.003 0.002 0.007 t-value 10.38 20.31 19.22 5.30 6.05 6.70 15.62 TIMING - -0.036 -0.028 -0.035 -0.041 -- -- -- t-value -23.41 -14.09 -20.67 -21.69 -- -- -- Average R2 0.141 0.140 0.142 0.010 0.079 0.089 0.163 Average observations 3,264 811 1,595 858 829 1,645 790 Notes: 1. The Table presents mean coefficients and standard errors based on 60 quarterly regressions (Fama and MacBeth, 1973 regressions) for the following model: SCOREit = α0t + α1tUEit + α2tNEGit x UEit + α3tLOGMKTit + α4tEARNVOLit+ α5tVOLUMEit + α6tFINAit + α7tANALYSTit + α8tTIMINGit + εit (1) 2. Variable definitions: a. SCORE – A variable between zero and one that captures the amount of detail in a 38
  • preliminary earnings press release. See details in the Appendix. b. UE – Unexpected Earnings, measured as quarterly earnings in quarter t minus quarterly earnings in quarter t-4, scaled by market value of equity at quarter end. c. NEG – An indicator variable obtaining the value of "1" if the change in quarterly earnings is negative, and "0" otherwise. d. LOGMKT – Logarithm of market value of equity (in million of dollars) at quarter-end. e. EARNVOL – The standard deviation of (earnings per share over share price) over the last 8 quarters divided by the mean of (earnings per share over share price). f. VOLUME -- Quarterly number of shares traded as a percentage of shares outstanding at quarter end. g. FINA – An indicator variable that obtains the value of “1” if average free cash flow over the prior 3 years is negative (financing is required) or if the firm issued stock in the current or subsequent year (financing actually used), and “0” otherwise. h. ANALYST – The number of analysts following the company that quarter. i. TIMING – Indicator variable. Initially, we measure the number of days between quarter- end and the preliminary earnings announcement date. We assign each observation into one of three groups according to the lag from quarter-end: lowest 25% into early group, middle 50% into the middle group and largest 25% into the late group. We conduct this analysis separately for quarters 1-3 and quarter 4. 3. Coefficients and standard errors in bold are significant at the 0.01 level (2-tailed test). 39
  • Table 5 The Association between signed unexpected earnings and unexpected return Fama-MacBeth Regressions using 60 quarters from Q1/90 to Q1/05 Entire Size levels Sample Small medium large Variable Sign Coeff. Coeff. Coeff. Coeff. t-stat. t-stat. t-stat. t-stat. INTERCEPT ? 0.004 0.009 0.002 0.003 t-statistic 10.56 11.74 5.15 5.97 UE + 0.022 0.037 0.015 0.009 t-statistic 10.72 10.71 5.95 4.36 Average R2 0.003 0.008 0.002 0.001 Average number of observations 3,601 900 1,801 900 Notes: 1. The Table presents results for the following model: RETPit = β0t + β1tUEit + νit (3); where RETPit is stock return in the three days centered on the preliminary earnings announcement of firm i in quarter t; and UEit is the change in quarterly earnings from quarter t-4 to quarter t scaled by market value of equity at the end of quarter t. 2. The model is estimated separately for 60 quarters. The regression coefficients and standard errors are obtained using the Fama and MacBeth (1973) approach. 3. Results are provided for the entire sample and also for three size levels (small, medium and large), where size is measured as market value of equity. Small and large portfolios contain the lower and upper quartiles of the sample, respectively, and the medium size portfolio contains the middle two quartiles. 4. Coefficients and standard errors in bold faces are significant at the 0.01 level (2-tailed test). 40
  • Table 6 Explaining the Absolute Value of Market Reaction to Preliminary Earnings Announcements Using Three Methods of Detail Scoring (Fama-MacBeth Regressions) Equal Scoring Pre Post All REG FD REG FD Quarters Variable Sign Coeff. Coeff. Coeff. t-stat. t-stat. t-stat. INTERCEPT ? 0.024 0.022 0.029 t-statistic 14.61 8.48 16.81 ABSUE + 0.003 0.005 0.004 t-statistic 1.25 3.27 2.17 SCORE + 0.001 0.007 0.003 t-statistic 0.66 6.20 3.63 ABSUE x SCORE + 0.036 0.018 0.030 t-statistic 4.63 1.87 4.88 TIMING + -0.000 0.001 0.000 t-statistic -0.61 1.11 0.29 LOGMKT - -0.003 -0.003 -0.003 t-statistic -11.51 -10.90 -15.33 EARNVOL + 0.001 0.002 0.001 t-statistic 5.60 12.64 9.09 VOLUME + 0.008 0.013 0.010 t-statistic 7.16 11.08 10.88 FINA + 0.000 0.001 0.001 t-statistic 0.70 0.44 0.80 ANALYST + 0.001 0.001 0.001 t-statistic 14.65 7.86 15.72 Average R2 0.012 0.023 0.016 Average observations 3,200 3,339 3,246 Quarters 40 20 60 41
  • Notes: 1. Equation (2) is estimated separately for each quarter and regression coefficients and standard errors are obtained using the Fama and MacBeth (1973) approach. The Table presents mean coefficients and corresponding t-statistics.. The model is: ABSRETPit = β0t + β1tABSUEit + β2tSCOREit + β3t ABSUEit x SCOREit + β4tTIMINGit + β5tLOGMKTit + β6tEARNVOLit+ β7tVOLUMEit + β8tFINAit +β9tANALYSTit + νit (2) 2. Variable definitions: a. ABSRETP – The dependent variable is absolute value of excess stock returns in the 3-day window centered on the preliminary earnings announcements date (day 0) minus the absolute value of excess returns in the 3-day window around day -7. b. ABSUE – Absolute value of quarterly earnings changes, scaled by market value of equity at quarter-end. The change in quarterly earnings is the difference between earnings in quarter t and earnings in quarter t-4. c. SCORE – A variable that captures the amount of detail in a preliminary earnings press release. We report results for three scoring methods (Equal, Subjective and Market) as demonstrated in the Appendix. d. TIMING – Indicator variable. Initially, we measure the number of days between quarter- end and the preliminary earnings announcement date. We assign each observation into one of three groups according to lag from quarter-end: lowest 25% into the early group, middle 50% into the middle group and largest 25% into the late group. We conduct this analysis separately for quarters 1-3 and quarter 4. e. LOGMKT – Logarithm of market value of equity (in million of dollars) at quarter-end. f. EARNVOL – The standard deviation of {earnings per share over share price} during the prior 8 quarters divided by the mean of {earnings per share over share price} during the same period. g. VOLUME -- Quarterly number of shares traded as a percentage of shares outstanding at quarter end. h. FINA – An indicator variable that obtains the value of “1” if the average free cash flow over the prior 3 years is negative (financing is required) or if the firm issued stock in the current or subsequent year (financing actually used), and “0” otherwise. i. ANALYST – The number of analysts following the company for that quarter. 3. Coefficients and standard errors in bold are significant at the 0.01 level (2-tailed test). 42
  • Table 7 Explaining the Absolute Value of Market Reaction to Preliminary Earnings Announcements Using Report Detail and by Timing Groups - Fama-MacBeth Regressions Equal Scoring Method Timing Groups Size Levels Early Middle Late Small Medium Large Variable Sign Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. t-stat. t-stat. t-stat. t-stat. t-stat. t-stat. INTERCEPT ? 0.021 0.024 0.025 0.038 0.018 0.021 t-statistic 9.21 14.56 10.86 8.96 7.45 8.66 ABSUE + 0.008 0.003 0.004 0.004 0.004 0.002 t-statistic 2.16 0.84 1.70 1.10 1.62 1.08 SCORE + 0.003 0.002 0.002 0.002 0.004 0.001 t-statistic 2.95 2.44 1.18 0.79 3.88 1.30 ABSUE x SCORE + 0.027 0.048 0.14 0.046 0.016 0.018 t-statistic 0.96 4.20 0.94 3.00 1.87 0.93 TIMING + -- -- -- -0.001 0.000 0.001 t-statistic -- -- -- -1.54 0.64 2.27 LOGMKT - -0.003 -0.003 -0.003 -0.007 -0.002 -0.002 t-statistic -8.22 -13.17 -7.83 -5.98 -6.10 -7.95 EARNVOL + 0.002 0.001 0.001 0.002 0.001 0.001 t-statistic 7.04 5.86 4.14 6.83 5.54 3.44 VOLUME + 0.011 0.010 0.008 0.004 0.011 0.011 t-statistic 6.94 9.15 3.96 1.91 10.55 8.54 FINA + -0.000 0.001 0.001 0.001 0.000 0.001 t-statistic -0.30 0.83 0.62 0.42 0.15 1.90 ANALYST + 0.001 0.001 0.001 0.001 0.001 0.001 t-statistic 7.05 10.51 6.74 1.68 9.76 8.50 Average R2 0.036 0.020 0.020 0.022 0.022 0.030 Average observations 819 1,632 778 799 1,582 846 Notes: 1. Equation (2) is estimated separately for 60 quarters and regression coefficients and standard errors are obtained using the Fama and MacBeth (1973) approach. The Table presents mean 43
  • coefficients and corresponding t-statistics. The dependent variable is absolute excess stock returns around preliminary earnings press releases minus the absolute excess return seven days prior to the preliminary earnings release date. Estimation is done separately for three timing groups and three size levels. The model is: ABSRETPit = β0t + β1tABSUEit + β2tSCOREit + β3t ABSUEit x SCOREit + β4tTIMINGit + β5tLOGMKTit + β6tEARNVOLit+ β7tVOLUMEit + β8tFINAit +β9tANALYSTit + νit (2) 2. Timing Groups - Initially, we measure the number of days between quarter-end and the preliminary earnings announcement date. We assign each observation into one of three Timing groups according to lag from quarter-end: lowest 25% into early group, middle 50% into the middle group and largest 25% into the late group. We conduct this analysis separately for quarters 1-3 and quarter 4. 3. Size levels - Size is measured as market value of equity. Small and large portfolios contain the lower and upper quartiles of the sample, respectively, and the medium size portfolio contains the middle two quartiles. 4. See Table 6 for variable definitions. 5. Coefficients and standard errors in bold faces are significant at the 0.05 level (2-tailed test). 44
  • Table 8 Trends in the Association between Absolute Unexpected Return and Absolute Unexpected Earnings, Detail Score and the Interaction between Absolute Unexpected Earnings and Detail Score* Equal Score Dependent Variable ABSUE SCORE ABSUE x SCORE β1t β2t β3t INTERCEPT x 100 1.192 -0.242 7.204 t-statistic 5.55 -2.15 4.51 TIME COUNTER x 100 -0.006 0.005 -0.028 t-statistic -2.85 2.81 -2.21 R2 0.04 0.06 0.04 *Notes: 1. The Table presents results for three linear regressions. The dependent variable in each regression consists of 60 quarterly coefficients obtained from the following regression: ABSRETPit = β0t + β1tABSUEit + β2tSCOREit + β3t ABSUEit x SCOREit + β4tLOGMKTit + β5tEARNVOLit+ β6tVOLUMEit + β7tFINAit + β8tANALYSTit + νit (2) 2. See Table 6 for variable definitions. 3. Coefficients and t-statistics in bold indicate significance at the 0.05 level. 45
  • Table 9 Differences in Absolute Excess Returns between Companies with High Detail Score and Companies with Low Detail Score* High Detail Score Low Detail Score Differences in t-statistics Excess Absolute Excess Absolute Excess Absolute Excess Absolute Return Excess Return Excess Return Excess Return Excess Matching by Return Return Return Return Firm Size 0.0041 0.0568 0.0029 0.0480 0.0011 0.0088 2.34 22.69 Firm Size and Earnings Surprise Decile 0.0042 0.0577 0.0050 0.0464 -0.0008 0.0112 -1.33 29.14 Firm Size, Number of Analysts and 0.0045 0.0595 0.0045 0.0518 0.0000 0.0077 0.04 12.80 Earnings Surprise Decile Firm Size, Number of Analysts, 0.0044 0.0611 0.0053 0.0519 -0.0009 0.0092 -0.84 11.50 Earnings Surprise Decile and Timing Notes: 1. The Table presents excess stock returns and absolute value of excess stock returns for a sample of companies with high detail score (score in the upper quartile) and a matched sample of companies with low detail score (score in the lower quartile). The table also presents the differences in excess returns and absolute value of excess returns and their significance levels. 2. Matching techniques: (i) Matching by Size (size difference is capped at 10%); (ii) Matching by Size and Earnings Surprise decile; (iii) Matching by Size, Earnings Surprise decile and the number of analysts following the firm, (iv) matching by Size, Earnings Surprise decile, number of analysts following the firm and the announcement timing (early, medium, late). 3. Excess returns are measured in the 3-day period (-1,+1) around the release of preliminary earnings. Excess Buy-and-hold returns are calculated as the Buy-and-hold return from CRSP minus the Buy-and-hold return on the portfolio of firms with the same size (market value of equity) and book-to-market (B/M) ratio. Daily returns and cut-off points on the size and B/M portfolios are obtained from Prof. Kenneth French’s data library, based on classification of the population into six (two size and three B/M) portfolios. Observations in the top and bottom 0.5% of excess return are deleted from the sample to ensure that our results are not driven by outlying returns. Portfolio returns are computed each quarter. The table presents average quarterly returns and t-statistics based on a Fama and MacBeth (1973) approach. Xt −Xt − 4−δ 4. Standardized unexpected earnings are measured as: SUE = , where Xt is earnings for quarter t, δ is the average of VAR Xt − Xt − 4) ( Xt- Xt-4 over the prior eight quarters, and the variance of Xt- Xt-4 is also estimated over the prior eight quarters. 46
  • Appendix Scoring Methods To measure disclosure detail, we initially identify 10 income statement items, 13 balance sheet items and 4 cash flow items that form the basis for our scoring mechanism. We then assign weights to each item based on the following methods - Equal Scoring, Subjective Scoring and Market Scoring. For Equal Scoring, we assign equal weights of "1" to each item found on the quarterly press release, but only if the item also appears in the subsequent SEC filing. If the item does not appear in the subsequent SEC filing, we do not assign the item any weight, and ignore it in our scoring. Under Subjective Scoring, we assign each item a relative weight of “1”, “2”, or “3”, where a weight of “3” indicates high relative importance. For example, the item “Sales” is assigned a weight of “3” whereas the item “Income Tax Expense” is assigned a weight of “1”. Another example relates to the balance sheet: The items “Current Assets” and “Current Liabilities” are assigned weights of “3” because they facilitate the estimation of operating cash flows, while the items “Accounts Payable” and “Account Receivable” are assigned a weight of “2” because they facilitate estimation of operating cash flows with greater accuracy and facilitate estimation of current accruals. Under the Market Scoring mechanism we initially estimate the following regression model: ABSRETPit = β0t + β1tITEMjit + β2tTIMINGit + β3tLOGMKTit + β4tEARNVOLit+ β5tVOLUMEit + β6tFINAit +β7tANALYSTit + νit (A1) Where ITEMjit is an indicator variable that obtains the value of "1" if item j (27 items) appears in company i's press release for quarter t, and "0" otherwise. All the other variables are 47
  • as defined above. We obtain average coefficients and corresponding standard errors using the Fama and MacBeth, 1973 approach for 60 quarters. βj We compute market weights for each item as: . Table A1 lists the financial elements ∑β j j and weights for each scoring mechanism. (Table A1 about here) To obtain a score for each quarterly observation, we initially examine the 10-Q filing of the company in order to determine the maximum score possible. For instance, the item “inventory” is included in computing the maximum score only if the item was separately disclosed in the 10- Q filing. So technically, it is possible for each firm/quarter to have a different maximum score. Only then, we compute the actual score for the preliminary press release and divide it by the maximum score. We demonstrate the scoring mechanisms for the quarterly press release of AAR Corp. The actual score is 0.500, 0.509 and 0.770 using the Equal, Subjective and Market scoring mechanisms, respectively. 48
  • Table A1 Weights Weights Weights Equal Subjective Market Income statement (10 items): Sales 1 3 12 Cost of goods sold 1 2 2 SG&A expenses 1 2 5 Interest expense 1 1 1 Special items 1 2 4 Depreciation expenses 1 1 1 Non-operating income 1 2 3 Income tax expense 1 1 5 Net income from continuing operations 1 3 28 Extraordinary items 1 1 0 10 18 61 Balance sheet (13 items) Cash (and equivalents) 1 1 4 Accounts receivable 1 2 2 Inventory 1 2 3 Current assets 1 3 6 Property Plant and Equipment 1 1 4 Total assets 1 3 2 Short-term debt 1 2 2 Accounts payable 1 2 1 Current liabilities 1 3 6 Long-term debt 1 2 2 Other liabilities 1 1 2 Total liabilities 1 2 2 Stockholders equity, total 1 3 3 13 27 39 Cash flow (4 items) Net operating cash flow 1 3 0 Capital expenditures 1 3 0 Total investing cash flows 1 2 0 Total financing cash flows 1 3 0 4 11 0 Maximum Score 27 56 100 49
  • An example of an application of the scoring mechanism to a press release AAR REPORTS FISCAL YEAR 2006 FIRST QUARTER RESULTS • 22% sales growth; 109% income growth • 25% commercial sales growth; 16% defense services sales growth • 45% growth in Asia sales WOOD DALE, ILLINOIS (September 21, 2005) — AAR (NYSE: AIR) today reported net sales from continuing operations of $199.6 million for the first quarter of fiscal 2006, an increase of 22% compared to the prior year. Income from continuing operations more than doubled to $5.3 million or $0.15 per diluted share, from $2.5 million or $0.08 per diluted share in the year ago period, which included a $1.0 million pre-tax gain on extinguishment of debt. The sales and earnings growth for the quarter were driven by increased sales in the Aviation Supply Chain, Maintenance, Repair & Overhaul and Structures & Systems segments. Within the Aviation Supply Chain segment, sales increased 25% reflecting strong demand from our commercial and defense customers as AAR creates and provides cost-effective solutions for managing their supply chains. MRO segment sales increased 78% reflecting the commencement of operations at the Indianapolis Maintenance Center as well as increased sales at the Oklahoma maintenance facility. Structures and Systems sales increased 14% as the Company experienced stronger volumes across all businesses within this segment. Sales in the Aircraft Sales and Leasing segment were lower primarily due to joint venture accounting treatment, which excludes joint venture revenues from consolidated net sales. “This is a great start to fiscal 2006,” said David P. Storch, President and CEO of AAR. “We are seeing the benefits of the actions we have taken over the past few years to strengthen and grow the Company. Increasingly, our airline and defense customers are turning to AAR to meet their maintenance and engineering, supply chain and deployment needs.” Higher sales and operational efficiencies drove an improvement in gross profit margin from 16.2% to 17.4% year over year. Although selling, general and administrative costs increased as the Company made investments and prepared for growth, they declined as a total percentage of sales from 12.2% to 12.0%. Net interest expense was $0.5 million lower for the quarter due to lower average borrowings. The Company also made progress in its goal to improve asset performance, increasing working capital turnover from 3.0x to 3.6x. Investments in inventory primarily to support supply chain programs resulted in an operating cash outflow of $22 million for the quarter. We expect the returns from these investments to favorably impact results in future periods. Subsequent to the Company’s quarter-end, two valued customers, Delta Air Lines and Northwest Airlines, filed for bankruptcy. AAR was proactive in minimizing its exposure to these events, and the financial impact was minimal and was provided for in the first quarter. The Company continues to support both airlines by providing cost-effective solutions for their maintenance and supply requirements. Storch added, “We made progress on many fronts. Our results were significantly stronger than last year, and we won several new programs during the quarter, including the Airbus A400M cargo system program, a contract to provide pallets to the U.S. Air Force and the United Kingdom’s Royal Air Force E-3D AWACS and MESA Air Group supply chain programs, all of which should have a positive impact on future periods.” Storch continued, “We are also very pleased with the progress made at our recently-opened Indianapolis Maintenance Center, as the business unit produced profitable results in the quarter.” AAR is a leading provider of diverse products and value-added services to the worldwide aviation/aerospace industry. Headquartered in Wood Dale, Illinois, with locations around the world, AAR serves commercial and government aircraft fleet operators and independent service customers by providing Aviation Supply Chain services; Maintenance; Repair and Overhaul services; Structures and Systems manufacturing and Aircraft Sales and Leasing. Further information can be found at www.aarcorp.com. 50
  • AAR CORP. and Subsidiaries Three Months Ended August 31, 2005 2004 (Unaudited) Consolidated Statements of Operations (In thousands except per share data) Sales $ 199,588 $ 163,773 Cost and Expenses: Cost of sales 164,906 137,248 Selling, general and administrative 23,901 20,040 Equity in earnings of joint ventures 205 --- Operating income 10,986 6,485 Gain on extinguishment of debt --- 995 Interest expense 4,122 4,463 Interest income 459 283 Income from continuing operations before income taxes 7,323 3,300 Income tax expense 2,065 787 Income from continuing operations 5,258 2,513 Discontinued Operations: Operating loss, net of tax --- (227) Net income $ 5,258 $ 2,286 Share Data: Earnings per share - Basic: Earnings from continuing operations $ 0.16 $ 0.08 Loss from discontinued operations --- (0.01) Earnings per share – Basic $ 0.16 $ 0.07 Earnings per share – Diluted: Earnings from continuing operations $ 0.15 $ 0.08 Loss from discontinued operations --- (0.01) Earnings per share – Diluted $ 0.15 $ 0.07 Average shares outstanding – Basic 32,961 32,243 Average shares outstanding – Diluted 37,040 36,198 August 31 August 31 2005 2004 (Unaudited) (Derived from audited financial statements) Consolidated Balance Sheet Highlights Cash and cash equivalents $ 24,411 $ 50,338 Current assets 462,526 474,542 Current maturities of recourse LTD 437 2,123 Current liabilities (excluding debt accounts) 164,118 156,280 Net property, plant and equipment 72,565 71,474 Total assets 757,826 732,230 Recourse long-term debt 201,288 199,919 Total recourse debt 201,725 202,042 Total non-recourse debt 28,612 28,862 Stockholders’ equity 319,902 314,744 Book value per share $ 9.69 $ 9.66 Shares outstanding 33,004 32,586 51
  • Three Months Ended August 31, 2005 2004 Sales By Business Segment (In thousands - unaudited) Aviation Supply Chain $ 107,111 $ 85,846 Maintenance, Repair & Overhaul 37,972 21,281 Structures and Systems 51,360 44,948 Aircraft Sales and Leasing 3,145 11,698 $ 199,588 $ 163,773 Diluted Earnings Per Share Calculation (In thousands except per share data, Unaudited) Net income as reported $ 5,258 $ 2,286 Add: After-tax interest on convertible debt 306 313 Net income for diluted EPS calculation $ 5,564 $ 2,599 Basic shares outstanding 32,961 32,243 Additional shares due to: Assumed exercise of stock options 475 351 Assumed conversion of convertible debt 3,604 3,604 Diluted shares outstanding 37,040 36,198 Diluted earnings per share $ 0.15 $ 0.07 52
  • Scoring Sheet Equal Scoring Subjective Scoring Market Scoring AIR Quarter ended 8/2005 Filing Prelim. Actual Max Actual Score Actual Max Income statement (10 items): Sales 199.588 199.588 1 1 3 3 12 12 Cost of goods sold 158.815 164.906 1 1 2 2 2 2 SG&A 23.901 23.901 1 1 2 2 5 5 Interest expense 4.122 4.122 1 1 1 1 1 1 Special items 0.000 0.000 1 1 2 2 4 4 Depreciation expenses (in C/F statement) 6.091 NA 0 1 0 1 0 1 Non-operating income 0.664 0.664 1 1 2 2 3 3 Income tax expense 2.065 2.065 1 1 1 1 5 5 Net income from continuing operations 5.258 5.258 1 1 3 3 28 28 Extraordinary items 0.000 0.000 0 0 0 0 0 0 Balance sheet (13 items) Cash (and equivalents) 24.411 24.411 1 1 1 1 4 4 Accounts receivable 119.771 N/A 0 1 0 2 0 2 Inventory 277.232 N/A 0 1 0 2 0 3 Current assets 462.526 462.526 1 1 3 3 6 6 Property Plant and Equipment 175.471 N/A 0 1 0 1 0 4 Total assets 757.826 757.826 1 1 3 3 2 2 Short-term debt 2.280 N/A 0 1 0 2 0 2 Accounts payable 94.426 N/A 0 1 0 2 0 1 Current liabilities 166.398 N/A 0 1 0 3 0 6 Long-term debt 228.057 N/A 0 1 0 2 0 2 Other liabilities 22.061 N/A 0 1 0 1 0 2 Total liabilities 437.924 437.924 1 1 2 2 2 2 Stockholders equity, total 319.902 319.902 1 1 3 3 3 3 Cash flow (4 items) Net operating cash flow -21.698 N/A 0 1 0 3 0 0 Capital expenditures 4.695 N/A 0 1 0 3 0 0 Total investing cash flows -4.089 N/A 0 1 0 2 0 0 Total financing cash flows -0.128 N/A 0 1 0 3 0 0 13 26 28 55 77 100 Score 0.500 0.509 0.770 53