Firms prepare their financial statements to provide the information to their end users including potential investors along with other capital market players. The incentive for firms to produce useful information is to protect those potential investors, who become one of their funds generating sources. They are also part of the capital market that influences the total market value of individual firms. For that purpose, Othman and Zeghal (2006) discuss the country policies on the investor protection to establish an economy that is sustainable and stable for the overall growth of the economy. Knowing these users influence the market value, firms have that added pressure of making up the numbers to present better view of their performance (Levitt, 1998). Schipper (1989) defines earnings management as the use of discretionary powers by firms to manage the earnings and dress up the numbers to show good performance.

Furthermore, Healy and Wahlen (1999) also define it as the use of discretionary choices to hide the actual financial performance and alter the financial reports to achieve the targets. Prior literature has provided the two techniques to used measure the earnings management. Jones (1991) introduces the Accruals Earnings Management (AEM) technique, which Kothari et al. (2005) modifies. Roychowdhury (2006) gives another technique that is, Real Earnings Management (REM). The authors use both techniques in their statistical analyses of this study.

Firms’ earnings announcements affect their share price returns. Potential investors require financial information to make any informed investing decision. First source of such information is the financial statements that firms prepare and issue that is, earnings announcement. Lyle et al. (2018) discuss the difference in the market reaction in relation to the timing of the earnings announcement. They believe that the firms, which announce the earnings outside of regular trading hours, give investors enough time to process the financial information before the trading begins again. Therefore, the announcements during the pre-open period have slower market reactions. Beaver et al. (2020) deal with the change in the market response towards the earnings announcement during different periods. They document increased response during 2001-2011 and over time. The authors analyze the effects of earnings quality on the market returns and differentiate the users of financial statements into potential investors and financial analysts. 

This study focuses on the study of earnings quality and its effects on investors’ decision-making, which further explains the behavior of firms’ returns adjusted against the market. Prior literature mostly deals with the earnings surprises. Frankel et al. (2010) investigate the effects of missing forecasting targets on investors’ relations. They use analysts’ conference calls with managers as the proxy of investor relations and analyze the effects of small negative earnings surprises. A survey study was done to analyze the effects of missing market expectations on the investor relations and they find that the firms that miss expectations generally have longer call lengths. This relationship is the negative effect of missing market expectation on investors’ relations. No significant evidence was found to support Graham et al. (2005) that missing earnings benchmark results in severe economic implications.

While Keung et al. (2010) studied market reaction to the positive earnings surprises, and found that investors are skeptical when firms just meet or beat their earnings expectations and consider the existence of earnings management. Other studies discuss the use of earnings management to meet or beat analysts’ forecasts in case of Buy (Sell) rated firms (Abarbanell and Lehavy, 2003), and use of earnings management to achieve financial targets (Burgstahler and Eames, 2006). Abarbanell and Lehav (2003) explain how firms are motivated to meet or beat their targets when rated as a Buy and vice-versa in case of Sell. Burgstahler and Eames (2006) find that firms manage their earnings to meet or beat their earnings expectation to have zero or small positive earnings surprises to avoid consequences of earnings shocks. 

The study is motivated by the prior literature and talks about the effects of earnings management on firms’ returns on the stock market adjusted by the capital market returns. We explain this phenomenon in two stages: the first stage explains how firms are motivated to manage their earnings to meet or beat earnings targets (Abarbanell and Lehavy, 2003) and the second stage talks about the reactions of the market to the quality of the earnings reports and earnings surprises thereof on firms’ stock returns adjusted against the market’s return. Existing literature mostly focuses on the relationship between small positive (negative) earnings surprises and the share price returns. Therefore, there is a need for an extension to the existing literature and our study contributes to the literature by including the share price returns of the firms adjusted against the markets, which minimizes the unwanted effects of extremely positive (negative) returns. 

The method used for the empirical analysis is in two- folds: the earnings management was measured at the first stage. At the second stage, the earnings management was applied as proxies to empirically test the study hypotheses. Prior studies often only use one measure of earnings management in their analysis. To provide robust results, both measures of the earnings management were used, AEM (Kothari et al., 2005) and REM (Roychowdhury, 2006). Kothari et al. (2005) used the performance-matching approach to estimate the earnings management, that is, equation (1). The discretionary accruals were estimated for each firm i in a year t (that is, residuals ) by regressing equation 1, cross-sectionally for the firms within the same 2-digit SIC code each year. 

The earnings surprise is measured as the difference between the reported earnings and I/B/E/S mean earnings forecast 45-days before the firms announce their earnings instead of using the latest I/B/E/S mean earnings forecasts commonly used in literature. The latest earnings forecasts do not provide firms sufficient time to manage earnings to meet or beat their targets. These forecasts might also generate the number closer to reported earnings anyway after incorporating all the recent and private information. Therefore, it is assumed that a 45-day window provides firms with reasonable incentives and motivations to manage their earnings to meet or beat the targets to avoid earnings shocks (or bad news) and untoward market reactions.

The multivariate models explain how firms manage earnings (PEM or NEM) to achieve their financial targets. The financial targets of firms can include meeting or beating forecasts, issuing good news to market players to receive positive market reactions and consequently achieve positive MAR. Similar to Keung et al. (2010), the initial primary MAR period consists of 3-day window from one day prior to one day after the earnings announcement; but a market model was used to measure the cumulative abnormal return based on Fuller et al. (2002) and Rosen (2006) who used Brown and Warner (1985)’s market-adjusted return model. The market-adjusted return model is used to eliminate the data complexity of the market model. Two 2-day windows were used to check for the robustness of the results. One of these two windows consists of the day of earnings announcement and a day after [0 +1], and the second window consists of the day before the earnings announcement and the day of earnings announcement [-1 0]. 

Given past studies in earnings management and earnings surprises, the models include several control variables. The variables Price-to-Book value and Analysts based on PBValue, Log_Assets and Log_AF, respectively explain varying degrees of the size of firms. Literature does not explicitly employ these variables on share price returns, but these variables have significant effect on earnings management and forecast accuracy (Embong and Hosseini, 2018; Richardson, 2000). PBValue is expected to have a positive sign with returns because it shows there is good news to market players if it is higher. Log_AF has positive relationship because bigger sized firms attract more followers (including all stakeholders), which generates public information for all analysts to produce a consensus forecast with low dispersion. One of the two incentives used to manage earnings is to avoid debt covenant violation (Richardson, 2000); therefore, Leverage (LEV) is included to control the firms’ leverage risk. Firms engage less with earnings management when they are audited by big four auditing firms, and it plays a role in their earnings quality (Clinch et al., 2012). Assuming market players react better when they have confidence in the quality of earnings report and its informational value. Thus we expect Audit Quality (AQ) to have positive sign with MAR. Table 2 describes the variables included in the empirical analyses.

The empirical analysis is in two-fold: in the first stage, the earnings management was measured by using equations 1 to 4. In the second stage, the regressions were run on equations 5 and 6. The second stage of the empirical analysis is in two-fold, which includes the primary analysis with earnings management, and robustness check with earnings surprises.

Primary analysis

The primary analysis includes regression of the multivariate-pooled OLS heteroscedasticity-consistent standard errors and firm-specified panel regression on equation 5. The earnings management was used as the explanatory variable on the firms’ MAR with 3-day window starting from one day before the earnings announcement to one day after [-1, +1].

Table 5 includes the results of the primary analysis. The results are consistent with Burgstahler and Eames (2006), who believe that firms manage their earnings to avoid severe economic consequences. The magnitude of earnings management (AEM and REM) has significant positive relationship with MAR. This means that firms, which involve in these discretionary activities, benefit from the positive market reaction with better stock returns. The results are in line with hypothesis H1 of this study, which states that, the magnitude of the earnings management is positively associated with MAR.

Moreover, as described earlier, the study extends the literature and divides the firms based on their attitude towards the earnings management. H1_a of the study says that firms with PEM attitude should realize better stock returns and vice versa in case of H1_b for the NEM firms. The results consistently show that firms with PEM (P_AEM or P_REM) have positive relationship with their MAR (that is, 0.380* or 0.058**). While firms with NEM (N_AEM or N_REM) show a negative relationship (that is, -0.167 or -0.051). In cases of N_AEM and N_REM, they do not find significant coefficients, but they show negative signs, as expected and in line with hypothesis H1_b. The control variables, except PBValue, show accurate signs of consistency with the prior literature and significant coefficients except AQ. Table 6 from firm-specified panel regression shows consistently similar results as in Table 5 from pooled OLS heteroscedasticity-consistent standard errors regression.

Robustness check

Similarly, the authors run multivariate-pooled OLS heteroscedasticity-consistent standard errors regression on equation 6. Earnings surprise is used as the explanatory variable on the firms’ MAR with all three short interval 3-day and 2-day windows [-1, +1], [0, +1] and [-1, 0], respectively.

Table 7 presents the results of hypotheses H2, H2_a and H2_b of this study. Hypothesis H2 states that the magnitude of the earnings surprises has positive relationship with firms’ MAR. Since magnitude uses the absolute values, that is, non–negative values, it is expected to have positive linear relationship. The results in Table 7 support hypothesis H2, which shows the significant positive coefficients of absolute values of earnings surprises (Abs_ES) with MAR across all three windows.

This study investigates the link between firms’ intentions to achieve financial targets and the stock returns. The study contributes to the extensive literature in using the stock returns adjusted against the market. The study also adds to the literature by using the 3 different short interval windows of the market-adjusted return. The researchers place little importance on the use of firms’ attitude (PEM and NEM) to analyze the effects on stock market performance. The researchers investigate earnings surprises (good news or bad news) separately. This study covers all these aspects of the literature and provides robust results. The results consistently support the study hypotheses and the existing literature from different empirical tests. They provide empirical evidence, using various analyses including multivariate pooled OLS heteroskedasticity-consistent standard error regression and firm-specific and industry-specific panel regression, that the firms use discretionary powers to manage their earnings to meet or beat the Wall Street Journal earnings expectations or forecasts. They do so to improve their stock market performance, that is, stock returns and avoid any severe consequences in the capital markets. The results are consistent with the earnings surprises, with good news or positive earnings surprises to improve the stock returns and vice versa in case of bad news or negative earnings surprises.

While this study contributes to the literature on a few fronts, there are limitations also. There is more work required on the use of PEM and NEM and earnings surprises. NEM attitude is not synonymous to bad news and this study does not differentiate between the NEM firms with good news and bad news. The other limitation of this study is the use of the US market only, which limits the sample size. This study includes 80.7% of firms audited by big four firms. This represents the number of big-sized firms limiting the wider application. Future research can help to overcome these limitations and expand the reach of the literature.

The authors have not declared any conflicts of interests