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مهندسی صنایع و مدیریت صنعتی - BOOK1
 
یکشنبه 29 آبان 1390 :: نویسنده : ALI MAHDAVI
BOOK 

Table 3

Pooled cross-sectional regressions of excess returns on change in earnings per share and analysts’ forecast errors

Estimated coefficients:

Regime CEPS AFE Adj. R2 F-value

North America (n = 22530) 0.177 (12.0)* 0.352 (8.72)* 0.0126 145.2*

Other Anglo-Saxon (n = 13604) 0.128 (6.95)* 0.305 (6.03)* 0.0105 73.3*

Nordic (n = 1918) 0.084 (3.99)* 0.171 (2.39)* 0.0118 12.4*

Developed Latin (n = 4163) 0.079 (4.11)* 0.223 (3.99)* 0.0073 16.2*

Emerging Latin (n = 420) 0.094 (2.46)** 0.153 (1.54) 0.0210 5.49*

Germanic (n = 3722) 0.124 (5.44)* 0.357 (5.70)* 0.0153 29.9*

Japanese (n = 16023) 0.049 (2.11)** 0.003 (0.04) 0.0002 2.97

Emerging Asian/Near East (n = 3741) 0.040 (2.47)** 0.144 (2.72)* 0.0059 12.2*

Regimes defined in Fig. 1. Excess returns are 1-month mean-adjusted returns during the month of earnings release. CEPS

are change in annual earnings per share between time τ and τ 1 deflated by price. AFE are Actual I/B/E/S annual

earnings per share less I/B/E/S forecast of annual EPS deflated by price. The t-tests (in parentheses) are calculated using

White’s (1980) consistency covariance matrix.

* Significant at p < 0.01.

** Significant at p < 0.05.

little reaction to the release of earnings during the early period providing limited support for the

rejection of H1mp in most regimes during this period. Results of regressions using data from the

middle time period (presented in PanelBofTable 4) reveal a substantial increase in the significance

of the market response to the release of earnings. Specifically, for both the regressions of excess

returns on CEPS and on AFE, coefficients are positive and are significant in five of the eight

regimes. The regressions estimated using data from the late time period, presented in Panel C of

Table 4, are similar to those from the middle period. Taken together, the tests of H1mp suggest

an increase in the market reaction to the release of earnings.12

The second multi-period hypothesis involves the examination of incremental information content

of AFE versus CEPS. The results of this analysis during the early period are presented in

Panel A of Table 5. CEPS is significant only in North America and Developed Latin regimes

while AFE is significant only in the North America regime. The results provide little support for

the rejection of H2mp in any regime other than the North America during this period. The results

from the middle and late periods (reported in Panels B and C) provide greater support for the

rejection of H2mp. Specifically, the AFE coefficient is positive and significant in six (five) of the

eight regimes during middle (late) period. Overall, the results from the middle and late periods

provide support for the rejection of H2mp, indicating that there is a market reaction when earnings

do not conform to analyst expectations. This suggests that investors incorporate analyst forecasts

in the formulation of earnings expectations. The lack of reaction to the AFE in the Japanese and

Emerging Asian/Near East regimes provides little evidence of a market reaction to forecast errors

in these regimes.

The results of the test of H2mp appear to reveal a substantial increase in the significance of

analyst forecast errors from the early time period to the middle time period. The final hypothesis

12 Though there is a trend toward increased significance of the earnings–returns relationship, exceptions exist. For

example, in the Developed Latin regime, the CEPS model is significant in the early period, moderately significant in the

middle period and loses significance in the late period. In contrast the AFE model gains significance in the middle period

and remains significant in the late period. Thus, a potential explanation for this trend is that investors are relying more on

analyst forecasts and less on prior years’ earnings in forming earnings expectations.

...........................................................

Table 3

Pooled cross-sectional regressions of excess returns on change in earnings per share and analysts’ forecast errors

Estimated coefficients:

Regime CEPS AFE Adj. R2 F-value

North America (n = 22530) 0.177 (12.0)* 0.352 (8.72)* 0.0126 145.2*

Other Anglo-Saxon (n = 13604) 0.128 (6.95)* 0.305 (6.03)* 0.0105 73.3*

Nordic (n = 1918) 0.084 (3.99)* 0.171 (2.39)* 0.0118 12.4*

Developed Latin (n = 4163) 0.079 (4.11)* 0.223 (3.99)* 0.0073 16.2*

Emerging Latin (n = 420) 0.094 (2.46)** 0.153 (1.54) 0.0210 5.49*

Germanic (n = 3722) 0.124 (5.44)* 0.357 (5.70)* 0.0153 29.9*

Japanese (n = 16023) 0.049 (2.11)** 0.003 (0.04) 0.0002 2.97

Emerging Asian/Near East (n = 3741) 0.040 (2.47)** 0.144 (2.72)* 0.0059 12.2*

Regimes defined in Fig. 1. Excess returns are 1-month mean-adjusted returns during the month of earnings release. CEPS

are change in annual earnings per share between time τ and τ 1 deflated by price. AFE are Actual I/B/E/S annual

earnings per share less I/B/E/S forecast of annual EPS deflated by price. The t-tests (in parentheses) are calculated using

White’s (1980) consistency covariance matrix.

* Significant at p < 0.01.

** Significant at p < 0.05.

little reaction to the release of earnings during the early period providing limited support for the

rejection of H1mp in most regimes during this period. Results of regressions using data from the

middle time period (presented in PanelBofTable 4) reveal a substantial increase in the significance

of the market response to the release of earnings. Specifically, for both the regressions of excess

returns on CEPS and on AFE, coefficients are positive and are significant in five of the eight

regimes. The regressions estimated using data from the late time period, presented in Panel C of

Table 4, are similar to those from the middle period. Taken together, the tests of H1mp suggest

an increase in the market reaction to the release of earnings.12

The second multi-period hypothesis involves the examination of incremental information content

of AFE versus CEPS. The results of this analysis during the early period are presented in

Panel A of Table 5. CEPS is significant only in North America and Developed Latin regimes

while AFE is significant only in the North America regime. The results provide little support for

the rejection of H2mp in any regime other than the North America during this period. The results

from the middle and late periods (reported in Panels B and C) provide greater support for the

rejection of H2mp. Specifically, the AFE coefficient is positive and significant in six (five) of the

eight regimes during middle (late) period. Overall, the results from the middle and late periods

provide support for the rejection of H2mp, indicating that there is a market reaction when earnings

do not conform to analyst expectations. This suggests that investors incorporate analyst forecasts

in the formulation of earnings expectations. The lack of reaction to the AFE in the Japanese and

Emerging Asian/Near East regimes provides little evidence of a market reaction to forecast errors

in these regimes.

The results of the test of H2mp appear to reveal a substantial increase in the significance of

analyst forecast errors from the early time period to the middle time period. The final hypothesis

12 Though there is a trend toward increased significance of the earnings–returns relationship, exceptions exist. For

example, in the Developed Latin regime, the CEPS model is significant in the early period, moderately significant in the

middle period and loses significance in the late period. In contrast the AFE model gains significance in the middle period

and remains significant in the late period. Thus, a potential explanation for this trend is that investors are relying more on

analyst forecasts and less on prior years’ earnings in forming earnings expectations.

.........................................

explicitly examines changes in the earnings–returns relation over time. Specifically, the relationship

between time, the estimated coefficients for unexpected earnings (i.e., change in earnings

per share and analyst forecast errors), the t-statistics of the estimated coefficients for unexpected

earnings and adjusted-R2s from the regressions. Each of the three models used in the previous

analysis are tested using this methodology.

Results of Spearman correlation analysis (presented in Table 6) reveal a significant relation

between time and adjusted-R2 in every model considered. In addition, Spearman correlations

reveal a significant positive relationship between the t-statistic from the regression of excess

returns on CEPS and time. Country-specific correlation analysis using a sample of 94 countryperiod

observations (not reported), reveals significant correlations between time and the AFE

t-statistic for both the regression of excess returns on AFE and the regression of excess returns

on CEPS and AFE. Thus, the results of this analysis support the rejection of H3mp.

Hypothesis H3mp is also tested by examining the statistical significance of changes in adjusted-

R2s over time. Table 7 reports time period comparisons in adjusted-R2s (and accompanying

Vuong statistics) for each regime. Specifically, adjusted-R2s are reported for the early versus late

period, the early versus the middle period and the middle versus the late period for each of the

three earnings–returns models. The results of this analysis suggest a significant increase in the

explanatory power of the three models. Specifically, the increase in adjusted-R2s is positive and

significant in 14 of 22 cases for the CEPS model, 12 of 22 cases for the AFE model and 17 of

22 cases for the combined AFE and CEPS model. In addition, the increase in adjusted-R2s is

positive and significant over the entire time period (early versus late) for five, four, and six of

eight regimes in the CEPS, AFE, and combined CEPS and AFE model, respectively. These results

provide support for rejection of the final hypothesis.

The results of this analysis document a significant increase in the importance of earnings data

and analyst forecasts in explaining returns around earnings releases. This could be the result of

many factors. First, improvements in accounting standards and corporate governance mechanisms

may have enhanced earnings quality. Earnings data may be more informative about a company’s

current and future performance, making it more value relevant. Investors may have more timely

access to earnings and analyst forecasts than in the previous period. In addition, typical investors

might have become more efficient and/or effective in their processing of information. Finally,

increases in the accuracy of analyst earnings forecasts may have strengthened the relationship.

7. Conclusion and implications

Using a global sample, I examine international differences in and the stability of the market

reaction to the release of earnings. Factors such as variation in accounting standards, corporate

governance and capital markets may cause differences in the reaction to the release of earnings.

A regression of returns on change in earnings per share and/or analyst forecast errors is used

to identify a market response to the release of earnings. A significant market reaction to the

announcement of accounting earnings is identified in all regimes when data from the entire research

period are used in analysis. This indicates that accounting information is relevant to investors

across the world. Additional analysis suggests that analysts forecast errors have incremental

explanatory power of change in earnings per share in many regimes, indicating the investors use

analysts’ forecasts when forming earnings expectations.

The multi-period analysis suggests a greater response to the release of earnings in recent years in

many accounting regimes. In the early time period, there is little evidence of a market reaction to the

release of earnings. From the early and middle time periods, there is an increase in the significance

...................................

of the relationship between unexpected earnings and returns. In addition the explanatory power and

significance of both the change in EPS and analyst forecast errors have increased over time. The

increase in the significance may be the result of improvements in accounting standards or corporate

governance mechanisms, changes in capital markets and increased access to information.

The results of this study may be of interest to researchers, investors, standard setters and

educators. Though the results of this paper suggest an increase in the reaction to the release of

earnings, factors influencing this trend are not empirically examined. Therefore, future research

in this area is necessary. Another potential research topic is a comparison of daily market response

to the release of earnings in a less extensive group of countries. Short-term may better allow for

the determination of relative quality of accounting standards.

Investors can use the results of this analysis to improve decisions. Specifically, the lack of

reaction to forecast errors may be an indication that investors are not incorporating this information

into earnings expectations, and thus, the security prices. This may indicate that abnormal returns

could be earned based on such information.

The results of this study may be of interest to standard setters. Specifically, the increase in

significance of earnings and/or analyst forecasts in recent time periods may be partially caused by

improvements in accounting standards. If so, such standards improvements may provide guidance

to less developed countries attempting to develop accounting standards. This could lead to higher

quality accounting standards in such countries.

Educators could integrate the results of this paper in upper level or graduate accounting classes.

Specifically, this paper could be used to show that the market reaction to earnings varies arcross

countries. In addition, it could be used to demonstrate that the market reaction to earnings may

not be stable over time. Thus, this could provide a basis for discussing the many factors that can

influence the market response to earnings.

Acknowledgements

This paper is based on my dissertation completed atKent State University. Iwould like to thank

each member of my dissertation committee for their encouragement and support: Ran Barniv

(Chair), James Baker, Robert Bloom (John Carroll University) and Joanne Healy. I would like to

thank Manoj Athavale, Dan Brickner, Chuck Brown, Judy Lane, Chris Luchs, the participants at the

2002 AAA International Section Midyear Meeting, the 2002 AAA National Meeting, workshops

at John Carroll University, and the University of Saskatchewan for their useful comments. I

gratefully acknowledge the contributions of I/B/E/S International Inc. for providing earnings

per share forecast data from their Institutional Brokers Estimate System. These data have been

provided as part of a broad academic program to encourage earnings expectations research.

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