A Study of Quarterly Earnings Announcement and Stock ... - EBSCOhost

A Study of Quarterly Earnings Announcement and Stock Price Reactions T Mallikarjunappa* and Janet Jyothi Dsouza**

The purpose of the study is to investigate whether there are any significant abnormal returns around the quarterly earnings announcement and to examine whether the semi-strong form of Efficient Market Hypothesis (EMH) applies to the Indian stock market. This study focuses on the BSE200 index-based companies listed on the Bombay Stock Exchange (BSE) and uses quarterly earnings announcement as an event. We use event study methodology to examine the behavior of the stock prices. The results show that the security prices are predictable based on quarterly earnings announcement information and predictability can generate abnormal profits.

Introduction The Efficient Market Hypothesis (EMH), developed by Fama in the early 1960s, says that stock prices reflect all the information, and trading on the basis of this information will not produce abnormal profit. Further, Jensen (1978) argued for the same theory by stating that it is not possible to make economic profits by trading on the basis of new information. Thus, EMH asserts that it would be difficult to consistently outperform the market based on any new information. The EMH has been debated and tested by academicians over the years in different markets by using different sets of data. Much of the work on EMH is not able to provide empirical evidence to conclusively prove the existence/non-existence of the market efficiency. Therefore, we examine the EMH in the Indian stock market by investigating the semi-strong form of EMH. Semi-strong form of EMH can be examined by taking different public announcements and by testing how the stock prices respond to these announcements. One of the ways to test the EMH is to examine the stock price response to quarterly earnings announcement. The stock prices move as the market moves. Therefore, we can use the movement of the market to find the expected returns on the stocks. In this paper, we use mean adjusted model, market adjusted model and market model to examine the abnormal performance of sample companies during the quarterly earnings announcement.

Literature Review Semi-strong form of market efficiency states that stock market prices reflect all publicly available information and therefore, trading on the basis of this information is not profitable. If this is true, investors have no scope to outperform the market by trading on publicly *

Professor, Department of Business Administration, Mangalore University, Mangalagangothri 574199, Mangalore, Karnataka, India. E-mail: [email protected]

* * Research Scholar, Department of Business Administration, Mangalore University, Mangalagangothri 574199, Mangalore, Karnataka, India. E-mail: [email protected] © 2014 IUP. All Rights Reserved. 94

The IUP Journal of Applied Finance, Vol. 20, No. 4, 2014

available information. The EMH was first formally stated by Fama (1965). He argued that actual prices of individual securities already reflect the effects of information based on events. Fama (1965, 1970) focused mainly on informational efficiency of security prices. Ball and Brown (1968), Foster (1977), Soffer and Lys (1999), and Brown and Han (2000) examined the security market’s reaction to information pertaining to earnings and found that the market is efficient. Fama et al. (1969) undertook the first ever event study and found that market reactions are considerably good prior to the stock split announcement and therefore, they concluded that market is efficient. May (1971), Brown and Kennely (1972) and Jordan (1973) examined the behavior of security prices and the evidences suggested that security prices reflect earnings information and therefore, the investors cannot outperform the market based on publicly available information. Srinivasan (1997) examined the security prices behavior associated with rights issue-related events. Rao (1994) investigated the share price responses to some of the corporate financial policy announcements. Kabir and Sackley (1996) supported EMH by stating that security prices absorb the new information and therefore, there is no abnormal return by trading on new information. Bharath and Shankar (2012) examined semi-strong form of market efficiency of Indian stock market and found that during the price adjustment period markets adjusted rapidly to the new information flow and the investors earned no abnormal returns. Even though the above studies supported the EMH in developed and developing economies like India, there are a few studies which questioned its validity and found that the market is inefficient. Rendleman et al. (1982), Foster et al. (1984), Bernard and Thomas (1989 and 1990), Freeman and Tse (1989) and Mendenhall (1991) argue that the stock markets do not adjust instantly to new information flow and therefore investors can make abnormal profits by trading on the basis of earnings data. Obaidullah (1990) tested the market efficiency by analyzing the stock price adjustment to half-yearly earnings announcements and this study did not support the semi-strong form of EMH. Ball and Kothari (1991) concluded that earnings announcement usually include information which is not available to the market and excess returns are generated on the announcement day. Chaturvedi (2000a and 2000b) provided evidence for the market inefficiency. Jijo and Narayan (2002) found 7.69% abnormal returns during the stock split announcements. Mallikarjunappa (2004), Iqbal and Mallikarjunappa (2007, 2008a, 2008b, 2010, and 2011) found that the Indian stock market is slow in reacting to quarterly earnings announcements and provided an opportunity to earn excess return. Raja and Sudhahar (2010) examined the efficiency of Indian stock market with respect to bonus issue announcement by IT companies which are listed on BSE and found that market is inefficient with respect to information disseminations and investors can earn abnormal returns. Rufus (2011) investigated stock price reaction in the Nigerian stock market and found that the stock market is inefficient. Mallikarjunappa and Dsouza (2013) found significant cumulative average abnormal return values after the earnings announcements. All these evidences demonstrate that earnings announcements contain information value which is not available to the market and the stock prices fail to reflect all the information released to the public. A Study of Quarterly Earnings Announcement and Stock Price Reactions

95

In the literature, a few studies supported the EMH by observing zero abnormal returns and some studies observed abnormal returns and empirically proved market inefficiency. This mixed evidence gives further scope for the empirical investigation of EMH of capital market.

Objectives This study is undertaken with the following objectives: • To test whether Indian stock market follows semi-strong form of EMH. • To test the stock market reactions to quarterly earnings announcement.

Hypotheses We have tested the following hypotheses: • The Average Abnormal Return (AAR) and Cumulative Average Abnormal Return (CAAR) are almost equal to zero. • There is randomness in the occurrence of AARs. • The numbers of positive and negative AARs are equal.

Data The event study methodology is used to examine the informational value in security prices following the quarterly earnings announcement. We observe abnormal return by using daily data. The BSE200 companies are selected as sample companies as they are liquid and well traded stocks. These companies are considered as top companies as they are ranked based on full market capitalization, average free-float market capitalization and average turnover for preceding three months. These companies accounted for about 84.13% market capitalization of the BSE on December 31, 2011. The highly liquid stocks are the Sensex stocks. We have taken BSE200 index companies to test on a larger sample. As they are liquid stocks, the impact of quarterly earnings announcement of these companies on the stock prices is expected to be fast. We took all the companies which had announced their quarterly results following December 2011 quarter ending. However, we could not get the data for 15 companies as their quarterly results were not available from the published sources. Therefore, we restricted our final sample to 185 companies. During 2011, the Indian economy witnessed the slowest pace of growth in almost all the sectors. The slow growth, high inflation and larger fiscal and current account deficits had negative influence on trade and commerce during 2011. During the year 2011-12, the capital mobilized through primary market also declined. Given this type of economic condition, we want to examine how the market reacts to earnings announcements by the companies. Usually, normal period is considered for assessing the market efficiency. But we want to examine whether the market participants absorb the information during low growth period also. Therefore, we chose December 2011 quarterly results to ascertain the stock market movement during this period. We have used four sets of data. The first set of data consists of quarterly earnings announcement made by the sample companies. Here, we have used media announcement or stock exchange announcement dates, whichever is earlier, as an event for the sample companies. The second set of data consists of daily adjusted closing prices of sample companies which are listed on BSE. The 96


third set of data consists of the daily closing prices of BSE200 index. Finally, we have collected the net profit and net sales of the sample companies for the construction of the portfolio. On the basis of percentage change in the net profit and net sales of current and corresponding quarters, the sample companies are categorized as ‘good news’ and ‘bad news’ portfolios. The firms with positive change in the net profit and net sales of current and corresponding quarters are considered as ‘good news’ portfolio and the negative percentage change in the net profit and net sales of current and corresponding quarters as ‘bad news’ portfolio. The third one is overall portfolio, which includes all the sample firms selected under the study. The good news portfolio consists of 102 companies, 83 companies are included in the bad news portfolio and all 185 companies are included in the overall portfolio. The data is collected from the Center for Monitoring Indian Economy (CMIE).

Methodology Fama et al. (1969) is the first available event study methodology. Thereafter, Brown and Warner (1980), Masulis (1980), Dann (1981), Holthausen (1981), Leftwich (1981), DeAngelo and Rice (1983), McNichols and Manegold (1983), Srinivasan (1997), Mallikarjunappa (2004), Iqbal and Mallikarjunappa (2007, 2008a, 2008b, 2010, and 2011) and Mallikarjunappa and Dsouza (2013) have used this methodology to examine the stock market behavior to various corporate events. We use the same methodology to examine the market reactions on quarterly earnings announcements. The dates on which quarterly earnings announcements are released by the sample companies are defined as the event dates (t = 0). The 61 days surrounding the announcement of earnings, 30 days prior and 30 days after the earnings announcement (i.e., t = –30, …, 0, …, +30 ) are denoted as the ‘event’ period or event window. The days before the event period (i.e., –280, …, –31) are designated as the ‘estimation’ or ‘non-event’ period. The abnormal returns of the companies for the event window are calculated using mean adjusted model, market adjusted model and market model (Cowles, 1933; Sharpe, 1964; Latane and Jones, 1979; and Masulis, 1980). The calculated abnormal returns are averaged across securities to obtain AARs. The AARs are cumulated over time to calculate CAARs. The above three models were used by Brown and Warner (1980, pp. 207-209) to generate excess return. We compute the AARs and CAARs based on this methodology. A number of other studies have also used this methodology. We expect that quarterly earnings impact the stock prices. To account for the general market movements, we fit an OLS that captures the price reactions due to market.

Parametric Significance Test Parametric t test is used to know whether the AARs and CAARs are different from zero. We test the hypothesis that the AARs and CAARs are different from zero at 5% level of significance. We expect that AARs and CAARs values should be close to zero in an efficient market.

Non-Parametric Significance Test In addition to t-test, non-parametric tests like Runs and Sign tests are used to test the hypothesis. A Study of Quarterly Earnings Announcement and Stock Price Reactions

97

Runs test: This test was developed by Levene (1952) to analyze the randomness in the behavior of observed numbers. In this paper, we apply Runs test on AARs before and after the event day and also for the entire event window to test for the randomness in the occurrence of AARs. Sign test: Mendenhall et al. (1989) developed Sign test which considers positive and negative signs instead of quantitative values. The null hypothesis of the equal number of positive and negative AARs is tested using this test. We apply Sign test statistics before and after the event day and also for the event window.

Results and Discussion We examine the stock price reactions to firms’ quarterly earnings announcements. We assess the abnormal performance of each sample securities by using mean adjusted model, market adjusted model and market model. We further subdivide the sample into good news, bad news and full sample portfolios. From Figure 1 it is observed that under the mean adjusted model, AARs are positive for 49 days and negative for 12 days. It is further observed that CAAR values are positive for 54 days and negative for only 7 days. When we observe market adjusted model for the event window of 61 days, AARs are positive for 42 days and negative for 19 days. The results of CAAR values show that they are positive for 51 days and negative for 10 days. In the case of market model, out of 61 days, AARs are positive for 43 days and negative for 18 days and CAAR values are positive for 52 days and negative for 9 days. The results of all the three models show that AAR and CAAR values are positive for majority of the days. Further, the AAR and CAAR values are positive on the event day (t = 0) for all the three models in the event period. This indicates that market expected good news from the quarterly earnings announcement and same is conveyed in the earnings. Figure 2 presents the results of bad news earnings announcements. Under the mean adjusted model, during the entire event window of 61 days, AARs are positive for 52 days and negative for 9 days. It is further observed that CAAR values are positive for 60 days and negative for only1day (t = –30). The results of market adjusted model reveal that AARs are positive for 35 days and negative for 26 days. The results of CAAR values show that they are positive for 58 days and negative for 3 days during the event window. In the case of market model, out of 61 days, AARs are positive for 46 days and negative for 15 days, whereas CAAR values are positive for 56 days and negative for 5 days. The AAR and CAAR values of all the three models are positive for majority of the days. This implies that good news is conveyed to the market even though individual company profits in the bad news portfolio have not increased. Figure 3 reports the results of full sample earnings announcements. The mean adjusted model shows that AARs are positive for 52 days and negative for 9 days. It is further observed that CAAR values are positive for 56 days and negative for only 5 days. In the case of market adjusted model, for the event window of 61 days, AARs are positive for 39 days and negative for 22 days. The results of CAAR values show that they are positive for 52 days and negative for 9 98


Figure 1: AARs and CAARs Trends of Three Models Over the 61-Day Event Window of Good News Earnings Announcement

AAR and CAAR

0.2500 Mean Adjusted Model AAR

0.2000

Mean Adjusted Model CAAR Market Adjusted Model AAR

0.1500

Market Adjusted Model CAAR 0.1000

Market Model AAR Market Model CAAR

0.0500 0.0000 –30 –26 –22 –1 8 –1 4 –1 0 –6 –2 2 –0.0500

6 10 14 18 22 26 30

Day Relative to the Announcement

Figure 2: AARs and CAARs Trends of Three Models Over the 61-Day Event Window of Bad News Earnings Announcement

AAR and CAAR

0.3498 0.2998

Mean Adjusted Model AAR

0.2498

Mean Adjusted Model CAAR

0.1998

Market Adjusted Model AAR

0.1498

Market Adjusted Model CAAR

0.0998

Market Model AAR

0.0498

Market Model CAAR

–0.0002 –30 –26 –22 –18 –14 –10 –6 –2 2

6

10 14

18 22

26 30


days during the event window. This implies that most of the AAR and CAAR values are positive both for before and after the event date. The market model reveals that out of 61 days, AARs are positive for 47 days and negative for 14 days. In the case of CAAR, the values are positive for 54 days and negative for 7 days. The results of all the three models show positive AAR and CAAR values during the earnings announcement. Further, a close observation of all the three portfolios reveals that all the CAAR values are positive after the event day for all the three models. This result indicates that an investor can benefit by buying the stocks and holding them for different number of days, especially after the earnings announcement. We use Runs test to assess the randomness of AARs. We test the hypothesis that the AARs occur randomly. It is observed that under good news earnings announcement, the AAR values A Study of Quarterly Earnings Announcement and Stock Price Reactions

99

Figure 3: AARs and CAARs Trends of Three Models Over the 61-Day Event Window of Full Sample Earnings Announcement 0.3480

Mean Adjusted Model AAR

AAR and CAAR

0.2980

Mean Adjusted Model CAAR

0.2480

Market Adjusted Model AAR

0.1980

Market Adjusted Model CAAR

0.1480

Market Model AAR

0.980

Market Model CAAR

0.0480 0.0020 –30 –26 –22 –1 8 –1 4 –1 0 –6 –2 2

6

10

14

18

22

26

30


of the mean adjusted model, market adjusted model and market model are significant during the entire event window. Therefore, the null hypothesis relating to AARs is rejected for the entire event window. In the case of bad news and full sample portfolios, the AAR values of the market adjusted model are insignificant and we conclude that AARs occur randomly. The AARs of the mean adjusted model and market model show significant values during the entire event window. Therefore, we reject the null hypothesis that AARs occur randomly for the event window. In the case of Sign test, we test the null hypothesis that there is no significant difference between the number of positive and negative AARs. Out of 61-day event window, the AAR values of mean adjusted model are significant at 5% level for good, bad and full sample portfolios. Therefore, we reject the null hypothesis and conclude that there is a significant difference between the number of positive and negative AARs. The AAR values of market adjusted model are insignificant for all the three portfolios. The AAR values of market model are insignificant for good and bad news portfolios. The results show that there is no significant difference between the number of positive and negative AARs for the entire event window (Table 1). Table 1: The Results of Non-Parametric, Runs and Sign Test Mean Adjusted Model

Market Adjusted Model

Runs Statistics

Runs Statistics

Sign Statistics

Sign Statistics

Market Model Runs Statistics

Sign Statistics

Good News Earnings Announcement Before

–2.7814

4.7374

–2.9277

2.9448

–3.4995

3.2009

After

–1.6400

4.0166

–0.5427

2.5560

–1.6400

4.0166

Overall

–3.0735

2.6941

–2.4402

1.6164

–3.1257

0.5388

Bad News Earnings Announcement Before

0.4795

5.5056

1.5182

1.1523

0.4795

3.9691

After

–2.3714

5.1121

–2.0057

0.7303

–2.0057

4.0166

100


Table 1 (Cont.) Mean Adjusted Model


Runs Statistics

Sign Statistics

Runs Statistics

–3.7345

2.6941

Overall

0.1485

Market Model

Sign Statistics

Runs Statistics

Sign Statistics

0.8980

–3.2267

1.6164

Full Sample Earnings Announcement Before

–2.2151

5.5056

–0.5427

2.1766

–2.2151

4.2252

After

–1.6066

4.7469

0.2380

1.4606

–1.6066

4.0166

Overall

–5.2770

3.0533

0.2397

1.6164

–5.2770

1.9757

Note: 1. Before: Number of Runs, Runs Statistics, and Sign Statistics before the event day. 2. After: Number of Runs, Runs Statistics, and Sign Statistics after the event day. 3. Overall: Number of Runs, Runs Statistics, and Sign Statistics for the event window (–30 through 30 days). 4. If the computed values of Runs and Sign test statistics are greater than the critical values at 5% level of significance (±1.96), the AARs are statistically significant at 5%.

Using the t-test statistics, we test the null hypothesis that AAR and CAAR values are close to zero. It is clear from Table 2 that under good and bad news portfolio, AAR values are insignificant during the entire event window for all the three models. Therefore, we accept the null hypothesis that AAR values are close to zero and there is no scope for abnormal profits by trading daily on shares based on the information of quarterly earnings announcement. In the case of full sample portfolio, the AAR values of mean adjusted model and market model show significant values, whereas the AAR values of market adjusted model show insignificant values for the 61-day event window. Therefore, the null hypothesis that AARs are close to zero is accepted for market adjusted model and rejected for mean adjusted model and market model. Table 2: The Results of t-Test Mean Adjusted Model AAR

%

CAAR

Market Adjusted Model %

AAR

%

CAAR

Market Model

%

AAR

%

CAAR

%

Good News Earnings Announcement Before

S

23

76.67

22

73.33

4

13.33

7

23.33

18

60.00

22

73.33

NS

7

23.33

8

26.67

26

86.67

23

76.67

12

40.00

8

26.67

After

S

7

22.58

31

100.00

5

16.13

28

90.32

5

16.13

31

100.00

NS

24

77.42

0

0.00

26

83.87

3

9.68

26

83.87

0

0.00

Overall

S

30

49.18

53

86.89

9

14.75

35

57.38

23

37.70

53

86.89

NS

31

50.82

8

13.11

52

85.25

26

42.62

38

62.30

8

13.11

Bad News Earnings Announcement Before

After

S

13

43.33

22

73.33

2

6.67

18

60.00

12

40.00

21

70.00

NS

17

56.67

8

26.67

28

93.33

12

40.00

18

60.00

9

30.00

8

25.81

31

100.00

6

19.35

29

93.55

8

25.81

31

100.00

23

74.19

0

0.00

25

80.65

2

6.45

23

74.19

0

0.00

S NS

A Study of Quarterly Earnings Announcement and Stock Price Reactions

101

Table 2 (Cont.) Mean Adjusted Model

Overall


Market Model

AAR

%

CAAR

%

AAR

%

CAAR

%

AAR

S

21

34.43

53

86.89

8

13.11

47

77.05

20

NS

40

65.57

8

13.11

53

86.89

14

22.95

%

CAAR

%

32.79

52

85.25

41

67.21

9

14.75

Full Sample Earnings Announcement Before

S

23

76.67

22

73.33

4

13.33

19

63.33

23

76.67

21

70.00

7

23.33

8

26.67

26

86.67

11

36.67

7

23.33

9

30.00

S

10

32.26

31

100.00

6

19.35

31

100.00

9

29.03

31

100.00

NS

21

67.74

0

0.00

25

80.65

0

0.00

22

70.97

0

0.00

S

33

54.10

53

86.89

10

16.39

50

81.97

32

52.46

52

85.25

NS

28

45.90

8

13.11

51

83.61

11

18.03

29

47.54

9

14.75

NS After

Overall

Note: S – Significant; NS – Non-significant at 5% level; Before – Before the event day; After – After the event day; and Overall – Event window of 61 days.

In the case of CAARs, the t-values of all the three models are significant for majority of the days for good, bad and full sample portfolios. Thus, we reject the null hypothesis that CAAR values are close to zero for the entire event window. This empirical evidence clearly states that there is a delayed price response and it is a sign of market inefficiency. Therefore, based on the above result we conclude that the market gives opportunity to earn the abnormal profits by trading on the basis of quarterly earnings announcement. This result shows that the market is inefficient in semi-strong form of EMH.

Conclusion In this study, we observe daily stock return data of sample companies. Event study methodology is employed to examine security price reactions to quarterly earnings announcement. The abnormal performance is measured by using the mean adjusted model, market adjusted model, and market model. The results show that AAR and CAAR values are positive for majority of the days during the event window and the earnings announcement had a positive impact on the market. From Runs test statistics, it appears that AAR values are non-random. The Sign statistics for the mean adjusted model shows that the numbers of positive and negative AARs are different and not equal. The t-test results show that CAAR values are significant for most of the days for all the portfolios in the event window. The significant CAARs show that the investors can use buy and hold strategy to gain abnormal returns. Based on these evidences, we conclude that the Indian stock market is not efficient in the semi-strong form. The quarterly earnings announcement information can be used by the investors to earn abnormal profits in the Indian stock market. The results of the study are consistent with those of Chaturvedi (2000a and 2000b), Jijo and Narayan (2002), Mallikarjunappa (2004), Iqbal and Mallikarjunappa (2007, 2008a, 2008b, 2010, and 2011), Raja and Sudhahar (2010) and Mallikarjunappa and Dsouza (2013) and are inconsistent with those of Rao (1994), Srinivasan (1997), and Bharath and Shankar (2012). The practical implication of this study 102


is that investors can benefit from the publicly available information like the earnings announcements. The findings show that corporates are not successful in disseminating the earnings information to a wide section of the market participants. The corporates seem to follow the mandatory regulation of announcing the quarterly earnings rather than concentrating on wide dissemination of the earnings information. Since the market is slow in absorbing the quarterly earnings content, the market exhibits the characteristics of inefficiency.

References 1. Ball R and Brown P (1968), “An Empirical Evaluation of Accounting Income Numbers”, Journal of Accounting Research, Vol. 6, No. 2, pp. 159-178. 2. Ball R and Kothari S P (1991), “Security Returns Around Earnings Announcements”, Accounting Review, Vol. 66, No. 4, pp. 718-738. 3. Bernard V and Thomas J (1989), “Post-Earnings Announcement Drift: Delayed Price Response or Risk Premium?”, Journal of Accounting Research, Vol. 27, pp. 1-36. 4. Bernard V and Thomas J (1990), “Evidence That Stock Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings”, Journal of Accounting and Economics, Vol. 13, No. 4, pp. 305-340. 5. Bharath M and Shankar H (2012), “Market Efficiency of Indian Stock Market – A Study of Bonus Announcement in Bombay Stock Exchange”, Indian Journal of Applied Research, Vol. 2, No. 1, pp. 45-49. 6. Brown L D and Han J C (2000), “Do Stock Prices Fully Reflect the Implications of Current Earnings for Future Earnings for AR1 Firms?”, Journal of Accounting Research, Vol. 38, No. 1, pp. 149-164. 7. Brown P and Kennelly J W (1972), “The Information Content of Quarterly Earnings: An Extension and Some Further Evidence”, Journal of Business, Vol. 45, No. 3, pp. 403-415. 8. Brown S and Warner J (1980), “Measuring Security Price Performance”, Journal of Financial Economics, Vol. 8, No. 3, pp. 205-258. 9. Chaturvedi Om H (2000a), “Anomalies Based on P/E Ratios: Empirical Evidence from the Indian Stock Market”, The IUP Journal of Applied Finance, Vol. 6, No. 3, pp. 1-13. 10. Chaturvedi Om H (2000b), “Empirical Anomalies Based on Unexpected Earnings: The Indian Experience”, The IUP Journal of Applied Finance, Vol. 6, No. 1, pp. 52-64. 11. Cowles A (1933), “Can Stock Market Forecasters Forecast?”, Econometrica, Vol. 1, pp. 309-324. 12. Dann L (1981), “Common Stock Repurchases: An Analysis of Returns to Bondholders and Stock-Holders”, Journal of Financial Economics, Vol. 9, No. 2, pp. 113-138. A Study of Quarterly Earnings Announcement and Stock Price Reactions

103

13. DeAngelo H and Rice E (1983), “Antitakeover Amendments and Stockholder Wealth”, Journal of Financial Economics, Vol. 11, No. 1, pp. 329-359. 14. Fama E F (1965), “The Behaviour of Stock Market Prices”, The Journal of Business, Vol. 38, No. 1, pp. 34-105. 15. Fama E F (1970), “Efficient Capital Markets: A Review of Theory and Empirical Work”, Journal of Finance, Vol. 25, No. 2, pp. 383-417. 16. Fama E F, Fisher L, Jensen M and Roll R (1969), “The Adjustment of Stock Prices to New Information”, International Economic Review, Vol. 10, No. 1, pp. 1-21. 17. Foster G (1977), “Quarterly Accounting Data: Time-Series Properties and PredictiveAbility Results”, The Accounting Review, Vol. 52, pp. 1-21. 18. Foster G, Olsen C and Shevlin T (1984), “Earnings Releases, Anomalies, and the Behavior of Security Returns”, The Accounting Research, Vol. 31, No. 2, pp. 216-230. 19. Freeman R and Tse S (1989), “The Multiperiod Information Content of Accounting Earnings: Confirmations and Contractions of Previous Earnings Reports”, Journal of Accounting Research, Vol. 27, Supplement, pp. 49-79. 20. Holthausen R (1981), “Evidence on the Effect of Bond Covenants and Management Compensation Contracts on the Choice of Accounting Techniques: The Case of the Depreciation Switchback”, Journal of Accounting and Economics, Vol. 3, No. 1, pp. 73-109. 21. Iqbal and Mallikarjunappa T (2007), “Stock Price Reactions to Earnings Announcement”, ACRM Journal of Business and Management Research, Vol. 2, No. 1, pp. 10-15. 22. Iqbal and Mallikarjunappa T (2008a), “An Empirical Testing of Semi-Strong Form Efficiency of Indian Stock Market”, Amity Business Review, Vol. 9, No. 1, pp. 24-33. 23. Iqbal and Mallikarjunappa T (2008b), “Quarterly Earnings Information, Stock Returns and Market Efficiency: An Empirical Study”, An International Biannual Refereed Journal of Management and Technology, Vol. 2, No. 2, pp. 37-52. 24. Iqbal and Mallikarjunappa T (2010), “A Study of Efficiency of the Indian Stock Market”, Indian Journal of Finance, Vol. 5, No. 4, pp. 32-38. 25. Iqbal and Mallikarjunappa T (2011), Efficiency of Stock Market: A Study of Stock Price Response to Earnings Announcements, Lambert Acad Publication, Germany. 26. Jensen M (1978), “Some Anomalous Evidence Regarding Market Efficiency”, Journal of Financial Economics, Vol. 6, Nos. 2 & 3, pp. 95-101. 27. Jijo L and Narayan R (2002), “Market Reaction to Stock Splits: An Empirical Study”, The IUP Journal of Applied Finance, Vol. 8, No. 2, pp. 26-40. 28. Jordan R J (1973), “An Empirical Investigation of the Adjustment of Stock Prices to New Quarterly Earnings Information”, Journal of Financial and Quantitative Analysis, Vol. 8, No. 4, pp. 609-620. 104


29. Kabir H M and Sackley W H (1996), “The June 1989 Regulatory Mandated Argentinean Loan Write-Offs and US Bank Security Returns: An Empirical Investigation”, Managerial Finance, Vol. 22, No. 3, pp. 28-44. 30. Latane H A and Jones C (1979), “Standardized Unexpected Earnings 1971-1977”, Journal of Finance, Vol. 34, No. 3, pp. 717-724. 31. Leftwich R (1981), “Evidence on the Impact of Mandatory Changes in Accounting Principles on Corporate Loan Agreements”, Journal of Accounting and Economics, Vol. 3, No. 1, pp. 3-36. 32. Levene H (1952), “On the Power Function of Tests of Randomness Based on Runs Up and Down”, Annals of Mathematical Statistics, Vol. 23, No. 1, pp. 34-56. 33. Mallikarjunappa T (2004), “How Do the Indian Stock Prices React to Quarterly Earnings”, The IUP Journal of Applied Finance, Vol. 10, No. 3, pp. 37-48. 34. Mallikarjunappa T and Dsouza J J (2013), “A Study of Semi-Strong Form of Market Efficiency of Indian Stock Market”, Amity Global Business Review, Vol. 8, No. 2, pp. 60-68. 35. Masulis R (1980), “The Effects of Capital Structure Change on Security Prices: A Study of Exchange Offers”, Journal of Financial Economics, Vol. 8, No. 2, pp. 139-177. 36. May R (1971), “The Influence of Quarterly Earning Announcements on Investor Decisions as Reflected in Common Stock Price Changes, Empirical Research in Accounting: Selected Studies”, Journal of Accounting Research, Vol. 9, pp. 119-163. 37. McNichols M and Manegold J (1983), “The Effect of the Information Environment on the Relationship Between Financial Disclosure and Security Price Variability”, Journal of Accounting and Economics, Vol. 5, No. 1, pp. 49-74. 38. Mendenhall R (1991), “Evidence of Possible Underweighting of Earnings-Related Information”, Journal of Accounting Research, Vol. 29, pp. 394-417. 39. Mendenhall W, Wackerly D D and Scheaffer R L (1989), “Nonparametric Statistics”, Mathematical Statistics with Applications, pp. 674-679. 40. Obaidullah M (1990), “Stock Price Adjustment to Half Yearly Earnings Announcements: A Test of Market Efficiency”, Chartered Accountant, Vol. 38, pp. 922-924. 41. Raja M and Sudhahar C (2010), “An Empirical Test of Indian Stock Market Efficiency in Respect of Bonus Announcement”, Asia Pacific Journal of Finance and Banking Research, Vol. 4, No. 4, pp. 1-14. 42. Rao N S (1994), “The Adjustment of Stock Prices to Corporate Financial Policy Announcements”, Finance India, Vol. 8, No. 4, pp. 941-953. 43. Rendleman R, Jones C P and Latane H A (1982), “Empirical Anomalies Based on Unexpected Earnings and the Importance of Risk Adjustments”, Journal of Financial Economics, Vol. 10, No. 3, pp. 269-287. A Study of Quarterly Earnings Announcement and Stock Price Reactions

105

44. Rufus A (2011), “The Impact of the 2004 Bank Capital Announcement on the Nigerian Stock Market”, African Journal of Economic and Management Studies, Vol. 2, No. 2, pp. 180-201. 45. Sharpe W F (1964), “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk”, Journal of Finance, Vol. 19, No. 3, pp. 425-442. 46. Soffer Land Lys T (1999), “Post-Earnings-Announcement Drift and the Dissemination of Predictable Information”, Contemporary Accounting Research, Vol. 16, No. 2, pp. 305-331. 47. Srinivasan R (1997), “Security Prices Behaviour Associated With Right Issue Related Events”, The IUP Journal of Applied Finance, Vol. 3, No. 1, pp. 50-62.

Reference # 01J-2014-10-07-01

106


Copyright of IUP Journal of Applied Finance is the property of IUP Publications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.