The Information Content of Stock Splits: In the Context of Stock Splits Concurrently Announced with Earnings
Abstract
:1. Introduction
2. Literature Review
2.1. Literature on Stock Splits
2.2. Literature on Concurrent Announcements
3. Background and Hypothesis
3.1. Does the Market React to a Split Incrementally in Response to Earnings News?
3.2. Does the Split Enhance Earnings Persistence?
4. Methodology
4.1. Event Study Approach
+ β5Control*UE + ε,
+ β5Control*UE + ε,
4.2. Cross-Sectional Approach
β7 CONCURRENT *Xt + β8 CONCURRENT *Xt3 + β9 CONCURRENT * Rt3 + εt
5. Data
6. Results and Discussion
6.1. Main Results
6.2. Does a Split Increase Earnings Persistence and Earnings Informativeness?
6.3. Extension—Decomposing Earnings into Cash Flows and Accruals
+ β8CONCURRENT_Q + β9 CONCURRENT_Q *CFOt1 + Β10 CONCURRENT_Q *CFOt
+ β11 CONCURRENT_Q *CFOt3 + β12 CONCURRENT_Q *ACCt1
+ Β13 CONCURRENT_Q *ACCt + β14 CONCURRENT_Q *ACCt3
+ β15 CONCURRENT_Q * Rt3 + εt
+ β8CONCURRENT + β9 CONCURRENT *CFOt1 + Β10 CONCURRENT *CFOt
+ β11 CONCURRENT *CFOt3 + β12 CONCURRENT *ACCt1
+ Β13 CONCURRENT *ACCt + β14 CONCURRENT *ACCt3 + β15 CONCURRENT * Rt3 + εt
6.4. Robustness Check
7. Conclusions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
Variable | Definition |
CARs | The 3-day, size, and book-to-market-adjusted cumulative abnormal returns for the period [−1, +1], where 0 is the earnings/split announcement day. |
UEt | Unexpected earnings for quarter t, calculated as quarter t’s actual EPS minus the average of individual analysts’ EPS forecasts of quarter t made within 60 days prior to quarter t’s earnings announcement date, deflated by the stock price at the beginning of quarter t. |
BMt | Book-to-market ratio at the beginning of quarter t. |
SIZEt | Logarithm of the market value at the beginning of quarter t. |
ATt | Total assets at the beginning of quarter t. |
EARNVOLt | Earnings volatility measured over the 3 years prior to the earnings announcement. |
EPSt | The earnings per share, adjusted for split and stock dividends for quarter t, undeflated. |
EPSt3 | The sum of earnings per share for quarters t + 1 through t + 12, undeflated. |
Xt1 | The annual EPS (cumulative quarterly EPS beginning from quarter t8 to quarter t4), deflated by the stock price at the beginning of the quarter. |
Xt | The annual EPS (cumulative quarterly EPS beginning from quarter t4 to quarter t), deflated by the stock price at the beginning of the quarter. |
Xt3 | The sum of EPS for fiscal quarters t + 1 through t + 12, deflated by the stock price at the beginning of quarter t. |
CONCURRENT_Q | Dummy variable that equals 1 if quarter t includes the concurrent split and earnings announcement date and 0 otherwise. |
CONCURRENT | Dummy variable that takes the value of 1 for the concurrent split–earnings announcers and 0 for the matched standalone earnings announcers. |
CFOt1 | The operating cash flows for fiscal year t1 (cumulative quarterly CFO beginning from quarter t8 to quarter t4), deflated by the market value at the beginning of quarter t. |
CFOt | The operating cash flows for fiscal year t (cumulative quarterly CFO beginning from quarter t4 to quarter t), deflated by the market value at the beginning of quarter t. |
CFOt3 | The sum of operating cash flows for fiscal year t + 1 through t + 3 (cumulative quarterly CFO beginning from quarter t + 1 to quarter t + 12), deflated by the market value at the beginning of quarter t. |
ACCt | The total accruals for fiscal year t1 (cumulative quarterly ACC beginning from quarter t8 to quarter t4), deflated by the market value at the beginning of quarter t. Quarterly ACC is obtained by subtracting operating cash flows from the net income before extraordinary items and discontinued operations. |
ACCt | The total accruals for fiscal year t (cumulative quarterly ACC beginning from quarter t4 to quarter t), deflated by the market value at the beginning of quarter t. |
ACCt3 | The total accruals for fiscal year t + 1 through t + 3 (cumulative quarterly ACC beginning from quarter t + 1 to quarter t + 12), deflated by the market value at the beginning of quarter t. |
1 | Existing studies suggest that managers are disinclined to make optimistic projections because they believe that such projections would expose them to lawsuits if they do not materialize (Ruhnka and Bagby 1986; Skinner 1997). Thus, managers might prefer to use indirect communication mediums such as stock splits and discretionary accruals over more direct mediums such as press releases and conference calls to convey their optimism (Louis and Robinson 2005). |
2 | For example, Huang et al. (2011) found that except for dividend paying firms, firms that split their stocks have negative future profitability. |
3 | As Fama (1998) and Titman (2002) pointed out, there remains substantial debate as to the statistical methodology and constructs used in studies on long-term stock performance. With respect to long-term returns subsequent to stock splits, Desai and Jain (1997) found that the use of a buy-and-hold strategy generates positive one-year and three-year abnormal post-split announcement returns of 7.05% and 11.87%, respectively, which confirms similar work by Ikenberry et al. (1996). However, when the long-term performance is measured from the ex-date instead of the announcement date, Byun and Rozeff (2003) did not find any consistent long-term abnormal returns. Boehme and Danielsen (2007) argued that the apparent anomaly in post-split long-term performance reflects modeling limitations and that modeling is not extremely robust. Behavioral finance constructs have also been used to evaluate the stock split event. Ikenberry and Ramnath (2002) confirmed this by showing that post-split stocks have excess returns for the year following a split and hypothesized that analysts are slow to update earnings estimates. They argued that this slowness causes an initial underreaction to the split signal. |
4 | Mechanically, returns must be explained either by positive cash flow news or negative expected return news (Campbell 1991), which is missing in the split event. |
5 | This analysis is related to prior research on market reactions to simultaneous information signals. For example, Ely and Mande (1996) examined analysts’ forecast revisions following earnings and dividend announcements. They found that analysts’ forecast revisions are more strongly associated with whether earnings and dividend signals are consistent than on the magnitude of the unexpected earnings and dividend news. These findings imply that market reactions to concurrent split and earnings announcements may be affected by either or both the consistency of signals and the magnitude of the news. |
6 | The information content of financial reports, particularly reported earnings, has been the major research interest among accounting researchers for over 30 years. The research findings suggest that the magnitude of the ERC depends on the precision of the earnings signal, which is determined using the feature of the financial reporting process as well as the chosen proxies, assumptions, and judgments made in arriving at the estimates. The higher the earnings precision, the more investors learn about firm activities, and the greater the stock price reaction. This idea is captured in several models, such as Collins and Salatka’s (1993) and Teoh and Wong’s (1993). A positive association between earnings persistence and the ERC is theoretically and empirically supported (See Kormendi and Lipe 1987; Easton and Zmijewski 1989 among others). For example, Kormendi and Lipe (1987) documented that abnormal returns for earnings increases are greater for high-persistence firms than for low-persistence firms. Holthausen and Verrecchia (1990) demonstrated, using their theoretical model, that the stock price response increases with the precision of the information. The investor’s perception of earnings precision has been measured with various proxies. For example, Teoh and Wong (1993) used a dichotomous variable: Big 8 vs. non-Big 8 auditors. |
7 | When testing on the Compustat universe, regressions were performed separately for each year within the sample period to address potential issues arising from positive cross-sectional correlations of the residuals. The mean coefficients and t-statistics reported were obtained using the Fama and MacBeth (1973) procedures. |
8 | For example, Nayak and Prabhala (2001) reported that many stock split firms contemporaneously announce dividends. |
9 | The values for asymmetry and kurtosis for all the variables were between −2 and +2, which were considered acceptable in order to prove a normal univariate distribution (George and Mallery 2010; Hair et al. 2010). I also conducted Jarque–Bera tests on the main variables and found test statistics ranging from 8.6 to 17.3, indicating significance and leading to the rejection of the null hypothesis of normality for most of my variables. To address potential nonlinearity in the data, I then performed rank-transformed regressions using decile values of all the variables to estimate the regression models (untabulated). The findings from this regression approach align qualitatively with those obtained from the main analysis. |
10 | I estimated Equations (1a)–(3b) using pooled cross-sectional ordinary least squares (OLS). One concern with pooled estimation is potential bias in the coefficient standard errors if the errors are serially correlated. To investigate this, I conducted Durbin–Watson tests (Durbin and Watson 1951) on the OLS estimations of Equations (1a)–(3b).The Durbin–Watson d-statistics for Equations (1a)–(3b) ranged between 1.8336 (p-value: 0.9935) and 2.1874 (p-value: 0.1323), indicating insignificance across all equations. These results suggest that there is no significant first-order autocorrelation in the pooled cross-sectional OLS estimation of Equations (1a)–(3b). I also checked variance inflation factors (VIFs) for all my regressions. As a rule of thumb, a variable with VIF values greater than 10 may merit further investigation. The mean VIF value of the variables in my regression models was 2.52, with the lowest VIF value being 1.12 and the highest VIF value being 3.16, suggesting that multicollinearity problems were unlikely to have affected my regression models. |
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Panel A | ||||||||||
Concurrent Announcers | Standalone Announcers | Differences | ||||||||
N = 1811 | N = 1811 | |||||||||
Mean | Median | Skewness | Kurtosis | Mean | Median | Skewness | Kurtosis | Mean Diff | Median Diff | |
CAR | 3.00% | 1.93% | 0.24 | −0.89 | 0.88% | 0.41% | 0.54 | −0.76 | <0.0001 | <0.0001 |
UE | 0.03% | 0.03% | −0.30 | −0.30 | −0.02% | 0.03% | −0.29 | −0.22 | 0.275 | 0.927 |
BM | 0.516 | 0.421 | 0.59 | −0.87 | 0.137 | 0.428 | 0.41 | −1.16 | 0.318 | 0.611 |
MCAP | 3081 | 478 | 1.80 | 1.82 | 3893 | 537 | 1.45 | 0.59 | 0.204 | 0.066 |
AT | 3517 | 435 | 1.58 | 1.04 | 4742 | 604 | 1.44 | 0.66 | 0.241 | 0.034 |
EARNVOL | 0.339 | 0.143 | 0.97 | −0.25 | 0.347 | 0.176 | 0.72 | −0.80 | 0.866 | 0.068 |
EPS | 1.152 | 1.080 | 0.22 | −0.95 | 1.339 | 1.060 | 0.23 | −1.12 | 0.363 | 0.753 |
EPS_t − 1 | 1.143 | 1.060 | 0.32 | −0.84 | 1.384 | 1.070 | 0.31 | −0.93 | 0.434 | 0.901 |
EPS_t + 3 | 1.206 | 1.170 | 0.20 | −0.74 | 1.287 | 1.050 | 0.30 | −0.99 | 0.669 | 0.135 |
Panel B | ||||||||||
CONCURRENT | CAR | UE | BM | MCAP | AT | EARNVOL | EPS_t1 | EPS_t | EPS_t3 | |
CONCURRENT | 1.00 | 0.15 | 0.00 | 0.02 | 0.06 | 0.07 | 0.06 | 0.01 | 0.00 | 0.05 |
CAR | 0.14 | 1.00 | 0.20 | 0.10 | 0.03 | 0.10 | 0.04 | 0.01 | 0.01 | 0.02 |
UE | 0.03 | 0.06 | 1.00 | 0.03 | 0.02 | 0.08 | 0.09 | 0.02 | 0.03 | 0.00 |
BM | 0.03 | 0.00 | 0.00 | 1.00 | 0.31 | 0.17 | 0.09 | 0.02 | 0.10 | 0.15 |
MCAP | 0.04 | 0.01 | 0.00 | 0.00 | 1.00 | 0.79 | 0.39 | 0.35 | 0.26 | 0.23 |
AT | 0.04 | 0.02 | 0.01 | 0.01 | 0.54 | 1.00 | 0.46 | 0.43 | 0.41 | 0.38 |
EARNVOL | 0.01 | 0.00 | 0.01 | 0.10 | 0.10 | 0.07 | 1.00 | 0.01 | 0.02 | 0.07 |
EPS_t1 | 0.03 | 0.06 | 0.03 | 0.03 | 0.29 | 0.14 | 0.27 | 1.00 | 0.81 | 0.61 |
EPS_t | 0.03 | 0.02 | 0.01 | 0.07 | 0.15 | 0.09 | 0.08 | 0.31 | 1.00 | 0.67 |
EPS_t3 | 0.01 | 0.02 | 0.02 | 0.12 | 0.21 | 0.11 | 0.21 | 0.54 | 0.54 | 1.00 |
Panel A | ||||||
Event Time | Market-Adjusted Abnormal Return | t-Statistics | p-Value | |||
−2 | 0.23% | 3.04 | 0.00 | |||
−1 | 0.23% | 3.00 | 0.00 | |||
0 | 1.33% | 12.87 | 0.00 | |||
1 | 1.23% | 10.33 | 0.00 | |||
2 | 0.39% | 3.95 | 0.00 | |||
Panel B | ||||||
All Firms in This Study | Concurrent Split/Earnings Announcers | Standalone Earnings Announcers | ||||
Event Window | Mean | Median | Mean | Median | Mean | Median |
[−1, +1] | 1.94% | 1.13% | 3.00% | 1.93% | 0.88% | 0.41% |
[−1, +2] | 1.91% | 1.14% | 3.26% | 2.43% | 0.55% | 0.13% |
[−2, +2] | 2.18% | 1.35% | 3.72% | 2.70% | 0.61% | 0.13% |
Panel C | ||||||
Concurrent Announcers | Standalone Announcers | Differences | ||||
Decile Rank | Mean | Median | Mean | Median | Mean | Median |
D1 | 0.000 | 0.018 | 0.035 | 0.026 | 0.035 | 0.044 |
D2 | 0.031 | 0.018 | 0.025 | 0.018 | 0.056 | 0.036 |
D3 | 0.010 | 0.008 | 0.018 | 0.013 | 0.028 | 0.021 |
D4 | 0.006 | 0.006 | 0.011 | 0.008 | 0.016 | 0.014 |
D5 | 0.023 | 0.016 | 0.002 | 0.001 | 0.026 | 0.017 |
D6 | 0.022 | 0.011 | 0.006 | 0.005 | 0.016 | 0.006 |
D7 | 0.050 | 0.037 | 0.014 | 0.011 | 0.036 | 0.026 |
D8 | 0.037 | 0.032 | 0.020 | 0.015 | 0.017 | 0.017 |
D9 | 0.033 | 0.026 | 0.027 | 0.020 | 0.006 | 0.006 |
D10 | 0.075 | 0.070 | 0.037 | 0.025 | 0.038 | 0.044 |
Differences D10–D1 | <0.0001 | <0.0001 | ||||
(t-statistics: 67.56) | (z-statistics: 71.49) |
CAR = α + β1 UE + β2 CONCURRENT + β3 UE* CONCURRENT + β4Controls + β5Control*UE + ε, (Equation (1b)) | ||
(1) | (2) | |
Intercept | 0.001 *** | 0.013 *** |
(4.45) | (4.46) | |
UE | 0.160 *** | 0.298 * |
(5.03) | (1.99) | |
CONCURRENT | 0.025 *** | 0.024 *** |
(6.01) | (5.77) | |
CONCURRENT*UE | 2.238 ** | 1.434 ** |
(2.63) | (2.10) | |
SIZE | 0.001 *** | |
(3.64) | ||
SIZE*UE | 0.098 *** | |
(3.93) | ||
EARNVOL | 0.000 | |
(0.94) | ||
EARNVOL*UE | 0.075 *** | |
(4.01) | ||
LOSS | 0.017 *** | |
(11.68) | ||
LOSS*UE | 0.492 *** | |
(3.62) | ||
Adj. R squared | 0.006 *** | 0.028 *** |
(5.53) | (6.71) |
Panel A | ||||||
CAR = α + β1 UE + β2 CONCURRENT_Q + β3 UE* CONCURRENT_Q + β4Controls + β5Control*UE + ε, (Equation (1a)) | ||||||
Coefficient | t-Statistics | p-Value | Coefficient | t-Statistics | p-Value | |
Intercept | 0.004 | 0.24 | 0.001 | 0.10 | ||
UE | 1.079 | 1.00 | 0.222 | 0.12 | ||
Concurrent_Q | 0.013 | 2.05 | ** | 0.014 | 2.26 | ** |
Concurrent_Q*UE | 1.133 | 0.77 | 1.951 | 1.69 | * | |
SIZE | 0.001 | 0.28 | ||||
Size*UE | 0.293 | 0.98 | ||||
Earnvol | 0.001 | 1.37 | ||||
Earnvol*UE | 0.194 | 0.44 | ||||
Loss | 0.010 | 0.79 | ||||
Loss*UE | 2.870 | 2.28 | ** | |||
Adj. R Squared | 3.37% | 3.12% | ||||
No. Obs | 3.622 | 3.622 | ||||
Panel B | ||||||
CAR = α + β1 UE + β2 CONCURRENT + β3 UE* CONCURRENT + β4Controls + β5Control*UE + ε, (Equation (1b)) | ||||||
Coefficient | t-Statistics | p-Value | Coefficient | t-Statistics | p-Value | |
Intercept | 0.005 | 2.82 | *** | 0.004 | 0.44 | |
UE | 0.114 | 1.89 | * | 0.592 | 0.86 | |
Concurrent | 0.003 | 1.20 | 0.003 | 1.08 | ||
Concurrent*UE | 1.548 | 5.17 | *** | 1.455 | 4.24 | *** |
SIZE | 0.001 | 1.09 | ||||
Size*UE | 0.077 | 0.72 | ||||
Earnvol | 0.002 | 1.35 | ||||
Earnvol*UE | 0.092 | 0.25 | ||||
Loss | 0.014 | 2.63 | *** | |||
Loss*UE | 0.098 | 0.27 | ||||
Adj. R Squared | 0.84% | 1.59% | ||||
No. Obs | 3.622 | 3.622 |
Panel A | ||||||
Rt = β0 + β1Xt1 + β2Xt + β3Xt3 + β4 Rt3 + β5CONCURRENT_Q + β6 CONCURRENT_Q *Xt1 + CONCURRENT_Q *Xt + β8 CONCURRENT_Q *Xt3 + β9 CONCURRENT_Q * Rt3. + εt (Equation (2a)) | ||||||
(1) | (2) | |||||
Coefficient | t-Statistics | p-Value | Coefficient | t-Statistics | p-Value | |
Intercept | 0.150 | 2.58 | ** | 0.164 | 1.62 | |
X_t1 | 0.029 | 3.18 | *** | 0.184 | 1.28 | |
X_t | 0.143 | 1.73 | * | 0.172 | 0.77 | |
X_t3 | 0.069 | 1.75 | * | 0.166 | 2.05 | ** |
R_t3 | 0.047 | 1.15 | 0.038 | 1.08 | ||
Concurrent | 0.091 | 1.84 | * | 0.085 | 1.67 | * |
X_t1*Concurrent_Q | 0.030 | 1.04 | 0.027 | 0.36 | ||
X_t*Concurrent_Q | 0.110 | 1.06 | 0.026 | 0.28 | ||
X_t3*Concurrent_Q | 0.132 | 2.00 | *** | 0.178 | 2.76 | *** |
R_t3*Concurrent_Q | 0.108 | 1.18 | 0.102 | 1.16 | ||
BM | 0.021 | 1.35 | ||||
Size | 0.002 | 0.17 | ||||
Earnvol | 0.000 | 0.04 | ||||
X_t1*BM | 0.120 | 1.50 | ||||
X_t1*Size | 0.019 | 1.22 | ||||
X_t1*Earnvol | 0.001 | 0.17 | ||||
X_t*BM | 0.322 | 1.93 | * | |||
X_t*Size | 0.009 | 0.32 | ||||
X_t*Earnvol | 0.013 | 0.52 | ||||
X_t3*BM | 0.009 | 1.23 | ||||
X_t3*Size | 0.019 | 1.72 | * | |||
X_t3*Earnvol | 0.037 | 1.10 | ||||
Adj. R Squared | 6.93% | 7.74% | ||||
No. Obs | 3.622 | 3.622 | ||||
Panel B | ||||||
Rt = β0 + β1Xt1 + β2Xt + β3Xt3 + β4 Rt3 + β5 CONCURRENT + β6 CONCURRENT *Xt1 + β7 CONCURRENT *Xt + β8 CONCURRENT *Xt3 + β9 CONCURRENT * Rt3 + εt (Equation (2b)) | ||||||
(1) | (2) | |||||
Coefficient | t-Statistics | p-Value | Coefficient | t-Statistics | p-Value | |
Intercept | 0.418 | 2.36 | ** | 19.512 | 2.56 | ** |
X_t1 | 0.803 | 1.58 | 6.313 | 1.58 | ||
X_t | 3.491 | 3.27 | *** | 8.866 | 2.45 | ** |
X_t3 | 1.303 | 2.25 | ** | 3.041 | 1.47 | |
R_t3 | 0.013 | 1.93 | * | 0.010 | 0.66 | |
Concurrent | 0.755 | 2.93 | *** | 0.759 | 2.79 | *** |
X_t1*Concurrent | 0.085 | 0.11 | 0.581 | 0.41 | ||
X_t*Concurrent | 3.189 | 2.84 | *** | 4.681 | 3.92 | *** |
X_t3*Concurrent | 1.044 | 1.72 | * | 1.412 | 1.98 | ** |
R_t3*Concurrent | 0.013 | 1.06 | 0.009 | 0.59 | ||
BM | 3.427 | 4.79 | *** | |||
Size | 0.067 | 0.74 | ||||
Earnvol | 0.027 | 0.23 | ||||
X_t1*BM | 5.466 | 1.55 | ||||
X_t1*Size | 0.254 | 0.60 | ||||
X_t1*Earnvol | 2.853 | 1.89 | * | |||
X_t*BM | 3.008 | 0.74 | ||||
X_t*Size | 0.214 | 0.53 | ||||
X_t*Earnvol | 1.922 | 4.15 | *** | |||
X_t3*BM | 1.208 | 1.41 | ||||
X_t3*Size | 0.134 | 0.44 | ||||
X_t3*Earnvol | 0.841 | 0.80 | ||||
Adj. R Squared | 3.23% | 3.94% | ||||
No. Obs | 3.622 | 3.622 |
Panel A | |||
Rt = β0 + β1CFOt1 + β2CFOt + β3CFOt3 + β4ACCt1 + β5ACCt + β6ACCt3 + Β7 Rt3 + β8CONCURRENT_Q + β9 CONCURRENT_Q *CFOt1 + Β10 CONCURRENT_Q *CFOt + β11 CONCURRENT_Q *CFOt3 + β12 CONCURRENT_Q *ACCt1 + Β13 CONCURRENT_Q *ACCt + β14 CONCURRENT_Q *ACCt3 + β15 CONCURRENT_Q * Rt3 + εt (Equation (3a)) | |||
Coefficient | t-Statistics | p-Value | |
Intercept | 0.426 | 2.70 | *** |
CFO_t1 | 0.012 | 0.69 | |
CFO_t | 0.028 | 2.01 | ** |
CFO_t3 | 0.007 | 1.93 | * |
ACC_t1 | 0.004 | 0.22 | |
ACC_t | 0.031 | 2.39 | ** |
ACC_t3 | 0.016 | 2.90 | *** |
Concurrent_Q | 0.170 | 1.99 | ** |
CFO_t1*Concurrent_Q | 0.022 | 1.58 | |
CFO_t*Concurrent_Q | 0.026 | 1.74 | * |
CFO_t3*Concurrent_Q | 0.015 | 2.68 | *** |
*ACC_t1*Concurrent_Q | 0.024 | 1.56 | |
*ACC_t*Concurrent_Q | 0.017 | 1.01 | |
*ACC_t3*Concurrent_Q | 0.011 | 2.39 | ** |
R3*Concurrent_Q | 0.136 | 1.15 | |
BM | 0.033 | 2.66 | *** |
BM*CFO_t1 | 0.008 | 0.97 | |
BM*CFO_t | 0.019 | 2.36 | ** |
BM*CFO_t3 | 0.003 | 1.19 | |
Size | 0.034 | 1.36 | |
Size*CFO_t1 | 0.002 | 1.20 | |
Size*CFO_t | 0.005 | 2.54 | ** |
Size*CFO_t3 | 0.001 | 2.17 | ** |
Earnvol | 0.021 | 0.45 | |
Earnvol*CFO_t1 | 0.001 | 0.92 | |
Earnvol*CFO_t | 0.004 | 0.75 | |
Earnvol*CFO_t3 | 0.000 | 0.16 | |
BM*ACC_t1 | 0.004 | 0.51 | |
BM*ACC_t | 0.016 | 2.06 | ** |
BM*ACC_t3 | 0.003 | 1.12 | |
Size*ACC_t1 | 0.001 | 0.50 | |
Size*ACC_t | 0.006 | 2.87 | *** |
Size*ACC_t3 | 0.002 | 2.94 | *** |
Earnvol*ACC_t1 | 0.000 | 0.06 | |
Earnvol*ACC_t | 0.004 | 0.84 | |
Earnvol*ACC_t3 | 0.002 | 0.90 | |
Adj. R Squared | 13.75% | ||
No. Obs | 3.622 | ||
Panel B | |||
Rt = β0 + β1CFOt1 + β2CFOt + β3CFOt3 + β4ACCt1 + β5ACCt + β6ACCt3 + Β7 Rt3 + β8CONCURRENT + β9 CONCURRENT *CFOt1 + Β10 CONCURRENT *CFOt + β11 CONCURRENT *CFOt3 + β12 CONCURRENT *ACCt1 + Β13 CONCURRENT *ACCt + β14 CONCURRENT *ACCt3 + β15 CONCURRENT * Rt3 + εt (Equation (3b)) | |||
Coefficient | t-Statistics | p-Value | |
Intercept | 0.149 | 0.30 | |
CFO_t1 | 0.096 | 0.59 | |
CFO_t | 0.168 | 1.03 | |
CFO_t3 | 0.004 | 0.10 | |
ACC_t1 | 0.290 | 1.67 | * |
ACC_t | 0.399 | 2.53 | ** |
ACC_t3 | 0.001 | 0.02 | |
Concurrent | 0.910 | 4.47 | *** |
CFO_t1*Concurrent | 0.073 | 0.78 | |
CFO_t*Concurrent | 0.125 | 1.46 | |
CFO_t3*Concurrent | 0.049 | 2.02 | ** |
*ACC_t1*Concurrent | 0.036 | 0.42 | |
*ACC_t*Concurrent | 0.117 | 1.41 | |
*ACC_t3*Concurrent | 0.044 | 1.56 | |
R3*Concurrent | 0.010 | 0.93 | |
BM | 1.614 | 3.16 | *** |
BM*CFO_t1 | 0.099 | 1.00 | |
BM*CFO_t | 0.020 | 0.47 | |
BM*CFO_t3 | 0.039 | 1.25 | |
Size | 0.030 | 0.48 | |
Size*CFO_t1 | 0.020 | 1.32 | |
Size*CFO_t | 0.007 | 0.34 | |
Size*CFO_t3 | 0.005 | 0.98 | |
Earnvol | 0.200 | 0.81 | |
Earnvol*CFO_t1 | 0.035 | 1.01 | |
Earnvol*CFO_t | 0.008 | 0.15 | |
Earnvol*CFO_t3 | 0.003 | 0.19 | |
BM*ACC_t1 | 0.244 | 1.68 | * |
BM*ACC_t | 0.224 | 1.55 | |
BM*ACC_t3 | 0.047 | 1.18 | |
Size*ACC_t1 | 0.032 | 2.02 | ** |
Size*ACC_t | 0.027 | 1.53 | |
Size*ACC_t3 | 0.004 | 0.61 | |
Earnvol*ACC_t1 | 0.035 | 0.78 | |
Earnvol*ACC_t | 0.017 | 0.38 | |
Earnvol*ACC_t3 | 0.004 | 0.21 | |
Adj. R Squared | 21.46% | ||
No. Obs | 3.622 |
Panel A | ||||||
CAR [−1, +2] or CAR [−2, +2] = α + β1 UE + β2 CONCURRENT_Q + β3 UE* CONCURRENT_Q + β4Controls + β5Control*UE + ε, (Equation (1a)) | ||||||
Depvar: | CAR [−1, +2] | CAR [−2, +2] | ||||
Coefficient | t-Statistics | p-Value | Coefficient | t-Statistics | p-Value | |
Intercept | 0.019 | 1.20 | 0.007 | 0.67 | ||
UE | −2.719 | 0.75 | 0.906 | 1.29 | ||
Concurrent_Q | 0.003 | 0.37 | 0.005 | 1.65 | * | |
Concurrent_Q*UE | 0.839 | 1.33 | 1.290 | 3.48 | *** | |
Size | −0.001 | −0.71 | −0.001 | −0.98 | ||
Size*UE | 0.631 | 1.78 | * | −0.121 | −1.10 | |
Earnvol | 0.001 | 0.54 | −0.002 | −1.47 | ||
Earnvol*UE | −0.222 | −0.32 | 0.211 | 0.55 | ||
Loss | 0.016 | 1.14 | −0.018 | −3.10 | *** | |
Loss*UE | −2.579 | −2.19 | ** | −0.314 | −0.84 | |
Adj. R Squared | 1.06% | 1.37% | ||||
No. Obs | 3.622 | 3.622 | ||||
Panel B | ||||||
CAR [−1, +2] or CAR [−2, +2] = α + β1 UE + β2 CONCURRENT + β3 UE* CONCURRENT + β4Controls + β5Control*UE + ε, (Equation (1b)) | ||||||
Depvar: | CAR [−1, +2] | CAR [−2,+2] | ||||
Coefficient | t-Statistics | p-Value | Coefficient | t-Statistics | p-Value | |
Intercept | 0.002 | 0.32 | 0.027 | 1.80 | * | |
UE | 0.957 | 1.81 | * | −1.151 | −0.42 | |
Concurrent | −0.001 | −0.45 | 0.003 | 0.42 | ||
Concurrent*UE | 1.145 | 5.80 | *** | 2.425 | 1.84 | * |
Size | −0.001 | −1.93 | * | −0.001 | −0.65 | |
Size*UE | −0.140 | −1.68 | * | 0.227 | 0.45 | |
Earnvol | −0.001 | −1.02 | 0.001 | 0.80 | ||
Earnvol*UE | 0.228 | 0.72 | 0.250 | 0.23 | ||
Loss | −0.001 | −0.41 | 0.018 | 1.13 | ||
Loss*UE | −0.306 | −1.06 | −0.714 | −0.28 | ||
Adj. R Squared | 1.23% | 1.17% | ||||
No. Obs | 3.622 | 3.622 |
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Ha, J. The Information Content of Stock Splits: In the Context of Stock Splits Concurrently Announced with Earnings. J. Risk Financial Manag. 2024, 17, 169. https://doi.org/10.3390/jrfm17040169
Ha J. The Information Content of Stock Splits: In the Context of Stock Splits Concurrently Announced with Earnings. Journal of Risk and Financial Management. 2024; 17(4):169. https://doi.org/10.3390/jrfm17040169
Chicago/Turabian StyleHa, Joohyung. 2024. "The Information Content of Stock Splits: In the Context of Stock Splits Concurrently Announced with Earnings" Journal of Risk and Financial Management 17, no. 4: 169. https://doi.org/10.3390/jrfm17040169