Comment letters and stock price synchronicity: evidence from China

Abstract

This paper studies the effectiveness of comment letters by exploring the relationship between comment letters and stock price synchronicity. Using a unique dataset from China, we find that the issuance of comment letters is negatively correlated with stock price synchronicity. The results are robust to a battery of tests. Further analysis indicates that the negative relationship between comment letters and stock price synchronicity is more prominent for non-state-owned enterprises (non-SOEs) than SOEs. Then, we explore what channels comment letters affect the stock price synchronicity. Our evidence shows that firms receiving comment letters (1) have a high negative skewness indicating more negative information released, and (2) are more likely to amend their annual financial reports, leading to less stock price synchronicity. Overall, the evidence indicates that the comment letter process can help increase the firm information incorporated in the stock price.

Appendices

Appendix A: Variable definitions

Variables measured on firm-level information
${Synch1}_{t}$	The first measure of stock return synchronicity. Logarithmic transformation of R2, which is the coefficient of determination from the estimation of Eq. (1)
${Synch2}_{t}$	The second measure of stock return synchronicity. Logarithmic transformation of R2, which is the coefficient of determination from this estimation: ${r}_{i,\tau }={\alpha }_{i}+{\beta }_{1,i}{r}_{m,\tau }+{\varepsilon }_{i,\tau }$
${Synch3}_{t}$	The third measure of stock return synchronicity. Logarithmic transformation of R2, which is the coefficient of determination from the Fama and French five-factor model
${Synch4}_{t}$	The fourth measure of stock price synchronicity. To avoid the weekend effect, we calculate weekly returns from Wednesday closing prices and follow Eq. (1) and (2) to calculate the fourth measure of stock price synchronicity ${Synch4}_{i,t}$
Comment letters
${CL1}_{t}$	A dummy variable equals one if firm $i$ in year $t$ receives at least one comment letter from Shanghai Stock Exchange or Shenzhen Stock Exchange, zero otherwise
${CL2}_{t}$	The number of comment letters that firm $i$ receives from the Shanghai Stock Exchange or Shenzhen Stock Exchange in year $t$
Control variables
${MB}_{t}$	The market-to-book ratio of firm $i$ at the end of year t
${Lev}_{t}$	Total liabilities scaled by the book value of total assets at the end of year t
${ROA}_{t}$	The ratio of income before extraordinary items to total assets at the end of year t
${Volume}_{t}$	The trading volume of firm $i$ in year t, i.e., the natural log of the Chinese yuan renminbi trading volume in year t
${Size}_{t}$	The natural logarithm of total assets of a firm at the end of year t
${Big4}_{t}$	A dummy variable that equals one if the firm is audited by one of the joint ventures of the four largest international accounting firms and domestic audit firms (the Big4 auditor) and zero otherwise
${Foreign}_{t}$	The average percentage of foreign institutional investors hold on firm $i$ in year t
${IndSize}_{t}$	The logarithm of total assets of the industry to which firm $i$ belongs in year t
${IndNum}_{t}$	The number of firms in the industry to which firm $i$ belongs in year t
${IndSpill}_{t}$	A dummy variable that equals one if the industry that the firm belongs to receives any comment letter in year t, otherwise zero
State-owned enterprises
${SOE}_{t}$	A dummy variable that equals one if the firm is a State-Owned Enterprise (SOE) and zero otherwise
Other variables of interest
${NCSKEW}_{t}$	The negative coefficient of skewness, calculated by taking the negative of the third moment of firm-specific weekly returns for each sample year and dividing it by the standard deviation of firm-specific weekly returns raised to the third power. The details of the calculation can be seen in Appendix B
${Restate}_{t}$	A dummy variable that equals one if the firm amends its annual reports in year $t$ and zero otherwise

Appendix B: Procedures for negative information release

Following Hutton et al. (2009), Kim et al. (2011a, 2011b), Baloria and Heese (2018), and Wen et al. (2019), we first estimate firm-specific weekly returns for each firm in each year on the following regression:

$${r}_{i,\tau }={\alpha }_{i}+{\beta }_{1,i}{r}_{I,\tau -1}+{\beta }_{2,i}{r}_{m,\tau -1}+{\beta }_{3,i}{r}_{I,\tau }+{\beta }_{4,i}{r}_{m,\tau }+{\beta }_{5,i}{r}_{I,\tau +1}+{\beta }_{6,i}{r}_{m,\tau +1}+{\varepsilon }_{i,\tau }$$

(B.1)

where ${r}_{i,\tau }$ is the week-τ return in year t of stock $i$, and ${r}_{m,\tau }$ is the week-τ return in year t of the value-weighted A-share market index. ${r}_{I,\tau }$ is the week-τ return in year t of the industry to which the firm belongs, which is the value-weighted return of all the firms within the same industry in the sample, omitting the weekly return of firm $i$. Then we measure the week-τ firm-specific return of firm $i$ as ${W}_{i,\tau }=\mathrm{ln}(1+{\widehat{\varepsilon }}_{i,\tau })$ where ${\widehat{\varepsilon }}_{i,\tau }$ is the week-τ residual of regression (B.1).

We take the “negative coefficient of skewness” (NCSKEW) as the first measure of the negative information release:

$${NCSKEW}_{i,t}=-\frac{n{(n-1)}^{3/2}{\sum }_{\tau =1}^{n}{W}_{i,\tau }^{3}}{(n-1)(n-2){({\sum }_{\tau =1}^{n}{W}_{i,\tau }^{2})}^{3/2}}$$

(B.2)

where n is the number of observations of stock i’s specific weekly returns in year t.

Appendix C: Other robustness tests

We run two tests: one uses the sample without the winsorization of variables shown in Column (1), and the other is to cluster the standard errors at the firm-year level shown in Column (2). The coefficients on $CL{1}_{t}$ are negative and significant, indicating the relation between comment letters and stock price synchronicity is unchanged under these two robustness tests.

3.1 Other robustness tests

Column (1) reports the regression results of the sample without the winsorization of variables, and Column (2) shows the results of clustering the standard errors at the firm-year level. *, **, and *** indicate statistical significance at the 10, 5, and 1% levels, respectively. The descriptions of these variables are provided in Appendix A

	(1)	(2)
	${Synch1}_{t}$	${Synch1}_{t}$
${CL1}_{t}$	− 0.2625***	− 0.2625*
	(0.0322)	(0.0961)
${MB}_{t}$	− 0.0088*	− 0.0088
	(0.0051)	(0.0092)
${Lev}_{t}$	− 0.2819***	− 0.2819*
	(0.0470)	(0.1149)
${ROA}_{t}$	− 0.0444	− 0.0444
	(0.0736)	(0.0756)
${Volume}_{t}$	− 0.1789***	− 0.1789**
	(0.0123)	(0.0555)
${Size}_{t}$	0.1229***	0.1229
	(0.0115)	(0.0582)
${Big4}_{t}$	− 0.0883*	− 0.0883
	(0.0457)	(0.0498)
${Foreign}_{t}$	0.0102**	0.0102
	(0.0040)	(0.0068)
${IndSize}_{t}$	0.1068	0.1068
	(0.1170)	(0.1236)
${IndNum}_{t}$	− 0.0235	− 0.0235
	(0.1717)	(0.4340)
${IndSpill}_{t}$	0.3530***	0.3530***
	(0.1265)	(0.0383)
Constant	− 1.8311	− 1.8311
	(3.5513)	(1.8955)
Industry	Yes	Yes
Year	Yes	Yes
N	9997	9997
Adj. R2	0.2947	0.2946