Luận án này thực hiện để nghiên cứu thông tin tài chính ảnh hưởng đến suất sinh
lời cổ phiếu khi công bố BCTC. Với những kết quả đạt được từ mô hình thực nghiệm, về
mặt học thuật, luận án mang mang lại đóng góp mới trên cơ sở bổ sung vào khoảng trống
nghiên cứu thông qua cung cấp bằng chứng thực nghiệm về tác động của thời gian công
bố BCTC và các thông tin tài chính tác động đến suất sinh lời.
(4) Nghiên cứu được thực hiện trên phạm vi toàn TTCK VN và có ưu điểm là nghiên
cứu trên từng nhóm ngành cụ thể, dựa trên phương pháp nghiên cứu sự kiện, lấp đầy các
khoảng trống nghiên cứu về phạm vi này. Kết quả cho thấy CAAR có xu hướng cao hơn
trong cả khoảng thời gian ngắn hạn [-5;0] và trong khoảng thời gian dài hạn [-90;0] cho cả
tin tốt và tin xấu trong giai đoạn trước sự kiện công bố BCTC.
Đối với các ngành: Thời gian các CTNY công bố BCTC trễ có tác động đến CAAR
trong hầu hết các ngành, phản ứng tiêu cực mạnh nhất và có ý nghĩa thống kê đối với hai
ngành là Dịch vụ tiêu dùng và Hàng hóa tiêu dùng; Đối với trường hợp công bố BCTC
sớm, chưa có bằng chứng thực nghiệm về các công ty có thời gian công bố sớm tác động
có ý nghĩa đến CAAR. Nếu các công ty có thời gian công bố BCTC sớm mà các thông tin
chứa đựng trong đó là xấu thì cũng nhận được phản ứng tiêu cực của thị trường và đều có
ý nghĩa thống kê, mạnh nhất là đối với ngành Chăm sóc sức khỏe, kế đến là ngành Hàng
hóa tiêu dùng, Dịch vụ tiêu dùng; Trong trường hợp công bố đúng thời gian thì thông tin
về thời gian công bố BCTC có tác động dương đến CAAR và có ý nghĩa thống kê, nhưng
những thông tin trên BCTC là xấu thì cũng chịu sự trừng phạt của thị trường, mạnh nhất ở
nhành Công nghiệp, sau đó là ngành Hàng hóa tiêu dùng
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t Thomson Reuter
Pt - Pt - 1
Pt – 1
(Breyley & Myers (2004), Nguyen Anh Phong
(2015))
15
SUE Thomson Reuter
Eit – Eit - 1
σit
(Chordia (2006), Vinh & Phuong (2014))
DVOL Thomson Reuter
LN(Pit * Volumeit)
(Chordia (2006), Vinh & Phuong (2014))
SIZE Thomson Reuter
LN(total assets)
(Banz (1981), Chordia (2006, 2014), Vinh & Phuong
(2014))
BM Thomson Reuter
= (Total assets – Debt – Fixed intangible assets) / (
No. of Oustanding shares * Stock price)
(Weiqiang (2008); Chordia (2006); Vinh & Phuong
(2014); Fama & French (1992)).
RET12 Thomson Reuter
Pit-2 – Pit - 12
Pit – 12
(Jegadeesh (1993); Chordia (2006); Vinh &Phuong
(2014))
|DA| Thomson Reuter
|DAi
,t| =
TAi,
t / Doanh thui,t –TAi,t-1/ Doanh thu i,t-1
(Friedlan (1994); DeAngelo (1986))
TA (Total
accruals)
= LNST -
Cash flow from
operations
Audit-S
Auditor size
(
KPMG, EY, PwC, Deloitte, AASC, A&C: dummy = 1
(auditor belongs to Big6) and 0 for other auditing
firms.
(Ranking criteria of auditing firms 2015 AASC)
Source: Author‘s compilation
3.2. Research data
The study focuses on the period from 01/2010 and 06/2016, of 482 firms that have
continuous listing time on HOSE and HNX for at least 2 years. Firms that have book
value < 0 will be eliminated. The data are collected from webstites of State Stock
Commission, and www.cophieu68.vn and database
of Thomson Reuters.
3.3. Research method
3.3.1. Impact of the time of financial statement publication on stock return (Model
1)
16
Event study: the length of windows in this study: [-90;90], [-5;5]. The following timeline
defines how these windows are used:
Graph 3.1: Length of windows
Estimation window Event
window
Post - event window
(1) Good news, bad news are defined based on UE (Bajo, 2010): good news is when UE
>0 and bad news UE <0. According to Begley, Joy and Paul Fischer 1998 UE can be
obtained from the following formula:
1,,, EPS tititi EPSUE
(16) EPS is calculated following Stock exchange:
EPS = Profit/Loss allocated to common shareholders
Average outstanding shares in the period
(17) SSL (Rt): according to Breyley and Myers (2004) and Nguyen Anh Phong (2015) with the
data from Thomson Reuters:
Rt =
Pt - Pt - 1 + Dt
Pt - 1
Trong đó: Rt is the return at t; Pt is the stock price at t
Pt-1 is the stock price at (t-1) ; Dt is the stock dividend (if any) at t
(18) Market return (Rm)
Rm is the market return, this variable is based on VNIndex and HNXindex. Based
on the daily close price, this variable is calculated using the following formula:
- For firms listed on HOSE :
Rm,t =
Vnindexi,t – Vnindexi,t-1
Vnindexi,t-1
- For firms listed on HNX:
Rm,t =
HNX-Indexi,t – HNX-Indexi,t-1
HNX-Indexi,t-1
(4) Abnormal return (AR):
ARi,t = Ri,t – αit– βRm
Where:
- ARit is the abnormal return of stock i at t
- Ri,t is the stock return of stock i at t
17
- Rm : market return at t
- it : constant ; is systematic risk
(19) Cumulated average abnormal return (CAAR): CAAR is the sum of the differences
between expected return from a stock and actual return around the publication date
of financial statements:
Where : AARt is the abnormal average return, calculated as the average of abnormal
returns for all firms in the sample from daily stock prices, with ARi, t+k being the
abnormal return of stock i at time t + k; is the cumulated stock return of stock i
from t to t + k.
Sample variance is calculated as follows :
Where : : average of AAR in 181 transaction days, without the effect of income
information CAR is expected to follow normal distribution:
(5) The author sorts CAAR of firms following the windows: [-5, - 4, -3,- 2, 0, 1, 2, 3, 4,
5 ] for short-term windows, and in long-term windows [-90, -60, -30, -10, 0, 10, 30, 60,
90 ], and divided into 2 groups: UE > 0 and UE < 0, in order to test whether CAAR
changes depending on UE > 0, UE<0 for the above windows. The results will help
conclude if the time of financial statement publication has impact on stock returns and
whether good news and bad news can influence CAAR.
(6) Conduct t test to check if CAAR is different from 0 significantly in each case
(7) The thesis examines each industry: Basic Materials, Consumer Goods, Consumer
Services, Health Care, Industrials, Oil & Gas, Technology, Others.
For firms that publish financial statements on time (Bagloni, 2002):
)*(CAAR ,,7,4,10, tk
negUE
tk
negUE
tktktk UEDDUE
For firms with late publication (Bagloni, 2002)
18
)**()*(
)*()*(CAAR
,,,10,,8
,,7,,5,4,2,10,
tk
negUE
tk
late
tk
negUE
tk
late
tk
ti
negUE
tktk
late
tk
negUE
tk
late
tktktk
UEDDDD
UEDUEDDDUE
For firms with early publication (Bagloni, 2002)
)**()*()*(
)*(CAAR
,,,11,,9,,7
,,6,4,3,10,
ti
negUE
tk
early
tk
negUE
tk
early
tktk
negUE
tk
tk
early
tk
negUE
tk
early
tktktk
UEDDDDUED
UEDDDUE
where: CAARkt is the abnormal cumulated average return (Bagnoli, 2002) of firms in
industry k at time t; D
late
is a dummy indicating firm issues financial statements late;
Dearly is a dummy indicating firm issues financial statements early; NegUE is a dummy
variable, indicating that unexpected earnings of firm is negative; UE is the difference
between actual and expected abnormal income on each share (Begley, Joy and Paul
Fischer, 1998; Bajo, 2010). K industries include: Basic Materials, Consumer Goods,
Consumer Services, Health Care, Industrials, Oil & Gas, Technology, Others.
(8) The author estimate models to examine the impact of the time of financial statement
publication on abnormal stock return, using Pooled OLS. The thesis further provides
descriptive statistics, correlation analysis and Woolridge test and Wald test for
unbalanced panel data. The author will propose ways to overcome problems related to
violations of OLS assumptions (if any) as suggested by tests.
3.3.2. Research methodology for the model on the impact of information contained
on financial statements and stock returns
In model 2, the study uses unbalanced panel data and Stata 12.0 to process data. The
study employs 3 methods: Pooled OLS, Fixed effects model (FEM) and Random effects
model (REM).
Tests for model selection: Selection between Pooled OLS and FEM: the study employs F
test to decide the choice between Pooled OLS and FEM. Choice between FEM and
REM: the study employs Hausman test to decide. Wald test is used to test
autocorrelation; Woolridge test is used to test for the heteroskedasticity. If tests suggest
there is either heteroskedasticity or autocorrelation, the author will overcome by using
robust/cluster option.
CONCLUSION OF CHAPTER 3
Chapter 3 presents in detail the methodology and data description for the study to deal
with research objectives.
19
CHAPTER 4: RESEARCH RESULTS AND DISCUSSION
4.1. Analysis of current status
4.1.1. The current status on the regulations regarding information publication in
Vietnam
From 2000 till now, the regulatory papers about information publication in Vietnamese
stock market have had great changes to accommodate market‘s revolution. Circular No.
48/1998/ND-CP is the first paper from the government providing guidance on
information publication. Next is Circular 144/2003/ND-CP, Law on Stock
70/2006/QH11, Circular 38/2007/TT-BTC, Circular 09/2010/TT-BTC in replacement of
Circular 38/2007/ND-CP, Circular 85/2010/ND-CP in replacement of Circular
36/2007/ND-CP, being the prerequisite to complementing part of Law on stock, but the
levels of fine imposed are not strong enough to act as a deterrent to violations. In 2012,
Circular 52/2012/TT-BTC was issued, replacing Circular no. 09/2010/TT-BTC with
many new regulations; Circular 155/2015/TT-BTC in replacement of circular
52/2012/TT-BTC with many changes. Moreover, Circular 155 also requires English
version of information to be published on Stock Exchanges and Stock Depository
Centers. State Stock Commission may grant an extension to the period of financial
statement publication, but not more than 100 days, from the end of fiscal year upon
receiving written text from firms. In cases of abnormal publication needed, in order to
allow for the timeliness of the information, Circular 155 states that the allowed time for
publication is 24 hours, which is much shorter than the 72 hours allowed in Circular 52.
Circular 155 also stipulates the same extension to half-year and quarterly financial
statement publication as in the case of full year financial statement publication. On
17/2/2017, Ministry of Finance issued paper No. 01/VBHN/BTC that combined Circular
145/2016/ND-CP and Circular 108/2013/ND-CP, which provides guidance on
punishment of administrative violations in fields of stock and stock market, effective
from 15/12/2016. The maximum cash fine for entity in violation is 2 billions and 1
billion for individuals.
These regulations have spurred the equality between listed and unlisted public firms, and
aimed to protecting the lawful rights of shareholders, investors and improved the
20
transparency of stock market, deterred and dealt with violations on information
publication in a timely manner.
4.1.2. The current status of information publication of listed firms in Vietnam
With the sprawling stock market, the delay in information publication, especially
financial statement publication, is on the rise.
Figure 4.1. Violations on information publication from 01/2008 to 20/09/2017
Source: Author’s compilation
In general, from the establishment event of Vietnamese stock market to 20/9/2017, most
of regulations of State Stock Commission are published and are open to reviews before
official issuance. The violations mostly center around reporting mode, information
publication of public firms, listed firms; insiders‘ stock transaction, large shareholders,
stock manipulation; and operations not consistent with license. State Stock Commission
have issued punishment decisions for cases of delay in information publication.
However, even with severe cash fines, violations in information publication are still hard
to harness. Insiders at least have gained enormously by purchasing or selling stocks from
delays in information publication on operation performances, and abnormal information.
The delay in information publication, especially quarterly financial statements, has
increasingly become common after 2010. Moreover, in the current context of abundance
of bad news, firms tend to exaggerate their expenses to inflat the losses in the current
periods so that they can reduce their expenses in the periods to come. This has t the
ability to predict corporate income, profitability forecasting and so hinders the
development of stock market.
21
4.1.3 Descriptive statistics on the information publication of listed firms in 01/2010-
06/2016
Figure 4.2. The number of firms publishing financial statements from 1/2010-6/2016
Source: Author‘s calculation
The thesis also analyzes the time of publication for firms of different industries in Figure
4.4.
Figure 4.4. Number of firms by industry that publish financial statements on time, late
and early as compared to regulation (1/2010-6/2016)
Source: Author‘s calculations
Figure 4.5: Number of firms publishing financial statements from 1/2010-6/2016 compared
to their own publication the previous year
22
Source: Author‘s calculations
From figure 4.5 we can see that in Vietnam the time of financial statement publication is
spread over 37 time periods, and unevenly scatters. However, it is clear that mainly firms
issue on day 0.
Figure 4.6: Number of firms publishing financial statements from 1/2010-6/2016
compared to their own publication in the previous year by industry
Source: Author‘s calculations
4.2. Results regarding the time of financial statement publication and stock return
(Model 1)
4.2.1. The relationship between good and bad news and the time of financial
statement publication
To quantify this relationship, the thesis adopts Nguyen (2010) by observing the changes
of the parameters of market model across the windows in question [-90,90]. CAAR is
23
calculated using market model and event study and t-statistics. Tables 4.3 and 4.4 show
that CAAR tends to be higher in short-term windows [-5,0] and long-term window [-
90,0] for both good and bad news prior to the publication of financial statements. This
trend continues after the event but only short-term [0,5] and long-term windows [0,90]
for good news. This could be because of the previous positive trend of the market. For
bad news, the market responds negatively in a prolonged period, both for long and short-
term windows.
a. In short term
Prior to the event (financial statement publication): in short term and with good news, t-
statistics changes in days of financial publication, tend to be high for firms with good
news and early publication. After the event: For good news after the publication t-
statistics show no significance and not economically meaningful. T-statistics for good
news is 0.55 for [0,1], 1.04 for [0,3] and 0.2 for [0,5].
Table 4.1. Relationship between good news, bad news and thet ime of financial
statement publication in short term
Good news ( UE>0) Bad news (UE<0)
Days CAAR t-statistic
Pr
(T>t)
Days CAAR t-statistic
Pr
(T>t)
-5 0.002829 1.7657
(**)
0.0389 -5 0.007680 4.2254
(***)
0.0000
-4 0.002460 1.7006
(**)
0.0446
-4 0.006405 3.8582
(***)
0.0001
-3 0.000731 0.5534
0.2910
-3 0.002481
2.2718
(**)
0.018
-2 0.000536 0.5224 0.243 -2 0.003482 2.2919
(**)
0.011
-1 -0.000256 -0.2553 0.6007
-1 0.001876 1.590
(*)
0.0561
0 0.000093 1.0376 0.1498 0 -0.000117 -0.1471
0.5585
1
0.000675 0.5521 0.2905
1 -0.003866 -0.369 0.6442
2
0.001090 0.0760
0.4697
2 -0.005081 -0.4017
0.656
3
0.001682 1.0450 0.1481
3 -0.007497 -0.5354 0.7037
4
-0.000195 -0.1299
0.7774
4 -0.001292 -0.7538 0.5517
5
0.003319 0.2014
0.4202 5 -0.000518
-0.2766
0.6089
Notes: *** significant at 1% level; ** significant at 5% level; * significant at 10% level
Source: Author’s calculations
24
b) In long term
In long term with good news, t-statistics show statistical significance and tend to be high
for good news being published early.
Table 4.2. Relationship between good, bad news and the time of financial statement
publication in long term
Good news (UE>0) Bad news (UE<0)
Days CAAR
t-
statistic
Pr
(T>t)
Days CAAR t-statistic
Pr
(T>t)
[-90,0] 0.00788 1.4176
(**)
0.0783 [-90,0] 0.03252 5.4547
(***)
0.000
[-60,0]
0.01811 3.8414
(***)
0.0001 [-60,0] 0.03579 6.9766 0.000
[-30,0] 0.01469 4.5379
(***)
0.0000 [-30,0] 0.02293 6.1678
(***)
0.000
[-10,0] 0.00627 3.1755
(***)
0.0008 [-10,0] 0.00898 3.9959
(***)
0.000
[10,0]
0.00021 0.1104 0.4561 [10,0] 0.00055 0.2468 0.4026
[30,0]
0.00309 0.5619
0.2871 [30,0] 0.00349 0.8158
0.2074
[60,0]
0.00298 0.5231
0.3005 [60,0] -0.00655
-1.0005
0.8714
[90,0]
0.00330
0.4978
0.3093 [90,0] -0.00930 -1.2910 0.9015
Notes: *** significant at 1% level; ** significant at 5% level; * significant at 10% level
Source: Author’s calculations
From tables 4.1 and 4.2, it is clear that for good news CAAR is highest on day -5 and +
5, and bad news CAAR is highest on day -5 and +3. If firms publish financial statements
early, CAAR in [-5,0] is positive, regardless of bad news or good news, and this window
also has high t-statistics and strong significance. On the other hand, the market responds
negatively right after receiving the bad news (day 0). CAAR tends to be higher in short
window [-5,0] and in long-term window [-90,0] for both good and bad news in the
periods prior to financial statement publication.
In summary, it can be concluded that the time of financial statement publication has
impact on abnormal stock return, and managers strategize on information publication:
bad news to be published late and good news to be published early. Therefore, there is
evidence to accept H1.
25
4.2.2 Regressions on the link between time of financial statement publication and
abnormal return
The results presented in tables 4.3, 4.4 and 4.5 are as follows:
For industry: This study employs Pooled OLS (from Bagnoli (2002)) to examine the link
for each industry in cases of early, late and on time publication compared to last year
publication. The findings show that the time firms publish financial statements late has
impacted CAAR the most and statistically significant for 2 industries which are
Consumer services and Consumer goods. There is no evidence that firms that publish earl
have significant impact on CAAR. In case of on time publication, firms that deliver bad
news are subject to punishment from market, especially Industrials, Consumer services.
There is no evidence showing the impact of time of financial statement publication on
CAAR for firms in industries like Energy & Gas and Technology.
a. Regressions on the link between the time of financial statement publication and CAAR
for firms that public late
Table 4.3. Good news, bad news and CAAR of firms publishing information late
CAAR ue late
neg
_ue
late_ue negue_ue
late
_negue
late
_negue_ue
_cons
Sum
Coef. 0.09724 -0.1816 -0.0944 0.0000 5.21E-06 -0.0139 -0.00001 0.28364
t 2.05 -4.29 -2.48 1.39 0.46 -0.23 -0.65 5.59
P>|t| 0.041 0.000 0.013 0.166 0.645 0.819 0.514 0.000
Obs 1081
R
2
0.1337
P > F 0.000
Basic
Materials
Coef. -0.0192 -0.4153 -0.0562 0.00002 -1.45E-05 0.14316 0.00001 0.41553
t -0.1 -2.83 -0.37 0.51 -0.23 0.64 0.13 2.1
P>|t| 0.918 0.005 0.71 0.613 0.822 0.524 0.897 0.037
Obs 131
R
2
0.1777
P > F 0.0225
Comsumer
Goods
Coef. 0.0939 -0.154 -1.231 -1.139 5.21E-06 -0.0409 7.4E-06 1.42407
t 1.98 -4.04 -1.93 -1.79 0.46 -0.7 0.38 2.23
P>|t| 0.048 0.000 0.053 0.074 0.645 0.482 0.704 0.026
Obs 153
R
2
0.1343
P > F 0.000
Consumer
Services
Coef. 0.10522 -0.5357 -0.4598 0.00001 2.01E-06 0.3512 -0.51560 0.63836
t 2.26 -9.77 -8.69 1.31 0.2 4.97 -9.59 10.31
P>|t| 0.024 0.000 0.000 0.19 0.841 0.000 0.000 0.000
Obs 72
26
R
2
0.1712
P > F 0.000
Health Care
Coef. 0.08642 -0.2133 -0.1771 0.00005 6.17E-06 0.05118 -0.00004 0.34473
t 1.22 -3.21 -2.82 1.64 0.19 0.52 -0.86 4.57
P>|t| 0.223 0.001 0.005 0.100 0.852 0.605 0.392 0.000
Obs 32
R
2
0.1394
P > F 0.00
Industrials
Coef. 0.19364 -0.3063 -0.1427 0.00012 -0.00011 0.05682 -0.00002 0.21200
t 1.26 -1.95 -0.93 1.11 -0.82 0.26 -0.14 1.24
P>|t| 0.209 0.054 0.354 0.269 0.412 0.796 0.888 0.217
Obs 595
R
2
0.1089
P > F 0.0402
Other
Coef. 0.09547 -0.1743 -0.0993 0.00001 3.88E-06 -0.0095 -2.32E-06 0.28694
t 2.01 -4.28 -2.58 1.13 0.29 -0.16 -0.22 5.57
P>|t| 0.044 0.000 0.01 0.257 0.770 0.876 0.830 0.000
Obs 47
R
2
0.1336
P > F 0.000
Source: Author’s calculations
b. Regression results on the link between the time of financial statement publication
and CAAR for firms publishing early
Table 4.4: Good news, bad news and the time of financial statement publication for firms
publishing financial statements early
CAAR ue early
neg
_ue
early
_ue
negue
_ue
early
_negue
early
_negue _ue
_cons
Sum
Coef. 0.1141 0.00001 -0.1528 -6.1E-06 -0.1381 -0.07485 -5.2E-07 0.2588
t 2.39 0.89 -3.98 -0.49 -3.37 1.23 -0.02 5.15
P>|t| 0.017 0.374 0.00 0.627 0.001 0.218 0.982 0.000
Obs 571
R
2
0.1203
P > F 0.00
Basic
Materials
Coef. 0.2327 0.00004 -0.0040 -4.5E-06 -0.2162 -0.11244 -5.3E-05 0.0365
t 1.82 1.16 -0.04 -0.1 -1.84 -0.64 -0.61 0.26
P>|t| 0.07 0.247 0.97 0.924 0.067 0.52 0.543 0.798
Obs 91
R
2
0.1569
P > F 0.0315
Comsumer
Goods
Coef. 0.0871 0.00001 -0.1971 -1.1E-05 -0.1253 0.02524 -2.3E-06 0.3322
t 1.22 0.71 -3.29 -0.35 -1.91 0.25 -0.04 4.36
P>|t| 0.222 0.479 0.001 0.727 0.056 0.801 0.967 0.000
Obs 137
R
2
0.1294
27
P > F 0.00
Consumer
Services
Coef. 0.1142 0.00001 -0.1545 -6.2E-06 -1.39E-01 0.07576 0.02357 0.2474
t 2.39 1.14 -4.21 -0.59 -3.44 1.27 0.87 4.77
P>|t| 0.017 0.256 0.00 0.558 0.001 0.205 0.382 0.00
Obs 71
R
2
0.1206
P > F 0.00
Health Care
Coef. 0.1135 0.00001 -1.2982 -6.3E-06 -1.36E-01 0.07340 -1.14682 1.4044
t 2.38 1.17 -2.02 -0.6 -3.37 1.23 -1.79 2.19
P>|t| 0.018 0.241 0.043 0.551 0.001 0.219 0.074 0.029
Obs 39
R
2
12.16
P > F 0.00
Industrials
Coef. 0.1155 0.000004 -0.1348 -1.4E-06 -0.1303 0.05709 1.71E-05 0.2449
t 2.41 0.33 -3.43 -0.13 -3.19 0.93 1.29 4.77
P>|t| 0.016 0.742 0.001 0.898 0.001 0.352 0.196 0
Obs 571
R
2
12.10
P > F 0.00
Other
Coef. -0.0394 0.00027 0.28563 -0.00022 -2.21E-01 -0.62653 -1,83E-04 0.5051
t -0.12 2.18 1.16 -1.16 -0.64 -1.42 -0.72 1.64
P>|t| 0.902 0.035 0.252 0.252 0.524 0.162 0.475 0.109
Obs 43
R
2
21.11
P > F 0.0505
Source: Author‘s calculation
c. Regression results on the link between time of financial statements and CAAR for
firms reporting on time compared to last year
Table 4.5. The link between good news, bad news and the time of financial statement
publication of firms publishing on time
CAAR ue neg_ue negue_ue _cons
Sum
Coef. 0.11970 -0.13597 -0.10706 0.24073
t 2.53 -5.11 -3.91 4.99
P>|t| 0.011 0.00 0.00 0.00
obs 161
R-squared 0.1197
Prob > F 0.00
Comsumer
Goods
Coef. 0.11425 -0.11288 -0.05599 0.20357
t 2.41 -3.7 -1.42 4.27
P>|t| 0.016 0.00 0.157 0.00
R-squared 0.1142
obs 31
28
Prob > F 0.00
Prob > F 0.00
Industrials
Coef. 0.21850 -0.21618 -0.00019 0.13713
t 1.43 -2.11 -2.23 0.87
P>|t| 0.154 0.036 0.028 0,385
obs 83
R-squared 0.164
Prob > F 0.0357
Source: Author‘s calculation
4.3. Research results (method 2)
4.3.1. Descriptive statistics
Table 4.6. Descriptive statistics
Variable Obs Mean Std. Dev. Min Max
return 2723 0.23438 0.34309 -0.82 4.39
sue 2718 0.23713 0.26900 -3.59 2.81
size 2717 12.9190 1.07142 10.43 17.88
bm 2692 0.25705 0.25482 0 0.81
dvol 2726 21.2345 4.25703 9.98 28.31
ret12 2721 0.03535 0.27271 -0.81 14.23
da 2730 0.19194 0.15557 0 1
audit_s 2730 0.91978 0.27168 0 1
Source: Author‘s calculation
4.3.2. Analysis of correlation coefficients
Table 4.7: Pearson correlation coefficient matrix
Variable return sue size bm dvol ret12 da audit_s
return 1.0000
sue 0.1971 1.0000
size -0.0990 -0.0853 1.0000
bm 0.0108 0.0216 -0.0447 1.0000
dvol 0.0157 0.0109 -0.0100 0.1023 1.0000
ret12 0.0103 0.0018 -0.0184 -0.0419 -0.0013 1.0000
da 0.0169 0.0271 0.0090 0.0125 -0.0177 -0.0039 1.0000
audit_s 0.0504 0.1031 -0.0154 -0.0247 0.0108 0.0051 0.0429 1.0000
Source: Author‘s calculation
29
The results from table 4.7 suggest that the absolute values of correlation coefficients
between variables are smaller than 0.8, indicating that multicollinearity is not a major
problem.
4.3.3. Multicollinearity test
The author performs VIF (Variance Inflation Factor). The result is presented in table 4.8,
showing that all coefficients are smaller than 10, which again confirms that
multicollinearity should not be a major problem.
Table 4.8: Results of multi-collinearity test
Variable VIF 1/ VIF
sue 1.02 0.981213
size 1.02 0.984628
audit_s 1.01 0.98698
dvol 1.01 0.988990
bm 1.01 0.990436
da 1.00 0.997305
ret12 1.00 0.997753
Mean VIF 1.01
Source: Author‘s calculation
4.3.4 Results of regressions
Table 4.9: Results using Pooled OLS method
Variable Coef. Std.Err. P>ǀtǀ
sue 0.2699635*** 0.025555 0.000
size -0.0986713*** 0.027333 0.000
bm 0.0118245 0.022789 0.604
dvol -0.0014924 0.006468 0.818
ret12 -0.0010370 0.001508 0.492
da -0.0007827* 0.000443 0.077
audit_s 0.0345192 0.025411 0.174
_cons 0.1842679** 0.090302 0.041
Số quan sát 2178
F(7, 2170) 19.46
Prob>F 0.0000
30
R-squared 0.1152
Adj R-squared 0.1134
Notes: *** significant at 1% level; ** significant at 5% level; * significant at 10% level
Source: Author’s calculations
The results from table 4.9 show that sue, size and da are statistically significant. The
study also employs FEM and REM to estimate panel data model.
Table 4.10: Results using Fixed effects model
Variable Coef. Std.Err. P>ǀtǀ
sue 0.2404454*** 0.032484 0.000
size -0.110325*** 0.036533 0.003
bm 0.0134836 0.027614 0.625
dvol 0.0088709 0.009666 0.359
ret12 0.0007759 0.002614 0.767
da -0.000759 0.000487 0.119
audit_s 0.038842 0.036751 0.291
_cons 0.0177913 0.139474 0.899
Observation 2178
F test that all u_i = 0: F(481,1689) = 0.57
Prob > F
R-squared :
0.7954
within 0.1296
between 0.2517
overall 0.1125
Notes: *** significant at 1% level; ** significant at 5% level; * significant at 10% level
Source: Author’s calculations
The results from table 4.10 show that FEM significant with Pvalue =0.0000, and the
model explains 12.96% the variation in the dependent variable. Only sue and size are
statistically significant.
Table 4.11: Results using Random effects model
Variable Coef. Std.Err. P>ǀzǀ
sue 0.2699635*** 0.025555 0.000
size -0.098671*** 0.027333 0.000
bm 0.0118245 0.022789 0.604
dvol -0.001492 0.006468 0.818
31
ret12 -0.001037 0.001508 0.492
da -0.000783* 0.000443 0.077
audit_s 0.0345192 0.025411 0.174
_cons 0.1842679** 0.090302 0.041
Observation 2178
Wald chi2 (7)
Prob > chi2
136.25
0.0000
R-squared :
within 0.1284
between 0.2646
overall 0.1591
Notes: *** significant at 1% level; ** significant at 5% level; * significant at 10% level
Source: Author’s calculations
The results from table 4.11 show that REM model is significant with pvalue =0.0000,
and the explanatories explain 12.84% of the variation in the dependent variable (stock
return). In this model, sue, size and da are statistically significant. The study continues
with Breusch & Pagan, Hausman tests to decide which model to choose (among Pooled
OLS, FEM, REM).
4.3.5. Tests for model selection
Table 4.12: Summary of tests for model selection
Test Pooled-OLS & FEM Pooled-OLS & REM FEM & REM
F - test F (481, 1689) = 0.57
và Prob > F= 0.7954
Breusch – Pagan
test
Chibar2 (01) = 0.00
Prob > chibar2 = 0.0447
Hausman test
Prob>chi2 =
0.6520
Conclude Choose Pooled-OLS Choose REM Choose REM
Source: author‘s calculations
b/Test for heteroskedasticity: the result shows that there is heteroskedasticity
c/Test for autocorrelation: the result shows that theire is no autocorrelation
32
d/Address heteroskedasticity: the study continues with REM method with robust option
to address heteroskedasticty
Table 4.13: Regression results after addressing heteroskedasticity
Variable Coef. Std.Err. P>ǀtǀ
sue 0.2699635*** 0.041146 0.000
size -0.098671*** 0.027148 0.000
bm 0.0118245*** 0.001729 0.000
dvol -0.001492 0.006909 0.829
ret12 -0.001037 0.001416 0.464
da -0.000783* 0.000448 0.081
audit_s 0.0345192 0.024845 0.165
_cons 0.1842679* 0.095204 0.053
Obs 2178
Wall chi2(7) 327.11
Prob > chi2
R-squared :
0.0000
within 0.1284
between 0.2646
overall 0.1594
Notes: *** significant at 1% level; ** significant at 5% level; * significant at 10% level
Source: Author’s calculations
Table 4.13 shows that among the 7 regressors, 3 (sue, size, bm) are significant at 1%
level and 1 (da) at 10%. Dvol, ret12 and audit_s are those that are not statistically
significant. Bm and sue are positively and correlated with stock returns, and size and
adjusted accounting income have negative correlation with stock returns. The other
variables are not significant.
4.3.6 Results and discussion
4.3.6.1. Statistically significant variables
SUE: this variable is positively correlated with stock return and significant at 1% level.
The coefficient is 0.26996, meaning that as standardized income increases by 1 unit,
stock return increases by 0.26996 unit, ceteris paribus. Hypothesis H8 about the positive
33
link between stock return and standardized unexpected earnings is accepted. This result
is also in line with studies such as Chordia (2006), Vinh and Phuong (2014).
Size: this variable is negatively correlated with stock return and significant at 1% level.
The coefficient is -0.098671, meaning that when size increases by 1 unit, stock return
decreases by 0.098671 unit. This is also consistent with Chordia (2006, 2013) and Vinh
and Phuong (2014). The hypothesis H2 is accepted.
BM: bm means the ratio of book to market value. The result shows that there is a positive
relation between book to market ratio and significant at 1% level. The coefficient is
0.011824, meaning that when book to market ratio increases by 1 unit, stock return
increases by 0.011824 unit, ceteris paribus. Therefore, the hypothesis H3 is accepted,
which is consistent with Yuenan Wang and Amalia Di Iorio (2007), Vinh and Phuong
(2014), Nguyen Anh Phong (2015).
DA: managers should abide by the laws and at the same time be flexible in preparing
financial statements that reflect firm‘s financial health the best. They should not illegally
perform earnings management as in Friedlan (1994). The regression result shows that
there is a negative relationship between discretionary accruals and stock returns at 10%
level. The coefficient is -0.000783, meaning that when discretionary accruals increase by
1 unit, stock return decreases by 0.000783 unit. This is consistent with hypothesis H6.
This is also compatible with the realit in emerging stock markets like Vietnam, with most
investors searching for profits from firms as soon as possible, especially right in the year
they hold the stock rather than years later in the future. This result is consistent with the
findings from Erlynda Y Kasim (2013) for Indonesian stock market.
4.2.6.2. Statistically insignificant variables
DVOL: Transaction volume in money is the volume of securities sold during the day,
calculated as the unadjusted price at closing multiplied by the number of shares traded in
the day, reflecting trading activities of investors in a certain time period. As the number
of shares traded per day can be very large, the transaction value in money used in the
research is also large. Therefore, this variable is calculated as its natural logarithm
(Bernnan, 1998). The analysis of this factor is to confirm the strength of the current
trend, or to determine the potential reversal of stock prices. The results show that there is
a negative relationship between the transaction volume in money and stock return but
with no statistical significance (P.value = 0.829). Therefore, the research results have not
34
proved the impact of traded volume in money and stock return. There is insufficient
statistical evidence to accept the H5 hypothesis, and this result is consistent with that of
Vinh and Phuong (2014).
RET12: The RET12 variable is stock return momentum. Based on this index, investors
can judge the trend of stock returns in the present and future. The research results have
not proved that there is a positive relationship between the momentum of stock return
and stock return (P.value = 0.464). Therefore, there is insufficient statistical evidence to
accept the hypothesis H4. The result is consistent with the results of Brennan (1998),
Chordia (2006) and in contrast with the results of Vinh and Phuong (2014).
Audit-s: This variable represents the size of the auditing firm (whether auditing firm
belongs to Big6). Regression results show that its coefficient positive and not statistically
significant (P.value = 0.165). This result shows that investors have not paid much
attention to whether the listed companies are audited by the Big 6 companies or not. In
short, there is insufficient statistical evidence to accept the H7 hypothesis which claims
that the influence of the size of the audit firm has impact on stock return. The results in
section 4.1 (descriptive statistics) show that the ratios of financial statements having
exception audit clause are pretty similar between the companies audited by Big6
(42.77%) and not Big6 (57.23%). This shows that investors have not paid attention to
whether the financial statements of companies are audited by one of the largest 6 auditing
companies in Vietnam. This result was also found in the Indonesian stock market as in
Erlynda Y. Kasim (2013).
Table 4.14. Summary of research results
Variable
Realistic
expectations
Result
Size
-
(***)
consistent with the hypothesis, and in consistent with
Chordia (2006, 2013), and the same sign as in Vinh and
Phuong (2014)
BM
+
(***)
consistent with the hypothesis, and in consistent with
Yuenan Wang and Amalia Di Iorio (2007), Vinh and
Phuong (2014), Nguyen Anh Phong (2015)
RET12
-
consistent with the hypothesis, in consistent with Vinh
and Phuong (2014), but in contrast with Brennan
(1998), Chordia (2006). RET12 is insignificant.
35
Dvol -
Inconsistent with the hypothesis, and this result is in
contrast with Vinh and Phuong (2014). This result
shows that DVOL is insignificant.
DA
_
(*)
Consistent with the hypothesis and is significant, and
consistent with Erlynda Y. Kasim (2013).
Audit-s +
Consistent with the hypothesis and is significant, and
consistent with Erlynda Y. Kasim (2013), showing that
audit_s is insignificant.
Sue
+
(***)
Consistent with the hypothesis and is significant, and
consistent with Chordia (2006), Vinh and Phuong
(2014).
Notes: *** significant at 1% level; ** significant at 5% level; * significant at 10% level
Source: Author’s summary
CONCLUSION OF CHAPTER 4
This chapter presents and discusses research findings.
CHAPTER 5: CONCLUSION AND POLICY IMPLICATIONS
5.1. Conclusion
The thesis draws following conclusions:
5.1.1. Research objectives and hypotheses
The thesis has finalized the testing of the following hypotheses:
Table 5.1: Synthesis of tested hypotheses
Hypothesis Content Reject/Accept
H1
There is a link between time of financial statement publication
and CAAR. Managers strategize on information publication,
meaning that bad news to be published late and good news to be
published early.
Accept
H2
There is a negative link between firm size and stock return when
financial statements are published
Accept
H3
There is a positive link between book to market ratio and stock
return when financial statements are published
Accept
H4
There is a positive link between return momentum and stock
momentum when financial statements are published
Does not
accept
H5
There is a positive link between transaction volume measured in
monetary unit and stock return when financial statements are
published
Does not
accept
36
H6
There is a negative link between discretionary accruals and stock
returns when financial statements are published
Accept
H7
There is a positive link between auditor‘s size and stock return
when financial statements are published
Does not
accept
H8
There is a positive link between standardized unexpected
earnings and stock returns when financial statements are
published
Accept
Source: Author’s summary
5.1.2. Research results
Domestic and foreign studies have shown that information on financial reports is
considered by managers, investors and regulators as one of the sources of official and
important information. Based on the study of the relationship between publication time
and financial factors, the dissertation has dealt with the following issues:
Firstly, the thesis has provided the theoretical foundations of efficient market, agency
theory, behavioral finance theory, information concepts, financial information and
publication time. In addition, the dissertation collects evidence from domestic and
international research on the impact of time and information on the published financial
statements.
Secondly, the thesis has synthetic the method of event research (with regard to the time
of financial statement disclosure), to study the stock return of each listed firm with late
and early publication, for the whole sample and each individual industry.
+ In addition, the thesis has proposed the research hypotheses, collect data to perform
regression analysis as well as test relevant hypothesess.
+ The dissertation has systematized the theoretical basis for quantitative research
methods to be conducted for this study.
Thirdly, the dissertation has conducted research on the impact of timing of financial
statements disclosure and the financial factors on stock returns.
Research has addressed the following issues:
(a) The timing of financial statement disclosure has an impact on abnormal stock returns
of listed firms and executives of listed firms do implement disclosure strategy, ie, good
information from the financial statements is released early and bad news is released late.
+ By using the event method and the adjusted market return model according to Brown
and Warner (1985), Hedge and McDermott (2003), Denis et al. (2003), Gregoriou and
37
Ioannidis (2006), Nguyen (2010) during 181 business days around the date of publication
of income, the following results are obtained:
For good news CAAR is highest on day -5 and + 5, and bad news CAAR is highest on
day -5. If firms publish financial statements early, CAAR in [-5,0] is positive, regardless
of bad news or good news, and this window also has high t-statistics and strong
significance. On the other hand, the market responds negatively right after receiving the
bad news (day 0). CAAR tends to be higher in short window [-5,0] and in long-term
window [-90,0] for both good and bad news in the periods prior to financial statement
publication.
For industry: This study employs Pooled OLS (from Bagnoli (2002)) to examine the link
for each industry in cases of early, late and on time publication compared to last year
publication.
The findings show that the time firms publish financial statements late has impacted
CAAR the most and statistically significant for 2 industries which are Consumer services
and Consumer goods.
There is no evidence that firms that publish early have significant impact on CAAR. In
case of on time publication, firms that deliver bad news are subject to punishment from
market, especially Industrials, Consumer services.
There is no evidence showing the impact of time of financial statement publication on
CAAR for firms in industries like Energy & Gas and Technology.
(b) The dissertation, using three regression models Pooled OLS, FEM, REM, has
identified and quantified the impact of information disclosed on the financial reports on
stock returns in Vietnam. Specifically, factors such as company size, book to market
value , standardized unexpected earnings, discretionary accruals significantly impact
stock returns. In addition, the study cannot find statistical evidence about the relationship
between stock return and transaction volume in cash, the momentum of stock return and
the size of the audit firm.
Fourthly, the thesis has made some recommendations related to the timing of publication
of financial statements and financial information on financial statements, thereby
enhancing the stock returns of listed firms.
+ Based on the results of regression and discussion of research results, the thesis
proposes 3 groups of recommendations for the following stakeholders:
38
* Investors:
When it comes to the time of financial statement disclosure of listed firms in short and
long term, investors should pay attention to firms in industries of Consumer Services and
Consumer Goods when late financial statements are released. The information disclosed
on the financial statements, such as book to market value, company size, abnormal
income fluctuations, especially discretionary accruals, etc.
* Listed companies:
When it comes to the time of financial statement disclosure, the disclosure should be in
accordance with the State regulations on disclosure, ensure good grasp and strict
management of internal information, timely auditing of financial statements, create
prestige and trust for investors as well as the authorities. It is not always easy to expand
the company to garner high stock returns, and instead firms need to effectively manage
the existing resources in the current economic situation, focus on public relations (IR),
corporate social responsibility, ...
* The authorities: need to have separate regulation on information disclosure for listed
firms with high market value, and impose strict delisting on firms that turn in financial
statements late...
5.2 Recommendations for future research
The thesis points out the limitations of the study and suggests directions for future
research, research sample and other factors affecting the stock market.
CONCLUSION CHAPTER 5
In Chapter 5, the thesis concludes and proposes recommendations to investors, managers
of listed firms and state authorities to enhance stock returns, step by step improve the
transparency of stock market, contribute to the effective operation of stock market. The
thesis also outlines the new research contributions and presents the limitations of the
research and further research.
39
LIST OF AUTHOR’S PUBLICATION
(1) Nguyen Thi Ngoc Diep (2017): ―The timing of financial statement publication and
stock return: the case of Vietnam‖. International Conference for Young Researchers
in Economics and Business (ICYREB 2017). ISBN: 978-604-84-2640-8
(2) Nguyen Thi Ngoc Diep (2017): ―Financial reporting information and impact on
stock returns‖. Financial Journal Vol 2-2017 (657) .pp 39
(3) Nguyen Thi Ngoc Diep, Bui Van Thuy, Hoang Thi Quynh Anh (2017): ―The Effect
Voluntary Disclosure, Macro and Micro Factors on Stock Returns: Evidence from
Vietnam‖. Journal of Science of Lac Hong University 2017- ISSN : 2525-2186.
Registration authentication.
(4) Nguyen Thi Ngoc Diep, Nguyen Thanh Lam (2017): ―The Impact of Earnings
Information on Financial Statements on Stock Returns in Vietnam‖. Journal of
Science of Lac Hong University 2017- ISSN : 2525-2186. registration
authentication
(5) Pham Ngọc Toàn, Nguyen Thi Hang Nga, Nguyen Kim Nam, Nguyen Thi Ngoc
Diep (2016): ―Effects of audit firm size and auditor charactereristics on firms‘
discretionaty accrual management‖. Proceedings of international conference on
accounting & finance 2016 (ICOAF 2016). ISBN 978-604-84-1563-1
(6) Nguyen Thi Ngoc Diep, Nguyen Thanh Lam (2017): ―Determinants of Liquidity of
Commercial Banks in Vietnam in the Period 2009-2016‖. International Journal of
Scientific Study, ISSN: 2321-6379, Vol 5. DOI: 10.17354/ijssSept/2017/45.
(7) Nguyen Thanh Liem, Nguyễn Thị Canh, Nguyen Thi Ngoc Diep (2017): ―Corporate
debt maturity structure: quantile regression and Oaxaca-Blinder decomposition
approaches‖. International Conference for Young Researchers in Economics and
Business (ICYREB 2017). ISBN: 978-604-84-2640-8
(8) Nguyen Thi Ngoc Diep, Nguyen Kim Nam, Nguyen Thi Hang Nga (2016): ―The
impact of foreign direct investment and financial development on economic growth:
Evidence Asean countries‖. Proceedings of the Foreign Trade University. ISBN:
987-604-73-9348-8
(9) Nguyen Thi Ngoc Diep, Nguyen Minh Kieu (2015): ― Effects of Specific Banking
Fctors on Credit Rick of Vietnam‘s Commercial Bank‖. Journal of Economic
Development. Vol 3 - ISSN 1859-1124.
(10) Nam K.Nguyen, Nga T.H.Nguyen, Diep T.N.Nguyen (2015) : ―The Impact Of
Business And Consumer Confidence On Stock Market Risk Premiums: Evidence
From Vietnam‖. Asian Journal of Management Sciences. ISSN 2348-0351.
(11) Nguyen Thi Ngoc Diep, Nguyen Minh Kieu (2013):― Financial factors affecting
investment decision by individual investors at HCMC trading floor‖. Science of
Open Unversity. Vol 3 – ISSN 1859-3453
THÔNG TIN TÓM TẮT
NHỮNG ĐÓNG GÓP MỚI VỀ MẶT HỌC THUẬT VÀ LÝ
LUẬN CỦA LUẬN ÁN
Tên đề tài: THÔNG TIN TÀI CHÍNH TÁC ĐỘNG ĐẾN SUẤT SINH LỜI CHỨNG
KHOÁN CỦA CÁC CÔNG TY NIÊM YẾT TẠI THỊ TRƢỜNG CHỨNG
KHOÁN VIỆT NAM
Chuyên ngành: Tài chính - Ngân Hàng. Mã số: 62.34.02.01
Cơ sở đào tạo: Trƣờng Đại Học Ngân Hàng TP. Hồ Chí Minh
Người hướng dẫn khoa học: PGS. TS. LÝ HOÀNG ÁNH
Luận án này thực hiện để nghiên cứu thông tin tài chính ảnh hưởng đến suất sinh
lời cổ phiếu khi công bố BCTC. Với những kết quả đạt được từ mô hình thực nghiệm, về
mặt học thuật, luận án mang mang lại đóng góp mới trên cơ sở bổ sung vào khoảng trống
nghiên cứu thông qua cung cấp bằng chứng thực nghiệm về tác động của thời gian công
bố BCTC và các thông tin tài chính tác động đến suất sinh lời.
(4) Nghiên cứu được thực hiện trên phạm vi toàn TTCK VN và có ưu điểm là nghiên
cứu trên từng nhóm ngành cụ thể, dựa trên phương pháp nghiên cứu sự kiện, lấp đầy các
khoảng trống nghiên cứu về phạm vi này. Kết quả cho thấy CAAR có xu hướng cao hơn
trong cả khoảng thời gian ngắn hạn [-5;0] và trong khoảng thời gian dài hạn [-90;0] cho cả
tin tốt và tin xấu trong giai đoạn trước sự kiện công bố BCTC.
Đối với các ngành: Thời gian các CTNY công bố BCTC trễ có tác động đến CAAR
trong hầu hết các ngành, phản ứng tiêu cực mạnh nhất và có ý nghĩa thống kê đối với hai
ngành là Dịch vụ tiêu dùng và Hàng hóa tiêu dùng; Đối với trường hợp công bố BCTC
sớm, chưa có bằng chứng thực nghiệm về các công ty có thời gian công bố sớm tác động
có ý nghĩa đến CAAR. Nếu các công ty có thời gian công bố BCTC sớm mà các thông tin
chứa đựng trong đó là xấu thì cũng nhận được phản ứng tiêu cực của thị trường và đều có
ý nghĩa thống kê, mạnh nhất là đối với ngành Chăm sóc sức khỏe, kế đến là ngành Hàng
hóa tiêu dùng, Dịch vụ tiêu dùng; Trong trường hợp công bố đúng thời gian thì thông tin
về thời gian công bố BCTC có tác động dương đến CAAR và có ý nghĩa thống kê, nhưng
những thông tin trên BCTC là xấu thì cũng chịu sự trừng phạt của thị trường, mạnh nhất ở
nhành Công nghiệp, sau đó là ngành Hàng hóa tiêu dùng. Chưa có bằng chứng thống kê
cho thấy tác động của thời gian công bố BCTC đến CAAR đối với ngành năng lượng &
khí đốt và ngành công nghệ.
(5) Từ kết quả nghiên cứu luận án đã xác định và định lượng được các thông tin công
bố trên BCTC có tác động đến SSL chứng khoán của các CTNY trên TTCK Việt Nam,
đặc biệt là lợi nhuận kế toán điều chỉnh có tác động ngược chiều và có ý nghĩa thống kê
đến suất sinh lợi chứng khoán.
(6) Cuối cùng, luận án cũng đưa ra những hạn chế và một số khuyến nghị liên quan đến
thời gian công bố BCTC và các TTTC trên BCTC, qua đó nâng cao SSL đối với nhà đầu
tư, đối với các CTNY và đối với cơ quan quản lý nhà nước.
Người hướng dẫn khoa học Nghiên cứu sinh
PGS. TS. LÝ HOÀNG ÁNH NGUYỄN THỊ NGỌC DIỆP
A SUMMARY OF INFORMATION ON
NEW CONTRIBUTIONS OF THE THESIS
TILE OF THE THESIS: THE IMPACT OF FINANCIAL INFORMATION
ON STOCK RETURN OF VIETNAMESE LISTED FIRMS
Major : Finance and Banking Code: 62.34.02.01
Institution : Banking University Hochiminh City
Science instructor: Assoc. Prof. Dr. Ly Hoang Anh
This dissertation is to study the impact of financial information on stock returns when
financial statements are announced. Academically, the thesis brings new contributions on
the basis of addition to the research gap by providing empirical evidence on the effect of
timing of financial statement announcement and financial information on firms‘
profitability.
(1) The research was conducted using a sample of all Vietnamese listed firms and event
study and it is advantageous to study specific industries. The results sugget that CAAR
tends to be higher in short window [-5;0] and in long window [-90;0] for both good news
and bad news in the period prior to the announcement.
With related to industries: the time when firms announce financial statements late tend to
have negative impact on CAAR for most industries, especially for two industries namely
Consumer Services and Consumer Goods; For firms that pubish financial statements
early, no empirical evidence is recorded that early announcement of financial statements
has impact on CAAR. If firms publish information early and information contained is bad
news then firms tend to receive statistically significant negative feedback from market,
especially strongest is Industrials, then Consumer Goods. There is no evidence showing
the impact of the timing of financial statement on CAAR in Energy and Gas and
Technology industries.
2) The empirical findings have identified and quantified that the information contained in
financial statement has impact on stock return of listed firms in Vietnam, especially
accounting profit (xem lại) has a significant and negative impact on stock return.
3) Finally, the thesis outlines several limitations and some suggestions regarding the
timing of financial statements and the content of financial statements, thereby improving
stock returns for investors, for both listed firms and the authorities.
Science instructor Research student
Assoc. Prof. Dr. Ly Hoang Anh Nguyen Thi Ngoc Diep
Các file đính kèm theo tài liệu này:
- 01_cap_phan_bien_kin_24112017_ban_nop_7144_2092601.pdf