Các yếu tố tác động tới quy mô thị trường trái phiếu doanh nghiệp việt nam tt tiếng anh

INTRODUCTION
1. Rationale
Corporations have many advantages in rasing fund by issuing bonds.
The size of Vietnam corporate bond market is still small.
Corporations mainly issue convertible bonds for existing
shareholders or issue bonds in private form for certain partners. So,
bondholders often hold bonds until due. As a result, there are almost
no transactions in secondary corporate bond market. Therefore, study
to increase the size of corporate bonds in Vietnam is necessary.
There are many studies about corporate bond market in developed
countries, such as United State, Korea, …. These corporate bond
markets are developed and have large size. Besides, many
researchers study about ermerging corporate bond markets in Asian
or South East Asian. Their studies mainly focus on factors that affect
to the market size. However, there are very few similar studies in
Vietnam.
The studies in Vietnam are often about Government bonds. In studies
about corporate bonds, researchers always used descriptive statistics
method. Meanwhile, the use of mathematical methods to identify or
quantify the factors affecting the size of the market, as an important
basis for developing market development solutions, should be
implemented.
In summary, the implementation of an in-depth study, which focuses
on identifying the factors that influence the size of the corporate bond
market in Vietnam, is a gap. Therefore, the topic "Factors affecting
the size of Vietnam's corporate bond market" was selected for
research.
2. Objectives
(i) Assess the status of the impact of factors on the size of Vietnam's
corporate bond market.
(ii) Propose some recommendations to increase the size of Vietnam's

corporate bond market.
Research questions:
(i) Are there any factors affecting the size of the corporate bond
market in general and the corporate bond market in Vietnam in
particular?
(ii) How is the impact of these factors on the size of the corporate
bond market in Vietnam?

(iii) Measures to increase the scale of Vietnam's corporate bond
market based on these factors?
3. Research subjects
The size of the Vietnamese corporate bond market and the factors
affecting the size of the market. The thesis focuses on issued bonds
and listed bonds traded on the secondary market.
4. Research scope
4.1. Vietnam primary corporate bond market
Macro – factors affect the size of Vietnam primary corporate bond
market in 2005 – 2018
4.2. Vietnam secondary corporate bond market
Factors affect the size of Vietnam secondary corporate bond market
in 2012 – 2017
5. Methodology
(1) Descriptive statistics: sort and describe the data about issuance
volume, trading volume and impact factors of corporate bonds.
(2) Regression models: The thesis uses secondary data and some
econometric models and econometric software (Eviews and Stata) to
estimate the correlation between factors affecting the size of
Vietnam's corporate bond market and the impact of these factors.
6. New contributions of the thesis
6.1. In terms of theory

Firstly, the thesis has developed a model for testing factors affecting
the issuance volume of corporate bonds and conducting testing for
the market of primary corporate bonds in Vietnam. Tested factors
include: (1) the size of the economy, (2) the openness of the
economy, (3) the development stage of the economy, (4) the size of
the banking system, (5) interest rate variability, (6) exchange rate
variability, (7) foreign exchange reserves and (8) creditors' rights.
The thesis also uses the value of bonds issued more in each quarter as
a scale for issuance scale instead of the current bond value. The data
used is time series data corresponding to the size of quarterly bond
issuance in the period 2005 - 2018.
Secondly, the thesis is the first research in Vietnam to test the factors
affecting the trading volume of listed corporate bonds. Tested factors
include: (1) issuance volume, (2) age, (3) default risk, (4) profit
volatility and (5) stocks’ trading volume. The data used is panel data,
corresponding to 28 listed bonds traded during 2012-2017.

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6.2. In terms of practice
The result shows that the size of the economy, the openness of the
economy, the size of the banking system, exchange rate variability,
foreign exchange reserves and creditors' rights are factors that affect
tothe issuance volume of corporate bonds in Vietnam.
In secondary market, age, credit risk, profit volatility, stocks’ trading
volume are factors that affect to trading volume of listed corporate
bonds.

CHAPTER 1: THE BASIC OF THEORY AND
LITERATURE REVIEW
1.1. The basic of theory about facors affecting the size of corporate
bond market
1.1.1. Structure of corporate bond market
1.1.2. The size of corporate bond market
1.1.2.1. Conceptions about the size of corporate bond market
According to Oxford dictionary: “Size is how large or small
something or someone”. Therefore, it can be understood that the size
of the corporate bond market is how large or small of market.
Because the corporate bond market includes both primary and
secondary markets, the size of the primary market is considered
through the issuance volume and the size in the secondary market is
shown by liquidity (Mizen and Tsoukas, 2014).
1.1.2.2. Measurement of the size of corporate bond market
Primary bond market
Issuance volume = Total value of outstanding bonds/GDP (1)
Issuance volume = Total value of bonds issued (2)
Secondary bond market
(i) Number of transactions (3)
(ii) Number of bonds traded (4)
(iii) Turnover (5)
1.1.3. Factors affecting to the size of corporate bond market
1.1.3.1. Factors affecting to the size of primary corporate bond
market
The size of economy. The small economy often lack
useful tools for growing bond market.
The openness of the economy. Economies with large
openness usually have more development corporate bond markets.
The development stage of the economy. The higher the

national stage of development, the greater the corporate bond market
Interest rate variability. The larger interest rate variablility
will increase the risk of long-term assets in the financial market,
especially corporate bonds and the size of the corporate bond market
will decrease.
The size of banking system. In some cases, the larger the
banking system, the less developed the corporate bond market.
However, in an open economy, commercial banks now become the
necessary subjects to promote the development of the corporate bond
market.
Exchange rate variability.
Foreign exchange reserves. Increasing of the level of
foreign exchange reserves will lead to the development of corporate
bond market.
Creditors’ rights. Countries that have strong creditors’
rights will promote the increasing of the size of corporate bond
market.
1.1.3.2. Factors affecting to the size of secondary corporate bond
market
Issuance Volume. Higher issuance volume, higher trading
transactions.
Bond’s age. Bonds issued in the latest time period will be
traded most often.
Credit risk. Investors do not want to invest to bonds that
have high credit risk.
Profit volatility.
Stock’s trading volume.
1.2. Literature review
1.2.1. Foreign studies

Research by Hawkins (2002) has made a multi-dimensional
assessment of the relationship between the banking system and the
size
of
corporate
bond
market.
Eichengreen
and
Luengnaruemitchai (2004) tested 15 factors affecting the size of the
bond market. The results show that the size of the economy, the size
of the banking system, the exchange rate, compliance with
international accounting standards, corruption and state management
are factors that influence the bond market of Asian countries.
Research by Bhattacharyay (2013) focused on understanding the

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correlation between the size of the bond market and the macro
factors. The testing results for corporate bonds show that the issuance
volume of the corporate bond market is affected by factors: the size
of the economy, the openness of the economy, the size of the banking
system, the stage of development of the economy and interest rate
variability. Kowalewski and Pisany (2017) suggested that creditors'
rights and market size are positively related. Mizen and Tsoukas
(2014) studied the factors affecting the issuance decision of
businesses. In this study, the authors believe that there are both

macro and micro factors that influence corporate decision making.
The results show that the size and growth of revenue of the business
has a positive relationship with the size of the issuance. The
regression results of Braun and Briones (2006)’s study showed that
the most important factor determining the size of the market. Bond is
the level of economic development, or GDP per capita. The size of
the banking system and the creditors' rights also have a positive
relationship with the size of the bond market. Focusing on emerging
economies, a study by Tendulkar (2015) concluded that international
corporate bond size is affected by GDP per capita, number of listed
enterprises, and domestic credit and interest rate variability. The total
size of the corporate bond market is affected by the size of the
government bond market, the number of listed companies, interest
rate spreads, domestic credit, CPI and hedging premiums. Mu et al.
(2013) suggested that domestic credit has a positive effect, interest
rate variability have a negative relationship to the size of the African
corporate bond market. Fredrick's (2014) showed different results.
Accordingly, only the exchange rate, interest rate fluctuations, the
size of the economy and average income affect to the size of the
corporate bond market. Another similar study was conducted in the
Indian corporate bond market by Maurya and Mishra (2016) which
also gave conclusions that are not very similar to those of previous
emerging market studies. According to Maurya and Mishra (2016),
the Indian corporate bond market was most significantly affected by
foreign exchange reserves.
Study of Alexander et al. (2000) focused on testing factors that affect
trading volume of high – yield corporate bonds. The results showed
that issuance volume and bonds’age are two factors that have strong
impact on trading volume of these bonds. Alexander et al. (2000)

supposed that bonds within 2 years of issuance are traded the most.
Besides, this study also showed that credit risk and profit volatility all
have positive impact to trading volume. In contrast, Wahyudi and
Robbi (2009) mentioned that issuance volume has a negative impact
to trading volume. Hotchkiss and Jostova (2007) expanded the scope
of research, confirmed that issuance volume and age have strong
impact to trading volume of corporate bonds.
1.2.2. Studies in Vietnam
Tran Thi Thanh Tu (2007) used descriptive statistic method to
compare and analyze data on Vietnam corporate bond market in the
period of 2003 - 2007. According to the author, most of corporate
bonds were issued at that time were long-term bonds, and they
belong to State enterprises or big enterprises. The secondary bond
market has almost no bonds traded. Trinh Mai Van (2010) and Phan
Thi Thu Hien (2014) suggested that the lack of legal framework on
corporate bonds and information transparency was reason of the
underdevelopment of the corporate bond market in Vietnam.
The research of Vuong and Tran (2010) analyzed Vietnam corporate
bond market in the period of 1992 – 2009 with a large dataset from
different aspects. They confirmed that the issuance of corporate
bonds focused on large enterprises, mainly state-owned enterprises
and the competition of state-owned enterprises limited the ability to
raise debt of SMEs. Stuydy of HNX (2016) also described the current
situation of the market in recent years.
Nguyen Thi Nhung and Tran Thi Thanh Tu (2019) gathered 11
groups of criteria to assess the liquidity of corporate bond market. In
particular, size of issuance, outstanding debts of corporate bonds
market, growth speed of corporate bonds in circulation are used to
measure the liquidity of primary bond market and volume of
corporate bonds traded and coefficient rotation are used to measure

the liquidity of secondary bond market in Viet Nam. This research
compared these criteria’s data of Vietnam and some other countries
to assess the liquidity of Vietnam bond market.
Research of Nguyen Hoa Nhan et al. (2014) is the first research in
Vietnam that uses regression analysis method to analyzie the
relationship between the issuance volume of corporate bonds and
some macro – factors. This study showed that the openness of
economy, the size of banking system and issuance volume in last

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period have positive impact to the issuance volume in this period. In
contrast, exchange rate and the stage of development of the economy
have negative impact to the issuance volume of corporate bonds in
Vietnam.
1.2.3. Research gaps
Tại Việt Nam, các nghiên cứu về TPDN chủ yếu ở dạng thống kê,
mô tả số liệu và có rất ít nghiên cứu về các yếu tố tác động tới quy
mô thị trường TPDN. Đối với quy mô của thị trường TPDN sơ cấp,
nghiên cứu của Nguyễn Hòa Nhân và cộng sự (2014) là nghiên cứu
đầu tiên sử dụng mô hình phân tích hồi quy. Tuy nhiên, các yếu tố
được phân tích trong nghiên cứu còn ít và tỷ lệ phần trăm giải thích
sự biến động của biến phụ thuộc thông qua biến độc lập còn thấp. Có
thể xem xét thêm nhiều yếu tố khác để xác định thêm các yếu tố tác
động tới quy mô phát hành TPDN Việt Nam. Ngoài ra, nghiên cứu về
quy mô thị trường TPDN Việt Nam chủ yếu tập trung vào quy mô
phát hành. Quy mô giao dịch của TPDN trên thị trường thứ cấp là

vấn đề ít được nghiên cứu. Đặc biệt là chưa có nghiên cứu nào sử
dụng mô hình hồi quy để xem xét các yếu tố tác động tới quy mô
giao dịch của TPDN Việt Nam.
CHAPTER 2: THE REAL SITUATION OF VIETNAM
CORPORATE BOND MARKET
2.1. Overview of Vietnam’s economic environment in the period
of 2005 – 2017
2.2. Overview of Vietnam corporate bond market
2.3. The structure of Vietnam corporate bond market
2.3.1. The primary cororate bond market
Issuance volume
The annual issuance volume greatly affects the size of the market. It
can be seen that the annual issuance volume of corporate bond in
Vietnam has tended to increase in the period of 2005 - 2018, from
over VND 137 billion in 2005 to over VND 40,000 billion in 2018.
Terms of bond
Terms of corporate bonds in Vietnam are very diverse, ranging from
1 to 20 years, depending on the target and issuance conditions. In
cases of supplementing NWC, or debt restructuring, firms will raise
short – term loans (<3 years). Loans for financing projects will be
more than 3 years, or more than 5 years. In general, in the period of
2005 - 2018, the average term of corporate bonds of less than 3 years.

2.3.2. The secondary corporate bond market
Trading
Corporate bonds are traded in 2 ways: (1) at stock exchange and (2)
OTC
Size of market
In the period of 2012 - 2015, the trading volume was only a few
trillion, an average of over 3.8 trillion per year, in 2016 reached over

10 trillion. In the period of of 2016 - 2017, each year there were
average of 7 trillion worth of corporate bonds trading on the
secondary market.
2.4. Policies to develop corporate bond market in some other
countries.
CHAPTER 3: METHODOLOGY
3.1. Research framework and models
3.2. Methodology
3.2.1. Descriptive satistics
3.2.2. Regression analysis
3.2.2.1. Regression analysis for time series data
The stationary of time series data
Augmented Dickey – Fuller (ADF) test is used to test the stationary
of variables. If
>
at significant levels of 1%, 5% and
10%, variables are stationary at the corresponding significant levels
(Levin et al., 2002).
Regression analysis
Data of factors affect the issuance volume is quarterly data and it is
called time series data. In which, t is used to refer time points in the
series. Model of time series data is as follow (Nguyen Quang Dong
and Nguyen Thi Minh, 2013):
(a)
Because (a) is a linear regression model, it will be estimated by the
least square method (Ordinary Least Square - OLS). When the
assumptions are satisfied, the estimation results are reliable.
Test for specification errors
Test for specification errors: multicollinearity, multivariate
normality, autocorrelation, homoscedasticity, functional form.

3.2.2.2. Regression analysis for panel dât
Regression methods

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Data of factors affect to trading volume is panel data. According to
Baltagi (2005), panel data model is as follow:
(b)
Model without

:

(c)
Depending on , there are 3 estimation methods: Pooled OLS –
POLS, Random Effects Model – REM and Fixed Effects Model –
FEM.
3.3. Dataset
3.3.1. Dataset of factors affect to issuance volume
(i) Data of issuance volume is secondary data that is collected
quarterly from website Asianbondsonline.adb.org in the period of
2005 – 2018.
(ii) The size of economy (Measurement as GDP), the openness of
economy (Measurement as Experts) are secondary data that are
collected from website finance.vietstock.vn. GDP is a non-linear data
so it will be taken as a logarithm.
(iii) Interest rate variability, the size of banking system
(Measurement as domestic credit), exchange rate variability and

foreign exchange reserves are secondary data that are collected
quarterly from website data.imf.org in the period of 2005 – 2018.
(iv) The stage of development of economy (Measurement as GDP per
capita) is secondary data that is collected yearly from website
data.worldbank.org in the period of 2005 – 2018 and is interpolated
in quarterly data. GDP per capita is a non-linear data so it will be
taken as a logarithm.
(v) Creditors’ right is analyzed and calculated basing on Djankov et
al. (2007) and Laws of bankruptcy 1993, 2004, 2014 of Vietnam.
3.3.2. Dataset of factors affect to trading volume
(i) Trading volume is primary data that is collected monthly from
HSX in the period of 2012 – 2017.
(ii) Bond’s age is based on time of issuance.
(iii) Credit rating of issuers is used to measure default risk of bonds
because corporate bonds have not rated in Vietnam. Credit rating of
issuers is secondary data that is collected from CIC.

9

(iv) Profit variability is measure as fluctuation of VWAP.
(v) Stock’s trading volume is secondary data that is collected from
finance.tvsi.com.vn/data
3.4. The process of testing
3.4.1. Factors affect to issuance volume
(i) Test the stationary of time series data (ADF test)
(ii) Estimate model by using OLS and test the model’s errors.
(iii)Test for specification errors: multicollinearity (VIF), multivariate
normality (Jarque – Bera test), autocorrelation (Breusch-Godfrey
test), homoscedasticity (Breusch – Pagan – Godfrey test and White
test), functional form (Ramsey test).

(iv) If model has errors, remedies will be performed.
3.4.2. Factors affect to trading volume
(i) Test the stationary of panel data
(ii) Analyze the correlation between variables.
(iii) Using Breusch – Pagan test to find out the most suitable
estimation method for panel data.
(iv) If prob > 0.1: using POLS.
(v) If prob < 0.1: using Hausman test to test the correlation between
and independent variables. If Prob < 0.1: using FEM; if prob >
0.1: using REM
CHAPTER 4: ANALYZE FACTORS THAT EFFECT TO THE
SIZE OF VIETNAM CORPORATE BOND MARKET
4.1. Factors affect to primary corporate bond market
4.1.1. Variables and measurement
Expected model:

(1)
In which: t = 1, 2, ..., 56 represent for 4 quarters/year of the period
from 2005 to 2018.
Table 4.1: Variables and Measurement of model (1)
Model Variables
Measurement
Symbol
Unit
(1)
Size
Issuance volume in IVOL
Billions
each quarter
VND

(1)
The size of Log(GDP)
GDP
%
economy

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Model Variables
(1)
The
openness of
economy
(1)
The stage of
development
of economy

Measurement
Exports

Symbol
EXPRT

Unit
%

Log(GDP per capita). PGDP
GDP per capita is

interpolated
in
quarterly data
(1)
Interest rate Leding interest rate – DRATE %
variablility
Deposit interest rate
(1)
The size of Domestic credit
CREDIT Millions
banking
VND
system
(1)
Exchange
Average exchange rate EXR
VND/USD
rate
in quarter
variability
(1)
Foreign
Foreign
exchange FER
Millions
exchange
reserves
USD
reserves
(1)

Creditors’
The index ranges from RIGHTS 0 – 4
right
0
(weak
creditor
scores
rights) to 4 (strong
creditor rights
2012 – 2014: 1 score;
2015 – 2017: 2 scores
4.1.2. Descriptive statistics
4.1.3. Test factors affect to the issuance volume
4.1.3.1. The stationary of time series data
Data of variables is tested the stationary on EVIEWS. The results
show that IVOL is stationary at 0 level (10%), log(PGDP) is
stationary at 0 level (1%), EXPRT is stationary at 2 level and other
variables are stationary at 1 level.
4.1.3.2. Regression analysis of model (1.1)
The results of regression analysis of model (1.1)

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Dependent Variable: IVOL
Method: Least Squares
Sample (adjusted): 2005Q2 2018Q4
Included observations: 55 after adjustments
Variable
Coefficient Std. Error
t-Statistic Prob.

C
1339.511
1675.374
0.79953
0.4281
LOG(GDP)
2.82E+02
1.35E+02
2.085928
0.0426(**)
D(EXPRT)
0.017436
0.008629
2.020693
0.0492(**)
LOG(PGDP)
-483.992
367.7746
-1.316
0.1947
CREDIT
0.037872
0.011563
3.275279
0.002(***)
DRATE
-5.31E+01
4.83E+01
-1.09984
0.2771

EXR
-0.051366
0.042415
-1.21106
0.2321
FER
1.47E-02
4.74E-03
3.109871
0.0032(***)
RIGHTS
65.55346
94.01795
0.697244
0.4892
R-squared
0.53508
Adjusted R-squared
0.454225
S.E. of regression
150.381
Sum squared resid
1040264
Log likelihood
-348.852
F-statistic
6.617725
Prob(F-statistic)
0.00001
(Source: Author’s calculations)

In which: (*): significant at 10%, (**): significant at 5%, (***):
significant at 1%.
Prob(F-statistic) of model (1.1) = 0.00001 < 0.05
Test the errors of model (1.1)
The results show that model (1.1) do not have errors except
multicollinearity because VIF index of some variables are more than
10. So that, variable with high VIF index is removed off model (1.1).
New model is as follow:

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(1.2)
4.1.3.3. Regression analysis of model (1.2)
The results of regression analysis of model (1.2)
Dependent Variable: IVOL
Method: Least Squares
Sample (adjusted): 2005Q2 2018Q4
Included observations: 55 after adjustments
Variable
Coefficient Std. Error
t-Statistic
Prob.
C
-470.421
9.64E+02
-4.88E-01
0.6279
LOG(GDP)
196.2759

119.4337
1.643388
0.107
D(EXPRT)
0.019231
0.008586
2.23984
0.0299(**)
CREDIT
0.039318
0.0116
3.389591 0.0014(***)
DRATE
-15.8087
39.40295
-0.40121
0.6901
EXR
-0.09919
0.022044
-4.49945
0.000(***)
FER
0.010778
0.003688
2.922729 0.0053(***)
RIGHTS
131.8318
80.00656
1.647762

0.1061
R-squared
0.517576
Adjusted R-squared
0.445726
S.E. of regression
151.5473
Sum squared resid
1079429
Log likelihood
-349.868
F-statistic
7.203536
Prob(F-statistic)
0.000007
(Source: Author’s calculations)
In which: (*): significant at 10%, (**): significant at 5%, (***):
significant at 1%.
Prob(F-statistic) of model (1.2) = 0.000007 < 0.05
Log(GDP), DRATE and RIGHTS have prob. > 0.1 and they are not
significant at 10%.
Test errors of model (1.2)
The results show that model (1.2) do not have errors. Because Prob.
of DRATE is more than 0.1, this variable is removed off. New model
is as follow:

(1.3)
4.1.3.4. Regression analysis of model (1.3)
The results of regression analysis of model (1.3)
Dependent Variable: IVOL

Method: Least Squares
Date: 12/17/19 Time: 14:00
Sample (adjusted): 2005Q2 2018Q4
Included observations: 55 after adjustments
Variable
Coefficient Std. Error
t-Statistic
Prob.
C
-609.552
891.742
-0.68355
0.4975
LOG(GDP)
206.748
115.5235
1.789661
0.0798(*)
D(EXPRT)
0.018589
0.008361
2.223195
0.0309(**)
CREDIT
0.041407
0.010275
4.0298 0.0002(***)
EXR
-0.10087
0.021453

-4.70171 0.0000(***)
FER
0.010688
0.003649
2.929367 0.0052(***)
RIGHTS
143.6858
73.69839
1.949646
0.0571(*)
R-squared
0.515924
Adjusted R-squared
0.455415
S.E. of regression
150.2169
Sum squared resid
1083126
Log likelihood
-349.962
F-statistic
8.526337
Prob(F-statistic)
0.000003
(Source: Author’s calculations)
In which: (*): significant at 10%, (**): significant at 5%, (***):
significant at 1%.
Prob(F-statistic) of model (1.3) = 0.000003 < 0.05
Test errors of model (1.3)
The results show that model (1.3) do not have errors. The last

model is as follow:
IVOLt = - 609.552 + 206748Log(GDP)t + 0.018589D(EXPRT)t +
0.041407CREDIT – 0.10087EXRt + 0.010688FERt +

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143.6858RIGHTSt (1.3)
4.1.3.5. Discuss the research’s results
(i) The stage of development of the economy (PGDP) and the interest
rate variability (DRATE) have no impact on the issuance volume of
corporate bonds. (ii) The size of the economy (GDP), the openness of
the economy (EXPRT) and the size of the banking system (CREDIT)
have a positive impact on the issuance volume of corporate bonds.
(iii) Exchange rate fluctuations (EXR) have a negative impact on the
issuance volume. (iv) Foreign exchange reserves (FER) have a
positive impact on the volume of corporate bond issuance. (v)
Creditors' rights (RIGHTS) have a positive impact on issuance
volume.
4.2. Factors affect to trading volume
4.2.1. Variables and measurement
Expected models:
(2.1)
(2.2)
(2.3)
In which: i = 1, 2, ..., 28 (represent for 28 bonds), t = 1, 2, …, 72
corresponds with 12 months/year in the period of 2012 – 2017.
Table 4.4: Variales and measurement of model (2)

Model Variables Measurement Symbol
Unit
Transaction
(2)
Trading
(1) Number of TIMES
volume
transactions in
month
(2) Number of NBOND Bond
bonds
are
traded
in
month

(2)

Issuance

(3) Turnover

TOVER

Billions VND

Issuance

SIZE

Thousands VND

15

volume

volume in par
value
Number
of AGE
months since
issuance

Qualitative variable
AGE_1: more than
2 years
AGE_2: in years
AGE_3:
Unreleased/Expired
(2)
Default
Firm’s credit RATING Qualitative variable
risk
rating
RATING_1:
In
rank A
RATING_2:
In
rank B

RATING_3:
not
rated
(2)
Profit
Volume
DVWAP %
variability Weighted
Average Price
(VWAP)
variability
(2)
Stock’s
Value of stock SVOL
Billions VND
trading
traded
in
volume
month
4.2.2. Descriptive statistics
4.2.3. Test factors affect to trading volume
4.2.3.1. Test the staytionary of panel data
Levin – Lin – Chu (LLC) test is used to test the stationary of panel data.
The rusults show that SVOL is stationary at 0 level (1%) and other
variables’ data are stationary at 1 level (1%).
4.2.3.2. Correlation analysis
The correlation between dependent variables
The correlation between TIMES, NBOND and TOVER is quite tight
because the correlation coefficient is approximately 0.7. So that,

TIMES, NBOND and TOVER are suitable to measure the trading
volume.
The correlation between independent variables
The absolut of correlation coefficients between independent are less
(2)

Age

16


than 0.7. This shows that model (2) does not have multicollinearity.
The correlation between independent variables and
dependent variables
The correlation between the independent variables and the dependent
variables is very low due to the correlation coefficient is less than
0.7.
4.2.3.2. Results
Table 4.11: Methods are used to estimate model (2)
Test
TIMES
NBOND
TOVER
Breusch – Pagan
Prob = 0.000 0.000
0.000
Hausman
Prob = 0.000 0.0797
0.0412
Method

FEM
FEM
FEM
(Soure: Athour’s calculations)
2
Table 4.12: Results of testing the R
Dependent variables
TIMES
NBOND
TOVER
Methos
FEM
FEM
FEM
R2 - overall
0.3250
0.1274
0.1292
P - value
Prob. = 0.0000
0.000
0.000
(Soure: Athour’s calculations)
Table 4.13: Results of testing 3 models

significant at 1%.
Because all three models use the fixed effects model (FEM), the
SIZE variable is removed from the models. Therefore, it is not
possible to assess the impact of SIZE on the trading volume
In 3 models, AGE_1, AGE_2, RATING_1 and RATING_2 are

significant at 1% and have positive impact to dependent variables.
The coefficient of these variables show that bonds are issued in 2
years and are rated in B category have bigger trading volume than
others.
In model (2.2) and model (2.3), SVOL variable has negative impact
to NBOND and TOVER but DVWAP has positive impact to them.
4.2.3.3. Discuss the research’s results
(i) Because SIZE did not change during the study period, it is
removed in FEM. (ii) Bonds with age is less than 2 years are traded
more than other bonds. (iii) Bonds with rank B have bigger trading
volume than bonds with rank A. (iv) The greater the volatility of the
bond's profit, the greater the trading volume. (v) The greater the
issuers’ stocks traded, the less bonds traded.

(Soure: Athour’s calculations)
In which: (*): significant at 10%, (**): significant at 5%, (***):

CHAPTER 5: RECOMMENDATIONS
5.1. Development orientation of Vietnam's corporate bond
market in the coming time
5.2. Recommendations
5.2.1. Economic growth, stabilizing exchange rates and increasing
the size of foreign exchange reserves
Growth is accompanied by curbing inflation, ensuring large balances,
maintaining macroeconomic stability. It is necessary to strictly
control and ensure that banks perform the policy on restricting
foreign currency loans to enterprises. At the same time, it should
license to some organizations that are allowed to trade in foreign
exchange, to meet the needs of foreign exchange trading of
businesses.

5.2.2. Promote the development of the banking system in terms of
market makers
Banks should be considered as market makers. They need to be
motivated to play this role.
5.2.3. Establish professional credit rating organizations and rate
corporate bonds

17

18

TIMES

NBOND

TOVER

Variable

SIZE

Coefficient

Prob

Coefficient

Prob

Coefficient

0

X

0

X

0

Prob
X

AGE_1

3.073938

0.000(***)

578346.1

0.000(***)

58.74211

0.000(***)

AGE_2

7.341274

0.000(***)

1133685.0

0.000(***)

117.7666

0.000(***)

AGE_3

0

0

0

RATING_1

2.740408

0.000(***)

917450.6

0.000(***)

92.58299

0.000(***)

RATING_2

3.860852

0.000(***)

1148857.0

0.000(***)

116.9805

0.000(***)

RATING_3

0

0

0

DVWAP

0.0116864

0.265

6805.795

0.031(**)

0.7757046

0.016(**)

SVOL

– 0.0001556

0.183

– 136.1458

0.000(***)

– 0.0132649

0.000(***)

CONS

– 4.063231

0.000

– 1071589.0

0.000

– 109.8196

0.000


Establish professional credit rating organizations. Banks which meet
Basel Accords can establish subsidiaries that provide credit rating
services. Government should issue regulations that require businesses
to make credit rating on bonds before issuance.
5.2.4. Market control and information disclosure
Information of bonds about credit rating, price, … should be publiced
for investors. Regulations about information disclosure (for both
public issuance and private issuance) should be issued.
5.2.5. Improve bondholder’s right
The missing regulations should be added: (1) creditors may refuse or
agree for the business's application for bankruptcy, (2) secured
creditors can regain the mortgaged properties after the business apply
for bankruptcy.
5.2.6. Revise and add reguations related to the corporate bond
market
In 2018, the Government issued Decree 163/2018 / ND - CP about
corporate bond issuance. However, there are still some issues in
Decree 163 that need to be adjusted. Regulators need to review laws
in a comprehensive way, eliminate duplicated content and agree on
conflicting content.
5.2.7. Upgrade technical infrastructure for corporate bond market

The technology infrastructure of the corporate bond market in
Vietnam still lacks a lot of tools to support market activities such as
issuance registration / issuing license system; standard bid system or
release survey support system; an online ISIN (international
securities trading code) system; information listing system on bonds;
bond pricing information system; National information system on
corporate bonds.
CONCLUSIONS
The corporate bond market plays an important role in the socioeconomic development of each country. Increasing the size of the
corporate bond market will help businesses finance most of their
activities, reduce dependence on the commercial banking system,
limit risks of the financial market, and promote economic
development. In order to develop appropriate solutions to increase
the corporate market size, it is necessary to learn about the factors
affecting the market size. The thesis has achieved the research
objectives.

1. The successes
Firstly, overview previous studies about the corporate bond market,
the size of the corporate bond market and the factors affecting the
size of the corporate bond market.
Secondly, test econometric models and identify factors affecting the
size of the corporate bond market in Vietnam.
Thirdly, based on the results of testing the econometric model on the
impact factors, propose some recommendations to increase the size
of the corporate bond market in Vietnam.
2. The limitations
Data
Factors affect to issuance volume
GDP per capita in Vietnam is only annualized and must use software

to interpolate to quarterly figures. Interpolation and actual statistics
may differ.
Factors affect to trading volume
Model about factors affect to trading volume is estimated by using
data of listed corporate bonds. However, trading volume of listed
bonds is very small compared with trading volume of whole
secondary corporate bond market. Besides, credit rating of bonds is
replaced by credit rating of issuers. In Vietnam, credit rating of
businesses is updated 2 times/year.
Models
In fact, there are many factors that affect the size of the primary
corporate market. However, the thesis only focuses on studying the
impact of macro factors without mentioning the micro - internal
factors of enterprises. Therefore, the variables in the model only
explain a small part of the fluctuation of the issuance volume of
corporate bonds in Vietnam.

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