The impact of macroeconomic factors on conditional stock market volatility in vietnam

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY --- oOo --- NGUYỄN THÚY VÂN THE IMPACT OF MACROECONOMIC FACTORS ON CONDITIONAL STOCK MARKET VOLATILITY IN VIE

MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY

- oOo -

NGUYỄN THÚY VÂN

THE IMPACT OF MACROECONOMIC FACTORS ON CONDITIONAL STOCK MARKET VOLATILITY

IN VIETNAM

MAJOR: BANKING AND FINANCE

MAJOR CODE: 60.31.12

MASTER THESIS

INSTRUCTOR: Doctor TRƯƠNG QUANG THÔNG

Ho Chi Minh City – 2011

ACKNOWLEDGEMENT

Firstly, I would like to express my sincerest gratitude to my supervisor, Dr Truong Quang Thong for his valuable guidance and helpful comments during the course of my study

I also would like to thank all of my lecturers at Faculty of Banking and Finance, University of Economics Hochiminh City for their English program, knowledge and teaching during my master course at school

I would like to specially express my thanks to my classmates, my friends for their support and encouragement

Special thanks should go to my family for their love and support during my life

ABSTRACT

The study looks at the relationship between macroeconomic factors and and stock market, and determined whether inflation, movements in exchange rate, interst rate have an effect on stock market return volatility in Vietnam The Generalised Autoregressive Conditional Heteroskedascity (GARCH) models are used in establishing the relationship between these variables and stock market

volatility The results confirms presence of GARCH (1,1) effect on stock return time

series of Vietnam stock market It is also found that there is strong and positive relationship between inflation and stock market return volatility It means that an increase in inflation leads to an increase in stock market return volatility in the long run However, there is no enough proof to conclude that change in interest rate and exchange rate can influence market return volatility

Keywords: volatility, leverage, interest rate, inflation, exchange rate,

returns, Hochiminh Stock Exchange

Table of contents



CHAPTER 1 Introduction 1

1.1 Introduction 1

1.2 Research problem 2

1.3 Research objectives 3

1.4 Research methodology and scope 3

1.5 Structure Of The Study 4

CHAPTER 2 Literature review 6

2.1 Introduction 6

2.2 ARCH and GARCH model 6

2.2.1 Autoregressive Conditional Heteroskedasticity (ARCH) 7

2.2.2 Generalized Autoregressive Conditional Heteroskedasticity (GARCH) 8 2.3 The impact of macroeconomic variables on stock market volatility 8

2.3.1 Inflation 10

2.3.2 Interest rate 11

2.3.3 Exchange rate 13

2.4 Application of Garch model in Vietnam 14

2.5 Conclusion 15

CHAPTER 3 Research Methodology 16

3.1 Introduction 16

3.2 Research data and construction of variables: 16

3.2.1 Research data 16

3.2.2 Construction of variables for the models: 23

3.3 DF unit root test: 25

3.4 Hypotheses and empirical models 26

3.4.1 Model 1: The standard GARCH (1,1) model 26

3.4.2 Applying GARCH (1,1) models to find out the impact of macroeconomic variables on stock return volatility 27

3.5 Conclusion 28

CHAPTER 4 Empirical Results of the Research 29

4.1 Introduction 29

4.2 Descriptive statistics 29

4.3 DF unit root test 30

4.4 Correlation Matrix of the variables 30

4.5 Emprical result of model 31

4.5.1 Model 1: Standard GARCH (1,1) 31

4.5.2 Model 2 32

4.5.3 Model 3 34

4.5.4 Model 4 35

4.5.5 Model 5 37

CHAPTER 5 Conclusions, Limitations and recommendations 39

5.1 Introduction 39

5.2 Conclusions and Implications 39

5.3 Limitations and recommendations: 40

REFERENCES 42

APPENDIX 45

1 Descriptive Statistics of variables 45

2 Monthly CPI from 2000 – 2010 (Source: GSO) 47

3 Unit root test 48

4 Data 50

Figures  Figure 3.1 The performance of VN-Index from 07/2000 – 12/2010 17

Figure 3.2 Inflation in Vietnam and selected countries 2000 - 2009 19

Figure 3.3 Vietnam‟s nominal exchange rate (VND/USD) and inflation rate 1992-2010 20

Tables  Table 3.1 Vietnam exchange rate arrangement 2000 - 2010 22

Table 4.1 Descriptive statistics of variables (07/2000 – 12/2010) 29

Table 4.2 ADF UNIT ROOT TEST 30

Table 4.3 Correlation Matrix of the variables 31

Table 4.4 Result of model 1 31

Table 4.5 Result of model 2 33

Table 4.6 Result of model 3 34

Table 4.7 Result of model 4 36

Table 4.8 Result of model 5 37

Glossary

CPI: consumer price index

SBV: State Bank of Vietnam

GARCH: Generalized AutoRegressive Conditional Heteroskedasticity ARCH: Autoregressive Conditional Hetroskedasticity

GDP: Gross Domestic Product

HOSE: Hochiminh Stock Exchange

CHAPTER 1 Introduction

1.1 Introduction

Stock return volatility refers to the variation in stock price changes during a period of time Normally investors and agents perceive this variation as a measure of risk The policy makers use estimate of volatility as a tool to measure the vulnerability

of the stock market Since understanding the nature of stock market volatility gives important implications for policy makers and investors, movements in stock prices volatility have been the central variable of many researches There have been numerous

of studies trying to answer an interesting question: what are the factors that derive stock market volatility

Researchers have analyzed the relative importance of economy-wide factors, industry-specific factors, and firm-specific factors stock volatility One of the earliest studies was of Officer (1973) which related changes in stock market volatility to changes in real economic variables He noted that variability in stock prices was unusually high during the period of great depression i e 1929-1939 compared with pre-and post-depression periods Schwert (1989) was a classic study which intended to verify Officer‟s (1973) findings and explored the relationship between stock prices volatility and macroeconomic variables This issue has been studied by numerous researches and their findings are not the same Many papers of Engle and Rangel (2005), Campbell (1987) and Shanken (1990)…confirmed that macroeconomic factors had significant effect on stock market volatility Contrary to this, Davis and Kutan (2003), Schwert (1989) evidenced that macroeconomic variables had weak predictive power for explaining variability of stock market prices and returns volatility Inconsistent

results depend on different characteristics of every countries as well as different time periods

Since ARCH model was proposed by Engle (1982) and generalized by Bollerslev (1986) and Taylor (1986), the models have been proved to be sufficient in capturing properties of time varying stock return volatility Literatures have found evidence in support the capability of GARCH models in volatility estimation as well as volatility forecast

Vietnam stock market was newly established in 2000 in Ho Chi Minh City on

28 July 2000 (Hochiminh Stock Exchange – HOSE) In the first trading session there were only two stocks with a total market capitalization of 270 billion VND Although the market has significantly grown over ten years of operation (until at the end of 2010), it is still rather small and incomplete in comparison to other stock markets in the Asian region Moreover, interest rate, inflation, exchange rate and stock market are hot subjects attracting attention of the government, investors and corporations in recent years Relationship among these macroeconomic variables as well as their effect on stock market has been discussed every day In fact, in Vietnam, do inflation, interest rate and exchange rate impact on stock market? Can we measure this impact?

1.2 Research problem

Research and practice have proved the important role of macroeconomic variables on the economy Stock market volatility is known as one of the most important phenomena that determine the amount of risk faced by investors The impact

of macroeconomic factors on stock market including market volatility is a major question to be posed and tested in many countries around the world However, as far as the author is concerned, in Vietnam there were not many researches exploring this issue In addition, unlike the stock market in the developed countries, Vietnam's stock market is not really operating under the law of supply and demand but it is influenced

by herb behavior and "crowd effect" Therefore, no one can confidently confirm that changes in macroeconomic factors impact to the entire stock market Moreover, inflation, exchange rate, interest rate and stock market are hot topics in recent years

As the importance of volatility as a proxy of risk, the advantages of GARCH family and Vietnam stock market‟s particular situation mentioned above, the paper chooses to study the impact of inflation, exchange rate and interest rate to stock market volatility by applying GARCH models My study will try to answer the following questions: What macroeconomic determinants of stock market volatility in Vietnam are? And how they specifically affect the stock market?

1.3 Research objectives

The main purpose of this study is to identify factors that impact stock market conditional volatility using the data from Hochiminh Stock Exchange

The present study contributes to the literature in three ways

Firstly, the present study will shed some light on the depth of the stock market activities especially in emerging market in addition to identifying and relating the changes in economic factors to the changes in stock market movements It is necessary

to have more and more researches about Vietnam stock market so that we can understand and develop our immature stock market

Secondly, the findings of this investigation should enable the investors to know about stock market volatility as a measure of risk and make their decision

Finally, the study will help the policy makers in seeing the effect of their policy

to stock market and choosing in which way they should adjust their policy

1.4 Research methodology and scope

To achieve the above mentioned objectives, the author employs quantitative research by using data of Hochiminh Stock Exchange Index (VNIndex), inflation,

exchange rate and interest rate from period August 2000 to December 2010 The analysis includes the following steps:

 Descriptive statistics

 Using DF unit root test to test stationary of time series data

 Using standard Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) models as proposed by Bollerslev (1986) and Nelson (1991) to capture the time varying volatility of stock market returns in Vietnam

 Applying GARCH model with additional dependent variables as inflation, exchange rate and interest rate to find out whether these variables effect stock market returns in Vietnam or not

Eviews software version 6 is used as data analysis tool

1.5 Structure Of The Study

This study including five chapters is organized as follows:

CHAPTER 1: Introduction This chapter introduces research background of the study, research problems, research objectives, research methodology and scope

CHAPTER 2: Literature Review

In this chapter, I review the relevant literatures and present the fundamental ideas on effect of macroeconomic variables on stock volatility as well as Garch model

CHAPTER 3: Research Methodology After determining the research objectives and scope, research methodology concerned in chapter 1 and referring important previous literatures in chapter 2, this

chapter particularly outlines the research methodology, data and builds empirical models

CHAPTER 4: Empirical Results of the Research Chapter 4 presents the empirical results, discusses the implications of the findings

CHAPTER 5: Conclusions, Limitations and Recommendations

In this chapter, I present conclusions and recommendations based on the results

of the previous chapters The limitations of the research and recommendations for future researches are also given

CHAPTER 2 Literature review

2.1 Introduction

This chapter will review previous researches that related to GARCH model, the impact of macroeconomic variables on stock market volatility Among macroeconomic factors, I will focus on three factors supposed by many studies, namely inflation, interest rate and exchange rate In addition, literatures that evidenced GARCH effect in Vietnam stock market are also provided

2.2 ARCH and GARCH model

Stock return volatility refers to the variation in stock price changes during a period of time Investors and agents perceive this variation as a measure of risk According to Pindyk (1984), an unexpected increase in volatility today leads to the upward revision of future expected volatility and risk premium which further leads to discounting of future expected cash flows (assuming cash flows remain the same) at an increased rate which results in lower stock prices or negative returns today Stock return volatility, therefore, refers to variations in stock price changes during a period of time

To forecast the conditional variances, Autoregressive Conditional Hetroskedasticity (ARCH) model was introduced by Engle (1982) and generalized as GARCH (Generalized ARCH) by Bollerslev (1986) and Taylor (1986) From this model, Nonlinear Asymmetric GARCH(1,1) (NGARCH) by Engle and Ng (1993), Integrated Generalized Autoregressive Conditional Heteroskedasticity (IGARCH) by Nelson (1991), Quadratic GARCH (QGARCH) model by Sentana (1995), The Threshold GARCH (TGARCH) model by Zakoian (1994)… were developed

2.2.1 Autoregressive Conditional Heteroskedasticity (ARCH)

In the analyses of macroeconomic data, Engle (1982) found evidence that for some kinds of data, the disturbance variances in time-series models were less stable than usually assumed For instance, the uncertainty of stock market returns, which are measured using variance and covariance, changes over time Thus, we should pay more attention to the heteroskedasticity when performing the time series analysis For this problem, it is necessary to specify the variance dynamics (volatility) Engle (1982) suggested the ARCH (autoregressive conditional heteroskedasticity) model as an alternative to the standard time series treatments It is well known that a period of high volatility continues for a while after a period of increased volatility, a phenomenon called volatility clustering The ARCH model takes the high persistence of volatility into consideration and so has become one of the most common tools for characterizing changing variance and volatility The ARCH (q) model formulates volatility as follows:

∑

Where:

Error term at time t

Conditional variance for the current time t

News about volatility from the previous period, measured as the lags of the squared residual

The time varying volatility is captured by allowing volatility to depend on the lagged values of the innovation terms and and q is chosen such that the residuals of

the variance equation are white noise All of the coefficients in the conditional variance equation are required to be non-negative

2.2.2 Generalized Autoregressive Conditional Heteroskedasticity

(GARCH)

The ARCH model is simple; the problem of parsimony among the other problems of

ARCH model such as how to specify the value of p and the violation of non-negativity

constraints led Bollerslev (1986) to extend the ARCH model into the generalized

ARCH (GARCH) model The virtue of this approach is that a GARCH model with a small number of terms appears to perform as well as or better than an ARCH model with many terms The equation for GARCH (p,q) is as follows:

: Error term at time t

: Conditional variance for the current time t

: News about volatility from the previous period, measured as the lags of the squared residual from equation

2.3 The impact of macroeconomic variables on stock market volatility

The effects of economic forces in a theoretical framework were based on the Arbitrage Pricing Theory (APT) developed by Ross (1976) The APT essentially seeks

to measure the risk premia attached to various factors that influence the returns on assets, whether they are significant, and whether they are “priced” into stock market

returns Accordingly, Chen, Roll and Ross (1986), having first illustrated that economic forces affect discount rates, the ability of firms to generate cash flows, and future dividend payouts, provided the basis for the belief that a long-term equilibrium existed between stock prices and macroeconomic variables Therefore, the dividend discount model (DDM), capital asset pricing model (CAPM) and arbitrage pricing theory (APT) provide important theoretical frameworks which show the conduits through which macroeconomic variables are factored into stock prices These models predict that any anticipated or unanticipated arrival of new information about GDP, production, inflation, interest rates, and exchange rates, etc., will alter stock prices through the impact on expected dividends or cash flows, the discount rate or both

As above mentioned, to forecast the conditional variances, Autoregressive Conditional Hetroskedasticity (ARCH), GARCH (Generalized ARCH), Nonlinear Asymmetric GARCH(1,1) (NGARCH) Integrated Generalized Autoregressive Conditional Heteroskedasticity (IGARCH) Quadratic GARCH (QGARCH), The Threshold GARCH (TGARCH) model … were developed Numerous studies have been conducted using these models to find out the relationship between macroeconomic variables and stock market volatility However, there are contradicting results regarding the impact of the health of economy on the stock exchange volatility and hence the amount of risk that inflation and other indicators might cause for the investors

Schwert (1989) tested the relationship between stock market volatility and a number of macroeconomic variables, including real and nominal economic volatility, financial leverage, and stock trading, covering the period from 1857 to 1987 for the U.S economy However, he found that macroeconomic variables have week predictive power for explaining variability of stock market prices and returns volatility Davis and Kutan (2003) confirmed the findings of Schwert (1989) that inflation and other

indicators are week predictors of the conditional stock exchange volatility in the emerging markets

Contrary to this, Engle and Rangel (2005) analyzed changes in unconditional volatility across 50 financial markets for 50 year‟s daily data and found that inflation, GDP growth, and short term interest rate have great positive impact on the unconditional stock exchange volatility Rizwan and Khan (2007) also examined role

of macroeconomic variables and global factors on the volatility of the stock returns in Pakistan They analyzed Pakistan‟s equity market as a consequence of interest rate, exchange rate, industrial production, and money supply being domestic macroeconomic variables and 6-month LIBOR and Morgan Stanley Capital International (MSCI) All Countries World Index as global variables After applying EGARCH and VAR models they collectively explained varying importance of domestic macroeconomic variables in explaining the relationship between stock returns and volatility in Karachi Stock Exchange and did not discussed contribution of each variable separately

Among a lot of macroeconomic variables, because of time limit, the author will focus on three variables, they are: inflation, exchange rate and interest rate

2.3.1 Inflation

Relationship of inflation and stock return has been widely examined by researchers The findings of Schwert (1989) and Davis and Kutan (2003) confirmed that inflation was weak predictor of the conditional stock exchange volatility in the emerging markets However, Engle and Rangel (2005) found that inflation has high predictive power for the emerging markets than it had for the developed nations like Canada Saryal (2007) employed GARCH model for the estimation of conditional stock market volatility using monthly data for Turkey from January 1986 to September

2005 and for Canada from January 1961 to December 2005 She estimated impact of

inflation on stock market volatility and found that inflation rate had the high predictive power for explaining stock market volatility in Turkey However, in Canada it was weaker though still significant

In Vietnam, Nguyen Thi Thu Hien and Dinh Thi Hong Loan (2007) investigated the effect of inflation on stock market by using OLS regression with data of VN-Index and each industry sectors The results of research showed that inflation was a systemic risk factor which impacted on the overall stock market Inflation significantly negative effected on stock return This also implied that investment in stock market was not an inflation shield

2.3.2 Interest rate

To investors, an increase in interest rate will induce investors to keep their money saving bank accounts rather than investing in the stock market Moreover, substantial amount of stocks are purchased with borrowed money, hence an increase in interest rates would make stock transactions more costly Investors will require a higher rate of return before investing This will reduce demand of stock and the stock markets go down To companies, most companies finance their capital equipments and inventories through borrowings Therefore, high interest rate will make cost of capital and bankruptcy probability increase, especially for companies that have high leverage This leads to a decrease in profit of firms and an increase in risk Mishkin (1977) proved that lower interest rates increase stock prices which in turn reduce the probability of financial distress

Available literature in finance discusses the relationship between interest rates and stock returns in different ways Relating short term interest rates with stock returns and market volatility, Bren‟ et al (1989) provided evidence that one-month interest rate is helpful in predicting the sign and the variance of the excess return on stocks Campbell (1987) and Shanken (1990) found that nominal one-month T-bill yield has a

significantly positive relation with market variance but negatively correlated with future stock returns Whitelaw (1994) also reported a positive relationship between market volatility and the one-month T-bill yield

Research results of Engle (2004) suggested that along with the long term volatility of other macroeconomic variables, volatility of interest rates is also a primary cause of unconditional market volatility Rigobon and Sack (2004) empirical results showed that increase in the short-term interest rate negatively impact the stock prices, with the largest effect on the NASDAQ index Léon, N K ( 2008) investigated this relationship using the Korean Stock Price Index 200 (KOSPI 200) and weekly negotiable deposit The results indicated that interest rates have a strong predictive power for stock return but weak impact on volatility These results were supported by Zafar (2008) who did a similar research based on Karachi Stock Exchange monthly returns and concluded that there exist significant and negative relationship between interest rate and market return and negative but insignificant relationship between interest rate and variance

Vardar‟et al (2008) examined the impact of interest rate and exchange rate changes on the sector and composite return and volatility in Istanbul Stock Exchange Although he found market volatility more responsive to changes in exchange rates, conditional volatility significantly relates to the interest rates in all indices except for service and industrial sector As per his conclusion, changes in interest rates have an increasing impact on volatility of technology sector and a decreasing impact on financial and composite indices volatility

In Vietnam, Hussainey and Le (2009) used monthly time series data in the period January 2001 to April 2008 to examine the impact of macroeconomic indicators on Vietnamese stock prices They found that industrial production has a positive effect on

Vietnamese stock prices However, they confirmed that long term and short term interest rates did not affect stock prices

2.3.3 Exchange rate

Basically, foreign exchange rate volatility influences the value of the firm since the future cash flows of the firm in line with the fluctuations in the foreign exchange rates Currency appreciation has both a negative and a positive effect on the domestic stock market for an export-dominant and an import-dominated country, respectively (Ma and Kao, 1990) In another way, companies that borrow in foreign currency will face with exchange rate risk Investors will consider this characteristic to evaluate stock price

It was MaysamiKoh (2000) and Choi et al (1992), who examined the impacts of the interest rate and exchange rate on the stock returns and showed that the exchange rate and interest rate are the determinants in the stock prices Aggarwal (1981) used monthly data for the floating rate period from 1974 to 1978 to infer significant positive correlation between the US dollar and US stock prices whereas in 1988, Soenen and Hennigan derived a significant negative relationship In 1992, Oskooe and Sohrabian used Cointegration test for the first time and concluded bidirectional causality but no long term relationship between the two variables Najang and Seifert (1992) employed GARCH framework for daily data from the U.S, Canada, the UK, Germany and Japan, showed that absolute differences in stock returns have positive effects on exchange rate volatility However, Ibrahim and Aziz analyzed dynamic linkages between the variables for Malaysia, using monthly data over the period 1977-1998 and their results showed that exchange rate is negatively associated with the stock prices

Erbaykal and Okuyan studied 13 developing economies, using different time periods and indicated causality relations for eight economies-unidirectional from stock price to exchange rates in the five of them and bidirectional for the remaining three

Adjasi, C (2008) carried out a research on the Ghana Stock Exchange The results indicated a negative relationship between exchange rate volatility and conditional stock returns In another study carried by Subair, K., & Salihu in the Nigerian Stock Market, they found a negative relation between exchange rate fluctuations and the Nigerian stock market returns

2.4 Application of Garch model in Vietnam

Vuong Quan Hoang (2002) tested the GARCH (1,1) effect in the daily stock returns series with Vietnam‟s market price index (VNI) and the first four listed individual stocks: REE, SAM, HAP and TMS from July 28, 2000 to August 22, 2002

He found GARCH (1,1) effect present on four out of five series tested, except for HAP and concluded that there was presence of GARCH (1,1) effect stock return time series

of Vietnam‟s newborn stock market

A Farber, Nguyen V.H and Vuong Q.H (2006) analyzed policy impact including daily price limit, technical and rule changes on Vietnam stock market By applying Garch (1,1) model, they found that the market had in general been sensitive to some type of decisions made by the authorities The ultimate impacts of the decisions made by these agencies were always unpredictable For instance, „good news‟ in the view of the general market only shows positive impact on daily returns of the index while significantly negative to returns of SAM stock In another instance, general market bad news, recently caused by new-listed stocks, renders the conditional variance portion of veterans significantly lower, by the minus signs found in the variance equations of the fittings

Manh Tuyen Tran (2009) explored the relevance of GARCH models in explaining stock return dynamics and volatility on the Vietnamese stock market in the period from 1/2009 to 10/2009 He showed that standard GARCH (1,0) model provided the best description of return dynamics There existed only Bull effect, one

characteristic of the emerging market However, they could not find Friday, and low

transaction effects on Vietnamese stock market

2.5 Conclusion

Finding out the impact of macroeconomic variables on stock market volatility

by applying GARCH model is the target of numerous studies in many countries

However the results are not consistent The previous researches evidenced that there

was presence of GARCH (1,1) effect on stock return time series of Vietnam The

impact of some policies such as daily price limit, technical and rule change were also

examined but to the author‟s knowledge, there was rarely previous researches

investigating the effect of exchange rate, inflation and interest rate on conditional stock

market volatility in Vietnam Filling this gap is the main objective of this work

CHAPTER 3 Research Methodology

3.1 Introduction

After determining the research objectives and research methodology concerned

in chapter 1 and reviewing related previous literatures in chapter 2, chapter 3 particularly presents details of research data and overview of stock market, inflation, interest rate and exchange rate in Vietnam in recent years and construction of variables After that, I will present hypotheses and empirical models

3.2 Research data and construction of variables:

3.2.1 Research data

The time period of this study is from August 2000 to December 2010, data is taken at the end of each month in research period The data frequency selected was monthly to ensure an adequate number of observations An observation lower than this (yearly) is not providing enough observations of which a reliable conclusion can

be drawn from We cannot select daily data because there is no CPI data every day The stock market indices of the Hochiminh stock market were downloaded from their official website http://www.hsx.vn The data on consumer price index (CPI) have been obtained from Vietnam General Statistic Office Official exchange rate, three month deposit interest rate was taken from International Financial Statistics (IFS) published by International Monetary Fund (IMF)

Let‟s first consider characteristics of Vietnam stock market and macroeconomic variables in this period:

3.2.1.1 The Vn-Index And The Performance Of Vietnam Stock Exchange:

Figure 3.1 The performance of VN-Index from 07/2000 – 12/2010

(Source: http://www.hsx.vn )

- Period 2000 - 2005:

The Vietnam's stock market was marked by the introduction of Trading Center

Ho Chi Minh City Securities on July 20th 2000 and implemented the first trading session on July 28th 2000 At that time, only two companies listed (stock codes: REE and SAM) with a capital of 270 billion VND In the first five years, the market did not seem to really attract the attention of investors Except for 2001, when VNIndex went

up 571.04 points in the first six months and down to 200 points (70% value was lost) in October 2001, market indices did not change much in this period However, in 2005, growth rate of stock market increased twice According to the State Securities Commission, by the end of 2005, market capitalization reached nearly 40,000 billion VND, accounting for 0.69% of total Gross Domestic Product (GDP)

The performance of VN-Index from 07/2000 - 12/2010

- 2008 -2010:

In 2008, market sharply went down due to effect of financial crisis and inflation control policy Starting the year at 921.07 points, VN-Index has lost nearly 60% in value and become one of the deepest markets fell around the world in the first half of

2008 At the end of December, 2008, stock market index declined by 70 percent in

comparison with the early of the year (921.7 points versus 308 points) In 2009 and

2010, stock market recovered at low level

3.2.1.2 Inflation

We use monthly consumer price index (CPI) as presented for inflation In general, it was obvious that inflation rate was high and volatile in Vietnam which we can see in figures below:

Figure 3.2 Inflation in Vietnam and selected countries 2000 - 2009

(Source: Nguyen Thi Thu Hang et al, 2010)

Figure 3.3 Vietnam’s nominal exchange rate (VND/USD) and inflation rate 1992-2010

(Source: Nguyen Thi Thu Hang et al, 2010)

The 1997-1998 Asian Crisis caused sharp decline in world prices and goods demand Therefore, our economy experienced a period of both declining growth rate and deflation in the years 2000-2001 During 2001-2003, inflation stayed at modest levels After this modest period, inflation started to pick up again with annual inflation rates of 9.5% in 2004 much higher than the 6% target set by the government Worried about high inflation, State Bank of Vietnam started to tighten monetary policy that made inflation down slightly in 2006

However in 2007, inflation increased and peaked at 12.6% and soared to 20% in

2008 Strong return of inflation during 2007-2008 was explained by many reasons These include the large increase in minimum wage, the rising international commodity prices, the loose and not flexible monetary policy, the rigid and irresponsive exchange

rate management, the opening up of Vietnam to the world economy since it joined the WTO in late 2006 which caused great influx of FII which in turn caused stock and asset prices to soar The rapid increase in money and credit during this period contributed to the inflationary pressure Vietnam‟s money and credit expansion has been strong for the past decade, reaching their peak in 2007 with money grew by 47% and credit grew by 54% per annum

In 2008-2009, the global economic crisis contributed to the downward trend in Vietnam‟s inflation until late 2009 In 2010, inflation was high during the first two months due to Tet holiday and the electricity price hike Inflation control policy made the inflation rate quite low and stable during the 5 months from April to August 2010 However, inflation started to rise again since September 2010

3.2.1.3 Exchange rate

The current exchange rate regime has been described by the authorities as a managed float In the case of Vietnam, State Bank of Vietnam no longer sets the official exchange, but simply „notifies‟ the average interbank rate determined on the preceding business day through the interaction between supply and demand in the market The regime is „managed‟ in that the exchange rate can move only within a stipulated band, the SBV remains a major participant in the market and various forms

of administrative exchange controls and rationing are maintained

Because US dollar plays an important role and high ratio in comparison with other foreign currency in Vietnam, we choose the official VND/USD exchange rate as presented for exchange rate in the thesis VND/USD exchange rate has followed a gradual upward trend with very little volatility except for the periods of the Asian Financial Crisis and the recent World Financial Crisis However, due to limited access

to USD supply, businesses had to either pay extra fees to purchase foreign exchange at commercial banks or turn to black market for their needs

Table 3.1 Vietnam exchange rate arrangement 2000 - 2010

- ER band was reduced to +/-0.1%

- OER was stable at around 14,000VND/USD

- ER band was adjusted many times, widened to +/-0.75% (from 23/12/07 to 09/03/08), then to +/-1% (from 10/03/08 to

25/06/08),

to +/-2% (from 26/05/08 to 05/11/08), to +/-3% (from 06/11/08 to 23/03/09), to +/-5% (from 24/03/09 to 25/11/09), narrowed to +/-3%

(from 26/11/09 until the end of 2010)

(Source: Nguyen Thi Thu Hang et al, 2010)

3.2.1.4 Interest rate

Last researches used short term Treasury bill interest rate to analyze the impact

of interest rate on stock market However, in Vietnam the treasury market has not yet

maturely developed Therefore, in this research, I use three-month deposit interest rate instead of Treasury bill interest rate

Interest rates have been gradually liberalized since the mid-1990s Previously, the SBV set deposit as well as lending rates and, since October 1992, ceilings for lending rates and floors for deposit rates Major steps towards market-determined interest rates were taken with the lifting of floors for deposit rates with the exception of foreign currency deposits in 1996 and of ceilings on lending rates in August 2000 The ceilings for lending rates were replaced first by a basic interest rate, which was announced by the SBV every month and which commercial banks could only exceed within a set margin Interest rates for foreign currency loans were liberalized in July

2001 and lending rates for loans in domestic currency in June 2002

Since 2002, commercial banks in Vietnam have been able to legally set lending rates as well as deposit rates according to market conditions However, when necessary, SBV influenced interest rate movements by other means than indirect monetary policy such as setting ceiling interest rates for dollar deposits In general, during 2001-2007, Vietnam experienced a period of stable interest rates in the range of 6% to 6.5% for a 3-month term However in 2008, interest rate increased until 16-17%

In 2010 the Vietnamese economy faced high interest rates, up to 17%, after a year of low interest rates in 2009

3.2.2 Construction of variables for the models:

- Stock market return:

From stock market index downloaded from official website of Hochiminh stock market exchange, stock market return is calculated as following formula:

Where: