Stock prices and macroeconomic variables MDE thesis

Interestingly, the mixed evidence from the study of Truong 2006 in the 2002-2004 period conclude that the Vietnamese stock market is, to some extent, characterized by the weak-form effic

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY THE HAGUE

======o0o======

VIETNAM – NETHERLANDS

PROJECT FOR M.A IN DEVELOPING ECONOMICS

STOCK PRICES AND MACROECONOMIC VARIABLES IN VIETNAM: AN EMPIRICAL ANALYSIS

BY

NGUYEN THI BAO KHUYEN

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY, 2010

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY THE HAGUE

======o0o======

VIETNAM – NETHERLANDS

PROJECT FOR M.A IN DEVELOPING ECONOMICS

STOCK PRICES AND MACROECONOMIC VARIABLES IN VIETNAM: AN EMPIRICAL ANALYSIS

A THESIS PRESENTED BY

NGUYEN THI BAO KHUYEN

IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE

DEGREE OF MASTER OF ARTS IN DEVELOPMENT ECONOMICS

SUPERVISOR

Prof Dr NGUYEN TRONG HOAI

HO CHI MINH CITY, 2010

ACKNOWLEDGEMENTS

IT IS A TREAT to have an opportunity to formally express my appreciation to people who have really created the concepts and methodology expressed in this research

I own the greatest debt to professors of MDE Programme, executive programme administrations in Vietnam and colleagues Their enthusiasm about the experience and what they were teaching, was an important motivator for me

I would like to express my deep and sincere gratitude to my supervisor, Professor, Doctor Nguyen Trong Hoai, Dean of the Faculty of Development Economics, University of Economics, Ho Chi Minh City His wide knowledge and his logical way of thinking have been of great value for me His understanding, encouraging and personal guidance have provided a good basis for the present thesis

I especially appreciate the VietFund Management colleagues, who have been eager supporters of the research

NGUYEN THI BAO KHUYEN

March 2010

ABSTRACT

The article employs the cointegration and error correction version of Granger causality tests to investigate whether the Vietnamese stock market exhibits the publicly informational efficiency The test results strongly suggest informational inefficiency in the Vietnamese stock market Specifically, the results from bivariate analysis suggest that the Vietnamese stock market is not informationally efficient in both short- and long-run In addition, the stock market seems to even divorce from the most part of the economy Therefore, it is still possible for a “professional” trader to make abnormal returns by analyzing good or bad news contained in some macroeconomic variables

The findings re-assure that the Vietnamese stock market is not well functioning in scarce resource allocation and not attractive enough to encourage foreign investors Since the market is not informationally efficient, especially with respect to monetary variables, it may be dangerous for policy makers to realize the role of monetary policies, the so-called demand stimulus packages In terms of the investors‟ point of view, fundamental analysis is still significant for their investment decisions Thus, companies with strong equity analysts would have higher comparative advantages in this inefficient market Furthermore, instead of becoming more efficient over time, as one might expect, the Vietnamese stock market appears to have become increasingly divorced from reality This also reveals that the last financial crisis has serious impact

on the Vietnamese stock market

TABLE OF CONTENTS

CHAPTER 1 1

INTRODUCTION 1

1.1RESEARCHCONTEXT 1

1.2THEPROBLEMSTATEMENT 2

1.3THERESEARCHOBJECTIVES 3

1.4RESEARCHQUESTIONSANDHYPOTHESES 4

1.5RESEARCHMETHODOLOGY 5

1.6STRUCTUREOFTHETHESIS 5

CHAPTER 2 6

LITERATURE REVIEW 6

2.1THECONCEPTOFEFFICIENTMARKET 6

2.2FORMSOFMARKETEFFICIENCY 7

2.3MARKETEFFICIENCYANDVALUATION 12

2.4THEDETERMINANTSOFSTOCKPRICES 13

2.4.1 The Determinants of True Value 13

2.4.2 The Determinants of Stock Price 17

2.5EMPIRICALSTUDIES 20

CHAPTER 3 24

RESEARCH METHODOLOGY 24

3.1STATIONARITYANDUNIT-ROOTTESTS 24

3.2VECTORAUTOGRESSIVEMODELSANDCAUSALITYTESTS 25

3.2.1 VAR Models 25

3.2.2 Granger Causality Tests 26

3.3SEMI-STRONGFORMEFFICIENCYTESTS 28

3.4ERRORCORRECTIONMODELS 29

3.4.1 Cointegration 30

3.4.2 Error Correction Mechanism 30

3.4.3 Testing for Cointegration and ECM 32

3.4.4 ECM and Long-Run Efficiency 33

3.5DATACOLLECTIONANDANALYSIS 35

CHAPTER 4 38

RESEARCH RESULTS 38

4.1DESCRIPTIVESTATISTICS 38

4.2BIVARIATECAUSALITYTESTS 42

4.3MULTIVARIATEGRANGERTESTS 48

CHAPTER 5 54

CONCLUSION AND POLICY RECOMMENDATIONS 54

5.1MAINFINDINGS 54

5.2POLICYIMPLICATIONS 55

5.3FURTHERSTUDIES 57

REFERENCES 58

CHAPTER 1 INTRODUCTION

This chapter will explain why the efficient market hypothesis is worth investigating in the case of the Vietnamese stock market In particular, this chapter is divided into six sections The first section will provide evidence that tells us why information becomes an issue of concern for the most part of market participants and policy makers as well From this background information, the second section will raise the problem necessary to make clear for the case of Vietnam The third section will set four main objectives the thesis expects to obtain in order to solve the research problem To obtain the proposed objectives, the fourth section will raise questions and corresponding hypotheses which direct the whole thesis to a systematic way The fifth section will briefly tell us how the research will be done in terms of analytical models, data collection, and data analysis The final section will describe structure of the thesis

1.1 RESEARCH CONTEXT

Efficient market hypothesis (EMH) has been at the center of debates in financial literature for several years The term efficiency is used to describe a market in which all relevant information is impounded into the price of financial assets If the capital market is sufficiently efficient, investors cannot expect to achieve superior profits from their investment strategies As a result, Capital Asset Pricing models can be useful for various investment decisions In the economic perspective, the efficient market is even more important because it implies that the stock market is well functioning in scarce resource allocation However, this

is not always the case, especially in the emerging stock markets

The last decades have witnessed spectacular growth in both size and relative importance of the stock markets in developing countries High economic growth, the pursuit of liberalization policies, and trends towards financial market globalization provided the environment in which stock markets could thrive In addition, foreign equity managers were attracted to these markets by the potentially high rates of return offered and the desire to pursue international diversification According to Antoniou and Ergul (1997), as these capital markets have developed, considerable attention has been given to the question of whether they function efficiently But why the efficiently functioning stock market becomes so important that every developing country does its best to direct toward

economies‟, so efficient allocation of scarce resources and encouragement of private foreign investment are both of vital importance They also stated that the

success of an increasing privatization of these economies will depend crucially

on the presence of an active and efficient stock market Indeed, rational investors expectedly drive their investments into the most profitable projects, given acceptable risks The efficient market can address the „mixed feelings‟ problem, which investors are always skeptical about the intrinsic value of any stock under consideration This may lead their decisions based on others In other words, this phenomenon is commonly considered as herding behavior For foreign investors, inefficient markets are usually equivalent to high risky markets when making their investments abroad Hence, they tend to apply higher hurdle rates, which in turn underestimate investment opportunities in developing countries Eventually, it‟s hard for any developing country with inefficient/weak stock market to attract foreign portfolio investment flows In recent years, the intensity of foreign direct investment competition among developing countries becomes fiercer, so foreign indirect investment may become a feasible alternative for economic development

For above reasons, the questions of whether the markets price securities efficiently and what makes markets informationally efficient or inefficient turn out to be ultimately empirical issues An understanding of these issues will help

to determine the appropriate regulatory framework for the establishment of the efficiently functioning stock market This appears to be the case of Vietnam

1.2 THE PROBLEM STATEMENT

Since its foundation in July 2000, the Vietnamese stock market has dramatically expanded and become one of the most important sources of capital mobilization

Up to June 2009, the Vietnamese stock market has 352 listed companies and a market capitalization of about US$17.5 Billion, approximately 21.3 percent of Vietnam GDP, which even reached above 45 percent before the financial crisis (Thomson Reuters)

Despite its impressive growth, the Vietnamese stock market is really struggling with various typical weaknesses of an emerging market (Truong,

2006) First, it is not fully characterized by the depth and maturity of a stock exchange observed in a developed country The legal framework is weak and few alternatives are available for investors Interest rates are strictly controlled by the State Bank The government deeply intervenes into stock trading transactions Accordingly, investors tend to speculate, and thus cause high market volatility Second, it is widely known that one of the biggest problems facing traders is lack

of transparency Reporting requirements for listed companies are not well defined, and significantly less comprehensive than those in the developed stock markets Third, publicly information disclosure is not only unclear but also unreliable As a result, trading behavior in the Vietnamese stock market may be much different from that in developed/newly emerging stock markets Investors may base their actions on the decisions of others who are well informed about market developments, by following the market consensus In other words, the

herding behavior may exist in the Vietnamese stock market1 Thus, the question

is whether the Vietnamese stock market is informationally inefficient?

Interestingly, the mixed evidence from the study of Truong (2006) in the 2002-2004 period conclude that the Vietnamese stock market is, to some extent, characterized by the weak-form efficiency in which current prices fully reflect all information contained in past prices This implies that, for some stocks, it is not possible for a trader to make abnormal returns by using only the past history of prices However, this lowest form of efficiency cannot assure the Vietnamese stock market is well functioning in scarce resource allocation and attractive enough to encourage foreign investors Both investors and policy makers mostly concern if the current market prices reflect all publicly available information, such as information on inflation, economic growth, money supply, exchange rates, interest rates, dividend payments, annual earnings, stock splits, etc Therefore, this thesis tries to investigate whether or not it is possible for market participants to make consistently superior returns just by analyzing good or bad news contained in annual reports or other published information In other words,

the focus of this thesis is to find out the relationship between stock prices and

macroeconomic variables in Vietnam

1.3 THE RESEARCH OBJECTIVES

This thesis attempts to apply the most widely accepted analytical approach in the studying of stock markets, namely, the efficient market hypothesis, to investigate the behavior of the Vietnamese stock prices Particularly, the goal of this thesis is

to test whether the possibility that the Vietnamese stock market exhibits the strong form efficiency such that no relationship exists between lagged values of changes in macroeconomic variables and changes in stock prices over the December 2000 to June 2009 period In order to meet this above goal, this thesis aims to obtain the following specific objectives:

semi-(1) Investigate whether the Vietnamese stock market exhibits the semi-strong form efficiency;

(2) Examine the speed of adjustment to long-run equilibrium takes place in the Vietnamese stock market;

(3) Evaluate the possible feedback from the stock prices to the macroeconomic variables;

(4) Investigate if the financial crisis has any impact on the pattern of efficiency in the Vietnamese stock market;

(5) Suggest some policy implications for improving the stock market efficiency

1 This was already tested by Nguyen (2009)

1.4 RESEARCH QUESTIONS AND HYPOTHESES

In order to obtain the above objectives, this thesis will attempt to answer the following questions:

(1) Do “past” changes in macroeconomic variables explain “current” changes

Some hypotheses that can be stated regarding the literature review in Chapter 2 and analytical framework in Chapter 3 are:

(1) This thesis hypothesizes that the semi-strong efficiency would not exist in the Vietnamese stock market According to Ross et al (2006), to be semi-strongly efficient, an investor must be skilled at economics and statistics, and steeped in the idiosyncrasies of individual industries and companies However, to acquire and use such skills requires talent, ability, and time And in Vietnam, it is still lack of professional institutions so this is rarely realistic In addition, based on previous studies (Ibrahim, 1999; Hanousek and Filer, 2000; Rousseau and Wachtel, 2000; Wongbangpo and Sharma,

markets, to which extent, remain Granger causality relationships from the macroeconomic variables to stock prices, and thus they are widely considered to be informationally inefficient

(2) This thesis hypothesizes that the Vietnamese stock market could take a long time to adjust itself toward good or bad news in the economy This expectation is expectedly suitable for three reasons First, the publicly information disclosure is unclear and unreliable Second, the ability of investors in analyzing and understanding macroeconomic and industrial news is still limited Third, macroeconomic/market and industrial analyses are mainly considered by equity analysts of professional investment companies Therefore, these concepts are still far away from individual investors In addition, based on previous studies (Habibullah and

relationship in developing markets is extremely slow

(3) This thesis hypothesizes that the Vietnamese stock market, to which extent, could play as a leading indicator of the economy as a whole The Vietnamese stock prices may provide predictive power for economic

variables because we believe that stock prices contain the market participants‟ expectations of future real activities (Ibrahim, 1999)

(4) This thesis hypothesizes that the financial crisis does really have significant impact on the Vietnamese stock market This hypothesis is based on the evidence from ASEAN countries after 1997 Asian financial crisis (Atmadja, 2005) and Central Europe countries after the second wave

of voucher privatization (Hanousek and Filer, 2000)

[[1.5 RESEARCH METHODOLOGY

The Granger causality and error correction mechanism tests are employed to test the proposed hypotheses Theoretically, these tests are only appropriate when the variables being analyzed, including stock index and macroeconomic factors, are stationary and co-integrated Therefore, it becomes necessary to conduct various priori tests of integration and cointegration In so doing, this thesis will apply the unit root test (specifically the augmented Dickey-Fuller tests and the Phillips-Perron tests) Following previous studies, this thesis will employ the Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC) to determine the optimal lag lengths

Data used in Granger causality and error correction mechanism models are collected from three official sources, namely, Thomson Reuters, Bloomberg and International Monetary Fund during the December 2000 to June 2009 period Similar to most previous studies in emerging markets, this thesis will use the monthly data because the Vietnamese stock market is not long enough to apply quarterly data as other developed markets For this reason, some fundamental variables presented the whole economy performance such as GDP will be chosen

in a different way The choice of proxy variables will be discussed in Chapter 3

For time series variables are usually non-stationary, most previous studies used the first-order difference form And this is also the case in this thesis As taking differences, the transformed data might take both positive and negative values, so it sometimes limits the possibility of applying the logarithmic functional forms in regression analysis

1.6 STRUCTURE OF THE THESIS

After this chapter the rest of this thesis will be presented four other chapters Chapter 2 reviews the literature about the market efficient hypothesis and stock price determination, including empirical studies Chapter 3 presents the research methodology, where details about variables of interest, econometric models, hypothesis formulating, and data collection Chapter 4 presents the research results, indicating whether the Vietnamese stock market exhibits semi-strong form efficiency Chapter 5 ends the thesis with a conclusion, policy implications and limitations for further studies

CHAPTER 2 LITERATURE REVIEW

This chapter will provide a conceptual framework of market efficient hypothesis,

of which we will examine why market efficiency is significant and what are key determinants of current stock prices An overview of literature about informational inefficiency testing helps make clear the research questions and provide basis for an analytical framework development (research methodology) discussed in Chapter 3 To achieve these aims, this chapter will be divided into four sections The first section will briefly define the concept of efficient market

To its end, we will understand the essence of market efficiency in stock valuation, investment, and policy-making process The second section will summarize three basic forms of market efficiency so as to help us narrow down the topic of interest The third section will justify the determinants of stock prices, which provide us the underlying foundation for developing the conceptual model of this thesis The final section will review a set of previous studies about market efficiency, especially those in emerging markets in order to logically drive this thesis into a correct direction

2.1 THE CONCEPT OF EFFICIENT MARKET

Investors determine stock prices on the basis of the expected cash flows to be received from a stock and the risk involved Rational investors should use all the information they have available or can reasonably obtain The information set consists of both known information and beliefs about the future (Jones, 1998) Regardless of its form, information is the key to the determination of stock prices and therefore is the central issue of the efficient market concepts

According to Clarke et al (2001), the term "efficient market" was first used in

1965 by Fama In an efficient market, competition forces will cause the full effects of new information on intrinsic values to be reflected "instantaneously" in actual prices The efficient market hypothesis implies that investors are unlikely

to earn abnormal profits by simply predicting the price movements Indeed, the underlying engine of price changes only depends on new information A market

is said to be efficient if prices are quickly adjusted to new information In this case, investors will compete to each others in making use of any new information for profitable opportunities Interestingly, the higher competition among investors exists in effort to searching for over- or under-valued securities, the lower probability of finding and exploiting such mis-priced securities becomes For the majority of investors, the gain derived from information analysis may not be in excess of the transaction costs Consequently, there is no reason to expect that market prices are too high or too low Security prices adjust before an investor has time to trade on and profit from a new piece of information

Generally, an efficient market is one in which the prices of all securities quickly and fully reflect all available information about the assets This concept postulates that investors will assimilate all relevant information into prices in making their buy and sell decisions (Jones, 1998) Therefore, the current price of

a stock reflects:

1 All known information, including:

 Past information (e.g., last year‟s or last quarters‟ earnings)

 Current information as well as events that have been announced but are still forthcoming (such as a stock split)

2 Information that can reasonably be inferred; for example, if many investors believe that interest rates will decline soon, prices will reflect this belief before the actual decline occurs

occur:

1 A large number of rational, profit-maximizing investors exist who actively participate in the market by analyzing, valuing, and trading stocks These investors are price takers2; that is, one participant alone cannot affect the price of a security

2 Information is costless and widely available to market participants at approximately the same time

3 Information is generated in a random fashion such that announcements are basically independent of one another This is still a question under the Vietnamese stock market circumstances because information disclosure is unclear and unreliable

4 Investors react quickly and fully to the new information, causing stock prices to adjust accordingly This is not always a case in the Vietnamese stock market, because investors are not equally informed

2.2 FORMS OF MARKET EFFICIENCY

We have defined an efficient market as one in which all information is reflected

in stock prices quickly and fully The key to assessing market efficiency is information According to Jones (1998), in a perfectly efficient market, security prices always reflect immediately all available information, and investors are not

2 This is similar to the concept of perfect competitive market in microeconomics

able to use available information to earn abnormal returns because it already impounded in prices In such a market, every security‟s price is equal to its intrinsic value, which reflects all information about that security‟s prospects If some types of information are not fully reflected in prices or lags exist in the impoundment of information into prices, the market is less than perfectly efficient In fact, the market is not perfectly efficient, and it is certainly not perfectly inefficient, so it is a question of degree

In financial theory, the efficient market hypothesis is viewed in three common forms, depending on the kind of available information embodied (Figure 2.1) These are commonly classified into weak-form, semi strong-form, and strong-form efficiency

Weak Form Efficiency

The weak form is the lowest form of efficiency that defines a market as being efficient if current prices fully reflect all information contained in past prices only That is, nobody can detect mis-priced securities and beat the market by analyzing the historical prices This form implies that one should not be able to profit from using something that “everybody else knows” For this reason, any attempt to generating profits by studying the past history of price information (using technical analysis) is in vain

Based on the above definition, Fama (1970) suggests three models for testing stock market efficiency, namely, Fair Game Model, Submartingale Model, and Random Walk Model According to Ross et al (2006), among these models, the

Random Walk is the most powerful model widely used This model assumes

price changes only depend on new information Since information itself arrives randomly, so prices will fluctuate unpredictably

Pt = Pt-1 + Expected return + Random errort (2.1) where

Pt: Stock price at time t

Pt-1: Stock price at time t-1

The expected return is a function of a security‟s risk and would be based on the model of risk and return (Capital Asset Pricing Model, Arbitrage Pricing Model) And the random component is due to new information on the stock It is not predictable from the past prices

Equation (2.1) can be rewritten as follow:

Pt = Expected return + Random errort (2.2) Equation (2.2) implies that if the weak form of the EMH is true, past price

changes with a k lag period ( Pt-k) should be unrelated to the future price changes ( Pt) In other words, a market can be said to be weakly efficient if the current price reflect all past market data The correct implication of a weak-form efficient market is that the past history of price information is of no value in assessing future changes in price Thus, most previous studies use autocorrelation test or unit root test to test whether the stock market exhibits the weak-form efficiency And they all conclude that the emerging stock markets are weakly efficient3

 Figure 2.1: Relationship among three different information sets

Source: Ross et al (2006)

Semi-Strong Form Efficiency

The semi-strong form efficiency suggests that the current price fully incorporates all publicly available information Public information includes not only past prices, but also data reported in a company‟s financial statements (annual reports, income statements, filings for the State Security Commission, etc.), dividend payments, stock split announcements, announced merger plans, new product

3 These empirical studies, including those on the Vietnamese stock markets are not explicitly presented in this thesis, because we mostly concern the next level of market efficiency

All information

Publicly available information

Past

Information

developments, financing difficulties, the financial situation of company‟s competitors, expectations regarding macroeconomic factors (such as inflation, money supply, exchange rate, interest rate, economic growth), etc Semi-strong efficiency requires the existence of market analysts who are not only financial economists able to comprehend implications of vast financial information, but also macroeconomists, experts adept in understanding processes in product and input markets And according to Ross et al (2006), acquisition of such skills, however, must take a lot of time and effort In addition, the “public” information may be relatively difficult to gather and costly to process It may not be sufficient

to gain the information from, say, major newspapers and company-produced publications One may have to follow wire reports, professional publications and databases, local papers, research journals, etc., in order to gather all information necessary to effectively analyze securities

equivalently measured by the future discounted value of cash flows that will accrue to investors If the stock market is efficient, the market price of share must

be equal to its intrinsic value And according to dividend discount model, the price of the security reflects the present value of its expected future cash flows which is really affected by the changes in the macroeconomic environment such

as money supply, trade activities, foreign capital flow, interest rate, exchange rate, industrial production, inflation, etc From this foundation, Hanousek and

simultaneously meets the following conditions First, a contemporaneous

relationship must exist between real variables and market returns Second, lagged values of real variables must not enable a potential investor to predict current

returns in the market Hence, various empirical studies have employed the Granger causality approach to test semi-strong form efficiency We will develop this idea in the research methodology Chapter

Strong Form Efficiency

The strong form efficiency states that the current price fully incorporates all existing information, both public and private (also called inside information) The main difference between the semi-strong and strong efficiency hypotheses is that,

in the latter, nobody should be able to systematically generate profits even if trading on information not publicly known at the time In other words, company‟s managements (insiders) would not be able to systematically gain from inside information by buying company‟s stocks ten minutes after they decided (but did not publicly announce) to pursue what they perceive to be a very profitable acquisition The rationale for strong-form market efficiency is that the stock market anticipates, in an unbiased manner, future developments and therefore the stock prices may have incorporated all relevant information and evaluated in a much more objective and informative way than the insiders According to Ross et

always zero However, this assumption hardly exists in reality, so the strong form

efficiency is not very likely to hold This form of market efficiency is, therefore, beyond the scope of this thesis

form efficiency, and strong form efficiency implies semi-strong form efficiency Therefore, it‟s impossible to expect semi-strong efficiency, if the market is currently weakly inefficient The efficient market hypothesis has various practical meanings However, within this thesis, two fundamental implications are of special concern

First, if the weak form efficiency exists, technical trading systems (technical analysis) that rely on knowledge and use of past trading data cannot be of value According to Keilly and Brown (1997), a basic premise of technical analysis is that stock prices move in trends that persist Technicians believe that when new information comes to the market, it is not immediately available to everyone but typically is gradually disseminated from the informed professional to the aggressive investing public and then to the great bulk of investors Also, technicians contend that investors do not analyze information and not act immediately This process usually takes time Accordingly, they hypothesize that stock prices move to a new equilibrium after the release of new information in a gradual manner, which causes trends in stock price movements that persist for certain periods This indicates that if the stock market is „weakly‟ efficient and prices fully reflect all „past‟ relevant information, technical analysis becomes meaningless

Second, if the semi-strong form efficiency is true, no form of “standard” security analysis4 based on publicly available information will be useful In this situation, since stock prices reflect all relevant publicly available information, gaining access to information others already have is of no value Traditionally, fundamental analysts believe that, at any time, there is a basic intrinsic value for the aggregate stock market, various industries, or individual stocks and that these values depend on underlying economic factors As a result, a fundamental analyst would determine the intrinsic value of an investment asset (common stock, bond)

at a point in time by examining the variables that determine value such as current and future earnings, interest rates, and risk variables According to Keilly and

enough to cover transaction costs, an investor should immediately take appropriate action However, if all investors can access the same publicly information, the market price tends to reflect the correctly intrinsic value of an investment asset This second implication of EMH raises an important question

4 This implies the conventional fundamental analysis, which seeks to estimate the intrinsic value of a security and provide buy or sell decisions depending on whether the current market price is less than or greater than the intrinsic value (Jones, 1998)

about the underlying relationships between general economic environment and stock prices, which is shortly explained in the next section

2.3 MARKET EFFICIENCY AND VALUATION

According to Damodaran (2002), the question of whether markets are efficient, and, if not, where the inefficiencies lie, is central to investment valuation If markets are in fact efficient, the market price provides the best estimate of value, and the process of valuation becomes one of justifying the market price If markets are not efficient, the market price may deviate from the true value, and the process of valuation is directed toward obtaining a reasonable estimate of this value Those who do valuation well, then, will be able to make higher returns than other investors because of their capacity to spot under- and over-valued firms To make these higher returns, though, markets have to correct their mistakes over time There is also much that can be learned from studies of market efficiency, which highlight segments where the market seems to be inefficient These inefficiencies can provide the basis for screening the universe of stocks to come up with a subsample that is more likely to contain undervalued stocks Given the size of the universe of stocks, this not only saves time for the analyst, but it increases the odds significantly of finding under- and overvalued stocks

price is an unbiased estimate of the true value of the investment The true value is also known as the intrinsic value, which becomes the central of concern in fundamental analysis Markets do not become efficient automatically It is the actions of investors, sensing bargains and putting into effect schemes to beat the market, that make markets efficient For this fact, Damodaran (2002) pointed out three propositions about market efficiency

First, the probability of finding inefficiencies in an asset market decreases as the ease of trading on the asset increases To the extent that investors have difficulty trading on an asset, either because open markets do not exist or there are significant barriers to trading, inefficiencies in pricing of the asset can continue for long periods

Second, the probability of finding inefficiency in an asset market increase as the transactions and information cost of exploiting the inefficiency increases The cost of collecting information and trading varies widely across markets and even across investments in the same markets As these costs increase, it pays less and less to try to exploit these inefficiencies

Third, the speed with which inefficiency is resolved will be directly related to how easily the scheme to exploit the inefficiency can be replicated by other investors The ease with which a scheme can be replicated is related to the time, resources, and information needed to execute it Since every few investors single-handedly possess the resources to eliminate inefficiency through trading, it is

much more likely that inefficiency will disappear quickly if the scheme used to exploit the inefficiency is transparent and can be copied by other investors

Above analysis provides three important points First, some segments of the Vietnamese stock market can be weakly efficient Second, the Vietnamese stock market as a whole can be semi-strongly inefficient because it seems to be costly

to obtain appropriate public information, especially macroeconomic variables Third, fundamental analysis can provide a good conceptual framework for identifying key determinants of stock prices As we will discuss in the consecutive section of valuation models that the intrinsic value of any asset is the present value of expected future cash flows on it which in turn determined by expected growth and discount rate These fundamentals are only determined by expected macroeconomic conditions In an efficient market, the current market prices (Pt) randomly deviate around its true value (Vt), so it must also depend on the expected macroeconomic conditions During this thesis, the term “expected” implies the period t+1 In other words, in an efficient market, all past macroeconomic conditions (i.e t-1 or t-p) do not explain the intrinsic value, and thus the current market prices as well Therefore, if we find any relationship between past macroeconomic conditions and current stock prices, we can conclude that the market is semi-strongly inefficient

2.4 THE DETERMINANTS OF STOCK PRICES

2.4.1 The Determinants of True Value

According to Damodaran (2002), there are three fundamental approaches to estimating the true value of investments5, namely, discounted cash flow valuation (DCF), relative valuation, and contingent claim valuation However, the DCF is the foundation on which all other valuation approaches are built To do relative valuation correctly, we need to understand the fundamentals of DCF valuation

To apply option pricing models to value assets, we often have to begin with a DCF valuation Although there are various variants of DCF models6, we will only discuss the easiest one, called Dividend Discount Model (DDM), because our objective is to identify key determinants of the true value, rather than fundamental analysis

5 During this thesis, we just call the term “investment” as the common stock investment

6 See Damodaran, 2002, Investment Valuation: Tools and Techniques for Determining the Value of Any Asset, 2nd Edition, Wiley & Sons

The dividend discount model (DDM) assumes that the true value of a common stock is the present value of all future dividends7 This model is specified as follows:

) k 1 (

D

) k 1 (

D )

k 1 (

D )

k 1 (

D V

e 3

e

3 2

e 2 e

1 j

n 1 t

t e

t

) k 1 (

D

(2.3)

where

V j = value of common stock j

D t = dividend during period t

k e = cost of equity

For infinite period model, with assumption that the future dividend stream will grow at a constant rate, g%/year, the equation (2.3) is then rewritten as follows:

n e

n 0

2 e

2 0

e

0 j

)k1(

)g1(D

)k1(

)g1(D)k1(

)g1(DV

g k

 Figure 2.2: Breakdown of Risk

Source: Damodaran (2002)

The equation (2.4) tells that the intrinsic value of a stock is determined by two

fundamentals, including cost of equity and expected growth rate According to

because k e depends heavily on risk, whereas g is a function of the retention rate

(or reinvestment rate) and the expected return on equity investments (ROE)

Risk is commonly classified into two components The first component

usually relates to one or a few firms In financial economics, this category is

known as firm-specific or unsystematic risk Another risk component has broader

effects on every stock such as interest rate and inflation This category is known

as market or systematic risk The breakdown of risk is illustrated in Figure 2.2

Figure 2.2 shows us that thanks to diversification strategies, rational investors

eventually face market risk, which in turn depends on the macroeconomic and

political conditions (Damodaran, 2002) Given this justification, we can

demonstrate determinants of k e as follows:

Entire industry may be affected

by action

Exchange rates and Political risk affect many stocks

Interest rates, inflation, and news

Turning back the second variable of the intrinsic value, g, we realize that the

growth rate in net income (for DDM models only) is a function of two

fundamental variables, including retention ratio (b) and return on equity

investment (ROE)

g = b * ROE (2.7)

Because retention ratio depends mainly on specific firm‟s dividend policy, so the rest of our concern is about the return on equity investment In financial economics, we have the famous equation as follows:

ROE = ROC + D/E[ROC – r(1-t)] (2.8) where

ROC = Return on capital investment

D/E = Capital structure

r = Interest expense on debt/book value of debt

t = Tax rate on ordinary income

Although the return on equity is affected by the leverage decisions of the firm,

it‟s also affected by macroeconomic factors Therefore, g will eventually depend

on both monetary and fiscal policies From equation (2.4) to equation (2.8), given political stability, we can conclude that the intrinsic value of a certain stock is a function of the following factors:

Vj = f( R, I, Es, FX, TB, GB, M) (2.9)

Where denotes changes in macroeconomic variables, R is interest rate, I is inflation, Es are economy health variables, FX is foreign exchange, TB is trade balance, GB is government budget, and M is money supply

If we assume the market is efficient, the stock price randomly deviates around its true value, the stock price is then demonstrated as follows:

Pj = Vj + (2.10) Thus, the stock price can be written as the following function:

Pj = f( R, I, Es, FX, TB, GB, M, ) (2.11) For these reasons, general economic environment influences stock prices It is obvious that monetary and fiscal policy measures enacted by various agencies of national government influence the aggregate economy The resulting economic conditions influence all industries and companies within the economy Fiscal policy initiatives such as tax cut credits or tax cuts can encourage spending, whereas additional taxes on income or goods can discourage spending Increases

or decreases in government spending also influence the general economy All such policies influence the business environment for firms that rely directly on those expenditures In addition, we know that government spending has a strong multiplier effect Monetary policy produces similar economic changes A tightening monetary policy that reduces the growth rate of the money supply reduces the supply of funds for working capital and expansion for all businesses Alternatively, a restrictive monetary policy that targets interest rates would raise market interest rates and therefore firms‟ costs, and make it more expensive for individuals and firms Monetary policy also affects all segments of an economy and that economy‟s relationship with other economies

consideration of inflation, which causes differences between real and nominal interest rates and changes the spending and savings behavior of consumers and corporations In addition, unexpected changes in the rate of inflation make it difficult for firms to plan, which inhibits growth and innovation Beyond the impact on the domestic economy, differential inflation and interest rates influence the trade balance between countries and the exchange rate for currencies In addition to monetary and fiscal policy actions, events such as war, political upheavals in foreign countries, or international monetary devaluations produce changes in business environment that add the uncertainty of sales and earnings expectations and therefore risk premium required by investors

2.4.2 The Determinants of Stock Price

dividends and cost of equity, can help identify the ultimate determinants of stock prices, a more complete model of economic variables is desirable This model was first introduced by Keran in 1971 Jones (1998) emphasizes that although presented many years ago, this classic model remains an accurate description of the conceptual nature of stock price determination then, now, and for the future The two primary exogenous policy variables, G and M, affect stock prices through two channels First, they affect total spending (Y), which, together with

the tax rate (tx), affects corporate earnings Jones (1998) states that both current levels and lagged changes in Y affect corporate earnings Expected changes in (real) corporate earnings (∆E*) are positively related to changes in stock prices (∆P) Second, they affect total spending, which, together with the economy‟s potential output (Y*) and past changes in prices, determine current changes in prices (∆I) ∆Y and ∆I determine current changes in real output (∆X) Changes in

X and I generate expectations about inflation and real growth, which in turn influences the current interest rate (R) Interest rates, a proxy for discount rate in

a valuation model, have a negative influence on stock prices ( P) Therefore, the Keran model remains a classic description of stock price determination because it indicates the major factors that determine stock prices

 Figure 2.3: Determinants of stock price

Besides the above theoretical models, we will only develop analytical models for testing semi-strong efficiency in the Vietnamese stock market after reviewing some empirical studies in order to answer the research questions were mentioned

Nominal corporate earnings ( E)

Real corporate earnings ( E*)

Expected real corporate earnings ( E*e)

Changes in price level ( I)

Changes in real money ( M)

Changes in real output ( X)

Interest rates (R)

Stock price (P)

2.5 EMPIRICAL STUDIES

Since its introduction into the financial economics literature over almost 50 years ago, the efficient markets hypothesis has been examined extensively in numerous studies The vast majority of these researches indicate that stock markets are indeed weakly efficient For this reason, the rest of concern is often placed on the semi-strong efficiency In this section, we briefly discuss the evidence regarding the semi-strong form of the efficient markets hypothesis

In his influential paper, Fama (1981) states that common stock returns are correlated with some macroeconomic variables of a country, such as money supply, inflation, interest rate, and capital expenditure The most important implication of his findings is that changes in macroeconomic variables can be used to predict changes in stock prices

The types of relationships between stock market returns and macroeconomic variables can be varied As Mahdavi and Sohrabian (1991) report, there was an asymmetric causal relationship between those variables when they explored the relationship between changes in stock prices and GDP growth in the U.S using Granger causality tests The stock market growth rate caused GDP growth rate, yet no reverse causation was found Chen (1991), however, finds that the current and future economic growth could be revealed by several domestic variables, such as the market dividend-price ratio, short run interest rates, the lagged production growth rate, the term premium, and the default premium Furthermore, Rousseau and Wachtel (2000) reveal that equity markets have been key institutions in promoting economic activity in 47 countries However, it is worth noting that this finding may be different in countries with less financially developed or smaller market capitalization (Minier, 2003)

account in forecasting output However, it should also be considered that the relationship between stock returns and economic growth has not been stable over time (Stock and Watson 1990) For example, Cheng (1995) argues that a number

of systematic economic factors significantly influenced the U.K stock returns Meanwhile, this result contradicts with that of Poon and Taylor (1991) who also observe the interrelationship between macroeconomic factors and stock prices in the U.K

The relationship between stock prices and economic activity is not only limited to the relationship between stock prices and economic growth, but may also be extended to other economic factors, as Fama (1981) mentioned Abdullah

and growth of the domestic money supply in the U.S, but negatively related to domestic interest rates Beenstock and Chan (1988) also report that interest rates, input (fuel and raw material) costs, money supply, and inflation are the significant risk factors of the London stock market

For the Pacific region, in Australia, there was a unidirectional relationship (in negative fashion) between inflation and the nominal stock returns during the 1965-1979 period, with price levels leading the equity index (Saunders and Tress

relationship between inflation or expected inflation and stock market prices

In terms of the relationship between stock market returns and exchange rate,

increase, leading to domestic price level increases, which would expectedly have

a negative impact on stock prices Morley and Pentecost (2000) also confirm that stock markets and exchange rates are linked, and note that this connection is through a common cyclical pattern rather than a common trend

For the Asia-Pacific region, Hamao (1988) found a significant relationship between the Japanese stock returns and several factors, such as the changes in expected inflation and the term structure of interest rates Ibrahim (1999) also observed the Malaysian exchange rate by using bivariate and multivariate cointegration as well as Granger causality tests and found cointegration when the M2 measure of money supply and reserves are included, but no long-run relationship between the exchange rate and stock prices was found using bivariate models These suggest that in the short run the exchange rate might play

a significant role in the domestic economy, and that the Malaysian stock exchange is informationally inefficient

However, in some cases, macroeconomic factors cannot be reliable indicators for stock market prices movement in the Asian markets because of the inability

of stock markets to fully capture information about the change in macroeconomic fundamentals (as is cited in Wongbangpo and Sharma, 2002)

In conclusion, macroeconomic variables (i.e economic growth, inflation, interest rate, and exchange rate) of a country are related to each other Above studies provide a comprehensive explanation for the relationship among the real sector, the monetary sector, and in the exchange rate within an economy Thus, changes in one of those factors may have an influence on the others Stock price movements are, either symmetrically or asymmetrically, related to macroeconomic variables In some cases, short run causal linkages between stock price movement and macroeconomic variables are also appear It is worth noting that the relationship between the stock market movement and macroeconomic variables may not be direct, consistent, and stable over time

For the focus of this thesis, the test results from emerging stock markets such

as Malaysia, Thailand, Indonesia, Philippines and Central European countries seem to be most significant Ibrahim (1999) investigates the dynamic interactions between seven macroeconomic variables (the industrial production index, consumer prices, M1, M2, credit aggregates, foreign reserves and exchange rates) and the stock prices for an emerging market, Malaysia, using Granger causality tests and error correction mechanism tests This analysis is conducted using

monthly data series for the period from January 1977 to June 1996 To smooth possible volatility, all data series are expressed in logarithmic forms Generally, the results suggest informational inefficiency in the Malaysian market

Using the bivariate causality tests, Ibrahim (1999) suggests three important points First, the results largely indicate that the lagged changes in macroeconomic variables have no significant predictive ability for the movements in stock prices Second, the stock market movements could help anticipate variations in the industrial production, the M1 money supply, and the exchange rate From this finding, he says that the causal link from stock prices to the M1 money supply may reflect the importance of the stock market on the M1 money demand Third, there exists the cointegration between the stock prices and three macroeconomic variables – consumer prices, credit aggregates and official reserves The results suggest that deviations from the equilibrium path are adjusted by about 5%–8% the next month through the movements in stock prices Thus, the adjustment toward the long-run relationship is extremely low in Malaysian stock market

equity markets in Central Europe exhibit semi-strong form efficiency such that

no relationship exists between lagged values of changes in macroeconomic variables (M1, M2, exports, imports, trade balance, foreign capital inflow, budget deficit, government debt, CPI, PPI, exchange rate, and industrial production) and changes in equity prices using Granger causality tests They find that while there are connections between real economy and equity market returns in Poland and Hungary, these links occur with lags, suggesting the possibility of profitable trading strategies based on public information and rejecting semi-strong efficiency hypothesis For Czech Republic and Slovakia, the situation is more complex In the early years of their existence, these markets may have possessed elements of semi-strong efficiency, with both lagged and contemporaneous relationships between real variables and equity markets However, these links have disappeared over time In other words, these stock markets appear to have become increasingly divorced from reality In the same manner, Azad (2009)

conducts a cross-market test including China, Japan, and South Korea and concludes that while Chinese stock market is inefficient, Japanese and South Korean stock markets are semi-strongly efficient These empirical studies, along with other studies about the U.S markets, suggest that developed equity and newly-emerging stock markets exhibit semi-strong form efficiency, while this is not a case in developing stock markets

prices indices and macroeconomic variables in five ASEAN countries, Indonesia; Malaysia; the Philippines; Singapore; and Thailand with particular attention to the 1997 Asian financial crisis and period onwards Using monthly time series data of the countries, a Granger-causality test based on the vector autoregressive (VAR) analytical framework was employed to empirically reveal the causality

among the variables This research finds that there were few Granger causalities found between the country‟s stock price index and macroeconomic variables This indicates that the linkages between domestic stock price movements and macroeconomic factors were very weak Due to that, the ASEAN stock markets were relatively unable to efficiently capture changes in economic fundamentals during the observation period in most of the countries in accordance to the literature in emerging stock markets, and that the influence of specific macroeconomic factors on the domestic economies differ across countries This also implies that the stock markets do not seem to have played a significant role

in most countries‟ economies, and macroeconomic variables are unlikely to be appropriate indicators to predict not only the future behavior of other macroeconomic variables, but also that of the stock market price indices

In summary, in a perfectly efficient market, security prices always reflect immediately all available information, and investors are not able to use available information to earn abnormal returns because it already impounded in prices However, only information about changes in past prices and macroeconomic variables is mostly concerned by investors, academics, and policy makers Regarding the resource allocation function, the stock market should be oriented toward semi strong form efficiency This is also the key concept of this thesis In order to test the existence of semi strong – form efficiency, most previous studies investigated the relationships between stock market returns and changes in macroeconomic variables in the form of cointegration approach to Granger causality tests These will be further discussed in Chapter 3

CHAPTER 3 RESEARCH METHODOLOGY

The conceptual framework discussed in Chapter 2 indicates that if the future changes in stock prices are dependent on past changes in macroeconomic variables, the market is characterized by semi-strong inefficiency To test whether the market is semi-strongly efficient, most previous studies employed the Granger causality model (short-run efficiency) and the error correction model (long-run efficiency) And these are also what this thesis intends to discover in the Vietnamese context

This chapter will first explain the fundamental concept in time series econometrics: “stationarity”, which provides an underlying guidance for the remaining parts of this thesis The widely accepted augmented Dickey-Fuller (ADF) tests and Phillips-Perron (PP) tests are also introduced in this section It seems that the most important analytical framework of this thesis places on the Granger causality and error correction mechanism analysis in the next sections Finally, we will discuss how the thesis deals with proxy variables, data collection, and data analysis

3.1 STATIONARITY AND UNIT-ROOT TESTS

This research design is completely based on the time series data And stationarity is the central issue of concern when working with this kind of data, including regression analysis and forecasting According to Asteriou and Hall

are non-stationary The problem with non-stationary data is that the standard OLS regression procedures can easily lead to incorrect conclusions, especially the phenomenon of spurious regressions For this reason, testing whether a certain set

of time series are stationary appears to be the first task in any time series based research This is also a case in this thesis

In stationary time series, shocks will be temporary and over time their effects will be eliminated as the series revert to their long-run mean values On the other hand, non-stationary time series will necessarily contain permanent components Therefore, the mean and/or the variance of a non-stationary time series will depend on time, which leads to cases where a series (a) has no long-run mean to which the series returns, and (b) the variance will depend on time and will approach infinity as time goes to infinity

There are various ways of identifying non-stationary series, such as line

graph, correlogram, t statistic test, or Ljung-Box Q statistic test However, these

methods are usually used in practical applications Asteriou and Hall (2007)

states that these methods are bound to be imprecise because a near unit-root process will have the same shape of autocorrelation function with that of a real unit-root process Most academic studies apply the widely approved unit-root test methods, introduced by Dickey-Fuller (1979) In statistics language, if a time series have a unit root, it is called „non-stationary‟

There are various versions of unit-root tests8, but for this thesis application purpose, I just concentrate on the augmented Dickey-Fuller (ADF) test Suppose that we want to test for the existence of a unit root of Yt (H0: = 0), three possible forms of the ADF test are given by the following equations:

p 1 i

t i t i 1

t

p 1 i

t i t i 1

t 0

p 1 i

t i t i 1

t 1

According to Ibrahim (1999), the PP9 test for unit roots is conducted in a similar manner using regression (3.3) without the lagged first differenced terms

3.2 VECTOR AUTOREGRESSIVE MODELS AND CAUSALITY TESTS 3.2.1 Vector Autoregressive (VAR) Models

According to Asteriou and Hall (2007), when we are not confident that a variable

is really exogenous, we have to treat each variable symmetrically Take for example the series Yt that is affected by current and past values of Xt, and simultaneously, the series Xt to be a series that is affected by current and past values of the Yt In this case, we will have the simple bivariate model given by:

1

Y

Xt = 20 - 21Yt + 21Yt-1 + 22Xt-1 + uxt (3.5)

where we assume that both Yt and Xt are stationary and uyt and uxt are uncorrelated white-noise error terms Equations (3.4) and (3.5) constitute a first-order VAR model, because the longest lag length is unity These equations are not reduced-form equations since Yt has a contemporaneous impact on Xt, and Xthas a contemporaneous impact on Yt

The VAR model has some good characteristics First, it is very simple because we do not have to worry about which variables are endogenous or exogenous Second, estimation is very simple as well, in the sense that each equation can be estimated with the usual OLS method separately Third, forecasts obtained from VAR models are in most cases better than those obtained from the far more complex simultaneous equation models However, on the other hand the VAR models have faced severe criticism on various different points First, they are a-theoretic since they are not based on any economic theory Second, as higher order or higher lag length, they face the loss of degrees of freedom Third, the obtained coefficients of the VAR models are difficult to interpret since they totally lack any theoretical background In addition, the same lag lengths among endogenous variables in VAR models are also another significant limitation

3.2.2 Granger Causality Tests

According to Asteriou and Hall (2007), one of the good features of VAR models

is that they allow us to test the direction of causality Causality in econometrics is somewhat different to the concept in everyday use; it refers more to the ability of one variable to predict (and therefore cause) the other Suppose two (stationary) variables, say Yt and Xt, affect each other with distributed lags The relationship between those variables can be captured by a VAR model In this case, it is possible to have that (a) Yt causes Xt, (b) Xt causes Yt, (c) there is a bi-directional feedback (causality among the variables), and finally (d) the two variables are independent The problem is to find an appropriate procedure that allows us to test and statistically detect the cause and effect relationship among variables This

is also one of the most important objectives of this thesis There are two interchangeable causality tests, namely Granger causality test and Sims causality test However, the Sims test, using more regressors (due to the inclusion of the leading terms), leads to a bigger loss of degrees of freedom (Asteriou and Hall,

Vietnamese stock market context

causality as follows: a (stationary) variable Yt is said to Granger-cause (stationary) variable Xt, if Xt can be predicted with greater accuracy by using past values of the Yt variable rather than not using such past values, all other terms remaining unchanged

The Granger causality test for the of two stationary variables Yt and Xt, involves as a first step the estimation of the following VAR model:

y t s

1 j

j t j r

1 i

i i 1

xt q

1 j

j t j p

1 i

i i 2

where it is assumed that both εyt and εxt are uncorrelated white-noise error terms

In this model, we can have the following different cases:

Case 1: The lagged X terms in (3.6) may be statistically different from zero as a

group, and the lagged Y terms in (3.7) not statistically different from zero In this case, we have that Xt causes Yt

Case 2: The lagged Y terms in (3.7) may be statistically different from zero as a

group, and the lagged X terms in (3.6) not statistically different from zero In this case, we have that Yt causes Xt

Case 3: Both sets of X and Y terms are statistically different from zero as a group

in (3.6) and (3.7), so that we have bi-directional causality

Case 4: Both sets of X and Y terms are not statistically different from zero in

(3.6) and (3.7), so that Xt is independent of Yt

The Granger causality test involves the following steps:

Step 1: Regress Yt on lagged Y terms as in the following model:

y t r

1 i

i t i 1

1 j

j t j r

1 i

i i 1

and obtain the RSS of this regression (which is the unrestricted one) and label it as RSSU