Therefore, the thesis focuses on assessing the impact of macroeconomic factors on share price index in Vietnam through variables such as exchange rate EX, money supply M2, interest rate
Tittle
The impact of macroeconomic factors on share price index in Vietnam
Abstract
The stock market is crucial for capital attraction and investor profit However, price fluctuations present challenges for policymakers and investment decisions This thesis analyzes the impact of macroeconomic factors on the Vietnamese stock market index (VN-Index) using the ARDL model The study examines the effects of exchange rate (EX), money supply (M2), interest rate (IR), inflation (CPI), and industrial production index (IIP) from January 2008 to December 2022 The results indicate that in the long run, EX negatively affects VN-Index, while M2 and IIP have positive effects In the short run, IIP has a negative impact, while CPI and IR do not affect VN-Index.
This thesis “THE IMPACT OF MACROECONOMIC FACTORS ON SHARE PRICE INDEX IN VIETNAM” is my article and there are no copies from This thesis is the author's independent research work, and the research results are honest and original, with no previously published content or content performed by others, except for properly cited references within the thesis
Nguyen Ngoc Tam An iv
First of all, I would like to express my sincere gratitude to the Banking University of Ho Chi Minh City and the team of lecturers who have dedicatedly provided guidance, assistance, and created conditions for me to develop and learn more, which has greatly contributed to the completion of this thesis
Special thanks are extended to Ph.D Du Thi Lan Quynh, my thesis supervisor, for her valuable guidance, support, and constant assistance throughout the research process, leading to the completion of this thesis
Although I have put in a lot of effort during the process of completing this thesis, there may still be limitations and errors due to my limited knowledge Therefore, I sincerely hope to receive understanding, guidance, and constructive feedback from scholars and esteemed teachers to further strengthen my knowledge and experience from this thesis
Once again, I would like to express my heartfelt appreciation
1.2 The urgency of the subject 11
1.5 Subjects and scope of research 13
CHAPTER 2: THEORETICAL BASES AND EMPIRICAL STUDIES 17
2.1 Theoretical basis related to the stock price index 17
2.1.1 The concept of the stock market 17
2.1.2 The concept of stock price index 19
2.1.3 Vietnam’s stock market Index (VN-Index) 20
2.2 The macroeconomic factors that influence share price index 21
4.1 Overview of the stock market and macroeconomic in the period 2008 -
4.2.3 Bound test and the co-integrating relationship 48
4.2.4 The results of estimating the long-run and short-run coefficients 49
4.2.5 Testing the stability of the model 52
5.3 Limitations of the study and directions for development 61
5.3.2 Directions for future study development 62
CAPM Capital Asset Pricing Model
FMOLS Fully Modified Ordinary Least Squares
HOSE Ho Chi Minh City Stock Exchange
IIP Index of industrial production
SEATS Signal Extraction in ARIMA Time Series
TRAMO Time series Regression with ARIMA noise, Missing values and Outliers ix
Table 2 1 Overview of empirical studies 28
Table 3.1 Summarizing the expectations of the variables in the research model 36
Table 4.1 Statistical analysis describes the variables in the model 46
Table 4.4 ARDL Long Run Form 49
Table 4.5 ECM Short Run Form 51
Figure 4.1 Macroeconomic and VN-Index developments in 2008 42
Figure 4 2.Macroeconomic and VN-Index developments in period 2011-2013 43
Figure 4 3 Macroeconomic and VN-Index developments in period 2019-2022 44
Figure 4.4 Testing the stability of the model (CUSUM Test) 52
INTRODUCTION
Rationale
Based on economic theory, net earnings generally indicate the extent of economic activity, while stock prices are expected to mirror forecasts for forthcoming corporate performance (Agwu & Haydar, 2023) If stock prices accurately mirror the underlying fundamentals, they serve as reliable leading indicators of future economic activity For a country, the financial market holds a significant role in attracting and mobilizing both domestic and foreign financial resources It serves as a platform for encouraging saving and investment, thereby fostering economic growth and enhancing the efficiency of financial utilization (Shubber & Nguyen, 2018)
Established in 2000, Vietnam’s stock market has now experienced more than two decades of operation and is growing day by day The most visible proof is rising number of individual investors actively participating This trend is evident in the continuous record-breaking numbers of new accounts opened each year After the period of strong growth in the stock price in Vietnam in 2021, a state of disequilibrium began to appear, the share price index continued to fall throughout 2022, investor psychology fell into crisis, especially when there is more and more negative information about macroeconomic factors such as falling interest rates, high inflation, decline in world oil prices due to the impact of the Russia-Ukraine war, etc Abrupt changes in macroeconomic variables have caused significant impacts on investor psychology and also disturbed the world stock market in general and the Vietnamese stock market in particular
This correlation between economic indicators and stock returns has been extensively studied by numerous academics, professionals, and analysts over the past few decades Throughout different periods, the effects of macroeconomic factors on the financial markets have been investigated and obtained different results (Kaplan et al., 2023) One of the primary benefits of studying macroeconomic factor’s impact on share price index is to make smart investment decisions The stock market is not merely a platform for buying and selling stocks and bonds but also serves as a
11 reflection of economic conditions and prospects for companies or entire nations By gaining a deeper understanding of how macroeconomic factors such as GDP growth, inflation, interest rates, exchange rates, … can affect the value of financial assets, investors can optimize profits and mitigate risks in their investment decisions
However, it's essential to acknowledge that researching these macroeconomic factors is not without its challenges The complexity and unpredictability of macroeconomic relationships, coupled with the uncertainty and volatility of the stock market, pose significant challenges for researchers Nevertheless, the importance of understanding these macroeconomic factors cannot be overstated, and research in this area remains a crucial part of the finance and economics fields In conclusion, studying the macroeconomic factors influencing the share price index brings numerous significant benefits to investors, policymakers, and the global financial system It's an area of immense potential and increasing interest within the finance and economics research community.
The urgency of the subject
Macroeconomic variables serve as key indicators that help assess the development stage or potential recessionary conditions within a country These variables offer a comprehensive overview of economic performance and is one of the indicators that stakeholders can rely on to make decisions
For instance, indicators like Gross Domestic Product (GDP), inflation rates, climate change, provide essential data points for analysts, policymakers, and investors to gauge the economic growth, stability, and sustainability within a nation When studying these macroeconomic variables, one can gain a clearer understanding of the current economic situation and make informed predictions about future trends Vietnam is currently one of the developing countries and the stock market is gradually attracting the attention of many investors The stock market is one of the important markets of our country's economy, it helps mobilize investment capital, create an investment environment, create liquidity for stocks, evaluate business performance and create an environment to help the Government implement appropriate
12 policies (Duy & Hau, 2017) So, understanding the relationship between macroeconomic indicators and stock market not only help investors seeking to make informed decisions but also policymakers formulating effective economic strategies, and businesses to develop business activities
So far, numerous research articles have been dedicated to this subject such as Shubber & Nguyen (2018); Trung (2022); Tuan Dao et al (2022), Bhattacharjee & Das (2023) However, macroeconomic and market factors exhibit continuous fluctuations, throughout different periods, the effects of macroeconomic factors on the financial markets have been investigated and obtained different results Kaplan et al (2023) Therefore, to clarify the impact of variables, I chose the topic “The impact of macroeconomic factors on share price index in Vietnam” to study the impact of Consumer Price Index, Interest rate, Inflation, M2 money supply, Index of Industrial Production and Exchange rate on HOSE (stand for share price index in Vietnam) in the period 2008 – 2022, thereby making new proposals to improve the efficiency of the stock market and macro policy.
Research objectives
The overall purpose of this study shows which macroeconomic factors impact and how it impacts on Vietnamese share prices, thereby providing suggestions to help the stock market develop through controlling macro factors
Base on overall purpose, detail objectives of topic are implemented such as: Identify the macroeconomic factors effect to VN-Index
Measure the level of influence of factors affecting the VN-Index
Proposed solutions to help the policy marker and investors can make the right decisions.
Research questions
What macroeconomic factors impact on VN-Index during the period 2008 –
How direction do the factors in the research model impact the VN-Index? What policy implications does the author propose to improve the stock market situation?
Subjects and scope of research
The subject of this research is macroeconomic factors impact on share price index in Vietnam HOSE will stand for share price index in Vietnam and macroeconomic factors include CPI, Interest rate, Money supply M2, IIP and Exchange rate
To provide comprehensive insights, data from January 2008 to December 2022 was meticulously collected from reputable sources such as Investing.com, FiinPro, and the International Monetary Fund (IMF) This extensive time frame encompasses significant economic events that have profoundly impacted our country, including the economic crisis, COVID-19 pandemic, and the Russia-Ukraine conflict This diverse data enables a thorough analysis of the economic landscape and its evolution over time.
Research methods
The author uses quantitative research method as the main method in the thesis Besides, there are other secondary methods such as statistical methods, synthesis, analysis and comparison methods
Using the Autoregressive Distributed Lag (ARDL) method, the study investigates the long-term and short-term relationships between macroeconomic factors and stock market performance The study begins by examining the stationarity of the variables through Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests Lag selection for the ARDL model is determined using the Akaike Information Criterion (AIC) in Eviews software Finally, the ARDL bound test is employed to establish the existence of a co-integrating relationship between the macroeconomic variables and stock market performance.
14 run and short-run model has been estimated To ensure model robustness, diagnostic tests for normality, serial correlation, and heteroskedasticity are performed, and the model's stability through CUSUM statistics
This study employed the model developed by Tuan Dao et al (2020), incorporating independent variables such as the Share Price Index in HOSE (VNI) The dependent variables included monetary supply (M2), interest rate (IR), exchange rate (EX), Consumer Price Index (CPI) representing inflation rate, and Industrial Production Index (IIP).
Contribution of the thesis
Study about impact of macroeconomic factors on share price index in Vietnam in period 2008 – 2022 will have practical contributions, specifically:
This study will provide specific information about macroeconomic factors impact on share price index and how does it impact, so that recommendations to stock market policy makers can adjust macroeconomic variables to formulating capital market policy for the better performance of stock market in Vietnam Besides, it helps investors make appropriate decisions and businesses have appropriate business strategies.
Layout of the thesis
The research paper consists of 5 parts, each part has introduction and conclude, beside it has table of contents, list of abbreviations, list of plaques, references and appendices As follows:
Author introduces about rationale, the urgency of the subject as well as information related to the topic such as purpose, research question, objective and scope, research methods and contribution of thesis
Chapter 2: Theoretical bases and empirical studies
This chapter will specifically outline the theoretical foundations of the stock market and the macroeconomic factors influencing it, thereby providing the basis for developing the research model in Chapter 3 Additionally, this chapter will review
15 previous studies to gain a broader overview of the topic
Based on the theories presented in Chapter 2, Chapter 3 will outline the research process, the applied model, and propose hypotheses Additionally, this chapter will elaborate on the variables included in the model, the data, and the research methodology
Chapter 4 will conduct the analysis, statistical tests, and examinations of results Consequently, discussions will be held to identify and determine which factors truly influence the Vietnamese stock market in the long and short term
From the findings obtained in Chapter 4, the author will draw main conclusions regarding the research process and provide specific recommendations These recommendations aim not only to enable governments to formulate appropriate regulatory policies but also to empower investors to make informed decisions for their portfolios Consequently, this will contribute to fostering a more stable and sustainable development of the stock market in the future
The study investigates the impact of macroeconomic factors on the share price index in Vietnam The research purpose is to examine the relationship between key macroeconomic variables and the performance of the Vietnamese stock market The thesis methodology includes literature review, data collection, and statistical analysis The research contributes to the body of knowledge by providing empirical evidence on the impact of macroeconomic conditions on stock market behavior The thesis is organized into five chapters, covering literature review, research methodology, data analysis, discussion of results, and conclusion.
THEORETICAL BASES AND EMPIRICAL STUDIES
Theoretical basis related to the stock price index
2.1.1 The concept of the stock market
According to Ket et al (2009), financial market as a place where various type of financial assets is traded, thereby capital is transferred from providers to seekers, either directly or indirectly Based on time horizon, financial markets are divided into two types: money markets and capital markets In which, the stock market is a typical form of operation and always holds a predominant position in the structure of capital markets in countries (Minh, 2004)
Stock market is where investors trade stocks, bonds, fund units, and other securities According Kieu and Yen (2009), the stock market operates by facilitating the direct transfer of capital from investment to issuers, thereby fulfilling the financial market's function of providing medium and long-term capital to the economy
The stock market plays a crucial role in the economy, and some important functions it performs Firstly, mobilizing capital for the economy The stock market provides businesses with an efficient and flexible channel for capital mobilization Through the stock market, companies can raise capital from individual and institutional investors worldwide Secondly, providing an investment environment for the public
It creates opportunities for individuals and organizations to invest in financial assets such as stocks, bonds, … Thirdly, creating liquidity for securities High liquidity enables investors to easily buy and sell securities, convert securities into cash, or switch to other types of securities Fourthly, evaluating the performance of businesses The stock price of a company in the stock market often reflects the market's assessment of the company's operations An increase in stock price indicates investors' confidence in the company and positive expectations for the future, while a decrease suggests the opposite Last but not least, providing a platform for the government to implement macroeconomic policies Governments can utilize the stock market to raise capital for important projects such as infrastructure development, social programs, and other development projects
Currently, there are many ways to classify the stock market, but according to Thu et al (2016), we can classify based on the following criteria:
Based on the circulation of capital:
Based on the circulation of capital, the stock market can be divided into two Types include secondary market and primary market Secondary market is where trading occurs and financial assets that have been previously issued are bought and sold, meeting the demand for investment capital transfer, thereby providing liquidity for instruments in the market This market operates regularly and continuously Primary market is a place where financial assets are issued, or in other words, it is a market that supplies instruments for participation in the financial market, thereby aiding in capital mobilization for the economy This market also operates irregularly but continuously
Based on the instruments circulating in the market:
Based on the instruments circulating in the market, stock market can be divided into three types, including stock market, bond market and derivatives market Stock market is where the issuance and trading of various types of stocks take place, including common stocks and preferred stocks Bond market is where the issuance and trading of various types of bonds take place, including corporate bonds, municipal bonds, and government bonds Derivatives market is where the issuance and trading of various types of derivatives take place Currently, this market is not yet widespread in our country
Based on the organizational of market
The stock market can be classified into the following types:
The first type is market focus This market is typically stock exchanges in countries They are legal entities established according to the law, carrying out securities trading organization for qualified listed issuers The buying and selling of securities are conducted at a centralized location, either through trading floors or via electronic computer systems operated by exchange members
The second type is decentralized market (or OTC Market – Over the counter
Market): This is a market where transactions do not occur at a specific location; investors can buy and sell securities through brokers or telecommunications systems Securities traded on this market are often those that are not qualified, thus they typically carry higher risks There are typically three main methods of trading in this market: simple negotiated transactions, quote-based trading, and trading with market makers' involvement
Based on the trading methods:
The stock market encompasses two distinct markets: the spot market and the futures market In the spot market, transactions involve the immediate exchange of securities at the current market price, with settlement occurring within a few days In contrast, the futures market operates with predetermined contracts specifying the price and delivery date for securities to be traded in the future.
2.1.2 The concept of stock price index
A stock price index is a statistical tool that measures and monitors the stock market's performance It is calculated by tracking a portfolio of stocks using specific methodologies According to Long and Trang (2008), it reflects the overall fluctuations in stock prices on an exchange, providing a basis for predicting market trends and informing decisions on security transactions Similarly, Kieu and Yen (2009) define it as an indicator of stock prices that captures the developmental trends of the stock market, including changes in prices and trading conditions.
Stock price index is often closely linked to the economy of a country So that they are not only of interest to economists but also attract many investors as they can use them to study, describe the market, and make appropriate investment decisions Each country will have different stock price index For example, in the current Vietnamese market, the VN-Index is popular on the Ho Chi Minh City Stock
Exchange, the HNX-Index on the Hanoi Stock Exchange, and other indices such as UPCOM-Index, VN30, and HNX30
2.1.3 Vietnam’s stock market Index (VN-Index)
According to Thuy (2016), over 20 years from the first trading session, VN- Index has affirmed its role as one vital indicator to reflect the performance of the whole economy This is the first stock price index in Vietnam, launched in 2000 by the Ho Chi Minh Stock Exchange (HOSE) It is an index that have most liquid stocks listed on HOSE, representing over 90% of the total market capitalization According to the Ho Chi Minh Stock Exchange (HOSE), the number of listed companies has grown from 5 at the end of 2000 to 380 by June 2020 Market capitalization has also increased from VND 986 billion at the end of 2000 to VND 3.2 million billion by the end of 2019, equivalent to 54% of GDP As a result, VN-Index is considered the benchmark for the Vietnamese stock market and is widely used by investors to track market movements and assess overall market performance That is the reason the VN- Index tends to receive more attention and research than other indices Therefore, I choose VN-Index is the dependent variable for this study
Currently, there are various methods for calculating stock price indices, and each country may have different calculation approaches In the case of the VN-Index in Vietnam, it is currently calculated using the Paasche method – the weighted average of the total market value of all listed stocks on the Ho Chi Minh City Stock Exchange This method, with the weight being the volume of listed securities at the calculation time, is quite common:
𝐼 𝑝 : VN-Index is calculated based on Paasche method
𝑝 𝑡 : is price at the observation period t
𝑝0: is price at the base period
𝑞 𝑡 : is the quantity (or weighting) at the calculation time (t) or the composition of the quantity at the calculation time
The Paasche weighted average price index is a weighted average price index, taking the weighting as the volume at the calculation period As a result, the calculated result depends on the volume structure (the structure of listed securities) at the calculation period.
The macroeconomic factors that influence share price index
In this research, the author focuses on studying the impacts on the VN-Index stock price index of 5 macroeconomic factors: Inflation, Lending interest rate, M2 money supply, Index of industrial production and Exchange rate
Inflation refers to a sustained increase in general price levels, indicating a decrease in the purchasing power of money (Curtis & Irvine, 2017) The general price level reflects the average price of a basket of goods and services As prices rise, consumers experience the effects of inflation, as the value of their money diminishes Various methods exist to measure inflation, including the Consumer Price Index (CPI), which the author utilizes in this research paper.
Inflation in the stock market induces investors to withdraw funds, decreasing demand and causing stock prices to decline This capital diversion results in idle capital, limiting investment opportunities for businesses and hindering economic growth Furthermore, inflation inflates business expenses, pressurizing operations and potentially affecting profit margins and revenue.
Researches of Nguyen & Nguyen (2013), Omoruyi et al (2015a) and Huyen
(2019) indicated that inflation is one of the macroeconomics strongly impact on stock price index The results show that when the Consumer Price Index (CPI) rises, consumers have to spend more money to maintain their living standards, indicating a tendency for inflation to increase Consequently, stock investment gradually loses attractiveness to investors
According to Minh, (2004) M2 money supply is referred to as asset currency or standard currency, comprising M1 money supply and substitute money such as time deposits, savings accounts, etc The characteristic of M2 money supply is its easy conversion into cash within a certain period M2 plays a significant role in the economy, and as the economy develops, the tendency to shift from M1 to M2 increases
Changes in the money supply can affect the prices and liquidity of the stock market When the M2 money supply increases, many investors tend to invest in stocks, creating strong purchasing power and driving stock prices higher However, excessive growth in the money supply can lead to inflation, negatively affecting the economy The structure of M2 money supply includes M1, Time deposits, Certificates of deposit (by denomination) and Deposits in monetary market funds (savings funds, credit funds, etc.)
The relationship between M2 money supply and the stock market is often considered to be positively correlated Some studies, such as those by Nguyen & Nguyen (2013), Phong (2015) and Fikri and Waquar (2023), support this view, while others suggest an inverse relationship between M2 and stock index prices, such as studies by Tuan Dao et al (2022), Omoruyi et al (2015a), and Trung (2022)
The interest rate, expressed as a percentage, is the prevailing market rate paid by lenders or charged to borrowers (Curtis & Irvine, 2017) Interest rates often fluctuate over time and are influenced by various economic and financial factors such as inflation and economic growth Market interest rates directly affect borrowing and
23 investment decisions of individuals, businesses, and organizations
Interest rates have an inverse relationship with the stock market Rising rates prompt investment in higher-yielding credit institutions and government bonds, diverting funds from the stock market and lowering stock prices Moreover, increased interest rates augment the cost of capital for businesses, impairing their expansion and profitability.
Some studies also agree with the above perspective, including Omoruyi et al (2015a), Tuan Dao et al (2022) Meanwhile, research by Quynh et al (2019), Trung (2022) suggests that interest rates and stock index prices have a positively correlated relationship On the other hand, Agwu & Haydar (2023) argue that interest rates do not affect the stock market
The exchange rate is a comparative measure of the value between two currencies, or in other words, the price of one currency in terms of another currency
It reflects the value of a unit of one currency in terms of another currency This is an important variable affecting the balance of trade and the balance of payments, which in turn can impact output, employment, and the overall economic equilibrium Additionally, exchange rates directly affect businesses Quynh et al (2019)
Appreciating exchange rates bolster the foreign currency against a depreciating local currency, resulting in a more favorable conversion rate for foreign exchange This disparity attracts foreign capital, drawn by profit opportunities in the stable investment climate Moreover, undervalued local currency stimulates exports, positively impacting the stock market.
However, various studies have shown that the exchange rate and stock index have positive effects in one country but negative effects in another country For
24 example, Asprem (1989), Mukherjee and Naka (1995) found evidence of a positive relationship between exchange rates and stock indexes in European countries and Japan, while Omoruyi et al (2015a), Bhattacharjee & Das (2023) supposed that exchange rate has a negative effect to the stock index in Nigeria and India In Vietnam, studies of Nguyen & Nguyen (2013), Phong (2015),Tuan Dao et al (2022) suggested that the exchange rate has a negative effect to the stock index, while Thuy (2015), Thu Trang et al (2021) argue for a positive relationship and Quynh et al (2019) did not observe any impact
The Index of industrial production (IIP) is the percentage ratio of the volume of industrial production generated in the current period compared to the volume of industrial production in the base period It assesses the growth rate of the industrial sector in an economic region This is one of the important indicators that helps economic analysts and investors quickly reflect the development situation of the entire industrial sector in general and the growth rate of each product and product group in particular
When the industrial production index increases, it indicates that the production activities of companies in the industrial sector are growing, leading to an increase in the stock prices of those companies Conversely, if the industrial production index decreases, it may cause investors to be concerned about the economic situation, leading them to be more cautious and tend to withdraw capital from the market to preserve profits Research by Omoruyi et al (2015a) suggests that the IIP does not have a long-term impact but has a positive impact in the short term Nguyet (2013), Thuy (2015) also share the same view that the industrial production index has a positive impact.
Overview of empirical studies
The financial market in general, and the stock market in particular, has always been a topic of great interest to researchers, investors, organizations, and governments Therefore, there have been numerous different research studies on the
25 impact of macroeconomic factors on the stock market In each country and different periods, various perspectives and assessments have been generated These research studies serve as abundant resources for authors to learn from and reinforce evidence for their own research
The research of Omoruyi et al (2015a) with the topic is “The impact of macroeconomic variables on stock market index in Nigeria” focused on six macroeconomic variables, namely, exchange rates, inflation rates, interest rates, money supply, industrial production index and international oil price with the period covered is between January 2000 to December 2010 Same as Vietnam, Nigeria is one among the emerging markets and the relationship between macroeconomics and stock price market remain unsettled conducted a study on the stock market index in Nigeria This study shown that inflation, exchange rates, and M2 had negative effects both in the short and long term, while interest rates and oil prices had positive effects, and IIP had no long-term effect but a positive effect on the stock market index in Nigeria in the short term In addition, the research of Aromolaran et al (2016) in Nigeria also have the same result which indicated that exchange rates had negative effects, IIP and FDI had positive effects on the stock price index
The research at Europe and America
Based on the research of Amado Peiró (2016), his study analyzed the dependence of stock prices on macroeconomic variables in the three largest European economies: France, Germany and the United Kingdom The author used indexes: CAC Industrial Index and later the CAC 40 for France, Commerzbank and later the DAX 30 for Germany, and FT30 and later the FTSE 100 for the UK with two macroeconomics: industrial production and interest rates from 1969 to 2013 The results demonstrate that the growth rate of industrial production affects stock return positively while the growth rate of long-term interest rate influences stock return negatively in all the three countries examined Similar conclusions are obtained by
26 using different proxies of the growth rates of industrial productions and long-term interest rates and also sub-periods Nonetheless, this study does not investigate the influence of the other variables such as: exchange rate, money supply and inflation on stock return
Mirza and Hashem (2013) researched the long-term equilibrium relationship between macroeconomic variables and the FTSE Bursa Malaysia Hijrah Shariah Index with 72 obvious from 9/2006 to 9/2012 This study statistically shows significant relationship with interest rates, exchange rate and money supply; it’s negatively affecting interest rate and exchange rate while positively money supply in the case of disequilibrium CPI has been statistically proven insignificant
Same opinion, in Nepal, the study by Shrestha and Lamichhane (2020), researchers investigated how Nepal's macroeconomic factors include interest rate, GDP, and money supply influence its stock market performance over a 32-year period (from 1987/88 to 2019/20) By using ARDL bound test approach, the study found that in the long run, broad money supply and interest rate have a negative significant relationship with the stock market performance however economic growth has a significant positive relationship in the long run
Vietnam's evolving status as an emerging market has stimulated research on stock price indices, particularly their relationship with macroeconomic factors This area of inquiry is gaining traction due to the potential insights it offers into the dynamics of the Vietnamese stock market.
Nguyen & Nguyen (2013) measured the impact of four macroeconomic factors including CPI, exchange rates, M2 money supply, and gold prices on the stock price index in Vietnam The data was compiled monthly from January 2004 to December
2021 The study was conducted using Fully Modified OLS (FMOLS) to assess the long-term effects and Granger causality test to evaluate the short-term effects The results showed that in the long run, money supply and gold prices had positive
27 effects while inflation had negative effects on stock price index Although the exchange rate did not significant influence in the long term, it had a negative relationship with the stock index Or the research of Nguyet (2013), with the same Granger method and amendment variable industrial production index With research samples from July 2000 to September 2011, the study showed that similar results to Nguyen & Nguyen (2013) and industrial production index (IIP) had positive effects on the VN-Index
Shubber & Nguyen (2018) implemented the topic “Vietnam’s stock market volatility under macroeconomic impacts” in period from August 2000 to December
2013 The author employed general autoregressive conditional heteroskedasticity (GARCH) framework to measure stock market volatility as well as to estimate this volatility under indicated macroeconomic impacts However, the results showed that only three out of six variables have impact on the VN-Index, whereas, exchange rates and CPI having positive effects and GDP had a negative effect About remain three variables, money supply, FDI and interest rate have not statistically significant
Huyen (2019) analyzed the impact of macroeconomic factors such as inflation, exchange rates, M2 money supply, industrial production index, and lending interest rates on the VN-Index from January 2005 to December 2017 Using the ARDL model, the results showed that only inflation had a negative relationship (-) with the stock index in the long run, while the other variables including industrial production, exchange rates, M2 money supply, and lending interest rates had no impact on the VN-Index
Tuan Dao et al (2022) used the ARDL method to study the long-term and short-term in the paper “Macro-Economic Factors Affecting the Vietnam Stock Price Index: An Application of the ARDL model” with the period from 2010 to 2021 The analysis included money supply, oil prices, interest rates, and exchange rates Research results show that in the long run, money supply and exchange rate respectively affect the stock market The money supply had a positive effect on the VN-Index, while the exchange rate showed the opposite effect However, the study
28 did not find a relationship between world oil price and interest rates on VN-Index in the long run On the other hand, in the short term, there are relationships between variables; specifically, interest rates and exchange rates have a negative impact on the VN-Index, while the world oil price and the fluctuation of money supply M2 of the previous one and two months showed an impact in the same direction on this index
RESEARCH METHODOLOGY
Research process
The topic "The impact of macroeconomic factors on the stock market in Vietnam" was investigated by the author according to the following scheme:
Step 1: Synthesis of theoretical foundations and empirical evidence
Based on relevant studies on the same topic both domestically and internationally, along with theoretical foundations and research methods, the author conducted a synthesis and analysis to select appropriate variables to serve the research model
Step 2: Formulating the Research Model Based on the theoretical framework and empirical evidence that have been analyzed and selected, the author constructs a research model linking macroeconomic factors (including CPI, IIP, EX, IR, and M2) with the Vietnam stock market index (VN-Index) Additionally, the research hypothesis is formulated to predict the relationships between the variables
Step 3: Selection and Processing of Study Samples and Data After selecting Synthesis of theoretical foundations and empirical evidence
Create model research Selection and processing of research samples and research data
Descriptive statistics of variables Unit root test of the data series Testing for co-integration Running the ARDL model to determine long-term effects
Running the ECM model to determine short-term effects
The research findings and discussion
32 suitable variables, the author proceeds to search for and collect data for these variables on a monthly basis from 2008 to 2022 through platforms such as Fiinpro, World Bank, IMF, etc
Step 4: Descriptive Statistics and Pre-regression Data Testing The processed data will be analyzed using Eviews 12 software to conduct descriptive statistics and provide basic characteristics of the factors affecting stock prices, such as sample size, mean values, standard deviations, etc
Step 5: Unit Root Testing The condition for running the ARDL model is that the variables must exhibit mixed-order stationarity at first and second differencing levels Therefore, before running the model, testing for unit root is crucial to determine whether the data is suitable for model estimation
Step 6: Cointegration Testing Cointegration testing is performed using the bounds testing approach This step helps identify whether the variables in the model have long-term relationships
Step 7: Running the ARDL Model After completing the aforementioned steps, the author runs the ARDL model to determine which variables have long-term effects and how they impact the dependent variable
Step 8: Running the ECM Model based on the ARDL Some variables may have long-term effects on the stock market index but not in the short term Therefore, the author runs the ECM model to identify which variables have short-term effects and how they impact the dependent variable
Step 9: Conclusion and Implications Based on the results obtained from the research model, conclusions, implications, and recommendations related to the model are drawn to address the objectives set forth in the study.
Data research
The data is used with a monthly frequency from January 2008 to December
In the realm of economics and finance, time series data frequently exhibit pronounced trends To mitigate these trends and enhance model stability, it is common practice to apply logarithmic transformation to the data By converting the values to logarithmic form, the strong trends are effectively eliminated, leading to increased stability and improved model performance.
The data is collected from secondary sources for analysis Specifically: Stock price index data is collected through the investing.com website Data on macroeconomic factors such as CPI, IIP of Vietnam are collected by the author from FiinPro at the library of the University of Banking in Ho Chi Minh City Other variables such as IR, M2, and EX are collected by the author through the IMF
After data collection, it will be aggregated in Excel and analyzed and tested using Eviews 12 software.
Research model
As follow diagram 3.2, research model built upon the findings of Omoruyi et al (2015a), Shubber & Nguyen (2018), Tuan Dao et al (2022) and Trung (2022), the thesis focuses on investigating the factors affecting the Vietnamese stock price index from January 2008 to December 2022, including factors such as exchange rate, money supply, interest rate, inflation and industrial production index
The research model in this thesis will primarily be built upon the ARDL model, and the author will also take the logarithm of all variables to increase the stability of the model The proposed model is as follows:
Where, ε t : The residual error term of the regression α0: The intercept of model
Dependent variable: VNI: Share price index in HOSE
IR: Lending interest rate (to stand for interest rate) (%)
CPI: Consumer price index growth compared to the same period last year (to stand for inflation rate) (%)
IIP: Industrial production index growth compared to the same period last year (%)
Research Hypotheses
Grounded in the content of Chapter 2, underlying theories, and prior research on the subject matter, the author establishes research hypotheses regarding the relationship between independent and dependent variables as follows:
Hypothesis 1: Exchange rate to have a negative impact on the Vietnam stock price index
When the exchange rates rise too high, it may raise doubts about the stability of the State Bank's exchange rate policies Foreign investors may become more concerned about macroeconomic instability, especially regarding medium and long- term investments Simply put, investors must consider the timing of withdrawing capital to complete each investment cycle This leads to a decline in the stock price index Based on the context of Vietnam and empirical studies conducted in our country, the author expects exchange rate to have an inverse relationship with the stock price index Empirical studies in Vietnam supporting this view include Nguyet (2013), Nguyen & Nguyen (2013), Phong (2015),Tuan Dao et al (2022)
Hypothesis 2: M2 money supply to have a positive impact on the Vietnam stock price index
M2 money supply is easily convertible into cash, and as the economy develops, the transition from M1 to M2 tends to increase Changes in money supply can affect market prices and liquidity An increase in money supply enhances liquidity and credit for stock buyers, creating greater purchasing power, which drives up stock prices Conversely, when loosening the money supply to stimulate economic growth, interest rates decrease, credit growth rates increase, business capital costs decrease, investment opportunities increase, and profit-seeking activities rise Therefore, the author expects an increase in money supply stimulates stock price index growth Studies by Nguyen & Nguyen (2013), Nguyet (2013), and Tuan Dao et al (2022) also support this view
Hypothesis 3: Interest rates to have a negative impact on the Vietnam stock price index
There is generally an inverse relationship between interest rates and the stock price index When interest rates rise, expected investor returns increase Consequently, idle funds are diverted into bank systems or government bonds due to increased profitability, reducing cash flows into the stock market and vice versa Most previous studies in Vietnam have yielded similar results, such as Nguyet (2013), Purna and Pitambar (2021), and Trung (2022) The data used is the lending interest rate in Vietnam from January 2008 to December 2022
Hypothesis 4: Inflation to have a negative impact on the Vietnam stock price index
Currently, there are numerous methods to measure inflation, but in this research paper, the author will measure it based on the Consumer Price Index (CPI) The CPI is a fundamental index used to measure the average price level of a basket of goods and services typically purchased by a typical consumer, often used to track changes in the cost of living over time The formula for calculating the inflation rate using CPI is as follows:
𝐶𝑃𝐼 𝑡 : Consumer Price Index at t period
As the Consumer Price Index (CPI) rises, indicating inflation, consumers experience a decline in their purchasing power This inflation erodes the value of stock investments, making them less attractive to investors Research conducted by Nguyen & Nguyen (2013), Omoruyi et al (2015a), and Huyen (2019) corroborates this relationship, demonstrating that inflation and stock market performance have an inverse correlation.
Hypothesis 5: Industrial production index to have a positive impact on the Vietnam stock price index
An increase in the industrial production index indicates growing production activities within the industrial sector, leading to higher stock prices for companies in that sector Conversely, a decrease in the industrial production index may cause investors to be concerned about the economic situation, prompting them to be more cautious and withdraw funds from the market to preserve profits Most studies suggest a positive relationship between the industrial production index and the stock price index, such as Nguyet (2013) and Omoruyi et al (2015a) The data used is the monthly IIP growth rate compared to the same period of the previous year
Based on the analysis of the relationship between independent and dependent variables, the author synthesizes and expects the impact between macroeconomic factors and the VN-Index stock price index as follows table 3.1:
Table 3.1 Summarizing the expectations of the variables in the research model
Research method
Descriptive statistical methods are utilized to describe the basic characteristics of the gathered data and offer a general understanding of the research sample Descriptive statistical measures encompass the mean, minimum, maximum, standard deviation, and number of observations
According to Nkoro & Uko (2016), although ARDL cointegration technique does not require pre-testing for unit roots, to avoid ARDL model crash in the presence of integrated stochastic trend of I(2), we are of the view the unit root test should be carried out to know the number of unit roots in the series under consideration This study focuses on ADF test and PP test to testing unit roots
Based on ADF test, the null hypothesis cannot be rejected about non-stationary cause its power is not strong Therefore, we can be verified using the other related test that is Philips Perror (PP) test It has the same null hypothesis as ADF and asymptotic distribution is the same as ADF test statistic Regardless of whether the variables are I(0) or I(1) or both, ARDL can be applied However, to avoid the appearance of unit roots after the second difference, unit root testing is necessary
The author utilizes the ARDL model to analyze the long-term and short-term data series According to Nkoro & Uko (2016), ARDL is an unrestricted dynamic model, where the dependent variable is expressed as a function of lagged values of the dependent variable and other independent variables This method can approach both the macro and micro levels, suitable for both large and small samples, and can provide unbiased estimates even when some explanatory variables are endogenous Additionally, conducting the bounds test in ARDL analysis helps estimate the long- term equilibrium relationship through ECM As a result, the adjusted ARDL parameters will provide more accurate short-term and long-term estimates
According to Pesaran (1997), the process of running the ARDL model will be
38 carried out in the following sequence:
Step 1: Determination the long-run relationship exists among variables
To determine the existence of a long-run relationship, the author uses Bound F-statistic (Bound test for cointegration) with the hypothesis as:
H0: The model does not have a long run relationship among variables
H1: The model has a long run relationship among variables
When F-statistic is greater than of fall within (between the lower and upper bound) the critical value band, then the H0 is rejected (the variables are cointegration), the long run relationship exists among variables On the other hand, if the F-statistic is below the lower bound critical value, the H0 cannot be rejected (there is no cointegration among the variables), therefore the long run relationship does not exist
Step 2: Choosing the lag length for the ARDL model
To ensure valid ARDL model estimation, it is crucial to determine the optimal lag length for minimizing Gaussian error terms The Akaike Information Criterion (AIC) is employed to select the best model order, ensuring non-normality, autocorrelation, and heteroskedasticity are addressed The non-differenced variables are alternately lagged, and the model is re-estimated and compared The model with the lowest AIC, minimized standard errors, and highest R2 is selected These estimates represent the long-run coefficients if a long-run relationship between the variables exists, preventing spurious regression.
Step 3: Running the ARDL model with the determined lag to test the long-term relationship between variables
The long run relationship between dependent variable and independent variables is estimated by ARDL model According to Pesaran (1997), the ARDL approach offers several advantages over other methods Firstly, when the sample size
39 is small, the ARDL model approach is more statistically meaningful Secondly, when examining long-run relationships, the ARDL approach only estimates a single equation Thirdly, ARDL approaches do not require the regressor variables to have the same lag length After determining the optimal lag, we proceed to run an autoregressive distributed lag (ARDL) bounds test is specified as follows:
Where, ε t : The residual error term of the regression α0: The intercept of model
∆: The first difference n: The optimum lag length
Dependent variable: VNI: Share price index in HOSE
IR: Lending interest rate (to stand for interest rate) (%)
CPI: Consumer price index growth compared to the same period last year (to stand for inflation rate) (%)
IIP: Industrial production index growth compared to the same period last year (%)
Step 4: Reparameterization of ARDL model into Error Correction Model
The short-run relationship of the model considers the temporary nature of the time period being studied and the monthly fluctuations of the stock price index (monthly changes) affected by the changes of macroeconomic factors (independent
40 variables) and the stock price index itself After determining that there is a long-run relationship between the variables being studied, estimating the short-run Error Correction Model (ECM) becomes necessary The ECM model measures the dynamics of the short-run model and the speed at which it adjusts to equilibrium whenever a shock occurs We estimate the following equation:
Finally, to stability of model, the author used cumulative sum (CUSUM) of the recursive residuals test at 5 percent level of significance If the plots of CUSUM statistics lies within the critical bounds at 5percent level of significance than all co- efficient in the given model became stable
In Chapter 3, the author will delve deeper into the research model, data collection methods, and research methodology The data input into the model is collected from reputable sources on a monthly basis from January 2008 to December
2022 There are 6 independent variables selected, including inflation, interest rate, M2 money supply, industrial production index, and exchange rate The topic applies quantitative research methods, utilizing the Autoregressive Distributed Lag (ARDL) model to determine the direction of the impact of macroeconomic factors on the VN- Index stock price index in both the long and short terms The results of Chapter 3 will serve as the basis for conducting regression and model testing, as detailed in Chapter
RESULT AND DISCUSSION
Overview of the stock market and macroeconomic in the period 2008 -
Established in 2000, the stock market has now operated for over 20 years, experiencing unpredictable fluctuations, especially during the period from 2008 to
2022 This period witnessed various economic shocks, including the 2008 financial crisis, the COVID-19 pandemic, the conflict between Russia and Ukraine, among others These disruptions have brought about significant changes in macroeconomic factors, making it increasingly challenging to predict stock market indices Below is a preliminary overview provided by the author of the stock market and the economy in Vietnam from 2008 to 2022:
Figure 4.1 Macroeconomic and VN-Index developments in 2008
Beginning in February 2008, the Vietnamese stock market faced significant turmoil as securities companies initiated massive sell-offs without corresponding buy orders This crisis was compounded by the global financial crisis, leading to elevated inflation and interest rates Figure 4.1 demonstrates that Vietnam's CPI surged over 20% in 2008 compared to the previous year, while interest rates climbed steadily, reaching approximately 21%.
Macroeconomic and VN-Index developments in 2008
43 point This sharp increase had negative impacts on economic development Lending rates also surged, causing many businesses to struggle to access bank loans Inflation control and macroeconomic stability were among the top priorities during this period With such significant fluctuations in macroeconomic conditions, the stock market inevitably suffered continuous declines In just under a year, the VN-Index plummeted by 68.86%, marking a record decline within a three-year period and making it the world's most sharply declining market
Figure 4 2.Macroeconomic and VN-Index developments in period 2011-2013
During the period of 2011-2013, macroeconomic instabilities such as high inflation and liquidity difficulties in the banking system, along with underperforming businesses, led to significant turbulence in the stock market in 2011 The market mostly showed red marks, and investor confidence eroded as reflected in the declining VN-Index and HNX-Index By the end of 2012 and the beginning of 2013, the market began to show signs of positive recovery, albeit amidst lingering global economic uncertainties and complexities However, Vietnam's macroeconomic indicators still experienced positive changes Inflation remained controlled, with the price index rising by only 0.51% compared to the previous month, equivalent to a 6.04% increase over the same period Both deposit and lending interest rates decreased significantly
Macroeconomic and VN-Index developments in period 2011-2013
CPI Interest rate VNI IIP
The stock market also showed some positive signs, with trading value increasing by 31%, the VN-Index rising by 22% compared to 2012, and the mobilization of government bonds reaching a significant level, contributing to fulfilling the state budget's financial tasks
Figure 4 3 Macroeconomic and VN-Index developments in period 2019-2022
In the period from 2019 to 2022, the Vietnamese economy operated against the backdrop of a slowing global economy Trade tensions between the US and China, along with geopolitical issues, exacerbated the instability of the global trade system Specially in 2020 and 2022, the global economy faced significant challenges, rapid and unpredictable fluctuations, and high levels of instability The world, including Vietnam, faced the unprecedented challenge of the COVID-19 pandemic Inflation rose to its highest level in decades, forcing countries to tighten monetary policies Strategic competition, geopolitical tensions among major countries, military conflicts such as the Russia-Ukraine conflict, natural disasters, pandemics, climate change, storms, and droughts have increased risks to global financial markets, currencies, energy security, and food security However, Vietnam managed to maintain positive growth momentum The stock market also witnessed continuous positive growth during this period, with liquidity reaching record levels By the end of 2020, the VN-
Macroeconomic and VN-Index developments in period 2019-2022
Index exceeded 1,100 points, reaching 1,103.87 points, a significant increase of 67% compared to the lowest point in 2020 (March 24, 2020, closing at 659.21 points), and a 14.9% increase compared to the end of 2019 The Vietnamese stock market was evaluated as the strongest performer in Southeast Asia and among the top 10 stock markets globally in terms of growth In 2021, the Vietnamese stock market experienced breakthroughs and set unprecedented records in its 21-year history The VN-Index reached a historic high, surpassing 1,500 points (reaching 1,500.81 points) on November 25, Vietnamese stock market among the top 7 markets with the highest growth rates in 2021, with a growth rate of 35.73% (behind Abu Dhabi, Argentina, the United States, Iceland, Austria, and the Czech Republic) However, subsequently, due to the impacts of domestic and international economic and social situations, the Vietnamese stock market entered a period of significant adjustment in 2022, reaching its lowest point when the VN-Index closed at 911.9 points By the end of 2022, the VN-Index had closed down by 32.8% compared to the end of 2021, and market liquidity had continuously decreased during this period
The above provides a preliminary overview of the macroeconomic situation and the stock market in Vietnam from 2008 to 2022 It is evident that macroeconomic factors have had significant impacts on stock market indices To further elucidate these impacts, the dissertation will utilize quantitative methods to conduct the next stages of research.
Resulting and testing research
After collecting data on the stock price index, M2 money supply, interest rates, exchange rates, inflation, and industrial producer price index of Vietnam for 180 months from January 2008 to December 2022 The results obtained when performing descriptive statistical analysis corresponding to the dependent variable and independent variables The results can be summarized in a table with the indices Obs (Number of observations), Mean (Average value), Std.dev (Standard deviation), Min (Minimum) and Max (Maximum)
Table 4.1 Statistical analysis describes the variables in the model
Variables Obs Median St.d Minimum Maximum
Based on Table 4.1, it has shown:
The Vietnam stock market index (VNI): With 180 observations, the average value is 592.81 points and the standard deviation is 306.3257 points In December
2021, the market recorded the highest point increase at 1498.280 points, and in February 2009, the market recorded the lowest point at 245.74 points
The M2 money supply (M2) has 165 observations with an average value of
The Vietnamese money supply has experienced consistent growth, with a mean of 6138610 trillion dong and a standard deviation of 3878949 trillion dong The peak value was observed in December 2022 at 14226792 trillion dong, while the lowest point was reached in January 2008 at 1561466 trillion dong, indicating a stable upward trend in the country's monetary circulation.
Interest rates (IR) with a total of 178 observations have an average value of 8.09% with a standard deviation of 3.45% In July 2008, the highest value was recorded at 20.25%, reflecting the macroeconomic fluctuations in our country in
2008, with continuous interest rate competition among banks, while the lowest rate was 6.95% in April 2017
The exchange rate (EX) has a total of 180 observations with an average value of 21757.5 dong and a standard deviation of 2151.654 dong The highest increase was
24840 dong in October 2022, and the lowest was 15960 dong in April 2008
Inflation is represented by the consumer price index (CPI) with a total of 180 observations, averaging around 4.2% with a standard deviation of 6.62% In August
2008, the highest increase compared to the same period the previous year was recorded at 28.32%, reflecting inflation events in our country, while the lowest increase was recorded in January 2021, when CPI decreased by 0.97% compared to the same period the previous year, during the time when the world in general and Vietnam in particular faced the impacts of COVID-19, causing economic stagnation
The industrial production price index has a total of 153 observations, ranging from a minimum of -15.12% in February 2013 to a maximum of 27.47% in January
2013, with an average of 8% and a standard deviation of 5.73%
Time series data commonly consists of four components: trend, seasonality, cycle, and randomness A graphical analysis revealed that variables IR and M2 displayed seasonality To address this, the TRAMO/SEATS tool in Eviews 12 was employed to remove seasonality Additionally, variables underwent logarithmic transformation to improve model stability.
The estimation of ARDL requires the integrated order of the variables to be either I(0) or I(1) To test the stationarity of the data series, the author used the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests The test results are presented in the following table 4.2:
Level 1 st difference Level 1 st difference
The ADF and PP test results in Table 4.2 indicate that the p-values are > 5% for all original series and p-values are < 1% for first-order differenced series In ADF test, we can conclude that the variables LOGM2-SA, LOGIR_SA, LOGEX, CPI, and IIP are integrated of order 1 (I(1)) In PP test, the variables LOGVNI, LOGM2-SA, LOGIR_SA, LOGEX, CPI, are integrated of order 1 (I(1)), while the variable IIP is integrated of order 0 (I(0))
According to Nkoro & Uko (2016), regardless of whether the variables are I(0) or I(1) or both, ARDL can be applied In ADF test, the result show that the variables were cointegrated of order 1, while in PP test, the variables were integrated of order
4.2.3 Bound test and the co-integrating relationship
The existence of long-run cointegration is tested using the bounds test The F- statistic values are utilized to determine the presence of a long-run relationship between the dependent and independent variables Based on the bounds test results of variables for the ARDL model, the author provides the data in Table 4.3 as follows:
Based on the Bounds Test, the F-value of 3.4343045 exceeds the 5% significance level upper bound for both I(0) and I(1) integrations This indicates a possible rejection of the null hypothesis, suggesting the presence of a cointegrating relationship between the variables and a long-run relationship.
4.2.4 The results of estimating the long-run and short-run coefficients
The ARDL model with optimal lag lengths (1,0,0,0,0,2) was selected for analysis based on the AIC criterion This model was employed to examine the long-run relationship between the variables.
Table 4.4 ARDL Long Run Form
Levels Equation Case 2: Restricted Constant and No Trend Variable Coefficient Std Error t-Statistic Prob
EC = LOGVNI - (-5.6788*LOGEX + 0.0663*LOGIR_SA + 1.3066
Based on the estimation results of the ARDL model in table 4.4, the author estimates the error correction regression function as follows:
LOGVNI = -5.6788* LOGEX + 0.0663*LOGIR_SA + 1.3066*LOGM2_SA + 1.1065*CPI + 1.4195*IIP + 42.8666
With a significance level of 5% in the long run, when the exchange rate increases by 1%, the VN-Index decreases by 5.6788 points, holding other factors constant; When the M2 money supply increases by 1%, the VN-Index increases by 1.3066 points, holding other factors constant; When the industrial production index (IIP) increases by 1%, the VN-Index increases by 1.4195 points, holding other factors constant
Thus, it can be seen that in the long run, exchange rate (EX) will have negative effects on the VN-Index, while money supply (M2) and industrial production index (IIP) have a positive effect As for the inflation (CPI) and interest rate (IR) variables, since p-value > 0.05, they are not statistically significant, meaning they do not have an impact on the VN-Index
As previously discussed, the ARDL model not only allows us to examine the long-term trends between variables but also allows us to examine short-term trends through the Error Correction Model (ECM) with the selected lags The results obtained are as follows:
Table 4.5 ECM Short Run Form
ECM Regression Case 2: Restricted Constant and No Trend Variable Coefficient Std Error t-Statistic Prob
Adjusted R-squared 0.168083 S.D dependent var 0.059279 S.E of regression 0.054068 Akaike info criterion -2.977202 Sum squared resid 0.426817 Schwarz criterion -2.916720 Log likelihood 224.8015 Hannan-Quinn criter -2.952629 Durbin-Watson stat 1.730393
The results in Table 4.5 show that the error correction term provides information on the response or speed of adjustment of the short-term coefficients towards the long-run equilibrium The coefficient of the error correction term ECM (-1) is statistically significant at 1% level, ensuring the existence of a cointegrating relationship in the study The error correction term falls within the range [-1 < - 0.194894 < 0] This indicates an adjustment level of up to 19.4894% to correct the short- term deviation to achieve long-run equilibrium
Discussing result of research
The results in table 4.4 and 4.5 indicate that out of the five independent variables included in the model, three variables exhibit statistical significance in the long run, one variable show statistical significance in the short run, and two variables lack statistical significance both in the long and short run Specifically, the results will be analyzed as follows:
The results in tables 4.4 and 4.5 indicate that the M2 money supply has a long- term impact on the VN-Index but no short-term effect, with a significance level of 5% In the long run, the M2 money supply shows a positive effect with the VN- Index When the M2 money supply increases by 1%, the VN-Index increases by 1.1046 points, holding other factors constant
In the short term, the results indicate that M2 does not have an impact on the stock price index This implies that short-term shocks in the M2 money supply will not cause fluctuations in the stock price index
M2 money supply has a positive long-term effect on stock prices, as evidenced by monetary policies This finding aligns with the expectations of the author and empirical studies by Nguyen & Nguyen (2013), Nguyet (2013), and Tuan Dao et al (2022), which support the relationship between money supply and stock market performance.
When implementing an expansionary monetary policy, more money is put into circulation, so more money will flow into the production and consumption of goods and also increase the use of financial assets such as securities In addition, an expansionary monetary policy reduces interest rates and high credit growth rates; reduces the cost of capital of enterprises, thereby increasing investors’ expectations as well as earnings This will stimulate cash flow into the stock market, increasing stock prices
The results in tables 4.4 and 4.5 indicate that in long term, the exchange rate has a negative effect on the VN-Index In long term, with a significance level of 5%, when the exchange rate increases by 1%, the VN-Index decreases by 5.3487 points, holding other factors constant
In the short term, the results indicate that EX does not have an impact on the stock price index This implies that short-term shocks in the EX will not cause fluctuations in the stock price index
Summary, EX exchange rate has a negative effect on the VN-Index in long-
54 term This outcome aligns with the initial expectations of the author as well as empirical studies by Nguyen & Nguyen (2013), Phong (2015) and Tuan Dao et al (2022)
According to theories of international economics, exchange rates often have a positive relationship with stock market indices When exchange rates rise and the domestic currency depreciates, export goods become more competitive, leading to an increase in export volume The local economy subsequently benefits Although our country is trade surplus which can potentially benefit from a rising exchange rate, the characteristic of Vietnam’s economy is that the export sector is dominated by FDI enterprises According to a report by the Ministry of Industry and Trade (2023), in
2022, 74% of export turnover was generated by FDI enterprises, surged by 11.8% compared to 2021, while exports by wholly domestic enterprises grew by only 6.8% These enterprises are rarely listed on the Vietnam stock exchange and our country is a developing country with a relatively weak scientific and technological foundation, Vietnam still relies heavily on imported machinery, raw materials, and other inputs from foreign countries, therefore an increase in the exchange rate can lead to numerous disadvantages for domestic enterprises Besides, when the exchange rate rises too high, it may raise doubts about the stability of the State Bank's exchange rate policies Foreign investors may become more concerned about macroeconomic instability, especially regarding medium and long-term investments Simply put, investors must consider the timing of withdrawing capital from Vietnam to complete each investment cycle, thereby it will negative effect on the stock price index
The ARDL model's estimations indicate a significant (5%) relationship between the Industrial Production Index (IIP) and the VN-Index in both the short and long term Notably, in the long run, a 1% increase in IIP corresponds to a 5.4473-point increase in the VN-Index, assuming all other variables remain constant.
In the short term, the IIP will have a negative effect to the VN-Index, but this
55 coefficient is not statistically significant On the other hand, when IIP of the previous
1 month increased by 1%, the current VN-Index decreased by -0.244340, with other factors unchanged In addition, the coefficient of the error correction term (ECM) is -0.194894 and statistically significant at the 5% level, which is entirely consistent with the ARDL model The results indicate that changes in IIP affect the adjusted stock price index by decreasing it by 19.4894% in the subsequent period to achieve long-term equilibrium
In conclusion, IIP have a positive effect to VN-Index in long-term and any short-term shock of IIP can have a negative impact on the VN-Index meaning that when the industrial production index increases compared to the same period last year, the VN-Index will also increase accordingly This result is consistent with the study by Nguyet (2013) and Aromolaran et al (2016)
When IIP increasing indicates that the manufacturing activities of companies in the industrial sector are growing, thereby leading to an increase in the stock prices of those companies Conversely, if the IIP declines, it can raise concerns about the economic situation, making investors more cautious or prompting them to withdraw capital from the stock market This often results in a decrease in stock prices and stock indices, reflecting uncertainty and negativity in investor sentiment Additionally, the IIP also impacts the government's monetary policy When the IIP unusually rises, industrial production increases, leading to an increase in the supply of goods and services domestically At this point, if aggregate demand is not tightly controlled, it can easily lead to significant economic fluctuations, further impacting the stock market indices
Inflation, as measured by CPI, and interest rates (IR) were found to have no significant impact on stock price index fluctuations This indicates that changes in both long and short-term inflation and interest rates may not lead to substantial variations in stock price index values.
Based on the research hypotheses discussed in Chapter 3 and the regression results presented in Tables 4.4 and 4.5, the author summarizes the conclusions as
In short-term In long-term Influence Significance Influence Significance
IR (-) - Not statistically (-) Not statistically
In this chapter, the author utilized secondary data to conduct quantitative methods Specifically, Eviews 12 software was employed for descriptive statistics, stationarity and bounds testing, ARDL regression, and model stability checks The results established both long-term and short-term relationships between variables and the VN-Index
CONCLUSION AND RECOMMENDATION
Conclusion
The research topic "The impact of macroeconomic factors on the stock market in Vietnam" aimed to identify and evaluate the direction of the impact of macroeconomic factors on the VN-Index Data was collected from January 2008 to December 2022 on a monthly basis
By using the ARDL model, the study provided data and evidence regarding the influence of factors such as exchange rate, M2 money supply, industrial production index, inflation, and lending interest rates The results indicated that in both the short and long term, the VN-Index is affected by industrial production index The M2 money supply and exchange rate only have an impact in the long term However, inflation and lending interest rates do not affect the VN-Index in either the short or long term
In reality, stock market fluctuations can be influenced by various other factors Besides domestic macroeconomic factors, the market is also affected by external information, company-related news, market sentiment, and investment behavior of both domestic and foreign investors
Based on the research results obtained in Chapter 4, in the long term, exchange rate has a negative effect, while M2 money supply and industrial production index have a positive effect In the short term, industrial production index has negative effects, and exchange rate, M2 money supply does not show significant impact Inflation and lending interest rates do not affect the VN- Index in either the short or long term
Harnessing macroeconomic indicators, as suggested by the Efficient Market Hypothesis, empowers investors and economic authorities with timely insights This enables them to make informed decisions and implement market policies that mitigate adverse effects of market volatility Moreover, policymakers can swiftly craft appropriate measures to stabilize and foster the growth of the stock market.
Recommendation
To implement stable and sustainable solutions for the development of the stock market, close coordination among the government, businesses, investors, securities brokerage firms, etc., is essential Among these, government policies play a crucial role in determining the market's development direction Based on the research findings, the author proposes several recommendations to foster the stable development of the stock market:
Firstly, when adjusting macroeconomic policies, the focus should be on creating stability and sustainability for the stock market
Stock markets often reflect anticipated economic developments Based on the regression results, factors such as M2 money supply, exchange rates, and IIP all have certain impacts in the short and long term Therefore, formulating and managing these macroeconomic factors not only affect economic management but also influence the sustainable development of the stock market
In the process of researching and proposing changes to macroeconomic policies in general and the stock market in particular, it is necessary to carefully study the behaviors of economic entities that may affect economic decision-making and market prices Policymakers also need to consider the impact of herd behavior In reality, investors do not always act rationally, so economic shocks can easily lead to investor panic selling, causing significant disruptions to the stock market
Secondly, macroeconomic information needs to be accurately, transparently, and timely disclosed
The stock market often reacts strongly to published information For policymakers when formulating short, medium, and long-term strategies, the information derived from these strategies will be received, analyzed, and evaluated by investors to incorporate into stock market price forecasts and investment strategies
The accuracy, transparency, and timeliness of information will have an impact on the market and investor behavior Therefore, information disclosure needs to be professionally executed and controlled by legal channels to avoid insider trading,
60 group interest manipulation, and market disruptions
Thirdly, monetary growth policies need to be implemented rationally
Monetary growth policies and strategies need to be implemented rationally based on the money demand function forecast to align with the economic objectives, adapting to the development stages The central bank needs clear directions and plans for adjusting money supply to stimulate the stock market without stalling the monetary market because excessive money supply not only fails to boost growth but can also lead to high inflation or economic recession and liquidity traps Additionally, unexpected actions that shock investors should be avoided, as they can have negative impacts on the stock market's development A decrease in the stock market can adversely affect foreign capital inflows, contributing to difficulties in policy implementation
Fourthly, caution is needed in managing exchange rates
Exchange rate management policies need to be flexible according to market supply and demand dynamics, aiming to maintain stability and ensure harmony with import-export policies It is crucial to continue attracting foreign capital into Vietnam and safeguard the interests of businesses operating and using foreign currencies Government and businesses borrowing foreign loans should mitigate risks when exchange rates fluctuate because such fluctuations can adversely affect the stock market both in the short and long term
Moreover, stronger development of derivative instruments such as futures contracts, options, etc., is needed to prevent foreign exchange supply-demand issues from hindering business operations Consequently, stock prices of companies will experience more stable growth, positively impacting the stock market
Fifthly, it's important to create conditions for the industrial production price index to develop, but it also needs to be tightly controlled
The government needs to proactively implement effective policies to support businesses in overcoming difficulties and obstacles in production and business activities, promoting the establishment of new industrial production projects to serve
61 both exports and domestic consumption, enhancing production capacity, providing goods for exports, and consumption in the domestic market Creating clean land funds, supporting production land clearance, forming industry-specific industrial clusters to attract investment, mobilizing all resources, especially resources from private economy and foreign investment, to invest in deep processing and trade promotion are also necessary These efforts will help improve the industrial production index, aiming towards set goals
However, in the short term, the industrial production index may have an adverse impact, as an increase in the index may cause negative market fluctuations But in the long run, this will help the market develop sustainably because when businesses operate in a favorable environment, their future business activities will gradually improve, contributing to the positive movement of the stock market Lastly, internal strength needs to be enhanced for the economy
Flexible and appropriate policies will help the stock market develop in the right direction Additionally, they will create conditions for businesses to expand their operations and increase profits, thereby increasing the quantity and quality of securities on the market Well-functioning businesses will enhance the economy's internal strength, providing a foundation for increasing national reserves, supporting the continued development of the stock market.
Limitations of the study and directions for development
Although the thesis has achieved its research objectives and yielded certain results, there are still some lingering limitations:
Firstly, in reality, there are many other macroeconomic variables that could impact the VN-Index, but the study only focused on a certain number of them for research purposes Limiting the variables may potentially lead to biases in the model as important explanatory variables could have been overlooked, affecting the validity of the proposed research model
Secondly, using the VN-Index as a representation of the stock market's
62 development may not be entirely appropriate This index is subject to significant fluctuations driven by large-cap stocks, potentially overshadowing the movements of low-value stocks and thereby influencing the results to some extent
5.3.2 Directions for future study development
Expanding the inclusion of additional macroeconomic variables to study their impact on the stock price index in the Vietnamese stock market is necessary Furthermore, extending the research period to the most recent year is also crucial to increase the urgency and accuracy of the results
To assess market trends effectively, it is crucial to employ a broader stock market index, such as the VNX Allshare Index or VNAllshare Index These indices mitigate the limitations of the VN-Index by capturing a more comprehensive representation of the market, enhancing the reliability and accuracy of market analysis.
In Chapter 5, the author provided a summary of the factors influencing the stock price index in Vietnam Based on these foundations, recommendations were proposed for policymakers to adjust policies in order to foster sustainable market development and provide investors with more tools to make appropriate decisions Additionally, this chapter also outlined the limitations of the study to lay the groundwork for future research lxiv
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