BANKING ACADEMY FINANCE FACULTY ---?????--- THESIS COURSE TOPIC: ANALYSIS OF MACROECONOMIC FACTORS IMPACT ON THE VIETNAM STOCK PRICE INDEX VN-INDEX Instructor : Dr... BANKING ACADEMY
OVERVIEW RESEARCH ON THE INFLUENCE OF
Studies in the world
1.1.1 Mondher Bellalah, Olivier Levyne and Omar Masood 11 (2013)- Impact of Macroeconomic Factors on Stock Exchange Prices: Evidence from USA Japan and China
This research investigates the correlations between stock market prices and macroeconomic factors, including the term of trade, oil prices, interest rates, money supply (M3), and index of industrial production, in China, Japan, and the United States The study specifically focuses on the period of the global financial recession The study employed the ARDL co-integration approach to investigate the co- integration of the NASDAQ Composite of USA, NIKKIE 225 of Japan, and Shanghai Composite of China Stock exchange price Index with the aforementioned macroeconomic variables over the period of 01/2005 to 05/2010 The analysis was conducted for both the long run and short run The findings indicate a positive correlation between stock exchange prices and the rate of interest, industrial production index, and money supply (M3) in both the short and long term in the United States and China
The findings from Japan indicate a statistically significant positive correlation between the interest rate and the stock exchange prices in the long run However, in the short run, the model demonstrates a negative association with the stock exchange prices In the context of Japan's data, the industrial production index exhibits a positive yet insignificant correlation with stock exchange prices in the long run However, in the short run, the index displays a positive correlation at the first lag, but a negative correlation at the second lag with stock exchange prices In the context of Japan, it can be observed that the money supply (M3) exhibits a positive correlation with stock exchange prices in the long run, while in the short run, this relationship is negative and statistically significant In the long run, there exists a positive relationship between the terms of trade (TOT) and stock prices in the economies of the United States, Japan, and China In the United States and
Japan, there exists a negative correlation between the terms of trade (TOT) and stock exchange prices in the short run
1.1.2 Sugeng Wahyudi, H Hersugondo, Rio Dhani Laksana, R Rudy (2017), Macroeconomic Fundamental and Stock Price Index in Southeast Asia Countries
The research examined the impact of macroeconomic factors on the composite index within Southeast Asian nations This study examines various variables, namely inflation, interest rate, exchange rate, gross domestic products (GDP), crude oil price, primary commodity price, and wages, across five Southeast Asian countries, namely Indonesia, Malaysia, Singapore, the Philippines, and Thailand The research employed time series data spanning from 2001 to 2015 in each respective nation
The findings of this investigation can be summarized as follows: (1) The impact of inflation on the aggregate stock price indexes in Indonesia, Malaysia, Singapore, and the Philippines is negative and significant However, in Thailand, inflation has a positive and significant effect on the aggregate stock price index The findings indicate that the impact of interest rates on the aggregate stock price index is negative and significant solely in Thailand Conversely, in Indonesia, Malaysia, Singapore, and the Philippines, interest rates exhibit a positive and significant influence on the aggregate stock price indexes The empirical findings indicate that the aggregate stock price indexes in Malaysia and Thailand are positively and significantly influenced by fluctuations in the exchange rate Whilst the aggregate stock price index is positively impacted by the exchange rate, the effect is not deemed statistically significant The aggregate stock price index in the Philippines is significantly impacted in a negative manner by fluctuations in the exchange rate
In the context of Indonesia, the impact of exchange rate fluctuations on the aggregate stock price index is observed to be non-significant According to the findings, it can be observed that GDP has a noteworthy and favorable impact on the aggregate stock price indexes in Indonesia, Malaysia, Singapore, and the Philippines However, in Thailand, the effect of GDP on the aggregate stock price index is unfavorable and significant Additionally, the results indicate that crude oil price has a favorable and significant impact on the aggregate stock price indexes in Indonesia, Malaysia, and Singapore In the context of the Philippines and Thailand, the impact of crude oil prices on the aggregate stock price indexes is observed to be positive, but not statistically significant Conversely, the primary commodity price exhibits a statistically significant positive impact on the aggregate stock price index solely in Singapore The impact of the primary commodity price on the aggregate stock price index in Malaysia is not statistically significant, despite exhibiting a positive correlation The aggregate stock price indexes in the Philippines and Thailand are significantly negatively impacted by fluctuations in primary commodity prices In Indonesia, the impact of primary commodity prices on stock price indexes is not deemed significant, whereas wages have a positive and statistically significant impact on stock price indexes in Indonesia, Malaysia, Singapore, and Thailand However, in the Philippines, wages have a negative and statistically significant impact on the overall stock price index
1.1.3 Amith Vikram Megaravalli & Gabriele Sampagnaro (2018),
Macroeconomic indicators and their impact on stock markets in ASIAN 3
The study endeavors to assess the impact of exchange rate and inflation on the stock markets of India, China, and Japan The independent variables considered in this study are inflation and the exchange rates of India, China, and Japan Meanwhile, the explanatory variables are Nifty, Shanghai stock market, and Nikkei
The aim of the research was to investigate the associations between the ASIAN stock index and macroeconomic factors (specifically, inflation as measured by the consumer price index and exchange rate) over a monthly timeframe spanning from 2008 to 2016 This was accomplished through the utilization of various statistical techniques, including Granger causality testing, cointegration testing, and pooled estimated results Based on the PMG estimation, it was determined that there exists a positive and statistically significant correlation between the exchange rate and the stock market in the long term across all three countries Conversely, it was found that there is no significant relationship between the stock market and inflation over the long term The empirical findings indicate a positive and statistically significant short-term correlation between the stock market and exchange rate, while the relationship between inflation and the stock market is deemed insignificant
1.1.4 AIGBOVO, Omoruyi (Corresponding Author) (2015), the impact of macroeconomic variables on stock market index in Nigeria
The objective of this research is to examine the correlation between macroeconomic indicators and the stock market index in Nigeria The study delves deeper into investigating whether fluctuations in the stock market index in Nigeria are influenced by macroeconomic factors In order to obtain this information, monthly time series data spanning from January 1980 to December 2010 were extracted The Johansen Co-integration test has confirmed the presence of a sustained association between the stock market index in Nigeria (ASI) and various macroeconomic factors The findings of the Granger causality analysis validate the existence of a correlation between the stock market index and the global oil price, as well as between the stock market index and the money supply The interdependence between the stock market index and international oil price is evidenced by a bidirectional relationship Specifically, fluctuations in the international oil price can cause changes in the stock market index (ASI), while movements in the ASI can, in turn, induce changes in the international oil price The aforementioned feedback relationship is applicable to both ASI and M1 monetary aggregates The observed relationship between the industrial production index and the stock market index, as well as between the interest rate and the stock market index, is unidirectional This implies that the causal direction runs from the former to the latter variables, rather than the reverse The aforementioned suggests that the stock market index serves as a prominent predictor of macroeconomic variables within Nigeria, and that fluctuations in stock prices can be attributed to macroeconomic factors The findings from both the multivariate ordinary least squares (OLS) and the error correction model (ECM) indicate that various factors, including inflation rate, interest rate, money supply, industrial production index, and international oil price, exert an influence on the stock market index, either in the short-term or long-term
1.1.5 Dimitrios N Subeniotis, Dimitrios L Papadopoulos, Ioannis A Tampakoudis, Athina Tampakoudi (2011), How Inflation, Market Capitalization, Industrial Production and the Economic Sentiment Indicator Affect the EU-12 Stock Markets
The present study has examined the influence of four crucial factors on the stock market price indices across 12 European nations The research has employed panel data analysis to analyse monthly observations from 2000 to 2005 The variables under consideration include market capitalization, industrial production, inflation, and the economic sentiment indicator
The findings from the empirical analysis indicate a positive correlation between stock market indices and both market capitalization and the economic sentiment indicator The statistical analysis reveals a significant and strong correlation between the two variables, as indicated by the high correlation coefficients Conversely, the analysis reveals a negative correlation between stock market fluctuations and both industrial production and inflation, albeit the statistical insignificance of the inflation coefficient The study has demonstrated a negative correlation between inflation and the stock market in the short term, but a positive correlation in the long term However, there is no consensus regarding the impact of industrial production on the stock market's wealth effect.
Studies in Vietnam
1.2.1 Nguyen Thi Nhu Quynh and Vo Thi Huong Linh (2019), the impact of some macroeconomic factors on stock price Index in Vietnam
This research effort seeks to evaluate the influence of six key macroeconomic determinants, namely oil price, consumer price index (as a proxy for inflation), money supply M2, interest rate, exchange rate, and gold price, on the market The VECM model was employed to analyze the performance of the Vietnam stock market, as represented by the VN-Index, during the time frame spanning from 2000 to 2018
Based on the findings of the study:
The regression analysis reveals that the impact of oil price on VN-Index is not statistically significant, as indicated by the regression coefficient
The regression analysis of the consumer price index (CPI) as a measure of inflation indicates a statistically significant, suggesting a positive influence of inflation on the VN-Index over an extended period Moreover, the VN-Index exhibits a negative correlation with interest rates, as evidenced by a statistically significant negative regression coefficient
The regression analysis indicates that the coefficient of money supply (M2) is not statistically significant, thereby suggesting that there is no long-term impact of money supply on the stock price index Furthermore, the findings indicate that there exists a favorable correlation between the money supply and the stock price index in the immediate period In the long run, the VN-Index is not significantly impacted by fluctuations in the exchange rate Additionally, according to the results of the Vector Error Correction Model (VECM), it can be observed that the exchange rate exerts a negative influence on the VN-Index within a short-term time horizon The VN-Index is not significantly affected by fluctuations in the price of gold over both short and long time horizons
1.2.2 Hoang Tuan DAO, Le Hang VU, Thanh Lam PHAM, Kim Trang NGUYEN, Macro (2022)-Economic Factors Affecting the Vietnam Stock Price Index: An Application of the ARDL Model
The purpose of this investigation is to examine the macroeconomic determinants that may impact the Vietnam stock market over both the long and short run, utilizing the ARDL approach Based on the findings of the ARDL model's regression analysis, it can be concluded that the variable of oil price exerts a favorable influence on the VN-Index in the immediate period This outcome is not unexpected as the Vietnam stock exchange is significantly influenced by the oil and gas sector The higher of oil prices has resulted in a corresponding increase in the anticipated profits of oil and gas corporations The VN-Index experienced a short- term increase due to the rise in stock prices within the oil and gas industry, which was accompanied by a significant capitalization in the market
The model's results suggest that the VN-Index is negatively impacted by the exchange rate variable, both in the short and long term In instances where the increase of exchange rate or devaluation of domestic currency is attributed to economic instability and apprehensions regarding forthcoming inflation, it is common for stock prices to be adversely impacted The variable of money supply, specifically M2, exhibits a favorable impact on the VN-Index in models of both short and long run The increase in the money supply generates a liquidity effect, leading to a surge in demand for financial assets, such as stocks
In the short term, the VN-Index experiences a negative impact as a result of fluctuations in the interest rate variable This finding is in line with the anticipated outcomes and is appropriate with both domestic and international empirical data In the long term, this variable exhibits a minimal positive impact on the VN-Index The observed effect does not exhibit statistical significance.
Gaps in domestic research
Upon reviewing numerous research papers, including both domestic and foreign articles with similar subject matter, it has been determined that a consensus exists among most researchers regarding the impact of macro factors on stock indexes The core concepts encompassing inflation, oil prices, gold prices, the S&P
500 index, exchange rates, and industrial production indices The stock index is a multifaceted variable that is subject to the influence of numerous factors The degree to which these factors impact stock prices varies depending on the research objectives and the rationale behind the selection of the variable by each author As such, the outcomes of such research endeavors will reflect the varying degrees of influence that these factors exert on stock prices It is noteworthy that the outcomes of said effects in a particular study may exhibit similarities or disparities in comparison to another country, with the extent of impact varying across different nations The outcomes of research papers may vary when authors employ distinct research models and conduct their studies at different stages, even if they are situated within the same geographical location It is not appropriate to utilize international research findings for the purpose of making inferences about the Vietnamese stock market Consequently, there is a pressing need for research pertaining to the influence of macroeconomic factors on the stock market of Vietnam Studies on this topic in Vietnam have a dated research period and lack recent updates, potentially compromising the accuracy of their findings in relation to current times Moreover, there exist variations in the outcomes of domestic research Henceforth, I have opted to conduct an analysis of the macroeconomic factors that impact on the VN-Index within the timeframe from July 2011 to December 2022.
THEORETICAL BASIS OF THE INFLUENCE OF
Stock Index
A stock market index is a metric that indicates the prevailing price level in the stock market on a specific day relative to the price level at a reference time
The VN-Index presently serves as the index that represents Hose, encompassing all stocks that are listed and traded on the stock market since its inception
This index is calculated as follows:
In which: Pit: Current market value of stock i
Qit: Current number of listed shares of stock i
Pio: Market value of stock i on the base date
Qio: Number of listed shares of stock i on the base date i: 1, …, n
The index is a measure of the fluctuations in the prices of stocks Consequently, during the computation of the index, it is imperative to eliminate variables that alter the index's magnitude without affecting the stock price Newly listed shares, split shares, and merged shares are among the various types of shares available in the stock market
In such instances, the divisor will be employed to maintain the uninterrupted progression of the VN-Index and precisely depict fluctuations in stock prices within the market
If additional shares are listed on the HOSE, the divisor will be computed in the following manner:
Macroeconomic factors affecting the stock market
Inflation is a macroeconomic occurrence that exerts an impact on many aspects of the economy, encompassing consumer expenditure, corporate investment, the level of joblessness, and interest rates In its most basic sense, inflation refers to a prolonged increase in the general price level The relationship between inflation and economic growth is a subject of debate Some believe that low inflation is positively associated with economic growth, whereas high inflation is risky and may indicate an overheated economy Furthermore, high inflation has the potential to impede economic growth and heighten the likelihood of a recession in the wider economy
The stock market serves as an ongoing instruments for assessing prevailing economic circumstances and factoring in upcoming conditions An optimal condition for the stock market would require a prolonged duration of inflation at a low-to-moderate rate, specifically ranging from 1% to 3% This ranging is favourable as it indicates that the economy is not experiencing an excessive level of inflation, the demand for goods and services is strong, the prices of goods and services exhibit a degree of stability, and the rate of depreciation of the currency is tolerable
The occurrence of inflation leads to a reduction in the purchasing power of income, savings, investments, and currency in general In periods of raised inflation, consumers experience a reduction in their purchasing power A trend of requiring a greater amount of monetary resources to purchase an equivalent quantity of goods in comparison to previous periods is observed
Higher rates of inflation give rise to a considerable amount of unpredictability As a result of consumers' increased prudence in their spending decisions, retail sales could decline; a decline in retail spending is a very negative development This happening has the potential to result in a reduction in overall economic growth
A decrease in economic growth is likely to have unfavourable implications for investors, with the stock market potentially exhibiting weakness in the presence of higher inflation
There is a positive correlation between higher levels of inflation and increased interest rates The reasoning behind increasing interest rates is based on the fact that it is an important tool employed by central banks to mitigate inflationary pressures and facilitate a reduction in prices The mechanism behind this thing is that an increase in interest rates leads to a rise in the cost of borrowing, which in turn causes a decline in consumer confidence and a consequent reduction in levels of consumer spending and business investment The net impact of this phenomenon is a reduction in the workforce, a decline in the aggregate price level of goods and services, and a general deceleration of the economic growth
Inflation has adverse effects on numerous companies, resulting in reduced revenue because of a decline in consumer spending and higher operating and production expenses Consequently, quite a few of investors exhibit an urge to remove themselves of these stocks, leading to a decline in share prices, thereby worsening the tendency of investors to sell of their shares The overall outcome is that the stock market exhibits a negative correlation with inflation, whereby an increase in inflation is associated with a decrease in stock market performance The rising rate of inflation require that investors need greater returns from their portfolio in order to reach a favorable real return
In the event of an increase in exchange rates, the domestic currency is expected to undergo a depreciation, thereby incentivizing foreign capital inflows into the country for the purpose of investment This is due to the potential for profit generation and price differentials in a stable investment climate A depreciated domestic currency can lead to a boost in exports, thereby resulting in a favorable influence on the equity market Given Vietnam's significant degree of trade openness, it is anticipated that fluctuations in exchange rates will affect a favorable influence on the stock index
Over the course of several decades, it has been noted that there exists a perceived inverse correlation between stocks and gold This suggests that there exists an inverse relationship between the gold prices and stock markets, whereby a decline in the former leads to an increase in the latter and vice versa Gold is frequently perceived as a more secure investment option during periods of market downturns due to its reputation as a reliable hedge against significant market instability Contemporary investors are presented with a wider array of investment alternatives in comparison to the conventional gold investment avenues such as gold bars, coins, or jewelry Currently, investors have the option to invest in Sovereign Gold Bonds, Gold ETFs, and other similar financial instruments, which allows them to mitigate the drawbacks associated with investing in physical gold
Oil is a crucial energy resource that serves as a vital fuel source and an indispensable input for transportation, which cannot be substituted in the production process Furthermore, oil is a widely traded commodity in the global market The volatility of increasing oil prices has an impact on various macroeconomic indicators, including inflation rates, monetary policy, national income, production costs, business sector profits, and asset values This, in turn, has implications for the broader financial markets Consequently, it is anticipated that fluctuations in the price of oil will exert a discernible impact on the stock market The escalation of oil prices is anticipated to exert strain on the augmentation of commercial expenditures and energy-reliant sectors Consequently, it leads to an escalation in anticipated forthcoming expenses, a decrease in cash inflows, and consequently, a reduction in the valuation of financial instruments When evaluating a specific security, the volatility of oil prices will result in an increase in revenue for companies that are net producers of oil, while companies that are net consumers of oil will experience a decrease in revenue In the context of a country that is a net importer, a surge in oil prices is likely to exert downward pressure on the exchange rates while simultaneously driving up the domestic inflation rate This, in turn, may result in an anticipated increase in the inflation rate, leading to a corresponding rise in the discount rate Therefore, an increase in oil prices is likely to adversely affect the profitability of stocks Conversely, in the case of a nation that exports more oil than it imports, a rise in oil prices is likely to have a favorable effect on the stock market The correlation between oil prices and stock prices can exhibit either a positive or negative association There is a gradual shift occurring in Vietnam's energy sector, whereby the country is transitioning from a crude oil exporter to an importer Nonetheless, the magnitude of the petroleum industry in the Vietnamese stock market is comparatively substantial The HOSE index comprises 45 companies with a market capitalization exceeding 1 billion USD Among these firms, several operate in the oil and gas industry, including PV GAS, PetroVietnam Power Corporation, PetroVietnam Technical Services Corporation, PetroVietnam Drilling and Well Service Corporation, and PetroVietnam Ca Mau Fertiliser JSC PV GAS has achieved a noteworthy market capitalization of 10 billion USD, placing it among the top 5 largest enterprises on the HOSE, as of October 2021 It is anticipated that the anticipated outcomes concerning the influence of oil prices on Vietnam's stock index will exhibit a favorable trend
Oil is a crucial input for transportation that cannot be substituted in the manufacturing process Furthermore, oil is a significant commodity that is exchanged globally The volatility of rising oil prices has a significant impact on various macroeconomic factors, including inflation rates, monetary policy, national income, production costs, and business sector profits These factors, in turn, have implications for asset values and financial markets more broadly Hence, it is expected that fluctuations in crude oil prices will exert an impact on the stock market The escalation in oil prices is anticipated to impose strain on the mounting business expenditures and industries that rely heavily on energy Consequently, the anticipated costs in the future are elevated, the cash flows are reduced, and the securities' value is diminished The variability in oil prices has the potential to impact a company's revenue positively if it is a net oil producer, and negatively if it is a net oil consumer In the case of a nation that experiences a net inflow of oil, a rise in oil prices will result in a decrease in exchange rates and an elevation of the domestic inflation rate This inflationary trend is further compounded by the anticipated increase in inflation rate, which in turn leads to a corresponding escalation in the discount rate As a result, the escalation of oil prices is expected to exert an adverse impact on the financial performance of stocks Conversely, the stock market of a net oil exporting country is expected to experience a favorable impact in response to a rise in oil prices Hence, the correlation between oil and stock prices may exhibit either a positive or negative association The trend of crude oil importation is on the rise in Vietnam Notwithstanding, the oil sector holds a considerable weightage on the stock exchange of Vietnam The HOSE index comprises 45 companies with a market capitalization exceeding $1 billion USD, among which are several entities operating in the oil and gas sector, such as PV GAS, PetroVietnam Power Corporation, PetroVietnam Technical Services Corporation, PetroVietnam Drilling and Well Service Corporation, and PetroVietnam Ca Mau Fertiliser JSC As of October 2021, PV GAS had achieved a market capitalization of 10 billion US dollars, positioning it as one of the top five most affluent companies listed on the HOSE Consequently, it can be inferred that the anticipated effect of fluctuations in oil prices on Vietnam's stock index would yield a favorable outcome
The Industrial Production index is regarded as a reliable gauge that mirrors corresponding fluctuations in the broader economic landscape A surge in industrial production is likely to increase the anticipated future cash flows and enhance the profitability of the corporations It is anticipated that there exists a positive correlation between industrial production and stock returns
In contemporary times, financial markets across the globe, including both developed and developing nations, have undergone a process of capital movement liberalization, financial reform, and technological advancements in information dissemination The aforementioned alterations have resulted in heightened engagement among domestic markets and global markets The correlation among stock markets has notably escalated Numerous academic studies have demonstrated that the United States stock market exerts a significant impact on other global stock markets To date, there exists no formal investigation into the impact of the United States stock market, including the S&P 500 and Dow Jones Indices, on the Vietnam stock market, as represented by the VN-Index In financial news, it is a common practice for market analysts to illustrate the fluctuations of the Vietnam stock market (VN-Index) by drawing a correlation with the movements of the U.S stock market Frequently encountered are declarations of the nature of "The VN-Index has experienced a decrease following the decline of Wall Street" and "The VN-Index has risen as a result of the surge of the Dow." The aforementioned assertions appear to imply that there exists a transmission of influence from the United States stock market to the stock market in Vietnam
DESCRIPTION OF DATA AND RESEARCH METHODS
Data sources
The present investigation employs a dataset consisting of monthly time series data spanning from July 2011 to December 2022, comprising a total of 138 observations The data source utilized in this study comprises of various variables, namely the Consumer Price Index (CPI) and Industrial Production Index (IIP), which were sourced from vietstock.vn Additionally, the VN-Index (VNI), S&P 500 Index (SP), Gold Price (GOLD), Crude Oil Price (WTI), and Exchange rate USD/VND (USD) were obtained from investing.com The variable CPI was computed with reference to the corresponding period in the previous year, while IIP was computed based on the preceding month The remaining variables were all derived from the initial day of the month
VN-Index (VNI) https://www.investing.com/indices/vn-historical-data
(CPI) https://finance.vietstock.vn/du-lieu-vi-mo/52/cpi.htm
S&P 500 Index (SP) https://www.investing.com/indices/us-spx-500-historical- data Gold Price (GOLD) https://www.investing.com/currencies/xau-usd-historical- data Crude Oil Price
(WTI) https://www.investing.com/commodities/crude-oil- historical-data
USD/VND (USD) https://www.investing.com/currencies/usd-vnd-historical- data
Index (IIP) https://finance.vietstock.vn/du-lieu-vi-mo/46/san-xuat- cong-nghiep.htm
Source: self-compiled by student
Research methods and models
The author of this thesis course opted to employ the Ordinary Least Squares (OLS) method for model analysis, as it is a widely utilized technique for parameter estimation in linear regression models One of the benefits of Ordinary Least Squares (OLS) is its simplicity and comprehensibility as a statistical technique Furthermore, it exhibits computational efficiency and has the ability to manage a substantial amount of predictor variables
OLS possesses the advantage of generating impartial estimations of the regression coefficients, given specific assumptions about the data The Ordinary Least Squares (OLS) method assumes that the errors in the regression model conform to a normal distribution with a mean of zero and constant variance Additionally, it assumes that the predictor variables are linearly independent
Furthermore, Ordinary Least Squares (OLS) offers an evaluation of the model's fitness, which is commonly referred to as the R-squared coefficient This metric denotes the fraction of the variability in the dependent variable that can be accounted for by the independent variables
In the context of multivariable linear regression, it is imperative that the model exhibits a linear association between the dependent variable and the independent variables, while simultaneously ensuring that there is no correlation among the independent variables, in order to achieve optimal predictive accuracy The occurrence in question may be denoted as Multicollinearity, which pertains to a circumstance whereby two or more autonomous variables within a regression model exhibit a high degree of correlation with one another The presence of multicollinearity poses a challenge in isolating the impact of individual independent variables on the dependent variable The outcome of this phenomenon is characterized by unreliable and inaccurate approximations of the regression coefficients, which may result in erroneous deductions regarding the association between the explanatory and response variables It is imperative to verify the existence of multicollinearity in a regression model and implement measures to mitigate it, if detected, due to the following justifications Multicollinearity can be evaluated by analyzing the correlation matrix of the independent variables and applying pairwise correlations between independent variables In the event of the existence of multicollinearity, a prevalent approach is to eliminate one or more of the correlated variables from the model or amalgamate them into a solitary variable
In addition to the issue of multicollinearity, heteroskedasticity may also pose a challenge The presence of heteroskedasticity in a regression model constitutes a breach of the underlying assumption of homoscedasticity, which posits that the variance of the error term is constant across all levels of the independent variable Heteroscedasticity is present in a statistical model when the variability of the residuals is not uniform across all independent variable levels The presence of bias and inefficiency in the estimation of regression coefficients may result in inaccurate inferences regarding the statistical significance of variables within the model To identify the presence of heteroskedasticity, the Breusch-Pagan Test would be employed by the researcher The procedure entails conducting a regression analysis of the squared residuals against the independent variables, followed by a statistical test to determine the significance of the coefficient of determination
Finally, it is advisable to take measures to account for autocorrelation Autocorrelation, which is also referred to as serial correlation, represents a transgression of the independence assumption in a time series or regression analysis Autocorrelation transpires in a model when the residuals or errors exhibit correlation with one another across successive time periods Autocorrelation has the potential to result in prejudiced and suboptimal approximations of the regression coefficients, as well as erroneous conclusions regarding the statistical importance of the variables in the model The identification of autocorrelation can be accomplished through an analysis of the autocorrelation function (ACF) and partial autocorrelation function (PACF) of the residuals
This thesis course employs Stata 15 software to conduct tests and models in order to provide commentary on the impact of macroeconomic factors on the VN- Index
Ln(VNI)=𝛃0 +𝛃1*CPI +𝛃2*Ln(USD) +𝛃3*Ln(WTI) +𝛃4*Ln(GOLD) +𝛃5*Ln(SP) +𝛃6*IIP +ɛ
𝛃1, ,𝛃6: Slope coef ficient of variables
Variables in the model
Table 2 Summary table of selected variable types in the model
Variable name Symbol Type of variable Transformation
VN-Index VNI Dependent variable =Ln(VNI)
Consumer Price Index CPI Independent variable %CPI
S&P 500 Index SP Independent variable =Ln(SP)
Gold Price GOLD Independent variable =Ln(GOLD)
Crude Oil Price WTI Independent variable =Ln(WTI)
USD Independent variable =Ln(USD)
Index IIP Independent variable =Ln(IIP)
Source: self-compiled by student 3.3.1 Dependent variable
The dependent variable in the model used is VN-Index This variable will be affected and explained by the independent variables in the model The author converts it into a Logarithmic variable VN-Index Because logarithmic transformation is a common technique employed in research to mitigate dispersion and minimize the impact of outliers in the original data
The independent variables in the model are the consumer price index, exchange rate USD/VND, crude oil price, gold price, S&P 500 index and industrial production index variable Similarly, the author converts all variables to logarithmic form However, it is noteworthy that the IIP and CPI indexes remain unaffected by this transformation, as they are expressed in percentage units rather than absolute values
H1: “Inflation has negative effect on VN-Index”
H2: “Exchange rate USD/VND has positive effect on VN-Index”
H3: “Crude oil price has positive effect on VN-Index”
H4: “Gold price has negative effect on VN-Index”
H5: “S&P 500 Index has positive effect on VN-Index”
H6: “Industrial Production Index has positive effect on VN-Index”
ANALYZE AND DISCUSS RESEARCH RESULTS
Overview of research data
VNI CPI USD WTI GOLD SP IIP Mean 6.60 4.61 10.01 4.18 7.28 7.78 2.13
Source: self-compiled by student
According to Table 3, which presents descriptive statistics, it can be observed that the Logarithmic variables exhibit varying degrees of dispersion from their respective mean values Notably, the Exchange rate USD/VND variable displays the largest standard deviation, indicating that the data points for this variable are widely dispersed from the mean value Furthermore, the upper limit of IIP has attained a value of 27.60%, while the lower limit of IIP is -22.30% The VN-Index exhibits a mean value of approximately 6.6, with its highest and lowest values being 7.31 and 5.86 points, respectively.
Research results and discussion
In order to test whether the OLS model has heteroskedasticity, the author uses the Breusch-Pagan test with the command “hettest”
Null Hypothesis course H0: “Data is NOT heteroskedasticity”
Alternative Hypothesis course H1: “Data is heteroskedasticity”
With a significance level of 5%, if p-value 5% then there is not enough evidence to reject H0
Figure 1: Running heteroskedasticity test model
Source: self-compiled by student
Based on Breusch-Pagan test’s result when p-value =0.0888, it means p- value >5% So the author cannot reject H0 In other words, the data is NOT heteroskedasticity
To assess the presence of multicollinearity among variables, the author employs pairwise correlation analysis
When the absolute value of the correlation between variables exceeds 0.8, it is possible to identify the presence of multicollinearity
The aforementioned command "pwcorr VNI CPI USD WTI GOLD SP IIP" is utilized for executing pair correlation
Figure 2: Running multicollinearity test model
Source: self-compiled by student
Upon examining the correlations between variables, it has been determined that the correlation coefficient between USD and SP exceeds 0.8 This indicates that the data exhibits multicollinearity A potential solution to address the issue of contributing to the aforementioned problem In reality, rectifying such variables in practical applications is a challenging task One feasible approach to identification involves iteratively eliminating variables from the regression model in a systematic manner until the degree of multicollinearity is effectively reduced The variables were selected by the author with the aim of minimizing multicollinearity This degree of multicollinearity may be deemed acceptable
In order to run Autocorrelation test in Stata 15, the author use the command
Figure 3: Running autocorrelation test model
Source: self-compiled by student
Autocorrelation was observed in all lags ranging from the 1st to the 10th, as indicated by the Autocorrelation column To address the issue of Autocorrelation in the dataset, the author employed the technique of first differencing The process of first differencing involves a mathematical manipulation whereby a time series is converted into a novel series, wherein each value denotes the disparity between successive observations in the initial series To be precise, if we represent the initial series as yt, then the primary difference series can be expressed as: yt’ = yt – yt-1
Figure 4: Running autocorrelation test model
Source: self-compiled by student
Upon reviewing the Autocorrelation column, it can be posited that the implementation of first differencing may serve to mitigate the presence of Autocorrelation
Upon analysis of three potential sources of deviation in the regression model, namely Multicollinearity, Heteroskedasticity, and Autocorrelation The researcher intends to employ a linear regression model and the Ordinary Least Squares Model technique to examine the potential influence of the independent variables on the dependent variable If affirmative, then the impact is either congruent or incongruent
Initially, it is imperative to assess the extent to which the variability of the dependent variable is accounted for by the independent variables, ascertained through the employment of the adjusted R-squared or R-squared coefficients In the event that the R squared value exceeds 50%, the newly proposed model can be deemed statistically significant Conversely, if the R squared value falls below 50%, it can be inferred that only a minor portion of the variability in VN-Index can be accounted for by the independent variables included in the model Hence, a higher value of R-squared would indicate greater statistical significance Furthermore, the Significance-F coefficient serves as a criterion for assessing the dependability of the model The statistical significance of the model can only be established if the F coefficient is below the threshold of 0.05
In order to determine the influence of the variables on the dependent variable VN-Index, it is necessary to examine the coefficient of the p-value In the event that a variable exhibits a p-value of less than 5%, it can be inferred that the variable exerts a significant influence on the dependent variable, VN-Index Conversely, if the p-value is equal to or greater than 5%, it can be concluded that the variable does not have any discernible impact When examining variables with a p-value less than 5%, it can be inferred that if said variable possesses a regression coefficient of 𝛃 greater than 0, it will exert a positive influence on the dependent variable Opposite
In the event that the regression coefficients of the variables are 𝛃