Influence of exchange rate fluctuations on vietnam's stock market

INFLUENCE OF EXCHANGE RATE FLUCTUATIONS ON VIETNAM'S STOCK MARKET ABSTRACT The Vietnamese Stock Market is experiencing robust growth and assuming a significant role in shaping and exer

INTRODUCTION

Vietnam is one of the emerging economies, so the Government urgently needs capital and other resources to support its growth goals The stock market, in particular, is an essential component of the capital market and a mechanism through which the government may mobilise financial resources without triggering inflationary pressures However, whether the stock market's positive function is successful or not is heavily dependent on its interaction with other macroeconomic factors such as interest rates, currency rates, inflation, and so on As a result, knowing the connection between stock markets and currency rates is critical for policymakers as well as professional investors, assisting them in applying policies effectively and forecasting the full impact of management and executive decisions In reality, a lot of experts have researched this link using various approaches, mostly in developed economies, and the conclusions are still disputed (Calvo, 2001) For developing nations like Vietnam, such research is still rare, and the hunt for credible data to support governance continues The goal of this article is to use the Ordinary Least Squares technique to analyse the link between exchange rates and stock prices on the Vietnamese stock market To achieve this, the next portion of the article provides an overview of the theoretical background and research challenge, followed by a description of the research methodology, experimental findings from the frequency domain analysis approach, and, lastly, the conclusion.

THEORETICAL BACKGROUND

Since the implementation of the floating rate system in the early 1970s, the volatility of exchange rate swings has greatly grown The connection between global stock markets has become increasingly ambiguous as a consequence According to traditional theory, changes in exchange rates are influenced by international trade The performance of the domestic stock market over several decades has played an important role in influencing investment or cash flows, indicating the significant impact of changes in exchange rates on stock price movements Economic theories have historically assumed that there are many ways in which the stock market and the foreign exchange market can interact with each other, which makes empirical studies of the interdependence between these markets all the more fascinating The theoretical approach in studies usually follows one of two main forms: the "Flow-Oriented" approach (Dornbush and Fisher, 1980) and the "stock-oriented" approach (Branson, 1983)

The "Flow-Oriented" method states that exchange rates and security prices have a positive connection, or positive correlation Because direct quotations cause the exchange rate to rise and the local currency to depreciate, domestic enterprises will find it more competitive to export products internationally at a lower cost Increased exports will boost domestic profits, which will raise firm stock prices since the current price of future earnings represents the company's increased value

According to the "Stock-Oriented" method, the supply and demand of financial assets like stocks and bonds affect the exchange rate By taking into account diverse international portfolios and the function of exchange rate fluctuations in balancing the supply and demand of domestic and foreign financial assets, this method acknowledges the presence of a negative connection between security prices and exchange rates Thus, there are two basic ways in which the appreciation of the local currency will result from a rise in domestic stock price earnings: direct and indirect According to the direct route, rising local stock prices will entice foreign investors to reevaluate their portfolio selections More precisely, in order to have more local currency available for the purchase of more domestic assets, they will collectively acquire more domestic assets and sell international assets, causing the value of the domestic currency to decline The primary tenet of the indirect channel is that wealth will rise in proportion to domestic stock holdings Interest rates will rise as domestic investors' demand increases Consequently, higher interest rates raise the demand from outside buyers for local currency to purchase new domestic assets, which raises the value of the local currency

LITERATURE REVIEW

The theoretical approaches of authors around the world hardly provide convincing evidence to prove a consensus or causal relationship between exchange rates and stock prices However, the ariticle of the relationship between exchange rates and securities in the world has a lot of empirical evidence, which can go deeper into analytical studies through the topics of authors around the world to see data sources, research methods, analytical models and conclusions through research articles

In analyzing the variables of oil prices, exchange rates and stock market indices to explain how they interact with each other in the South Africa, NKazeem Abimbola Sanusi and Forget Mingiri Kapingura (2022) employed a monthly database from January 2003 to July 2019 and used DCC- GARCH, time-varying VAR, and multivariate Markov regime switching models to analyze the relationship between oil prices, nominal exchange rates, the South Africa stock market index, and the consumer price index The results of DCC-GARCH model show that dynamic conditional correlation among the variable was stable with few exceptionalities The empirical results from time-varying VAR demonstrate the presence of stock market and oil price feedbacks Results from the Markov regime switching VAR model demonstrate that market capitalization and exchange rate have a considerable impact on oil price during a boom The analysis concludes that stock market performance offers significant policy assistance in managing the unpredictable swings in oil price Additional empirical evidence of Delgado et al (2018) analyzes the variables of oil price, exchange rate and stock market index to explain how they interact with each other in the Mexican economy The period under consideration covers monthly data from January 1992 to June 2017 Oil prices, the nominal exchange rate, the Mexican stock market index, and the consumer price index are all included into a Vector Autoregressive Model (VAR) The results indicated that the exchange rate has a negative and statistically significant influence on the stock market index, which means that a rise in the stock market index is associated to an increase in the exchange rate The consumer price index is also shown to have a favorable influence on the exchange rate but a negative effect on the stock market index The results also indicate that there is a statistically significant relationship between oil prices and the exchange rate This suggests that when oil prices increase, the exchange rate tends to appreciate Moreover, the impulse-response functions indicate that the observed effects gradually diminish over time

According to empirical findings and economic theory, Gokmenoglu & Fazlollahi (2015) have constructed a regression equation with crude oil spot price, gold price, oil price volatility, and gold price volatility as independent variables, and the stock market price as the dependent variable Their paper's objective is to determine whether the gold price, oil price, gold price volatility, and oil price volatility have a significant impact on the stock market price index Using a series of tests (Unit root test, ADF, and so on…) and the integrated analytical ARDL model to estimate the parameters, the results indicate that the S&P500 stock market price index converges on the long-term at 1.2% of the daily correction rate due to oil and gold prices and their movements While all variables have a long-term impact on the S&P500 stock market price index, gold prices have the greatest both long and short-term impact on stock prices, which has significant implications for investors Investors can react to changes in the price of gold by recognizing that gold is an excellent substitute for securities Because gold is more accessible and investors can mitigate against inflation on their own, gold price changes have the greatest impact on the stock market In the short term, fluctuations in the prices of oil and gold have no effect on the S&P500 stock market Another empirical study by Coronado et al (2018) examines the direction of causality among oil, gold, and stock markets for the world's largest economy in relation to the

US markets By applying non-linear Granger causality test, they discovered that there was a nonlinear causal relationship among the three-market considered (with the causality going in all directions) for the entire sample, for subsamples starting from January 2, 1986 and ending in the last available observation of any year beyond 1992 and for subsamples starting in the first available observation of any year beyond 1987 and ending in February 5, 2015 The finding of a causal relationship between three markets suggests that changes in the S&P 500 index may be tracked by watching changes in the returns of the two commodities markets under consideration (and vice versa), which is useful for policymakers

Studying the impact of exchange rate fluctuations on stock market returns in Colombo, Perera

K (2016) using the daily market value of the Stock Price Index (ASPI of the Colombo Stock Exchange) (CSE and daily exchange rate values of US Dollars, Euros and British Pounds for a period of six years from 5 January 2010 to 31 December 2015 Furthermore, in order to detect the influence of exchange rate volatility on stock market return volatility, the research used the Generalised Autoregressive Conditional Heteroscedasticity (GARCH) estimating model The study's empirical findings show that Euro exchange rate movements have a positive and significant effect on ASPI earnings volatility while exchange rate movements of US Dollar and British Pound

7 are negative and insignificant Overall, the study's findings highlight that exchange rate volatility is another determinant of stock market return volatility, which should be properly considered when making capital market investment decisions

The relationship between the foreign exchange market and the stock market has attracted the attention of many scholars, and various empirical studies show complex and even contradictory results As far as the previous research is concerned, most researchers still use static methods for research and analysis, such as the Granger causality test, cointegration analysis, and the GARCH model For example, the results of Liu and Wan (2012) show that there is a cross-correlation between the Chinese Shanghai Composite Index (SCI) and the exchange rate of the renminbi (RMB) against the USD, but no cointegration relationship exists between them Moreover, there was no causality between the two variables before the financial crisis, while there was unidirectional causality from the foreign exchange market to the stock market after the financial crisis Tsai (2012) conducts a quantile regression analysis of the relationship between the foreign exchange market and stock markets in six Asian countries The results suggest that there is a significantly negative correlation between them, especially when the exchange rate is extremely high or low

Many academics have studied the relationship between the foreign currency market and the stock market, and many empirical investigations have produced complicated, even contradicting conclusions In relation to prior research, most academics used static approaches for study and analysis, such as the Granger causality test, cointegration analysis, and the GARCH model For instance, Liu and Wan (2012) discovered a cross-correlation between the Chinese Shanghai Composite Index (SCI) and the renminbi (RMB) exchange rate versus the USD, although no cointegration connection existed between them Furthermore, before to the financial crisis, there was no causation between the two variables, however after the financial crisis, there was unidirectional causality from the foreign currency market to the stock market Tsai (2012) examines the link between the foreign exchange market and stock markets in six Asian nations using quantile regression The findings indicate a considerably negative link between them, particularly when the exchange rate is exceptionally high or low

Yang (2017) has shown that exchange rate shocks would quickly influence the stock prices of these tiny economies, notably Singapore, Hong Kong, Taiwan, and South Korea, and that the effect converges to a benchmark in the long run The multivariate GARCH model is used by Tule, Dogo, and Uzonwanne (2018) to look at the connection between exchange rate volatility and stock market

8 returns in Nigeria They emphasize that when a breakpoint occurs, there is a bidirectional spillover between the two markets They therefore contend that the inflow of short-term money into the stock markets of developing nations would threaten the long-term balance of the foreign currency market Mahapatra and Bhaduri (2019) investigate the effects of exchange rate volatility on the Indian stock market using a two-factor arbitrage pricing model Their findings suggest that, during the global financial crisis of 2008, exchange rate volatility had a significant influence on the stock market Additionally, their research demonstrates that between 2012 and 2016, currency rate risk was a key factor in determining the results on the Indian stock market Both Sikhosana and Aye (2018) and Mitra (2017) choose South Africa as their study focus, although their findings are somewhat different Mitra discovers that the stock market benefits from the exchange rate's increase The short-term spillover of volatility between the stock market and foreign exchange market is reported by Sikhosana and Aye, who found that the negative rather than the positive effects of foreign currency shock on the stock market are more substantial

Tsai (2012) applies the quantile regression model to monthly stock and forex market data for Singapore, Thailand, Malaysia, the Philippines, South Korea, and Taiwan from January 1992 through December 2009 in order to estimate the relationship between stock price index and exchange rates in Asian countries In this study, augmented Dickey or Fuller tests and Phillipsron Perron tests are used to perform unit root testing The empirical findings of this study demonstrate that there are trends in the data from all six Asian nations that may be seen in the various regression function-derived coefficients The results demonstrate that the link between the two variables in six nations is substantially negatively associated and that they vary considerably whether exchange rates are exceptionally high or low This indicates that an increase (reduction) in the return on the stock price index will result in a drop (increase) in the exchange rate, which will lead to an appreciation (depreciation) of the local currency In a different study conducted in Indonesia, Nasri et al (2016) looked at both the macro and micro levels of the relationship between the exchange rate and the Indonesia Composite Stock Price Index (JCI), taking an example from the agricultural sector In this analysis, the rupee's value versus the US dollar, agriculture sector share prices, and daily closing stock index prices were employed From 1 January 2007 to 30 December 2016, a sample was collected, and the research sample was limited to listed firms during those period The data is subsequently subjected to a number of tests, including the Granger causality test, the VAR/VECM test, the merging test, and the unit root test According to the descriptive study, the market capitalization, the proportion of foreign shares, and the proportion of publicly traded shares

9 that the firm owns are likely to have an impact on the trend difference The findings indicate a two- way link between JCI and the exchange rate, and there are various conclusions about the micro- level relationship between the exchange rate and stock price

Another valued study by Ma & Kao (1990) examines stock price responses to exchange rate changes under the floating interest rate regime The article used monthly stock index of six major industrialized countries and corresponding monthly exchange rate collected from the Exchange Rates and Interest Rates Tape provided by the Federal Reserve The UK, Canada, France, West Germany, Italy, and Japan are selected to have less regulated foreign exchange markets and more mobile capital markets Monthly US exports and imports for each of these countries are obtained from Business Statistics and the sampling period is from January 1973 to December 1983 The study makes some conclusions that if the underlying currency value is fluctuating, the financial impact of exchange rate swings is the transaction risk investors incur High exchange rates are related with positive stock price movements because an investment becomes more appealing when denominated in a strong currency The economic consequences of exchange rate swings, on the other hand, demonstrate that currency appreciation reduces export market competitiveness and has a negative effect on the export market for an export-dominant economy

In contrast, for an importing nation, currency appreciation lowers import costs and has a favorable influence on the stock market Shiu-Sheng Chen (2009) uses monthly data from 1957: M1 to 2009: M5 of the S&P 500 Stock Price Index and the world average crude oil price index from International Financial Statistics compiled by the International Monetary Fund publication, focusing on the US stock market and investigating its stock returns In addition to performing the conventional unit root tests such as the Augmented Dickey-Fuller (ADF) test, the Phillips-Perron (PP) test, and the Elliott-Rothenberg-Stock DF-GLS test, the author also considers Zivot and Andrews' (1992) unit root test, which allows for unforeseen breakdowns since the oil and stock markets may have undergone structural changes Evidence suggests that the greater the price of oil, the more probable it is that the market will convert from bull to bear Higher oil prices, on the other hand, have been shown to lead the market to remain in bear mode for longer, albeit the evidence for this is slightly weaker However, it can be concluded that higher oil prices will push the stock market into bear territory Sajjadur Rahman and Apostolos Serletis (2019) used a high-frequency dataset to identify oil price shocks in a simple Bivariate structural model that fit the author's dataset reasonably well The author uses daily data on two variables: change in oil prices (xt) and stock

10 returns (yt), based on the spot price of crude oil offered by West Texas Intermediate (WTI) and types of returns various returns including aggregate and split returns of the US stock market; aggregate and distribute excess profits of the United States; energy sector profitability based on the Global Industry Classification Standard (GICS); profits of large oil and gas companies; profits globally, Eurozone and some specific countries including emerging and advanced economies By parametric estimates of the VAR Bivariate model, experiments have supported the view that a positive oil price shock has a negative and statistically significant impact on the stock market

DATA AND RESEARCH METHODOLOGY

Research methodology

This research paper references the method through the following 2 research papers:

- The Interactions among Gold, Oil, and Stock Market: Evidence from S&P500-Korhan K Gokmenoglua Negar Fazlollahi (2015)

- Effects of Exchange Rate Volatility on Stock Market Return Volatility: Evidence from an emerging Market- Perera H A P K (2016)

Numerous studies have been conducted to examine the various elements that influence the stock market, including but not limited to the price of gold, crude oil, foreign currency exchange rates, interest rates, volatility in exchange rates, and oil shocks In several economies and areas around the globe, the outcomes often exhibit inconsistency and variation

In this study, the author utilizes econometric knowledge, methodologies, and reasoning derived from research articles by economists worldwide to investigate the impact of exchange rate fluctuations on Vietnam's stock market Furthermore, it is evident that the variables of gold and sadness consistently have significant influence on both the Vietnamese economy and the global economy Oil plays a significant role in industrial production, manufacturing, and international trade, whereas gold serves as a medium of daily exchange, a commodity for buying and selling, and an investment instrument for safeguarding against economic volatility These aspects have been discussed in various research articles Building upon this foundation, the present study incorporates two additional variables, namely oil price and daily gold price, into the equation to examine their influence on the

However, it is worth noting that the Consumer Price Index (CPI) serves as the prevailing metric for assessing price levels and gauging the annual inflation rate within Vietnam's vibrant economy

In recent years, numerous forums and domestic financial publications have extensively examined this topic Consequently, the author suggests incorporating this analysis into the proposed analytical model

Based on this premise, the regression equation is constructed with Vnindex serving as the dependent variable, which is elucidated by four independent variables: USD/VND exchange rate, oil price, gold price, and CPI The Ordinary Least Squares (OLS) approach was used in conjunction

13 with a battery of assessment tests for the purpose of conducting analysis The regression equation in question may be expressed as follows:

VNINDEX t = β 0 + β 1 USD t + β 2 OIL t + β 3 GOLD t + β 4 CPI t +μ t in which:

 VNINDEXt is a dependent variable representing VNIndex, USDt is the independent variable representing the daily USD/VND index, OILt is the independent variable representing the daily price of oil, CPIt is the independent variable representing the consumption index in the above time sample

 VNINDEXt, USDt, OILt, GOLDt, CPIt are calculated using the logarith fuction:

Indicators Formula Convention in Eviews

VNINDEX t Ln (Pt/Pt-1) Ln_VNI

USD t Ln (USDt/USDt-1) Ln_USD

GOLD t Ln (GOLDt/Dollart-1) Ln_GOLD

OIL t Ln (OILt/OILt-1) Ln_OIL

CPI t Ln (CPIt/CPIt-1) Ln_CPI

 β0 is the blocking factor; β1 to β4 is the eigenregation/angular coefficient corresponding to the independent variables and μt is the noise coefficient of the model

Data resources

The data sample was taken over a period of 9 years from 01 January 2014 to 30 December 2022 The study sample includes daily market values such as the Ho Chi Minh Stock Exchange- VNINDEX Stock Price Index; Exchange rate index of USD/VND; World Oil Price Index; World Gold Price Index The data was then tested for stability using the Augmented Dickey-Fuller (ADF) test to avoid false regression construction that may occur due to failure of the original unit when working with non-fixed time series data along with the tests that will be detailed in chapter 4 The data is derived from the following sources:

 VN-index: Website https://vn.investing.com/indices/vn-historical-data

 USD/VND index: Website https://vn.investing.com/currencies/usdvnd-historical-data The US dollar is a strong currency in Vietnam and the economies of small countries, developing countries used to represent the Exchange Rate Index in the Regression Model

 US Dollar Spot WTI Crude Oil Price: Website https://vn.investing.com/currencies/wti- usd

 US Dollar Spot Gold Price: Website https://vn.investing.com/currencies/xau-usd

 Consumer Price Index CPI: website of the General Statistics Office https://www.gso.gov.vn

The Consumer Price Index (CPI) just provides monthly statistical data, which is not consistent with the daily figures of independent variables such as exchange rate, oil price, and gold price The Consumer Price Index (CPI) is a metric expressed as a percentage that serves to indicate the relative fluctuations in prices of consumer products over a certain period The rationale for the observed phenomenon is mostly attributed to the relative nature of the change This can be attributed to the fact that the index in question is derived from a single basket of commodities that aims to reflect the whole of consumer goods Furthermore, it is worth noting that the daily price changes within the given month do not exhibit significant or drastic variations Based on this premise, the author suggests using monthly Consumer Price Index (CPI) data as a proxy for the number of days in a month when doing computations

Research Process

The study was conducted in turn through the following steps:

 Step 1: Collect data-sort data

 Step 2: Formulate, measure, and describe research variables

 Step 3: Build a descriptive statistics table

MODEL ANALYSIS AND DISCUSSION

Descriptive statistics of the variables

The summary statistics of variables in the empirical model are presented in the table below:

Figure 1: Descriptive statistics using Eview

Test the appropriateness of OLS regression model

5.2.1 Testing for Nonstationarity and Stationarity

H0 theory to ensure that the estimated model is reasonable and has practical value

Aggregate results are as follows using ADF test statistics:

Figure 2: Summary of ADF test statistics using Eview

VNINDEX USD OIL GOLD CPI

We see that the coefficient β < 0 => refutes the H0 hypothesis, which means that the data series with variables over time in this research is nonstationary to ensure that the model avoids false regression

5.2.2 Correlation between independent variable and dependent variable

Correlation r(x,y) Є [-1;1] Theoretically, the higher the correlation between the dependent variable and an independent variable, the better it is (high is understood as closer to 2 sides -1 or 1), and vice versa the lower it is when it is closer to 0

Figure 3: Computation of Correlation Analysis using EViews

The correlation coefficients for both constructs are shown in the table provided above This approach involves assessing the presence of multicollinearity within the analysed data and investigating potential associations among the variables The summary of Figure 3 indicates that the correlation between constructs does not meet the 80% threshold Consequently, the absence of multicollinearity is seen

 It could be seen that the significant level (probability) of exchange rate (USD) and GOLD are lower than 10% which means these 2 independent variables are meaningfully correlated with the dependent variable (10% significance level)

Probability VNINDEX USD OIL GOLD CPI

 For OIL and CPI, the probability is higher than 10% means these two independent variables have not determined the degree of correlation with the dependent variable at the 10% significance level

USD -0.131240 Negative correlation (i.e the higher the USD rate, the lower the VNINDEX, and vice versa) OIL 0.032518 Positive correlation (i.e the higher the oil price, the higher the VNIndex and vice versa) GOLD -0.041349 Negative correlation (i.e the higher the gold price, the lower the VNIndex and vice versa) CPI 0.027097 Positive correlation (i.e when CPI increases, the

VNIndex increases and vice versa)

Figure 4: Descriptive statistics using Eview

5.2.3 Test of Model conformity and data dependencies

 P-value of F – statistic is much lower than 10% so it can reject the H0, that means the model is consistent with having R squared is different from 0 and can be used for statistical analysisand can be used for statistical analysis

Dependent Variable: VNINDEX Method: Least Squares Date: 09/06/23 Time: 15:44 Sample: 1/01/2014 12/30/2022 Included observations: 2348 Variable Coefficient Std Error t-Statistic Prob

R-squared 0.020191 Mean dependent var 0.000294Adjusted R-squared 0.018518 S.D dependent var 0.011452S.E of regression 0.011346 Akaike info criterion -6.117810Sum squared resid 0.301608 Schwarz criterion -6.105542Log likelihood 7187.309 Hannan-Quinn criter -6.113342F-statistic 12.07048 Durbin-Watson stat 1.941787Prob(F-statistic) 0.000000

 The USD index has P = 0.000; GOLD has P = 0.0528 which lower than 10%, then these two variables are statistically significant/influence the dependent variable As for OIL with

P = 0.1239 and CPI with P = 0.2656 larger than 10%, these two variables do not have a clear basis to determine the impact on the VNINDEX dependent variable

With a significance level of 5% we have: Prob = 0.2173 > 5% should accept the hypothesis H0 => model without variance change

Thus, the VIF of all coefficients is less than 5%, so the phenomenon of linear multi-additive in the model does not occur

Correlated errors will make regression coefficient tests unreliable The study tested the hypothesis without autocorrelation on the table data, with hypothesis H0: no self-correlation

We see: 1 < 1 941787 < 3 thus accepts the H0 assumption that there is no self-correlation of variables in the regression model.

Heteroskedasticity Test: Breusch-Pagan-Godfrey Null hypothesis: Homoskedasticity

F-statistic 1.442121 Prob F(4,2343) 0.2175 Obs*R-squared 5.766597 Prob Chi-Square(4) 0.2173 Scaled explained SS 19.20665 Prob Chi-Square(4) 0.0007

Variance Inflation Factors Date: 09/06/23 Time: 16:03 Sample: 1/01/2014 12/30/2022 Included observations: 2348

Analysis of empirical results

The dependent variable in this study is denoted as VNINDEX After conducting regression analysis using the Ordinary Least Squares (OLS) method, it was shown that two independent factors, namely USD and GOLD, significantly influence the dependent variable VNINDEX However, the impact of two other variables, OIL and CPI, remains undetermined or very insignificant

VNINDEX = 0.000364 – 1.172982*USD + 0.012992*OIL – 0.0052477*GOLD + 0.054815*CPI

5.3.1 The influence of independent factors on dependent variables

 Under the condition that other factors remain constant, the stock of independent variables without impact VNINDEX will increase every day by 0.000364%

 With independent variables USD and GOLD, we have β1 and β3 are equal – 1.172982 and – 0.0052 repectively This means that under the condition that other factors remain constant, the USD exchange rate and the gold price decrease by 1%, the VNINDEX tends to increase to 117.3% and 0.52% respectively, and vice versa

 With independent variables OIL and CPI, we have β2 and β4 equal 0.0129 and 0.0548 respectively This means that under the condition that other factors remain constant, the oil price and the CPI increase by 1%, the VNINDEX tends to increase to 117.3% and 0.52% respectively, and vice versa

In the preceding analysis, we have evaluated the influence of each individual explanatory variable on the dependent variable, VNINDEX Next, we will proceed to evaluate the influence of the independent factors on the dependent variable, VNINDEX The model provides an indicator, known as the index R2 or the deterministic coefficient, which precisely quantifies the extent of influence exerted by the independent factors on the dependent variable

According to the regression results table, the coefficient of determination (R2) is calculated to be 0.023, which corresponds to 0.23% of the variation in the dependent variable VNI that can be explained by the included explanatory variables (USD, OIL, GOLD, CPI)

The objective of this study is to examine the impact of exchange rate changes on the stock market The research paper has presented findings that indicate a generally favorable relationship between these two variables The negative connection between the exchange rate and VNINDEX has a

21 substantial impact Specifically, a 1% rise in the exchange rate leads to a tendency for VNINDEX to decline by 117%, and conversely

CONCLUSION

Evaluation of empirical results

The research results show that the exchange rate and the stock index are negatively correlated, which is in line with practice, because when the exchange rate increases, it means that the local currency depreciates, leading to the source of money will not participate more in the stock market but tend to go out to compensate for the difference when there is a commercial transaction that has to be paid in foreign countries bad

The fact that the price of gold has a negative correlation with the VNINDEX is also reasonable compared to the theory in practice that gold will be a good shelter when the market has many risks such as inflation, high interest rates, deep stock market declines

Oil prices are positively correlated, which shows that Vietnam also has certain interests in crude oil exports and industrial production and manufacturing in general is being well controlled by the government without fuel scarcity.

Limitation

Limited findings have been derived about the impact of the USD exchange rate on the whole stock market

An examination was conducted on several significant variables pertaining to the stock market, including the United States Dollar (USD), oil price, gold price, and consumer price index (CPI) It is worth noting that numerous other factors also exert influence, such as interest rates, inflation, macroeconomic policies implemented by the government, various sectors within the economy, import and export activities, the rate at which foreign capital is attracted, as well as credit activities undertaken by both commercial and central banks

Another constraint is in the very limited impact of the Exchange Rate and the Essay's Factor Group on VNINDEX, necessitating more extensive and comprehensive investigation to enhance the practical significance of the study.

Expansion and development recommendations for research directions

It is essential to use alternative models for the purpose of analyzing and conducting cross- evaluations on the outcomes derived from the ordinary least squares (OLS) approach of basic statistical analysis

The findings of this study may provide a foundation for future research endeavours that prioritise certain sectors, such as those associated with import and export operations, foreign currency, tourism, and agriculture By doing so, researchers can draw more practical and applicable conclusions

In order to derive more practical and beneficial findings, it is essential to gather comprehensive and extensive datasets including many aspects such as inflation, interest rates, FDI growth index, GDP, and social indicators.

Conclusion

Although this essay has not brought high-value and detailed applications to specific financial activities in the Vietnamese economy, it has partly shown the normative relationship of the USD exchange rate to the Vietnam stock market in particular From the above conclusions, the author wishes to contribute a part as a foundation for scientific research articles of individuals and organizations specialized in the field of Finance to further develop and bring more practical application values to promote, the country's economic development is increasingly strong

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Null Hypothesis: VNINDEX has a unit root

Lag Length: 0 (Automatic - based on SIC, maxlag&) t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -46.18041 0.0001

Null Hypothesis: USD has a unit root

Lag Length: 5 (Automatic - based on SIC, maxlag&) t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -14.53797 0.0000

Null Hypothesis: OIL has a unit root

Lag Length: 0 (Automatic - based on SIC, maxlag&) t-Statistic Prob.*

Augmented Dickey-Fuller test statistic -43.75271 0.0000