Group 14 - STUDY THE IMPACT OF GOLD, OIL, GAS PRICE AND EXCHANGE RATE ON VN-INDEX 2001-2021 PDF

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FOREIGN TRADE UNIVERSITYFACULTY OF INTERNATIONAL ECONOMICS=====000=====ASSIGNMENT REPORTSTUDY THE IMPACT OF GOLD, OIL, GAS PRICE AND EXCHANGE RATEON VN-INDEX 2001- 2021Class: KTEE310. Instructor: Ph. Vu Thi Phuong Mai Group of students: Group 14 Ta Phuong Mai: 2014340207 Nguyen Minh Hanh: 2014340203...

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FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS =====000=====

ASSIGNMENT REPORT STUDY THE IMPACT OF GOLD, OIL, GAS PRICE AND EXCHANGE RATE ON VN-INDEX 2001-2021

Class:

KTEE310.1

Instructor:

Ph.D. Vu Thi Phuong Mai

Group of students:

Group 14

- Ta Phuong Mai:

1234565432345 2014340207

- Nguyen Minh Hanh:

2014340203 2345654343

- Le Mai Anh:

2345654345654 2012340003

- Tran Hoang Minh:

2345654345 2011340205

OCTOBER 2021

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INTRODUCTION ............................................................................................................. 5 CHAPTER 1: RESEARCH OVERVIEW ....................................................................... 6 1.1 Overview of stock market ....................................................................................... 6 1.2 VN-Index .................................................................................................................. 6 1.3 Formula ..................................................................................................................... 8 1.4 Factors affecting the VN-index used in the report ............................................... 8 1.4.1 Gold price ........................................................................................................... 8 1.4.2 Oil price .............................................................................................................. 9 1.4.3 Exchange rate .................................................................................................... 9 1.4.4 Gas price ........................................................................................................... 10 CHAPTER 2: RESEARCH METHOD ......................................................................... 11 2.1 Research method and data .................................................................................... 11 2.1.1 Research method ............................................................................................... 11 2.1.2 Data description ................................................................................................ 11 2.2 Building model........................................................................................................ 12 2.2.1 The population regression function model ........................................................ 12 2.2.2 Sample regression function model .................................................................... 12 2.2.3 Data description of the model ........................................................................... 12 2.2.3.1 Statistics description ................................................................................... 12 2.2.3.2 Matrix correlation between variables: ........................................................ 12 CHAPTER 3: ESTIMATED MODEL AND STATISTICAL INTERFERENCES .. 15 3.1. Initial estimated model ......................................................................................... 15 3.2 Testing and fixing problems of the model ............................................................ 16 3.2.1. Model testing .................................................................................................... 16 3.2.1.1. Test the statistical significance of the regression coefficients ................... 16 3. 2.1.2. Testing the suitability of the model ......................................................... 16 3.2.1.3 Testing Ramsey RESET’s test .................................................................... 18 3.2.1.4 Testing Heteroscedasticity .......................................................................... 19 3.2.1.5 Testing multicollinearity ............................................................................. 21

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3.2.1.6 Testing autocorrelation ............................................................................... 23 3.2.2 Fixing the problems of the model...................................................................... 24 3.3 Hypothesis testing .................................................................................................. 26 3.3.1 Hypothesis testing of regression coefficient ..................................................... 26 3.3.2 Test the statistical significance of the regression coefficients........................... 26 3.3.3 Test the suitable of the model............................................................................ 26

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LIST OF TABLE Table 1. Data description .............................................................................................................. 11 Table 2. Statistics description ....................................................................................................... 13 Table 3. Matrix correlation between variables ............................................................................. 13 Table 4. Results of initial regression parameters .......................................................................... 15 Table 5. Results of the initial estimated coefficients .................................................................... 15 Table 6. Regression model after removing lnoil variable ............................................................. 17 Table 7. Ramsey’s reset test results .............................................................................................. 18 Table 8. Heteroscedasticy result by White test ............................................................................. 19 Table 9. Robust test....................................................................................................................... 20 Table 10. Multicollinearity test results by vif ............................................................................... 20 Table 11. The regression model after removing lnExr ................................................................. 21 Table 12. Breusch-Godfrey Autocorrelation Test ........................................................................ 22 Table 13. Regression with Newey-west standard errors ............................................................... 25

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INTRODUCTION The stock market plays an extremely important role in the economic development of a country. Stocks and stock markets are measures of the strength of the economies of many countries around the world. Indicators or stock prices help to show the health of a country's economy. Vietnam's stock market has developed rapidly in recent years. The Ho Chi Minh City Securities Center (the forerunner of the Ho Chi Minh City Stock Exchange, or HOSE) held its first trading session in July 2000, marking the birth of Vietnam’s securities market. Two decades later, the market has affirmed its role as an effective capital mobilising channel for the economy, contributing significantly to the equitisation of State-owned enterprises (SOEs), together with the bank's credit system to create a more efficient and balanced Vietnamese capital market structure that support the development of an entire economy. The stock market is affected by many factors at once. No single factor can affect the stock market. Instead, many factors come together to form an overall investment environment and impact the stock market. Therefore, to predict the future of the stock market, the impact of macroeconomic factors on the stock market needs to be carefully analyzed. Understanding the relationships between these variables and the stock market index assists investors in making investment decisions and helps policymakers in designing policies in order to maintain market stabilization. For the reasons stated above, as well as a desire to get a better grasp of economic challenges in the stock markets, we investigate the issue of "Factors Affecting VN-index from 2001 to 2021" in order to examine macro factors affecting the VN-Index stock and, as a result, providing suggestions for macroeconomic development and improvement of management policies in Vietnam. 1.

Objectives of the study

The essay aims to understand and clarify the factors affecting the stock market of Vietnam in the period 2001-2021; namely: oil price, gas price, gold price and exchange rate; from there, evaluating the influence of these factors on the VN-Index. To achieve the

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above goal, the research team has read and researched the previous topic and related theories and tested these theories in the field. 2.

Research object and scope

Research object: Factors affecting the VN-Index, specifically: oil price, gas price, gold price and exchange rate Research scope of time: From January 2001 to October 2021 Research scope of space: Vietnam 3.

Limitations and difficulties in conducting research.

During the research process, due to lack of experience and knowledge, the essay has not been able to analyze all aspects of the problem in depth. Moreover, the stock market is also affected by many other factors but adding new variables to the model can cause many defects and make the verification process more difficult and complicated. Therefore, we look forward to receiving your suggestions to improve the essay.

4.

Essay structure

The essay consists of 3 chapters Chapter 1: Research overview Chapter 2: Building model Chapter 3: Statistical evaluation and analysis results.

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CHAPTER 1: RESEARCH OVERVIEW

1.1.

Overview of stock market:

Stock market is a place where shares of public listed companies are traded. The primary market is where companies float shares to the general public in an initial public offering (IPO) to raise capital. A stock exchange facilitates stock brokers to trade company stocks and other securities. A stock may be bought or sold only if it is listed on an exchange. Thus, it is the meeting place of the stock buyers and sellers. A stock market index, also known as a stock index, measures a section of the stock market. In other words, the index measures the change in the share prices of different companies. The stock index is determined by calculating the prices of certain stocks (generally a weighted average). It is a tool widely used by financial institutions and investors to compare the return on specific investments and to describe the market, help track market trends and measure changes. Currently, methods such as the Passcher method, Laspeyres method, Fisher average price index method, simple average digital method, and simple geometric average method are widely used in generating stock price indexes. The VN-Index is an index that has a significant impact on investor psychology. For this research, we will use VN-index to represent the Vietnamese stock market.

1.2.

VN-Index:

The VN-Index is aggregated and calculated based on the daily price movements of all companies listed on the Ho Chi Minh Stock Exchange. Ho Chi Minh City (HOSE). VnIndex is used to analyze and evaluate market volatility and help investors make investment decisions. City Securities Trading Center Ho Chi Minh City Stock Exchange (HOSE) is the first centralized securities trading organization in Vietnam and held the first trading session on July 28, 2000, marking the official birth of the Ho Chi Minh Stock Exchange securities (stock market) in Vietnam. 7

1.3.

Formula: VN-Index = (CMV / BMV) x 100 CMV = ∑pit x qit BMV = ∑pio x qio

Contain : - CMV: The current market capitalization. - BMV: The value of the market capitalization - is adjusted in cases such as new listing, delisting and cases of change in listed capital. - pit: The price of stock i at the time of calculation. - qit: The listed volume of stock i at the time of calculation. - pio: The price of stock i at the base time. - qio: The listed volume of stock i at the base time.

1.4.

Factors affecting the VN-index used in the report

In fact, the VN Index is affected by many factors. However, for knowledge, our ability to gather and find information is limited, so in this report, we just focus on few macroeconomic variables to consider the correlation: oil price, gas price, gold price and exchange rate. 1.4.1.

Gold price

Gold is a precious metal, used in jewelry, medicine, and industry. Gold has high chemical stability with a shiny appearance. Pure gold has high ductility, is easy to be laminated into foil and spun, so it is very suitable for making jewelry, components and electronic circuits.With its preeminent and widely recognized properties, gold has become a special material in the form of a commodity - currency. When playing the role of money, gold has had all the functions of money in general and to this day, there is no currency with 8

such full functions, including the function of means of payment, a measure of value and means of storage. Traditionally, gold has been an indicator of future inflation, acted as a hedge against inflation, an important asset in portfolio allocation and has shown its role in crises, because gold creates a hedge to diversify the increasing risk in the market during the crises. Central banks and international financial institutions retain a large amount of gold for diversification, and economic security. 1.4.2.

Oil price:

Oil is one of the very important input materials of most industries in the economy and has a direct impact on the economy as well as the stock market in countries. Studies in the world have shown that oil price is a factor affecting macro variables and profitability on the stock market through analyzing the impact of oil prices on industries and inflation in the economy (Hamilton, 1983; Burbridge and Harrison, 1984; Gisser and Goodwin, 1986; Ciner 2001; Miller and Ratti, 2009). Vietnam has the second largest oil reserves in East Asia, after China. With export turnover accounting for an increasingly high proportion of crude oil, oil price is increasingly important for the economy as well as the stock market of Vietnam. Oil prices can affect stock market volatility, both directly and indirectly. The direct effect can be explained by the volatility of oil prices creating uncertainty in financial markets, which in turn leads to a decline in the prices of securities. The indirect effect of oil prices is described through a decrease in production output and an increase in the rate of inflation when oil prices rise. This affects the macro variables of the economy and thereby affects the stock market. 1.4.3.

Exchange rate:

An exchange rate is the value of the US dollar against other currencies. The value of the dollar is caused and reflected by interest rates, and interest rates are very much related to stock prices. Therefore, the exchange rate will affect the stock market and can be used to predict the market. Some studies have eased symmetric assumptions and found support for the asymmetric effect of exchange rate changes on stock prices (Bartram, 2004; Hsu et al., 2009; Koutmos & Martin, 2003; Miller & Reuer, 1998; Nguyen & Do, 2020). The 9

exchange rate can have two different effects on stock prices. When the exchange rate rises in a direct manner, the local currency is lost, as well as the stable investment climate that attracts more capital from international investors seeking profit and price discrepancy in the country. The stock market, on the other hand, suffers as a result of the increased exchange rate. When the exchange rate is adjusted, it has an impact on exports, which has an indirect impact on the company's economic growth and manufacturing operations, reducing stock prices.

1.4.4.

Gas price

Gas prices indirectly, rather than directly, affect stock markets. Increases in natural gas prices appear to impact industrial manufacturing growth, which, in turn, influences stock prices. An increase in the price of an imported commodity such as crude oil and gasoline will increase the input costs of the economy, increasing pressure on prices. Price pressure increases, while earnings are not expected to improve, will adversely affect GDP growth momentum.On the other hand, the increase in the import price of crude oil and gasoline of all kinds also contributed to the increase in the trade deficit, thereby putting pressure on the VND/USD exchange rate.

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CHAPTER 2: RESEARCH METHOD

Research method and data:

2.1.

2.1.1. Research method

-

Quantitative research

-

Run the software STATA regression model by least squares estimator to analyze and find the dependency relationship of a variable called the dependent variable on one (or more variables) called independent variables to predict the outcome based on known values of the variable.

2.1.2. Data description:

The data used in the study are secondary data, collected through sources available on the internet. The data type is time series data from January 2001 to October 2021. Information about the variables used in the model is described below: No. Variable

Variable

Data source

Unit

sign 1

VN-

VNI

Index 2

Gold

Oil price

d sign https://www.investing.com/currencies/usd-

Point

vnd-historical-data gold

price 3

Expecte

https://vn.investing.com/commodities/gold-

USD/ounce

+

USD/gallon

+/-

USD/liter

+/-

USD

+

historical-data oil

https://www.investing.com/commodities/crude -oil-historical-data

4

Gas price

gas

https://www.investing.com/commodities/natur al-gas-historical-data

5

Exchange rate

Exr

https://www.investing.com/currencies/usdvnd-historical-data Table 1. Data description 11

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Therein: o Dependent variables: VNIndex. o Independent variables: gold price, gas price, oil price and exchange rate.

2.2.

Building model:

2.2.1 The population regression function model: (PRF): ln(VNI) = 𝛽0+𝛽1.ln(gold) + 𝛽2.ln(oil) + 𝛽3.ln(gas) + 𝛽4.ln(Exr) + 𝑢𝑖 𝛽0: intercept

𝛽1: partial slope of ln(gold) 𝛽2: partial slope of ln(oil)

𝛽3: partial slope of ln(gas)

𝛽4: partial slope of ln(Exr) 𝑢𝑖 : random error

2.2.2 Sample regression function model:  2.ln(oil) + 𝛽 1 .ln(gold) + 𝛽 0 +𝛽 𝑖 (SRF): ln(VNI) = 𝛽 3 .ln(gas) + 𝛽4 .ln(Exr) + 𝑢 0 : estimated 𝛽0 𝛽

1 : estimated 𝛽1 𝛽

2 : estimated 𝛽2 𝛽

3 : estimated 𝛽3 𝛽

4 .: estimated 𝛽4 𝛽

𝑢𝑖 : random error 𝑢𝑖

2.2.3 Data description of the model: 2.2.3.1 Statistics description: Running sum command on Stata software, we got the result:

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Table 2. Statistics description

2.2.3.2 Matrix correlation between variables: Before running the regression model, we consider the degree of correlation between variables using the corr command. We obtained the correlation table between the variables as follows:

Table 3. Matrix correlation between variables Based on the correlation coefficient matrix, we can see: Analyze the correlation between independent variables and the dependent variable: • Regarding the direction of correlation: -

The variables: lngold, lnExr, lnoil have a positive correlation coefficient, showing the same directional impact on the dependent variable. 13

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The variable: lngas has a negative correlation coefficient, indicating the opposite effect on the dependent ...