Factors affecting the world’s gold price an ARDL approach.pdf

UNIVERSITY OF ECONOMICS
HOCHIMINH CITY
VIETNAM
INSTITUTE OF SOCIAL
STUDIES
THE HAGUE
THE NETHERLANDS
VIETNAM – NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
FACTORS AFFECTING THE WORLD’S GOLD PRICE: AN
ARDL APPROACH
BY
VU THUY DUONG
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
HOCHIMINH CITY, OCTOBER 2013

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES
HO CHI MINH CITY THE HAGUE
VIETNAM THE NETHERLANDS
VIETNAM - NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS
FACTORS AFFECTING THE WORLD’S GOLD PRICE: AN
ARDL APPROACH
A thesis submitted in a partial fulfillment of the requirements for the degree
of
MASTER OF ARTS IN DEVELOPMENT ECONOMICS
By
VU THUY DUONG
Academic supervisor:
Dr. CAO HAO THI
HOCHIMINH CITY, OCTOBER 2013

1
Acknowledgement
The thesis could not be completed without considerable supports from my academic
supervisor, Dr. Cao Hao Thi, who provided me valuable instructions and comments
throughout the process of this thesis. From bottom of my heart, I would like to give
my sincerest thanks to him.
I am also grateful to Dr. Le Van Chon and Dr. Truong Dang Thuy for their
enthusiasm help about Econometrics techniques and useful advice. Therefore, I can
overcome many obstacles to complete my research.
I also take this opportunity to express my thanks for my colleagues. They provided
me many assistance and encouragement during the time I do the research.
Last but not the least, I would like to thank my family members for their love,
encouragement, support for me to finish the Master course as well as the thesis.

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Abstract
The paper focuses on investigating factors affecting global gold prices in the short-
run and long-run with daily data from January 2007 to December 2012. By applying
autoregressive distributed lag (ARDL) bound test, the empirical results show that
there is no evidence of long-run relationship among London gold price, West Texas
Intermediate (WTI) crude oil sport price, US dollar index and S&P 500. However,
when financial crisis is taken into the research as a dummy variable, the results
reveal that financial crisis affects the relationship of gold price with oil price, US
dollar index and S&P 500 and cannot conclude that long-run relationship among
them existed. Therefore, the State Bank of Viet Nam cannot base on the movement
of those variables to forecast the movement of world gold price for making their
decision in selling or buying gold.

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Table of Contents
CHAPTER 1: INTRODUCTION ...............................................................................6
1.1. Problem Statements..........................................................................................6
1.2. Research objectives ..........................................................................................8
1.3. Research questions ...........................................................................................9
1.4. Scope of the research........................................................................................9
1.5. Structure of the thesis .......................................................................................9
CHAPTER 2: OVERVIEW OF VIETNAM’S GOLD MARKET...........................11
2.1. The national gold brand of Vietnam...............................................................11
2.2. The connection of Vietnam’s gold price to global gold price........................11
2.2.1 Domestic gold’s Cost price.......................................................................11
2.2.2 Domestic gold’s market price...................................................................12
2.2.3 The connection between domestic and global gold markets ....................12
2.2.4 The big gap still exists between the two gold markets.............................13
CHAPTER 3: LITERATURE REVIEW ..................................................................15
3.1. The relationship between gold and oil prices.................................................15
3.2. The relationship between gold price and US Dollar exchange rate ...............16
3.3. The relationship between gold price and stock market ..................................17
CHAPTER 4: RESEARCH METHODOLOGY ......................................................21
4.1. Research process ............................................................................................21
4.2. Model establishment.......................................................................................21
4.3. Data collection................................................................................................21
4.4. Data analysis...................................................................................................24
4.5. Analysis method .............................................................................................25
4.5.1. Stationary and unit root test.....................................................................25
4.5.2. Cointegration test.....................................................................................26
CHAPTER 5: RESEARCH RESULTS ....................................................................31
5.1. Descriptive statistics.......................................................................................31
5.2. Correlation matrix ..........................................................................................32
5.3. Stationary and unit root test............................................................................33
5.4. Cointegration analysis ....................................................................................34
5.4.1. Optimal lag length ...................................................................................34
5.4.2. Serial correlation test ...............................................................................35
5.4.3. Dynamic stability test ..............................................................................35

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5.4.4. Bound tests...............................................................................................36
CHAPTER 6: CONCLUSION AND POLICY IMPLICATIONS ...........................38
6.1. Main findings .....................................................................................................38
6.2. Policy implications.........................................................................................39
6.3. Limitation .......................................................................................................40
6.4. Future research ...............................................................................................40
References.................................................................................................................41
Appendix A: Lag structure choosing .......................................................................46
Appendix B: Bound test result .................................................................................50
List of Figures
Figure 4.1: Research process.....................................................................................22
Figure 4.2: Analysis method .....................................................................................25
Figure 5.1: Inverse Roots ..........................................................................................36
List of Tables
Table 2.1: Correlation matrix between SJC and London’s gold price......................13
Table 2.2: Correlation testing between SJC and London’s gold price .....................13
Table 3.1: Summary of empirical studies in Literature review ...............................18
Table 4.1: Asymptotic critical value bounds for the F-statistics ..............................29
Table 5.1: Descriptive statistics of all series.............................................................31
Table 5.2: Correlation matrix....................................................................................32
Table 5.3: Unit root test for stationary at level .........................................................33
Table 5.4: Unit root test for stationary at first difference .........................................33
Table 5.5: VAR lag order selection criteria ..............................................................34
Table 5.6: Serial correlation test’s result ..................................................................35
Table 5.7: Bounds test procedure results without crisis interaction .........................36
Table 5.8: Bounds test procedure results with crisis interaction ..............................36

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Abbreviations
ADF: Augmented Dickey-Fuller
AIC: Akaike Information Criterion
ARDL: Autoregressive Distributed Lag
CPI: Consumer Price Index
ECM: Error correction models
EIA: U.S. Energy Information Administration
PP: Phillips-Perron
SBV: State Bank of Viet Nam
SJC Saigon Jewelry Company Limited
UECM: Unrestricted error correction model
US: United States
VAR: Vector Autoregression Estimates
VND: Vietnam Dong

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CHAPTER 1: INTRODUCTION
1.1. Problem Statements
There is much attention recently on gold, partly due to the surges in its price and the
increase in its economic uses.
Gold has a critical position among the major precious metals. Gold is not only an
industrial commodity but also an investment asset which is commonly known as a
“safe haven” (Baur & Lucey, 2010; Coudert & Raymond-Feingold, 2011) to avoid
the increasing risk in the financial markets. However, gold prices have been
remained unabated, even accelerated further in recent years. Since the beginning of
financial crisis in August, 2007 to December, 2012, the nominal gold price has
increased 146.65%
For central banks, gold keeps an important position in their reserve asset. Its role is
increasingly enhanced from 2009 when there was so much worry about the health of
US economy. Central banks increase to buy gold due to they want to reduce their
reliance on the US dollars as a reserve asset, and to encourage borrowings and to
ensure interest rates on these loans were reduced. Bellowing is some evidence
recently relating to the trend of buying gold from central banks:
i. “Asked what the most important reserve asset would be in 25 years, about half
of officials polled by UBS said the US dollar but 22 percent pointed to gold”
(Farchy & Blas, 2010). This is showed that the central banks’ demand for gold
will remain strong over time.
ii. And the report of the World Gold Council published on August 14, 2012,
mentioned that: “The second quarter was another period of significant
purchasing by official sector institutions, with demand accounting to 157.5
tonnes. This was a record quarter for central bank buying since the sector
began recording net purchases in Q2 2009 and was more than double the 66.2
tonnes of purchases made in the same period of 2011. Purchases in the first
half of the year totaled 254.2 tonnes, 25% up on 203.2 tonnes from the same

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period last year. The official sector accounted for 16% of overall Q2 gold
demand”(“Gold Demand Trends Q2 2012”,2012). It is clearly showed that the
role of gold for central banks is even expanding.
In addition, there are some notable policies in relation to gold that central banks and
nations are applying to ensure that gold accumulated either in their citizens’ hands
or in central bank hands (Phillips, 2012):
i. China putted a ban on exporting gold to ensure that all gold that enters the
country stays in the country;
ii. If the country can produce gold, its central bank will be the directly purchaser.
For example: Russia & Kazakhstan bought its locally produced gold in March,
2012;
iii. There is the fact that the trend of buying gold mostly comes from central
banks of emerging and newly wealthy nations. Their gold holdings are very
small in comparison to central banks of US and Europe.
In Viet Nam, the domestic gold prices got so much fluctuation since September
2009. Especially in 2012, the gap between global and domestic prices had been
largely widen, sometimes reaching VND 5 million per tael (a tael is equal to 1.2
ounces) when the demand for gold is larger than the supply for gold due to the “big
guy banks”. This has caused serious problems to the exchange rate as well as
economy. Khanh (2010), the General Director of Sai Gon Gold and Silver ACB-
SJC Joint Stock Company, argued that the increasing in gold price will have both
direct and indirect impact to the USD/VND exchange rate, indirect impact to the
CPI, affect monetary policy, stock market and real estate market, etc.
To solve the problem of gap or to stabilize the gold market that is also the
requirement of the National Assembly of the Socialist Republic of Vietnam from
Resolution No. 51/2010/QH12 on the 2011 Socio-Economic Development Plan,
there are some notable legal documents issued by the Government and The State
Bank of Vietnam (SBV) from 2010 such as: (i) Circular No. 01/2010/TT-NHNN

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dated 06/01/2010 about closing the gold trading floor and terminating all activities
of gold trading on foreign account; (ii) Circular No. 22/2010/TT-NHNN dated
29/10/2010 about not allowing the commercial bank to convert gold into paper
currency and lend for gold trading activities; (iii) Decree No. 24/2012/ND-CP dated
03/04/2012 about using gold bars as a tool of payment will be illegal and the State
will keep a monopoly on gold bar production, export and import of raw materials
for gold bar production via the SBV; (iv) Circular No. 16/2012/TT-NHNN dated
25/05/2012 guiding some articles of Decree No. 24/2012/ND-CP. Yet, those
documents have limited the gold supply to the market while the gold demand is still
large that make gold prices still “crazy” when global gold price increases. In
addition, according to the Decision No. 16/2013/QD-TTg issued by the Prime
Minister on 04/03/2013, gold bullion would be bought and sold by the SBV as
needed to keep the gold prices stable and SBV, based on its monetary policies,
would buy additional gold bullion from other countries for the aim of controlling
foreign reserves. This decision is highly appreciated due to it will be an opportunity
for the SBV to fully perform the role of “conductor” to stabilize gold prices. So, it is
necessary that SBV should choose appropriate time to buy gold from abroad in
order to increase reserve asset or to boost the supply side. In other words, SBV
should find out tools to forecast the movement of global and local gold prices when
other factors changed.
From the above features, the paper will focus on analyzing factors (that are
addressed in the literature) affecting global gold prices.
1.2. Research objectives
The main objectives of this paper include:
i. To investigate the relationship between local and global gold prices;
ii. To identify variables that affects global price of gold in the short-run and long-
run periods;

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iii. To find out whether the SBV can base on the movements of global gold price
while making their decision.
1.3. Research questions
To obtain the mentioned objectives, the paper will try to answer the following
questions:
i. Do Vietnam’s gold prices and global gold prices correlated?
ii. What are the factors affecting global gold prices?
iii. What is the recommendation to the SBV?
1.4. Scope of the research
The research focuses on finding main factors affecting to global gold prices.
Primarily, the paper will give an overview of Vietnam’s gold market and the
connection between it with global gold market. Secondly, following the literature,
the paper will explore variables affecting to global gold prices and their directional
relationships. Thirdly, a model of global gold price will be estimated in which
global financial crisis is included as a dummy variable.
Data used for the research are secondly time series for the daily period from 2007 to
2012 due to daily data for Vietnam gold prices are not adequate.
1.5. Structure of the thesis
The paper is organized as followings:
The chapter 1 explains reason why the topic of thesis is chosen, gives main
objectives, major research questions and the scope of the research.
Chapter 2 provides some overview of Vietnam’s gold market, the connection
between Vietnam and global gold markets.
Chapter 3 covers the literature about the relationship between gold price and oil
prices, US dollar exchange rate, and stock market.
Chapter 4 presents the research methodology, data collection.

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Chapter 5 shows statistic results from adopted model. Findings are analyzed to get
answers for questions mentioned in the chapter 1.
Chapter 6 concludes with the main findings and gives some suggestions.

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CHAPTER 2: OVERVIEW OF VIETNAM’S GOLD MARKET
This chapter is divided into two sections. The first section mentions about the
national gold brand of Vietnam. The second section presents connection of
Vietnam’s gold price to global gold price.
2.1. The national gold brand of Vietnam
From November 25, 2011, Saigon Jewelry Company Limited (SJC)’s gold brand
became Vietnam’s gold brand and under SBV’s control. This is reasonable decision
due to:
i. SJC accounted for 90% of market share in the domestic gold bullion market;
ii. SJC brand is well known in Vietnam as well as in Asia-Pacific region;
iii. SJC is a 100% stated-owned Company and directly managed by Hochiminh
City Party Committee.
Moreover, the decision also received consensus from many analysis. Some
advantage of the decision is that: firstly, when the domestic gold prices fluctuate too
much, it can be easily intervened by the SBV; secondly, this will terminate the
mechanism of “ask and grant”; thirdly, the quality of bullions gold can be
controlled.
2.2. The connection of Vietnam’s gold price to global gold price.
2.2.1 Domestic gold’s Cost price
Cost price represents all expenses to have a unit of gold. This value is used as the
main factor in profit and loss calculation.
In Vietnam, gold is mainly imported from abroad due to mining production is not
significant. Therefore, the price of SJC in Vietnam is predominantly affected by
world gold price and calculated as following:
PVN = [(PTG + CVC + I) x (1 + TNK): 0.82945] x E + CGC

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In which:
- PVN is the Vietnam’s gold price (VND per tael);
- PTG is the world gold price (USD per troy ounce);
- I is insurance premium (VND);
- TNK is imported tax (%);
- E is USD/VND exchange rate;
- CGC is processing cost (VND per tael);
- One troy ounce = 0.82945 Tael.
2.2.2 Domestic gold’s market price
Market price is the economic price for which a good is offered in the market place
(Wikipedia, 2013). In addition, it is also the intersection of supply and demand.
For most all kind of goods, the market price is often higher or equals their cost price
to avoid losses. Nevertheless, domestic gold’s market prices sometimes are not in
the same way because they are affected not only by world gold price but also the
demand, purchasing power, etc.
2.2.3 The connection between domestic and global gold markets
In general, Vietnam’s gold price tends to move along with the world gold market
(Cong, 2012; Hoang, 2004).
Hoang (2004) checked the connection between Viet Nam and London markets for
daily sub-sample from January, 2004 to May, 2004 by using correlation coefficient.
He found that the positive correlation existed.
The paper has continued to further test the connection for the daily period from
January, 2007 to December 2013 between SJC price (called as SJC) and London’s
gold price (called as Gold). In which, SJC data is collected from Saigon Giai Phong
newspaper; London’s gold prices obtained from the World Gold Council (details
will be mentioned in the Chapter 4). The result is presented in Table 2.1.

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Table 2.1: Correlation matrix between SJC and London’s gold price
SJC GOLD
SJC 1.000000 0.994249
GOLD 0.994249 1.000000
The result in the Table 1 showed that: r(SJC, GOLD) equals 0.99. It means that the
two market have had a strongly positively correlation.
In addition, the paper also takes the following hypothesis testing:
- Null hypothesis H0: ρ = 0 (there is no actual correlation);
- Alternative hypothesis H1: ρ ≠ 0 (there is an actual correlation).
And its result is included in Table 2.2.
Table 2.2: Correlation testing between SJC and London’s gold price
Covariance Analysis: Ordinary
Correlation
Probability SJC GOLD
SJC 1.000000
-----
GOLD 0.994249 1.000000
0.0000 -----
P-value is equal 0.0000, the null hypothesis is rejected. In other words, there is an
evidence that a true relationship between domestic and global gold markets.
The above results confirmed the conclusion of Hoang (2004).
2.2.4 The big gap still exists between the two gold markets
The gap between domestic and global gold markets had been largely widen,
sometimes reaching VND 5 million per tael (a tael is equal to 1.2 ounces),
especially in the year 2012. For understanding why the gap still exists, the Bank
Governor Nguyen Van Binh has divided Vietnam’s gold market into three phases:
2007-2009, 2009-2012, 2012-2013 (An et al., 2013).
2007-2009 stage: Regulations concerning gold management were incomplete, so
the gold floors were built spontaneously and rapidly widen. During this time,
officially imported gold was about 40-50 tons while gold smuggling was about 50-

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60 tons per year. The difference between the two markets was very low, but the
domestic gold market under instability, gold fevers occurred frequently, people
rushed to buy or sell gold, speculative activities seriously affected foreign exchange
markets, price indices and macroeconomic stability. Therefore, the government had
banned and officially terminated the operation of gold floors, gold trading activities
in foreign accounts.
2009-2012 stage: the difference between the two markets remained low, but higher
than the above stage. The domestic market was still under instability that causing
negative impact to exchange rates, macro-economy, etc. but at the lower level.
2012-2013 stage: New legal framework has been developed and come into effected.
The State has got a monopoly on gold import and gold bar production. Gold
smuggling is also controlled tightened. The features of this period are: the gap
between two market are much higher than the two periods, but the domestic market
is more stable, speculation pushed back, no scenes of people of people rushing to
buy gold, “goldenization” in the national economy is restrained, stable macro-
economy, etc.
In conclusion, the domestic gold price correlated with the international gold price
in the researching period. The difference between two markets still exists due to
domestic gold demand and supply as well as State’ policies in each periods.

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CHAPTER 3: LITERATURE REVIEW
The aim of this chapter is to give an overview of literature about the research
problem in a logical manner to make the thesis going into the right direction. Three
sections included in the Chapter. The first section gives literatures about the
relationship between gold and oil prices. The second section includes literatures on
the relationship between gold price and US Dollar exchange rate. The third section
will present studies on the relationship between gold price and stock market. The
method adopted to use in this thesis will be mentioned in the conclusion of the
Chapter.
3.1. The relationship between gold and oil prices
There are considerable studies on the relationship between gold and oil prices.
However, results on the relationship are still mixed.
Some studies explained the relationship through two following channels:
i. Firstly, oil price affects gold price through the inflation-channel (Narayan et
al., 2010; Malliaris et al., 2011). When oil prices increase, the general price
level will rise (Cunado et al., 2003, 2005). It follows that when the general
price level (or inflation) rises, the price of gold will go up because gold is also
a kind of goods. This leads to the possibility that gold could be used to hedge
against inflation (Jaffe, 1989); hedge against the dollar (Capie et al., 2005).
ii. Secondly, oil price affects gold price through the export revenue channel
(Melvin & Sultan, 1990). With the assumption that gold accounts for a
significant share in asset of the international reserve portfolio of several
countries, including the oil producing countries. The rise in oil prices (and
hence oil revenues) may have implications for the rise of gold prices. This can
be explained that the increase of revenues from oil enhances the demand for
gold and therefore, the price of gold will be increased
Empirically, Narayan et al. (2010), via inflation channel, proved that the
relationship between gold and oil prices exists in both short-run and long-run. For

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the short-run, they used an ordinary least squares approach to test the relationship
between gold and oil prices via inflation over the period 1963-2008 for the United
States and found that an increase in oil prices led to inflation, an increase in
inflation led to a rise in the gold price, and a rise in oil price led to a rise in the gold
price. For the long-run, they applied a structural break cointegration test proposed
by Gregory and Hansen (1996) which has more advantage than the traditional
cointegration test proposed by Engle and Granger (1987) because it allows for a
regime shift. The data they used is for the period 1995 to 2009. They found that
gold and oil spot and future markets up to the maturity of 10 months were
cointegrated; oil prices can be used to predict gold prices and vice versa.
However, Harmmoudeh et al. (2008) and Sari et al. (2010), by their empirical
studies, do not have the same results as Narayan et al. (2010). They found that oil
price does not force gold price in the long-run and vice versa. When prices of gold
fluctuates due to affected by factors related to the jewelry industry, and subject to
intervention by central banks as part of their foreign reserve policies to influence
exchange rates, it seems not to have anything related to oil price.
In addition, Malliaris et al. (2011) did not found any evidence of cointegration
between gold and oil prices when taking Johansen test as well as Granger causality
test for the period from January 4, 2000 to December 31, 2007. But, gold price can
be used to predict oil price in the short-run very well and vice versa when they took
neural network methodology.
3.2. The relationship between gold price and US Dollar exchange rate
The price of gold and the value of the US dollar have been argued that they tend to
move in opposite directions. In particular, when gold went up, the dollar went
down, and vice versa. The reason is that a weaker dollar can make worries about
inflation. That will encourage investors to turn to gold to hedge against inflation;
and when the dollar strengthens, gold price will usually fall.
Relating to the relationship, Hammoudeh et al. (2008) found that an increase in the
price of gold has implication for a depreciation of the US dollar versus the major

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currencies in both short-run and long-run, not vice versa. In contrast, Kim and Dilt
(2011) found that the value of dollar and the gold price has negative relationship.
But value of dollar has Granger-causality to gold price, not vice versa.
3.3. The relationship between gold price and stock market
It is also logically to expect that the inverse relationship exists between gold price
and stock price. When stock price rises, investors will get more money from stock
market and then they will want to sell their gold to invest more in the stock market.
This will cause the price of gold decreased.
Smith (2001) examined the short-term and long-term relationships between four
gold price series and six different US stock price indices over the 1991-2001 period.
He found that there is a negative Granger causality from US stock index returns to
gold returns in short-run, not vice versa. However, Gilmore et al. (2009) did not
have the same result. They only found that the unidirectional causal effect exists
only in short-run. In addition, Wang et al. (2010), by applying Granger causality
analysis, found that gold prices and Taiwan’s stock prices are independent. It means
that they cannot affect each other. And Bhunia & Das (2012) also have other view.
By applying Granger causality analysis, they found that stock market can be used to
predict gold prices in India and vice versa.
In summary, a general judgment is that researches’ results are still mixed. That is,
while some papers found causality existing between variables, others figure out no
causality and/or bi-directional causality between variables. The differences among
them may be lie on the sample periods, research methodologies, and variables used.
Therefore, the paper will continue to test against the relationship of gold price with
oil price, stock market and US dollar exchange rates with the updated data set. The
autoregressive distributed lag bound test (ARDL) and unrestricted error correction
models will be used in this study as: (i) they are applied successfully by
Hammoudeh et al. (2008), Sari et al. (2010); (ii) ARDL has many advantages than
Engle and Granger (1987) or Johasen (1988) and Johasen and Juselius (1990) that
will be mentioned in Chapter 4.

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The summary of empirical researches listed in Table 3.1.
Table 3.1: Summary of empirical studies in Literature review
Author
(year)
Methodology Key variables Period Main Results
Narayan et
al. (2010)
Gregory and
Hansen (1996)
Spot and future
prices of gold
and oil
1995 - 2009 Gold ↔ Oil in
long-run
Harmmoude
h et al.
(2008)
ARDL bound test,
unrestricted error
correction models,
diagostic tests
Spot prices of
oil, gold,
silver, copper;
interest rate;
US dollar
index; some
dummy
variables
1990 - 2006 Gold → Oil in
short-run;
Gold, Oil → US
dollar index in
long-run
Sari et al.
(2010)
ARDL bound test,
unrestricted error
correction models;
the generalized
forecast error
variance
decompostions,
the generalized
impulse response
functions
Spot prices of
oil, gold,
silver,
Palladium,
Platinum,
USD/EUR
exchange rate
1999 - 2007 Oil → Gold in
short-run;
Gold →
exchange rate
Malliaris et
al. (2011)
Johansen test for
long-run
relationship;
Spot prices of
gold, oil, euro
2000 - 2007 Gold ↔ Oil in
short-run

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Pairwise Granger
causality; VAR
Granger
Causalitys; Neural
network
methodology
Kim and
Dilt (2011)
Granger causality;
Vector
autoregression
(VAR); Impulse
response functions
and variance
decomposition
Prices of gold,
oil, value of
dollar
1970 - 2008 Value of dollar
→ gold price,
oil price
Smith
(2001)
Granger causality;
error correction
model
Four gold price
series and six
different US
stock price
indices
1991 - 2001 US stock index
returns → gold
returns in short-
run
Gilmore et
al. (2009)
Johansen and
Julius (1990);
Vector error
correction (VEC)
model; variance
decomposition
and impulse
response functions
Gold prices,
stock price
indices of gold
mining
companies,
broad stock
market indices
1996 - 2007 Stock prices →
gold prices in
short-run
Wang et al.
(2010)
Johansen test,
vector error
Oil price; gold
price; exchange
2006 - 2009 Oil price ↔
stock prices in

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correction model,
granger causality
rates of US
dollar; stock
price indices of
United States,
Germany,
Japan, Taiwan,
Chian
Taiwan;
Gold prices ↔
oil price;
Oil price →
exchange rate;
Gold price →
exchange rate;
Exchange rate
→ stock prices
in Taiwan
Bhunia &
Das (2012)
Johansen test,
vector error
correction model,
Granger causality
test
Gold price,
stock returns in
India
2001 – 2011 Gold price
↔Stock returns
Note: ↔ means that bi-directional causality exists between two variables; → means
that uni-directional causality exists between two variables.

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CHAPTER 4: RESEARCH METHODOLOGY
The chapter is constituted by five sections. The first section is research process that
gives steps to conduct this research. The second section is the model establishment.
The third one will mention about data collection as well as the sample size. The
fourth one is steps carried out in data analysis. The final section is analysis method
that will give details about unit root test and cointegration test chosen.
4.1. Research process
This study will be conducted through steps described in the Figure 4.1.
4.2. Model establishment
After reviewing empirical studies, the unrestricted error correction model that
successfully applied by Hammoudeh et al. (2008), Sari et al. (2010) is applied in the
paper. Since the directions of the relationship among gold price with other variables
in the long-run are uncertain, the paper will construct the unrestricted regressions in
which each of them is dependent variable.
4.3. Data collection
The data set utilized for the paper is secondary data. It consists of daily time series
over January 2007 to December 2012 (1,498 observations for each series).
Following the previous researches, oil price, US Dollar Index, S&P 500 Index are
considered as the independent variables affecting to gold price. Global financial
crisis (called as Crisis) occurred from August 2007 up to the end of 2008
(Wikipedia, 2013) will be used as a dummy variable.

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Figure 4.1: Research process
Policy implication
- Role of gold in economy, in reserve asset
of Central Banks;
- Recent policies relating to gold of some
Central Banks and of the State Bank of Viet
Nam;
- Target of Vietnam’s government in
stabilizing the gold market.
Problem statement
Literature review
- Studies on the relationship between gold
and oil prices;
price and US dollar exchange rate;
price and stock market;
- Method and model will be chosen in
Thesis.
Overview of Viet
Nam’s gold market
- Vietnam’s national gold brand – SJC;
- Connection between Vietnam’s gold price
and International gold price.
Model establishment
- Unrestricted error correction model
(UECM).
Data collection
- Data of oil price, gold price, US dollar
index, S&P500 index; global financial crisis
occurred in 2007 and 2008 as dummy
variable
- Sources: EIA, World Gold Council,
Federal Reserves.
Data analysis
- Descriptive analysis, Correlation matrix;
- Cointegration analysis: ARDL.
Research result
- Conclusion about the relationships of gold
with other variables; the impact of global
financial crisis

23
The sources that data obtained are as following:
i. Crude oil price, quoted in US dollars/barrel, denoted as OIL. The paper
chooses West Texas Intermediate (WTI) crude oil spot price as a representative
of world oil price obtained from the US’s Energy Information Administration
under the website: http://www.eia.gov. WTI crude oil price is chosen due to:
(1) its quality and prices are often higher than quality and prices of OPEC or
Brent crude oil (Wikipedia, 2012); (2) the international price are observed here
because United States is the world’s largest consumer of oil while WTI crude
oil is the main source of oil for them;
ii. Gold price, quoted in US dollars/ troy ounces, denoted as GOLD. It is the
daily average of the London afternoon (pm) fix obtained from the World Gold
Council under the website: http://www.gold.org. These prices are chosen as
representative due to London has been the global center for gold refining and
exchange since early 19th century; today, the London gold market is still the
largest and the most important gold-trading center in the world.
iii. US dollar index, denoted as USDX. It is a measure of the value of the US
dollar in comparison to seven other major currencies including Euro, Japanese
yen, Canadian dollar, Swiss franc, British Pound, Swedish krona and
Australian dollar. USDX can be obtained from the United States’ Federal
Reserve under the website: http://www.federalreserve.gov.
iv. S&P 500 index, quoted in points, denoted as SPX. It is a stock market index
based on 500 leading publicly traded American companies’ stock prices. It is
considered as the best indicator of the US economy or “a bellwether for the US
economy” (Wikipedia, 2012). The historical data can be obtained from Federal
Reserve Bank of St. Louis under the website: http://research.stlouisfed.org.
It is noted that all variables (dummy variable excluded) are modeled in natural
logarithms and takes the first difference. This provides stationary time-series data
and allows for meaningful independent variables (Sari et al., 2010; Le et al., 2011).

24
4.4. Data analysis
Firstly, the paper will carry out the descriptive statistics of all series in level, in log
and first different of log level to understand what variable has the highest volatility
and average return as well as their distribution forms.
Secondly, correlation matrix will be built and analyzed to know the correlation
relationship among variables.
Thirdly, Augmented Dickey-Fuller (ADF) test and Philips-Perron (PP) test will be
used for stationary and unit root test.
Finally, the cointegration test will be taken – autoregressive distributed lag (ARDL)
bound test. To test the equilibrium relationship as well as the causual linkage among
variables, many empirical studies used the co-integration tests, such as Engle and
Granger (1987) or Johasen (1988) and Johasen and Juselius (1990). Those methods
required that all variables to be integrated in the same order of one, that is I(1). So, a
pre-testing step for unit roots should be involved to determine the order of
integration of variables in models. However, in practice, variables are not same
order of integration. Some variables are stationary at level I(0), while others are
stationary at level I(1) or I(2), etc. This problem may make the estimating results to
be spurious. Therefore, to overcome the above problems, the research will use
ARDL bound test approach suggested by Pesaran and Shin (1999) and Pesaran et al.
(2001). This test is based on unrestricted error correction model (UECM). And it is
said that ARDL is more advantage than previous mentioned methods: (1) it allows
variables to have different orders of integration. In particular, it allows some
variables to be integrated of order 1 and some of order 0 or mutually cointegrated
and it does not require a pre-testing for unit roots; (2) it is more powerful even with
a small sample size; (3) It helps to examine the short-run and long-run relationships;
helps to determine the causality effects; (4) dummy variables can be included in the
test process (Frimpong & Oteng-Abayie, 2006; Hoque & Yusop, 2009).

25
4.5. Analysis method
The flow chart of statistical analysis method showed in the Figure 4.2.
Figure 4.2: Analysis method
4.5.1. Stationary and unit root test
Although ARDL bound test approach does not require taking unit root tests, it is
critical to conduct those tests to ensure that all variables are either I(0) or I(1). This
study will employ the conventional unit root tests widely known as ADF and PP
unit root tests. Generally, a variable is said to be stationary after differencing d
times. The variable is integrated of order greater than or equal to 1 is non-stationary.
However, most economic variables are cointegrated of order 1(Asteriou & Hall,
2007).
ADF test based on the choosing of following three regression forms in testing for
the existence of a unit root of time series Yt:
The difference between the three forms is the deterministic elements α0 and α1T. In
order to choosing the best equation, it is suggested that we can first plot the data of
Stationary test - Augmented Dickey-Fuller (ADF) test;
- Phillips-Perron (PP) test.
Cointegration test
- ARDL bound test;
- Unrestricted error correction models
(UECM).

26
each variable and observe the graph due to it can indicate the existence or not of the
deterministic trend regressors (Binh, 2011).
The hypothesis is:
H0: δ = 0 (Unit root),
H1: δ ≠ 0
Decision rule: If t statistic (t*) is greater than ADF’ critical values (in absolute
terms), the null hypothesis (Ho) cannot be rejected. It means that unit root exists; If t
statistic (t*) is smaller than ADF’ critical values (in absolute terms), the null
hypothesis (Ho) can be rejected. It means that unit root does not exist.
However, if problem of serial correlation occurs, Phillip-Perron (PP) test conducted
in a similar manner of ADF test will be used alternative.
4.5.2. Cointegration test
After the order of integration of each variable is established, the paper will
investigate whether the variables under consideration is cointegrated. Cointegration
implies that causality and long-run equilibrium relationship exists among variables,
but the direction of the causal relationship does not indicated.
For testing the existence of cointegration, the paper uses ARDL bound test. This
test is computed based on an estimated of unrestricted error correction models
(UECM) by Ordinary Least Squares (OLS) estimators (Pesaran et al., 2001).
Basically, the bound test developed by Pesaran et al. (2001) is the Wald test (F-
statistics version of the bound testing approaches) for the lagged levels variables in
the right-hand side of UECM.
By taking each of the variables in turn as a dependent variable, the research will
estimate UECM models as followings:
Tải bản FULL (59 trang): https://bit.ly/3wC8e7O
Dự phòng: fb.com/TaiHo123doc.net

27
Group 1 without crisis interaction:
(1) ∆lnGOLDt = ∝0+ ∑ ∝1i
p
i=1 ∆lnGOLDt−i + ∑ ∝2i
p
i=1 ∆lnOILt−i +
∑ ∝3i
p
i=1 ∆lnUSDXt−i + ∑ ∝4i
p
i=1 ∆lnSPXt−i + ∝5 lnGOLDt−1 + ∝6 lnOILt−1 +
∝7 lnUSDXt−1 + ∝8 lnSPXt−1 + ε1t
(2) ∆lnOILt = β0 + ∑ β1i
k
i=1 ∆lnGOLDt−i + ∑ β2i
k
i=1 ∆lnOILt−i +
∑ β3i
k
i=1 ∆lnUSDXt−i + ∑ β4i
k
i=1 ∆lnSPXt−i + β5lnGOLDt−1 + β6lnOILt−1 +
β7lnUSDXt−1 + β8lnSPXt−1 + ε2t
(3) ∆lnUSDXt = Υ0 + ∑ Υ1i
r
i=1 ∆lnGOLDt−i + ∑ Υ2i
r
i=1 ∆lnOILt−i +
∑ Υ3i
r
i=1 ∆lnUSDXt−i + ∑ Υ4i
k
i=1 ∆lnSPXt−i + Υ5lnGOLDt−1 + Υ6lnOILt−1 +
Υ7lnUSDXt−1 + Υ8lnSPXt−1 + ε3t
(4) ∆lnSPXt = φ0 + ∑ φ1i
n
i=1 ∆lnGOLDt−i + ∑ φ2i
n
i=1 ∆lnOILt−i +
∑ φ3i
n
i=1 ∆lnUSDXt−i + ∑ φ4i
n
i=1 ∆lnSPXt−i + φ5lnGOLDt−1 + φ6lnOILt−1 +
φ7lnUSDXt−1 + φ8lnSPXt−1 + ε4t
Group 2 with crisis interaction:
(1) ∆lnGOLDt = ∝0+ ∑ ∝1i
p
i=1 ∆lnGOLDt−i + ∑ ∝2i
p
i=1 ∆lnOILt−i +
∑ ∝3i
p
i=1 ∆lnUSDXt−i + ∑ ∝4i
p
i=1 ∆lnSPXt−i + ∝5 lnGOLDt−1 + ∝6 lnOILt−1 +
∝7 lnUSDXt−1 + ∝8 lnSPXt−1 + ∝9 D1G + ∝10 D2O + ∝11 D3U + ∝12 D4S +
ε1t
(2) ∆lnOILt = β0 + ∑ β1i
k
i=1 ∆lnGOLDt−i + ∑ β2i
k
i=1 ∆lnOILt−i +
∑ β3i
k
i=1 ∆lnUSDXt−i + ∑ β4i
k
i=1 ∆lnSPXt−i + β5lnGOLDt−1 + β6lnOILt−1 +
β7lnUSDXt−1 + β8lnSPXt−1 + β9D1G + β10D2O + β11D3U + β12D4S + ε2t
(3) ∆lnUSDXt = Υ0 + ∑ Υ1i
r
i=1 ∆lnGOLDt−i + ∑ Υ2i
r
i=1 ∆lnOILt−i +
∑ Υ3i
r
i=1 ∆lnUSDXt−i + ∑ Υ4i
k
i=1 ∆lnSPXt−i + Υ5lnGOLDt−1 + Υ6lnOILt−1 +
Υ7lnUSDXt−1 + Υ8lnSPXt−1 + Υ9D1G + Υ10D2O + Υ11D3U + Υ12D4S + ε3t
Tải bản FULL (59 trang): https://bit.ly/3wC8e7O
Dự phòng: fb.com/TaiHo123doc.net

28
(4) ∆lnSPXt = φ0 + ∑ φ1i
n
i=1 ∆lnGOLDt−i + ∑ φ2i
n
i=1 ∆lnOILt−i +
∑ φ3i
n
i=1 ∆lnUSDXt−i + ∑ φ4i
n
i=1 ∆lnSPXt−i + φ5lnGOLDt−1 + φ6lnOILt−1 +
φ7lnUSDXt−1 + φ8lnSPXt−1 + φ9D1G + φ10D2O + φ11D3U + φ12D4S + ε4t
Where:
- lnGOLDt is the log of the London gold price;
- lnOILt is the log of international crude oil prices which measures the price of
West Texas Intermediate (WTI) crude oil;
- lnUSDXt is the log of US dollar index;
- lnSPXt is the log of S&P 500 index;
- D1G = lnGOLDt-1* Crisis;
- D2O = lnOILt-1 * Crisis;
- D3U = lnUSDXt-1 * Crisis;
- D4S = lnSPXt-1 * Crisis;
- ∆ is the first difference operator;
- p, k, r, n are the lag lengths and determined by the Akaike Information Criterion
(AIC) (supporting by Eviews 6 software);
- α0, β0, 𝛶0, φ0 are the drift;
- αxi, βxi, 𝛶xi, φxi (x = 1 to 4) are the short-run coefficients;
- αx, βx, 𝛶x, φx (x = 5 to 8) are the long-run coefficients in Group 1;
- αx, βx, 𝛶x, φx (x = 5 to 12) are the long-run coefficients in Group 2;
- εxt (x = 1 to 4) are white noise errors;
- Crisis = 1, over the period 01/08/2007 – 31/12/2008, 0 elsewhere.
The null hypothesis of no cointegration in the long run in each equation of Group 1
is that:
i. Equation 1: H0: α5 = α6 = α7 = α8 = 0
6677748

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