INTRODUCTION

1.1 Background of Study

The global gold market has recently attracted a lot of attention and the price of gold is relatively higher than its historical trend. In 2008 and early 2009 most metal prices fell and the global economy was in recession. Many mining companies had difficulties surviving during this period. Some reduced their production rates and postponed projects while others switched to hedge instruments or long-term contracts to guarantee commodity prices.

Prerana,B. et al (2013) define the gold as the most precious metals and valuable. It’s become symbolic in life. Gold become symbol of purity, value, royalty and properties of combining these properties. Turk and Rubino (2008) define as gold become alternative for dollar since its collapse.

Cash flows in mining projects are volatile and are significantly influenced by the fluctuation of mineral commodity prices. The price and production behavior of gold differs from most other mineral commodities. In the 2008 financial crisis, the gold price increased by 6% while many key mineral prices fell and other equities dropped by around 40% (Shafiee S. and Topal E.,2010). Like other goods, gold price depend on supply and demand. Gold is storable and the supply is accumulated over centuries.

In global view, there are broad of studies on determinants that contribute to prices of gold. According to Toraman C, Basarir C, and Bayramoglu M. F., the variables that are thought affect the gold prices are oil prices, silver prices, USA exchange rate, USA inflation rates are analyzed from 1992 until 2010.

Figure 1.1: Fluctuation gold price in Malaysia

The Figure 1 shows the fluctuation gold price in Malaysia. We can see that along the price of gold increase from 2006 until it reached its peak at 2011 until 2013 and slowly decrease until this year. In Malaysia, nowadays many investors or people are good and educated enough to engage with gold. They will update the current gold prices in order to grab the chances where they can buy gold at lower prices and sell it at high price later on. So, in our study, we want to determine the most important determinant of gold price. This study will begin with the problem statement and a little bit explanation of factors affecting gold price in the literature review. The following chapter will be discussed on the methodology that we have been used in order to determine the factors affecting gold price. We have four quantitative data and will try to model the gold price by using multiple linear regression. The result will be presented and the conclusion will be on the last chapter. We will study the determinants of gold price in Malaysia by analyzing 9 years data from January 2006 until September 2015.

1.2 Problem Statement

Detrixhe (2011) highlighted that the downgrade of S&P rating on US Treasury Bond from AAA to AA+ was the reason for the highest price of gold breakthrough. He mentioned that from the first quarter of 1980, gold price vigorously increased from USD 38.50 per ounce to USD 631.10 per ounce. Since this trend ongoing until the gold price reached the peak level at August 2011. So, the gold price has the highest price of USD 1917 per ounce. Yi Tian (2011) said that, since the downgrade of S&P rating on US Treasury Bond from AAA to AA+, it led to US debt crisis. So, many investors lost their confidence towards US Paper Currency. So, they tend to shift their investment into gold that can protect their investment value. This is the reason of gold have higher demand and the gold price increase until USD 1917 per ounce in August 2011. Choong et. al (2012) mentioned that some investor become worried due to high gold price. This is because gold price may not stay long lasting at current increasing trend. In Malaysia, Datuk Meer Sadiq Habib said that the price of 916 gold has dropped to RM156 per gram previously in the early of 2013. Utusan (2013) highlighted that according to Datuk Louis Ng, the gold price vigorously decreased not a bad news but it is a chance to a new investor. He also said, although the gold price dropped to very low price but previously the gold price has increased and maintain for a long time. So, in our study, we would like to find out the factors that contribute to the gold price in Malaysia.

1.3 Theoretical Framework

Figure 1.2: Theoretical Framework of Gold Prices in Malaysia

We have decided to use four independent variables to find the most significant variable that contribute to the gold price in Malaysia. The first independent variable is inflation rate. Inflation rate is a worldwide macroeconomic problem owing to its adverse implication for economic expansion. Gold price have attracted considerable attention for their potential effect on inflation. Second independent variable refers to silver price. Silver price generally tends to exaggerate gold price and substitute goods of gold. Third independent variable is crude oil price. The main idea behind the gold and oil relationship is the increase in the price of oil result in increased prices of gasoline which is derived from oil. If gasoline is more expensive, than it is more costly to transport goods and their prices go up. Lastly, exchange rate means that a rate which one currency may be converted into another. Gold is a prime candidate for a study of the effects on commodity prices of fluctuation in major currency exchange rates.

1.4 Research Questions

Below are the research questions for this study. The research questions consist of two questions which are;

• What are the factors that affect the gold prices?

• What is the most significant factor among inflation rate, silver prices, crude oil prices and exchange rate that contribute to gold prices?

1.5 Research Objectives

Below are the objectives that we want to achieve. There are two objectives in this study.

The objectives for this study are to determine:

• The significant factor that affect the gold prices.

• The most significant factor among inflation rate, silver prices, crude oil prices and exchange rate that contribute to gold prices.

1.6 Research Hypothesis

Below are the research hypotheses in this study. The hypotheses are:

• There is at least one independent variable among inflation rate, silver prices, crude oil prices and exchange rate that affect to gold prices.

• There is a significant relationship between inflation rate and gold prices

• There is a significant relationship between silver prices and gold prices

• There is a significant relationship between crude oil price and gold prices

• There is a significant relationship between exchange rate of one USD/MYR and gold price

1.7 Scope and Limitation

This study focuses on the gold price for each month starting from January 2006 to September 2015. This means that it only involves 117 samples of data. The data that we used is the secondary data that are obtained from The Central Bank of Malaysia official portal and other international website. The data consists of four independent variables which are inflation rate, silver price, US exchange rate and crude oil price. Other variable that may affect gold price are not use. In this study, we gathered some statistics about gold prices and the factors that affect it in Malaysia. We are using multiple linear regression model to analyze the data. The major conceptual limitation of all regression techniques is it can only ascertain relationships, but we can never be sure about the underlying causal mechanism.

1.8 Significance of Study

Gold is the most precious metal that is popular for investment. Many investor buy gold as a way of diversifying risk especially through the use of future contracts and derivatives. Some people also buy gold not only because of its value but it also because it is easy to store, easy to transport, and is very useful in many modern applications. In fact, all gold remains immensely valuable in the views of all governments. That is why every central bank of any significance buys and holds gold in reserve in a world of almost universal paper money. So, this research will help the investor and people to find the best time period to buy and trade the gold. Besides, they also can get better understanding about the factors that will affect gold price especially in Malaysia,

1.9 Definition of Terms

• Gold is a chemical element in its purest form; it’s a bright, slightly reddish yellow, dense, soft, malleable and ductile metal. Gold is a precious metal which has a long and illustrious relationship and continues to do so. Gold served as money until other form of currency were devised and even now gold is used for an investment (Michael, 2007).

• Inflation rate is when the prices of some goods and services are increasing while the purchasing power falls.

• Exchange rate means that a rate which one currency may be converted into another. It is being used when simply converting one currency to another such as for the purpose of travelling to another country or engaging in speculation or trading in the foreign exchange market (Martin, 2011).

• Crude oil is a mixture of naturally occurring hydrocarbon that is refined into diesel, gasoline, heating oil and literally thousands of other products called petrochemicals. Crude oils are named according to their contents and origins and classified based on their per unit weight (specific gravity) (Martiani and Rahfiani, 2009).

• Crude oil price refers to the gasoline. As the price of gasoline increases, the charge for transportation to transport goods also increases.

• Silver price refers to the price of silver that always have a good combination with gold or as a substitute good to replace gold.

CHAPTER 2

LITERATURE REVIEW

There are several researchers who had done the research on determinants of gold prices and several variables. For example, Choong et al. (2012) has carried out the study on determinants of gold prices. Ismail et al. (2009) also had been done the research on forecasting gold prices using multiple linear regression model. So, this study concerns on the relationship between dependent variable which s gold prices and the predictor variables such as silver price, inflation rate, exchange rate and oil prices. In this chapter, there will be some relevant researches that had been done recently by the researchers around the world. Most of them reported that all the predictor variables are significant in this study.

2.1 Gold price and silver price

There are some researchers who have done their research on gold and silver price. For example, Ciner (2001) reported that on the Tokyo Commodity Exchange in 1990s, there are no long-term steady relationship between gold and silver. This is show these two market cannot be approached on the same market .

Escribano and Granger (1998) stated that based on their study, they found that in certain periods, especially during bubble and after bubble period, cointegration may existed. They found that there is strong relationship found using the actual return of gold as the dependent variable and silver as independent variable in the regression. Tulley and Lucey (2006) as cited by Choong et al. (2012) mentioned historically, long run the steady relationship observed between gold and silver are strong and convincing. According to Lee and Lin (2012) as cited in Choong et al. (2012), gold and silver can be substitute goods to each other. Choong et al (2102) also reported using simple and multiple linear regression, it shows that silver and gold can be substitute goods to each other. So, they said that there is positive relationship between gold and silver.

According to Choong et al. (2012), they reported Solt and Swanson (1981) results. Solt and Swanson (1981) mentioned that there is positive relationship in United States between gold and silver markets. Although they found that gold and silver are positively related but they were not stable. So, they conclude that even though only weak correlation exists between gold and silver but there is still existed steady long-term relationship.

2.2 Gold price and inflation

The findings of relationship existed between gold and inflation was positively related. There are a few studies that have been done on the relationship between gold and inflation. For example, Siti et al. (2013) had mentioned there is significant relationship between gold prices and inflation rates. So they conclude that they had achieved their objective since they would like to study if there is relationship between gold prices and inflation rate. According to Ismail et al. (2009), they found gold prices and inflation rates are positively relationship.

According to Baur (2011) as cited by Choong et al. (2012), claims that in simple linear relationship between gold price and inflation, positive coefficients can be found. Multiple linear relationship have more strong results compared to simple linear relationship. According to Tully and Lucey (2007), they claims that insignificant relationship between gold price and inflation was found using GARCH approach (Choong et al., 2012). Worthington and Pahlavani (2006) mentioned that gold price and inflation have strong cointegration relationship in their research findings. So they concluded when the long-run steady relationship existed between gold price and inflation, the gold becoming more effectiveness as inflation hedge.

Choong et al. (2012) stated that using both simple linear regression and multiple linear regression model and multiple linear regression model, they still found that positive and significant relationship existed between gold price and inflation. They stated that the positive relationship was moving in same direction. This is show that gold are strong hedge against inflation.

2.3 Gold price and exchange rate

Choong et al. (2012) reported that between gold and USA dollar trade weighted show significant and negative relationship existed. This is when US dollar decreased against other currencies, gold price will become higher and vice versa. Choong et al. (2012) also claims that majority transactions of gold were in US dollar. When US dollar decreased against other currencies, gold price in US dollar increased in its value. Soytas et al. (2009) as cited in Choong et al. (2012) said that gold can be used to hedge against US dollar exchange rate.

Levin and Wright (2006) as cited in Choong et al. (2012), said that they applied different cointegration regression techniques in order to examine the key factors of gold price movements. They find out that between changes in gold price with changes in the US dollar trade weighted exchange rate and gold price lease rate, there are statistically significant relationships exited.

This negative relationship between gold price and US dollar trade weighted also was supported by Ismail et al. (2009). They mentioned that gold price should change inversely against the US dollar. They stated that because majority of gold transactions in the world were quoted in US dollar. Akar (2011) found the relationship between stock exchange, gold and foreign exchange returns in Turkey from period of 1990 to 2010 by using dynamic conditional correlations GARCH model. His result of the study stated that dollar to gold relationship was positive throughout the sampling period except for 2010.

Sujit K. S et al. (2011) said that through the simple relationship between currencies, there are no interconnection exists between exchange rate and gold price. Choong et al. (2012) concluded that based on some researchers studies before, the results are seems to be mixed between gold price and US dollar exchange rate. So they stated that relationship is still not clear between the variables. This issue will lead researchers to investigate the relationship between gold price and exchange rate.

2.4 Gold price and crude oil

On the previous study, the relationship between gold price and crude oil prices are found to be positive. However, some researchers claims that bilateral and unilateral relationship existed among gold prices and crude oil prices. Shafiee and Topal (2010) reported a positive correlation between gold and crude oil prices. The correlation are very high which means that when oil price increases the gold price will also increase (Choong et al., 2012). Soytas et al. (2009) cited by Choong et al. (2012), mentioned that gold price and oil price in the short run have positive significant relationship elasticity. According to Narayan et al. (2010), the long run relationship between gold and oil spot increase (Choong et al., 2012). There was highly correlated found in the result of cointegration test. Oil market can be used in order to forecast gold market price and vice versa and it is show that bilateral relationship existed among them.

Zhang and Wei (2010) found significant unilateral linear Granger causality between crude oil and the gold markets existed increase (Choong et al., 2012). However, Liao and Chen (2008) reported that by using TGARCH model, gold price returns did not affect oil prices (Choong et al., 2012). Choong et al. (2012) concluded that using simple linear regression and multiple linear regression model, the relationship was positive and significantly between crude oil and gold price. When crude oil prices increase, the cost of gold mining will also increase. So crude oil can be served as the main cost in gold prices. Sujit K. S et al. (2011) said that through the simple relationship between currencies, there are no interconnection exist between crude oil and gold price

Overall, the relationship of gold prices between silver price, inflation, exchange rate and crude oil are seems to be positively related. However, the relationship between gold price and crude oil price are still unclear and need to study more.

CHAPTER 3

METHODOLOGY

3.1 Introduction

In this chapter, we will discuss the method that will be using to determine the factors that affect the gold price in Malaysia. The method that we found to be the most suitable for this research is Multiple Linear Regression (MLR) method. Thus, further explanation will be elaborated from the beginning of analyzing the data until we find the best model and accurate result.

3.2 Study Data

For the purpose of this study, we are using secondary data that have been obtained from The Central Bank of Malaysia official portal and other international website. From the website, we are only interested in collecting data related to silver price, inflation rate, exchange rate (USD/MYR) and crude oil price as they are our independent variables for this study. The data are recorded according to month. The sampling period for this study covers a period of 10 years from January 2006 until September 2015.

3.3 Software used

In this study, we are using the latest versions (2015) IBM SPSS Statistics, Microsoft Word and Microsoft Excel. SPSS software is used to run automatic linear modeling regression to find the output for the significant variables.

3.4 Data Analysis Technique

In this topic, further explanation regarding to the process of systematically applying statistical techniques to describe and evaluate data is carried out. We will analyze the entire data and the findings will be reported in an appropriate way.

3.4.1 Descriptive Analysis

Descriptive statistics is a basic analyze of the data like mean and standard deviation. The average value of data shows the mean while the deviation of value from mean represent the standard deviation. Descriptive statistics enables us to present the data in a more meaningful way, which allows simpler interpretation of the data. The formula is shows as below:

Mean

Where, n = sample size

x = correspond to the observed value

Standard deviation

Where, n = sample size

x = correspond to the observed value

x = mean value

3.4.2 Pearson’s Correlation Coefficient

Correlation is used to determine the relationship or correlation between two numerical variables. Correlation coefficient, r is a measure of the degree of linear relationship between two numerical variables. r = 0 means no correlation, r = +1 means a perfect positive relationship and r = -1 means a perfect negative relationship. According to Norleha and Norhasliza (n.d) they rate the r as below:

• ≤ 0.20 : very weak

• ≤ 0.5 : weak

• 0.50 – 0.70 : moderate

• ≥ 0.70 : strong

• ≥ 0.90: very strong

3.4.3 Multiple Linear Regression

Multiple linear regression is a statistical technique that uses several explanatory variables to predict the outcome of a response variable. The goal of multiple linear regression is to model the relationship between the explanatory and response variables. We are using stepwise regression method because we want to improve a model’s prediction performance by reducing the variance caused by estimating unnecessary terms. For this study, the dependent variable is gold price while independent variables are silver price , inflation rate, US exchange rate, and crude oil price that used to determine the factors that affect the price of gold.

The general model for Multiple Linear Regression :

Yi = β0 + β1X1 + β2X2 + …+ βnXn + ε where i= 1,2, …, n

The model in this study:

Yi = β0 + β1X1 + β2X2 + β3X3 + β4X4 + ε

where:

Y : Gold price (USD/oz)

X1 : Silver price (USD/oz)

X2 : Exchange rate (USD/MYR)

X3 : Inflation rate (%)

X4 : crude oil prices (USD/barrel)

Model assumptions

1. There is a linear relationship between dependent variable and independent variables

2. The error terms are normally distributed

3. It is assumed that the predictors are independent for one another

4. The error terms are independent of one another (Autocorrelation)

5. The error variance is constant (Homocedasticity)

Firstly, multiple linear regression needs the relationship between independent variables and dependent variable to be linear. It is also important to check for outliers since MLR is sensitive to outlier effects. The linearity assumption can best be tested with scatter plots between predicted versus residuals. It is said to be linear when all points are random and no pattern.

Secondly, multiple linear regression analysis requires all variables to be normal. This assumption can best be checked with a histogram and a fitted normal curve or a Q-Q plot. Normality can be checked with the goodness of fit test, for example the Kolmogorof-Smirnof test. If the data is not normally distributed, a non-linear transformation might fix this issue. However, it can introduce effects of multicollinearity.

Thirdly, multiple linear regression assumes that there is a little or no multicollinearity in the data. Multicollinearity occurs when the independent variables are not independent from each other. A second important independence assumption is that the error of the mean is uncorrelated.

Multicollinearity is checked against 3 key criteria:

i. Tolerance – it measure the influence of one independent variable on all other independents variables. T < 0.01, so multicollinearity exist.
ii. Variance Inflation factor (VIF) – VIF > 10, so multicollinearity exist

Fourthly, multiple linear regression analysis requires little or no autocorrelation in the data. Autocorrelation occurs when the residuals are not independent from each other. It can be tested with Durbin –Watson test. As a rule of thumb values 1.5

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