According to Bosworth and Lawrence (1982), commodities are commonly refers as products grown on land (like crops), extracted from land (like minerals), or raised on land (like cattle) that have been subject to only the initial stage of processing. Examples of commodity are crude oil, crude palm oil, gold, sugar, iron ore, wheat, corn, soy bean, live cattle, natural gas and others. Among the world’s major exchange that trade commodity base futures are Chicago Mercantile Exchange (CME), New York mercantile exchange (NYME), London Futures and Options Exchange, Sidney Futures Exchange and Kuala Lumpur Commodity Exchange (Sahadevan, n.d). In Malaysia perspective, the commodity futures trades in Malaysia derivatives market are Crude Palm Oil Futures (FCPO), USD Crude Palm Oil Futures (FUPO) and Crude Palm Kernel Oil Futures (FPKO). (Bursa Malaysia, 2009) Basically, the commodity prices are decided between the trading done among investor in those major mercantile exchanges.
Commonly, in commodity futures market, there are 3 kinds of participant namely investor, hedger and speculator. Investors are investing in the commodity in the intention to gain profit when the price is going up; they have no intention to take the physical commodity product. Hedgers are usually oil refiner, crops suppliers, farmer, commodity wholesalers, commodity retailer and others. They try to hedge their risk in futures market for the uncertainty of commodity price. On the other hand, speculator is those kinds of people that involved themselves in futures market to gain profits from speculating the price change. Those kinds of players actually just buy and sell futures contract accordingly to the price movement without any intention to take the physical commodity. Generally, commodity price have a direct relationship with the principle of demand and supply. Excess demand will push the price up while excess supply will pull the price down. From here, demand and supply of commodity product are influence by factors such as weather, political uncertainty, trade policy, sudden disaster, macroeconomic variables, human lifestyle and others. To give a clear picture of movement for commodity price, the following table has been include to illustrates the price movement of world’s major commodity product from year 2004-2008.
Types of Commodity/Year
|Cattle (Live) (USD) CME||89.85||96.375||92.5||96.175||86.05|
|Corn (USD) CME||204.75||215.75||390.25||455.5||407|
|Crude Oil (light sweet) (USD) NYMEX||43.45||61.04||61.05||95.98||44.6|
|Crude palm oil (RM) BURSA MALAYSIA||1384||1397||1976||3070||1685|
|Electricity PJM (USD) NYMEX||53.63||95.25||52.5||72||63.8|
|Gold (100oz) (USD) CBOT||437.9||517.2||634.7||835.3||884.5|
|Natural Gas (USD) NYMEX||6.149||11.225||6.299||7.483||5.622|
|Soybean (USD) CBOT||547.75||602||683.5||1199||972.25|
|Sugar#11 (USD) NYBOT||9.04||14.68||11.75||10.82||11.81|
|Wheat (USD) CBOT||307.5||339.25||501||885||610.75|
Source: Datastream Notes: CME- Chicago Mercantile Exchange; NYMEX- New York Mercantile Exchange; CBOT- Chicago Board of Exchange; NYBOT- New York Board of Exchange. Table 1.1 World’s major commodities price from year 2004 to 2008 From the table above, it shows that the price of most of the world major commodities like corn, crude palm oil, gold, soybean, wheat, and crude oil are on an increasing trend from year 2004 to 2007. This is mainly cause by an encouraging economic surrounding. According to the data from International Monetary Fund web site (2009), it shows that world’s GDP growth is on a significance level which achieves averagely 5.05% from year 2004 to 2007. The substantial global economic growth has boosted the demand of raw material that further pushes the commodities’ price. Unfortunately, on year 2008, global financial crisis which originated from US subprime mortgage has badly impact the world economy. According to International Monetary Fund, the world economic growth has slow down to 3% in 2008. High unemployment and low domestic demand in most country has reduced the demand for raw material in production. These kinds of situation have put a pressure towards almost all kinds of commodities prices into downward trend.
In order to illustrate more clearly regarding the variable that cause the movement in Commodities price, One of the world’s major economic indicator which is world’s economic growth is taken to shows how the movement of commodities price is correlated by the variables mentioned. For instance, 5 types of world’s major commodities which is Crude Oil (light Sweet) (represent for energy commodities), Soybeans (represent for Agriculture commodities), Gold (100oz) (represent for metals commodities), cattle (Live) (represent for Livestock commodities), and Crude Palm Oil (represent for Agriculture commodities) is chosen in the illustration. The reason which Crude Oil (Light Sweet) is chosen in this illustration is that it is the world’s popular commodity futures to trade. According to the sources from Cleartrade.com web site (2009), sweet crude oil futures contract is the world’s most active instrument for crude oil trading, besides that, it also the physical commodity that having the world’s largest-volume futures contract. From the graph, it shows that the movement of crude oil price is almost parallel with the world’s economic growth. On the year between year 2004 to 2007, both the world economic growth and crude oil price is on an increasing trend. Commonly, World economic growth which leads to the increase in aggregate output will contribute to the usage of fuel and raw material thus increase the price of crude oil. However, the economic crisis happened in 2008 cause and economic slowdown and badly impact crude oil price. The reason why Gold (100oz) is chosen in this illustration is that gold is the universally recognized store of wealth, it can be gold reserve that store in central bank of many countries and also the gold bar that people buy as the secure of wealth. Nowadays, gold futures have become more and more popular investment instrument whereby people assume it as a hedge to inflation. This shows gold value is much more stable than paper money. From the graph, it shows that the price of gold is increasing from year 2004 to 2008, which is not parallel with the trend of world economic growth. This can be illustrate by the awareness of people in holding gold as secure of wealth beside depend on paper money with value that depreciate year by year. The reason why Crude Palm Oil is chosen in this illustration is that Crude palm oil is the major agriculture product in Malaysia. According to Department of Statistics (2009), the production of crude palm oil is amounting to 17,734,400 tones. Amount the highest if compare with the production of other commodities. The production of Crude Palm Oil has contributed a lot to Malaysia economy in terms of export. In the graph, it shows that the appreciation in Crude Palm Oil price is parallel with expansion in world economic growth. This shows that, crude palm oil has become more and more important nowadays and has a potential in substituting Crude oil as the raw material in fuel production. The reason why Gold (100oz) is chosen in this illustration is that soybean is that Soybeans are major input for different kinds of food and industrial products. It also provides the raw material for livestock feeds, and cooking oils. (Cleartrade.com, 2009). From the chart, it shows that the movement of soybean price is consistent with the world economic growth from year 2004 to 2008. A significance growth in world economy has enhanced the demand of foods and foods related product. This will directly cause the demand for input and raw material required in producing those kind of product. Thus, excess demand will push the price up. The reason why Cattle (Live) is chosen in this illustration is that refer to the information from CME group, the U.S. cattle and beef industry is estimated at $71 billion in 2006 which substantially contribute to US economy (CMEgroup, 2009). From the graph, it shows that live cattle price is fluctuating year by year and less consistent with world’s economic growth. Besides that, it also shows the fluctuation is not as much as other commodity such as crude oil and soybean. The investment in live cattle is much more risky because certain factors like weather and disease may influence the production of life cattle.
According to (Mobius, 2007) stock is a equity base capital raising instruments besides bonds which is debt base, A stock gives the holders the right to own property in a company which they are not physically possess at that time. Stock market is the place where investor trade share with each other to make profit, every day, millions of share trading transaction has been done on stock market. Among the world’s leading stock market are NYSE (new York stock exchange), shanghai stock exchange, Hong Kong stock exchange, Tokyo stock exchange, Bombay stock exchange and others. Malaysia’s stock market is name as Bursa Malaysia. On 18 April 2005, Bursa Malaysia has listed on its own exchange. As of 31 December 2007, the total market capitalization of bursa Malaysia is about 325 bilions (Wikipedia.com, 2009). According to the listing statistics in Bursa Malaysia web site (2009), it shows that as at 4 November 2009, there are a total numbers of 956 listed companies which comprise of 839 listing in main market and 117 listing in ACE market. Due to the characteristics of stock, there are many factors that influence stock price which are company fundamental, macroeconomic variables, business cycle and others. Predicting the stock price is the important step for an investor for them to gain profit in the stock market. The 2 most popular analyses employs by analysts which are fundamental and technical analysts. These 2 kinds of analysis are complement with each other to give a clearer direction for investor about the stock price movement. In fundamental point of view, stock price is much more influence by the determinant of the stock price like earning, revenue of the company and so on. While in the technical point of view, there are certain trends and patterns like moving average, Bollinger bands and others, that can be apply in predicting stock price movement.
In Malaysia, due to the geographical nature and suitable weather condition, lots of commodities like crude palm oil, crude oil, natural gas, rubber, gold, iron are available here. According to Statistics Department website (2009), the production of crude oil in year 2008 is amounting to 254,055,000 barrel, while the production of crude palm oil in year 2008 is amounting to 17,734,400 tonnes. The large amount of commodity production has given an opportunity to the expansion of plantation, mining, and oil and gas companies. For plantation sector, the example of companies are Sime Darby, IOI corp, Kuala Lumpur Kepong, Batu Kawan, Genting Plantation, IJM plantation and others. For gold mining sector, the examples of companies are Poh Kong and Habib Jewel. For oil and gas sectors, the examples of companies are Petronas dagangan, Petronas gas, Kecana Petroleum, KNM, Tanjong offshore, Petra and so on. Due to the business nature, those kinds of company are more easily influence by the volatility in commodity price. The revenue and profit margin may fluctuate due to the uncertainty in commodity price.
To give a clear picture of movement for commodity base company stock price, the following table has been include to illustrates the stock price movement of Malaysia’s major commodity base company from year 2004-2008.
Source: Datastream Table 1.2: Stock Price of Commodity Base Company in Malaysia from year 2004 to 2008 In terms of commodity base company, the table shows that most of the performance of commodity base company base on stock return is encouraging from year 2004 to 2007. Most company in the list like Batu Kawan, Genting Plantation, IOI Corp, KNM Group, Petronas dagangan, and Shell are achieve an increasing trend of stock return in this 4 years period. This situation is mainly influence by strong economic fundamental in Malaysia. According to Economic Planning Unit website (2009), the Malaysia’s GDP growth was averagely 6.05% from year 2004 to 2007. Stronger domestic demand has improved the performance of companies’ in terms of revenue and profit generated. This has further contributed to the appreciation in stock price. On the other hand, the appreciation in stock price of those commodity base companies can also link with the movement of commodity price. For example, the increase in crude oil price has contributed to the stock price appreciation of companies like Petronas Dagangan, Shell, and KNM group. Besides that, the stock price of Batu Kawan, Genting Plantation, and IOI Corp also parallel with the increase in crude palm oil price. Unfortunately, the global financial crisis happen on year 2008 has badly impact the world’s economy and commodity price. The stock price of commodity base company cannot remain resilient from this economic turmoil that has pull down their stock price
In order to illustrate more clearly regarding the movement in commodity base company stock price in relation with movement of commodity price, three commodities taken are Crude Oil (light Sweet), Gold (100oz), and Crude Palm Oil. While the stock price taken from three public listed companies namely, Petronas Dagangan, IOI Corp, and Poh Kong. The reason why Petronas Dagangan is chosen in this illustration is that Petronas Dagangan is one of the public listed companies that include in the calculation of FTSE Bursa Malaysia KLCI (FBMKLCI) (Bursa Malaysia, 2009). The market capitalization of Petronas Dagangan is large enough to represent for oil and gas industry. Basically, the principal activity of Petronas Dagangan is involved in the petrol station. The fluctuation in petrol price has show a direct effect towards it business. From the graph itself, it shows a significance sign of correlation between the crude oil price and the stock price of Petronas Dagangan. When the crude oil price goes up, it might contribute more to the revenue and profit of this company that will boost up its stock price. The reason why IOI Corp is chosen in this illustration is that IOI Crop is the leading plantation company in Malaysia. The major portion of IOI Corp is involved in palm oil plantation and production. Besides that, IOI Corp is also one of the companies that include in the calculation of FTSE Bursa Malaysia KLCI (FBMKLCI) (Bursa Malaysia, 2009). From the graph itself, it shows that the stock price of IOI Corp is quite parallel with the movement of crude palm oil price. Take note also in year 2007, the price for crude palm oil has increased about 35.6% compare to previous year. Higher price for crude palm oil will contribute to the larger profit margin of Plantation Company that also boosts the stock price. The reason why PohKong is chosen in this illustration is that PohKong is one of a few public listed company that involve in gold jewel business in Malaysia. From the graph itself, it shows that PohKong Stock Price is fluctuating from year 2004 to 2008 and shows less correlation with gold price. This happen because PohKong business is affecting by other external factor like economic condition, consumer preference and so on besides only affect by the movement in gold price. In summary, base on the illustration and explanation in the beginning of the chapter, it shows that the main interest of this research will be focus on the commodity price and stock price. As a result, the purpose of this research is to discover the relationship between the commodity price and stock price for selected companies involved with commodity related business.
Commodity price is basically determine by the market demand and supply, nowadays, it come more and more volatile cause by the external factors such as world events, political unrest happen that disrupt the production of commodity, world’s economy climate, weather, speculation activity and others. Those factors can lead to an increase or decrease in price by influence the pattern of demand and supply for commodity. Among the most important factor that leads to volatility of commodity is that excess speculation activity in futures market. Sometimes, speculators will come out with some rumors in order to gain profits from speculate the commodity price in the form of futures contract. The phenomenon mentions above actually is a big problems that influence the investment for kinds of parties like statutory bodies, fund managers, retail investors and commodity base company operator. First and foremost, the statutory body mentions here is refer to bodies like Kumpulan Wang Simpanan Perkerja (KWSP), Permodanan Nasional Berhad (PNB), Lembaga Tabung Haji (LTH), Lembaga tabung Angkatan Tentera (LTAT) and so on. These kinds of bodies are established by government to take care for the interest of specific parties like employees, public, Muslim, armed force and so on. Most of the statutory body is holding a large amount of fund which contributes by its members. They will fully utilize those kinds of fund into investment purpose in order to give maximum return to its members. For example, Refer to KWSP web site (2009), on year 2008, Kumpulan Wang Simpanan Perkerja has allocate 25.71% or RM87, 948 millions of total fund into equity investment. Besides the good track record achieve by those commodities base companies, a significance portion of fund from statutory bodies will used to purchase the stock of commodity base company. For example KWSP, PNB, and LTH have holding total amount of 15.29% stake in Kuala Lumpur Kepong Berhad. (Kuala Lumpur Kepong Annual Report, 2008) So, volatility in commodity price which cause the fluctuation in stock price of commodities base company will cause an uncertainty in the investment of statutory bodies. Sometimes, when the commodities price is going down, revenue of company will decrease that will push down the earnings per share of the company. Thus, market will pessimist for this stock and the price will go down also. When the value of commodity base stock goes down, it will affect the investment of statutory bodies which therefore reduce the capability for them to give good rerun to their members. For the view point of fund managers, uncertainty in commodity price which cause instability in commodities stock price will incur a higher risk for them. The fund manager mention here is the one who manage for privately issues unit trust and mutual fund. According to the statistics provided in Securities Commission web site (2009), as at 31 October 2009, the total Net Asset Value for unit thrust is amounting to RM190.523 billions or 20.34% of Bursa Malaysia market capitalization. With such a Hugh amount of fund, usually large portion of it will flow into equity market. Commonly, those fund manager that manage those fund will always like to allocated those fund into blue chip stock listed in Bursa Malaysia for long term investment purpose to earning for dividend and also wait for the appreciation of stock price. In Malaysia cases, large and reputable commodities base companies like IOI Corp, Kuala Lumpur Kepong, Kulim, Sime Darby, Petronas Dagangan are always the choice of those fund manager to invest in. But, the stock price of those companies may fluctuate due to the uncertainty in commodities price. The commodities price are the risk and uncontrollable by the company. Sometimes, a overly low commodities price will cause a depreciation for stock price of the company besides the revenue and profit margin has reduced. As a results, when a fund manager is holding a significance amount of commodities base company stock, he /she will need to bear for higher risk beside the uncertainty in commodities price cause the fluctuation in stock price. In term of the retail investor, the investments of retail investor are usually on a small scale basis. They are lacks of knowledge and expertise in analyzing for the whole macro and micro environment factors that influence the stock movement especially in terms of commodities base company. Those kinds of investor are not able to weather the storm early by discovering the direction of movement for commodities price whereby they will usually just value the fundamental of those commodities base company without considering the external factors like commodities price in influencing commodities company stock price. When world’s major commodities price are moving downward, retail investor that unrealized this condition will continue to hold those commodities base stock they have without considering the risk where the value of the particular stock will go down also. The things come worse where the fall in commodities price has cause the depreciation in stock price and retail investor has suffer loss whereby they are too late in sell off their share. On the other hand, problems also occur when the commodities price is on an upward trend. Retail investors that do not consider the correlation between commodities price and stock price may miss the chance in buying those commodity base stock. For the commodity base company operator position, the phenomenon mentions above actually will cause damage to them. Those companies rely heavily with the price of commodity. The volatility in commodity price will directly influence the stock price, operation cost, revenue, profit margin and etc for those companies. They need to keep track with everyday commodity price and adjust themselves with the price change. Several tactics like hedging has been employed by them in order to hedge their risk from volatility in commodity price. With this tactics, they are able to lock the commodity price for the commodity that need to be deliver to customer on future date. On the other hand, even thought, tactics has applied, but if the movement of commodity is in a reverse direction, a higher cost maybe loss. The cause of this phenomenon is that speculator in major world’s commodity futures market try to manipulate the price to gain windfall profits. Besides that, maybe those party involve in commodity sector are too sensitive with the changing in commodity price. The news that show potential influence towards for commodity price may cause them over respond and cause unnecessary increase or decrease in demand and supply of commodity that further cause volatility in stock price. This research is crucial to investor, fund manager and operator for commodity base company whereby it will convince them that there is some soft of relationship between the commodity price and company’s stock price. By knowing for this concept, they will able to forecast and estimate the influence of commodity price towards stock price. This will assist them to weather the storms earlier and minimize the exposure to risks.
The aim of this study is to provide a clear picture for investor; fund manager, stock analysts, and commodity base company owner regarding the relationships exist between commodity price and commodity base company stock performance. For this aim, the following are the objectives of this research.
In chapter 1, for introduction part, the overview and background of this research is stated. For problem statement part, the problem statement has outlined the problems that arise from the main interest of this study. For objective part, it shows the aim of the study that proposes to achieve in the end of the research. For significance of study part, the contribution of this research is sated. For organization part, flow and arrangement of all content in this research is present. In chapter 2, for literature review part, the previous researches are review and the model employ, methodology, outcome, and conclusion from previous study are record down. The arrangement for this part is base on the sequence of variable follow by variable. In chapter 3, for theoretical framework, all the variables are list down and the relationship between independent and dependent variable are describe in diagram. For Model specification and estimation procedures, for research design part, all the model and methodology that are employ in the research are describe. For data collection part, the time horizon and the characteristic of data are described. Besides that, the source of data is described. Last but not least, the rationale of why the specific data is chosen also include in this chapter. In chapter 4, for results and discussion part, the result get from the statistical analysis software are presented. The interpretation, explanation, analysis, comparison and discussion for the results will also be include in this chapter to let the reader a clearer understanding for the outcome of the topic. In chapter 5, conclusion and recommendation part, the summary and conclusion for this research was included. The recommendation for the future researcher also has been include as an advice for the future researcher for this topic.
According to chapter 1, this research examines the relationship between commodity price and commodity base company stock returns. In order to have a clearer understanding for the research, a literature survey has been done to discover the related research and study which has been done by others in this field. In this chapter, the literature survey has been dividing into 4 parts, which are Part 1, the literatures for relationship between commodity price and commodity base companies stock return are review. In Part 2, the literatures for relationship between crude oil price and oil companies stock return are review. In Part 3, the literatures for relationship between crude palm oil and palm oil companies’ stock return are review. In Part 4, the literatures for relationship between gold price and gold companies’ stock return are review.
Barkoulas, Hu, and Santos (2008) have conducting a study which investigates the link between commodity prices and commodity equity on 60 trading days before and after 911 events. This can be shows as an attempt to investigate the relationships between commodity prices and the value of commodity base equity during the event of 911. In this study, the authors have obtained data which consists of stock price of oil and gas industry, gold price and crude oil price. For the methodology part, authors have employed Capital Asset Pricing Model (CAPM) and Seemingly Unrelated Regression (SUR) analysis in this research. After the testing, the results show that the correlation is low between the changes in oil prices and gold indexes returns. Furthermore, a negative correlation is discovering between the returns from gold indexes and oil indexes. Chong and Miffre (2007) has conduct a research using series of data from the period 1979 to 2004.In order to discover the strength of correlation between equity return and commodity futures returns. On early part of this research, the authors have using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and diagonal VECH as the methodology in this research. The findings from this research state that the correlation between commodity futures and Standard and Poor’s 500 Index (S&P 500) has become weaken over time. Besides that, the authors also discover that equity market and commodity futures market has become more segmented. Sadorsky and Henriques (2001) has contribute effort to discover the effects of exchange rates, market return, and commodity prices towards the stock price return of Canadian paper and forest product industry. They has employed data that consists of monthly equity return on paper and forest products stock index, monthly return on market index, market beta and commodity price. Among the methodology that employed in this research are Ordinary least Squares (OLS) and Regression Diagnostic Tests. At the end of the study, the results indicate that stock returns for paper and forest products industry are sensitive to factor such as market return, commodity price, and exchange rate. Hong and Sarkar (2007) explored the commodity beta (the sensitivity of stock price towards commodity price) in gold mining industry. In the research, the authors have using the sample which consists of 30 gold mining firms for the period ranging from year 1983 to 2004. Besides that, other data obtained are company financial information, risk free interest rate, Compagnie Maritime D’expertises (COMEX) closing prices, and Center for Research in Securities Prices (CRSP)/ New York Stock Exchange (NYSE)/ American Stock Exchange (AMEX)/ National Association of Securities and Dealers Automated Quotation (NASDAQ) composite value-weighted index returns. In this research, there are 2 valuation models to measure the commodity beta which are Brennan and Schwartz (1985) and Mello and Parsons (2000) models. On the other hand, the commodity beta, which is the main interest in this paper, is calculated by the elasticity of the stock price with respect to commodity price. The empirical results show that commodity beta is proof to have increasing implication towards operating and financial leverage, and a decreasing implication of company tax rate and output price. Labys, Achouch, and Terraza (1999) examine to what extent the macroeconomic variable such as industrial product, consumer prices, interest rates, stock prices, and exchange rate are influence the price movement of metals like copper, tin, zinc, and aluminum. The data used by Authors consists of monthly metal prices over the period 1971 to 1995 in London Metal Exchange. Before authors start the study, they have to identify first the univariate and multivariate properties and the structure of time series in doing the price observation. In doing the univariate tests, authors has employed technique like random walk, stationarity, homoscedasticity, chaos, long memory, and normality. After the preliminary testing has done, the authors have employed methodology like cointegration test and Granger causality test in identify how the macroeconomic variables influence the metal price. At the end of the research, the results show that industrial product is the main factor that influence metal price. While the influence of stock price towards metal price is less significance. Besides that, in the case of France, Italy, Japan, and Organisation for economic Co-operation and development (OECD), Influence of industrial activity towards metal price is most significance. Last but not least, the authors have found that besides industrial activities, the influence of other macroeconomic variable is less significance towards metal price. Bartram (2005) has done an analysis relating to the impact of commodity price change on firm value. The aim of this research is to discover the commodity price exposures in nonfinancial firms. In this research, the author has collect data which consists of 490 non financial companies from period 1987 to 1995. Furthermore, after the collection has done, the companies selected have further been divided into 20 industry category. Moreover, the regression test has been done between different commodities prices indices and stock market index. At the end of the research, the results shows that industry that having a significant exposures to commodity price are agriculture, industrial metals, livestock, energy, and precious metals.
Aktham Maghyereh and Ahmad Al-Kandari, (2007) has employed the stock market data from Kuwait, Bahrain, Saudi Arabia and Oman on period from 1 January 1996 to 31 December 2003. In order to investigate the relationship between oil price and stock market in Gulf Cooperation Council Country (GCC). Several test ranging from rank unit root test, rank test for cointegration, and score statistics for nonlinear cointegration has been done to identify the relationship between oil price and stock market indices. The results get from traditional, linear cointegration analysis suggest that there is no linear long run relationship between oil price and stock market. While the results gets from rank tests suggest that a non linear cointegration relationship between GCC stock market and oil price is discovered. Last but not least, for score statistics for nonlinear cointegration, it also shows that the relationship between oil price and GCC stock market is consider as non linear cointegration. Sari and Soytas (2006) has conducted a study to determine the relationship between crude oil price, stock returns, output and interest rate in Turkey. They have used series of data like crude oil whole sale price index, stock indices from Istanbul Stock exchange, 12 month interest rate, and industrial production index as a tool in calculating stock return. The methodologies employed are Variance Decomposition and Impulse Response technique. For variance decomposition test, the results suggest that movement in oil price has the largest effect towards stock return, follow by interest rate and industrial product. For impulse response test, the results suggest that in initial stage, a change in oil price does not show a significance impact for stock return in turkey, but it is significance after the initial stage. As a conclusion, the finding from this research indicates that change in oil price does not significantly affect stock return in Turkey. EryiÄŸit, (2009) has used the index from different sectors in Istanbul Stock Exchange (ISE) market in the process of identifying the effect of oil price towards stock market indices in Istanbul Stock Exchange (ISE). The model created by Faft and Brailsford’s (1999) has been employed in this research. Besides that, author also using Ordinary Least Square (OLS) regression technique to test the model. From here, the results show that the changes in oil price have a significant effect towards all sectors excluding financial and transportation sectors. Mohamed El Hedi and Julien (2009) has conduct a study examining the relationships between oil prices and Gulf Cooperation Council Country (GCC) countries’ stock market in long term. In this study, the authors has using 3 kinds of techniques namely unit root test and linear & asymmetric cointegration testing. For the data selection, the author has used monthly data range form year 1996 to year 2007 available from Arab Monetary Fund (AMF). In the results get from unit root test, it shows that the oil price and stock market data are integrated with each other. Then, for linear cointegration testing, it shows that this testing are not able to explain the long term relationship between oil price and stock market in GCC countries. Next, for asymmetric cointegration tests, it shows that when oil prices are increase, a stable long run relationship is appearing between GCC’s stock market and oil prices. Thornton and Welker (1999) put effort in expanding the literature for financial and economic area by contributing to determine the relationship between oil and gas price to stock price with the influence of disclosure on market risk, has collect the data for companies returns, Standard and Poor’s (S&P) stock market indices, and prices for oil and natural gas. The technique that use in this research is regression test. At the end of the research, the results suggest that those companies that involve themselves deeply in commodity derivatives trading tend to increase the sensitivity of its stock price towards the movement of commodity prices. Lanza, Manera, Grasso and Giovannini (2003) have taking data such as exchange rates, stock market indexes, and crude oil prices. With the intention to determine the factors that casing the movement of oil company stock price in European countries, Besides that, the target oil companies that include in this research are BP, Royal Dutch Shell, Chevron-Texaco and so on. In order to conduct this research, authors have using a model call cointegrated Vector Autoregressive (VAR) model. As a results, authors find that a oil companies that focus on upstream activities may benefits from the increase in oil price while for the companies that focus on downstream activities, they may negatively been affected by the increase in oil price. Kuper (2002) has employed the data consists of the price of a barrel Brent crude on 20 years ranging from 1982 to 2002 to determine the oil price volatility. A model call Generalized Autoregressive Conditional Heteroskedasticity (GARCH) has been used by author to generate a testing for the data collected in research. Form the results, it shows that the daily and monthly price for oil price is highly correlated. Jansen (2009) has contributing in examine the existence of relationship between oil futures and oil stock prices, he has employed data for equities and futures that traded in New York stock exchange and New York merchantile exchange. Beside that, the author using a model calls “stochastic differential equation” to monitor the price movement. Then, the author also using realized and bipower variation in monitor the variance between price. At the end of the research, the authors suggest that oil companies’ stock performances are affected by the movement in stock price. Tansuchat, McAleer and Chang (2009) attempt to examine the relationship between the oil futures return and oil companies share returns. They has taking data for West Texas Intermediate (WTI) crude oil futures price and 10 largest oil companies stock price from year 1996 to year 2009. Those models used in this study are CCC, Vector Autoregressive Moving Average- Generalized Autoregressive Conditional Heteroskedasticity (VARMA-GARCH) and Vector Autoregressive Moving Average-Asymmetric Generalized Autoregressive Conditional Heteroskedasticity (VARMA-AGARCH) model. At the end of the study, the results show that there is a low conditional correlation of CCC model testing between WTI crude oil futures price and stock price. While, the results from VARMA-GARCH and VARMA-AGARCH model testing show that non existence of spread over effect between oil futures price and stock price. Last but not least, the authors also make a conclusion that VARMA-AGARCH is more suitable to use in this study compare with VARMA-GARCH models. Boyer and Filion (2004) attempt to identify the common factors that influence the stock price of Canadian oil and gas companies, they has examine the respond of Canadian oil and gas company stock price towards 5 factors namely interest rates, Canadian currency exchange rate, market return, oil and natural gas prices. The unit analysis of this research consists of 105 Canadian oil and gas base company. To begin this research, the authors have employed a Generalized Least Squared (GLS) cross-sectional time series linear model. The results shows that market return, crude oil and natural gas price has positively impact the stock price for oil and gas company. While interest rate and exchange rate shows a negative impact on stock price. On the other hand, the results has suggest that the impact derive from oil price towards stock market return of Canadian oil and gas company are more significance compare with the movement in natural gas price. H1: Crude Oil Price is positively related to oil company stock price.
Warren Bailey (n.d) has do a research relating to one of the rubber and palm oil producer call Highlands and Lowlands Bhd which listed in Stock Exchange of Singapore. This can be counted as an effort to identify the effect of variability in spot palm oil price towards the stock price of Plantation Company. In doing this research, the author has applied a discounted cash flow model developed by McDonald and Siegel (1985) with the assist of regression technique. The unit of analysis in this research consists of monthly share price, production and output data of Highlands and Lowlands Bhd. Moreover, the author also apply the data such as Singapore All-Share Index, taxable Singapore government bond yield, spot palm oil price, and spot rubber price. The result shows that spot palm oil price is positively correlated with Singapore All- Share Index on a level of 0.160. At the end of the research, the author hopes that the explanation of stock price behavior using the case of Plantation Company may give a clear picture for reader to understand. Basri and Zaimah (2002) are conducting a research in order to investigate the factors that influence Malaysia palm oil industry, has take into consideration the total oil palm yield, oil palm area, domestic consumption, export and imports into the research. The observation period fall between years 1970 to 1999. The authors have obtained data from Ministry of Primary Industries, Oil World, International Monetary Fund, and Malaysian Palm Oil Board. Among the methodology used are ordinary least squares (OLS), F-statistics, t-statistics, Durbin-h statistics, and Lagrange Multiplier (LM) statistics. For the testing done through oil palm area, the results shows that the variation in rubber and palm oil price is not significance in identifying the total area of oil palm plantation in Malaysia. For the testing done through total yield, results show that the technology that applies in palm oil industry has significant effect towards the improvement in palm oil yield. For domestic consumption, it shows that the consumption of palm oil do not fully depend on palm oil price and coconut oil price. Lastly, for export and import activities, the results shows that during the time when Malaysian Ringgit is soften, the exported quantity of palm oil tend to increase. For import activities, the results show that world price for palm oil and domestic price for palm oil are not significance in identifying the import level. Shamshuritawati (2002) has employed data ranging from January 1985 to December 2001.to investigate the fluctuation of palm oil price from time to time. Among the forecasting model used in this research are linear models, nonlinear model, moving average, seasonal variation, quadratic model, exponential smoothing and Box-Jenkins model. Besides that, there a total of 13 variables has take into the consideration of this research. At the end of the study, 3 models which are quadratic model, exponential smoothing model and Autoregressive Integrated Moving Average (ARIMA) model has been proof to be most effective to test the time series data of the palm oil price. Mad Nasir and Fatimah (1999) have come out a research with an effort to make a forecasting of Malaysia Crude Palm Oil Prices in short term period. The forecast period in this research fall between January to June 1999. Among the methodology employed in this study are Multivariate Autoregressive Moving Average (MARMA) model and Normal Autoregressive Integrated Moving Average (ARIMA). Besides that, the authors also come with equations that explain price, production, and consumption. The results from econometric analysis indicated that stock level has a influential towards the palm oil price. Fatimah and Zainalabidin (1994) have come out with a study relating to the price of crude palm oil futures as a contribution to the literature of palm oil price research. In this research, the data collected consists of monthly prices of crude palm oil fall on the period within 1983 to 1992. Among the two models that have been employed by authors are traditional efficient market model developed by Hanson and Hodrick, (1980), Bilson, (1981) and Bignman et al., (1983) and the recent efficient market hypothesis created by Rausser and Carter, (1983). After the testing has done, it has shows that futures market is efficient in process the information available. Thus, the price at any point of time has shows the information for demand and supply and other related information. Zuhaimy and Azme (2003) has put into effort to discover the application of feed forward neural network in forecasting the palm oil price. In this research, kinds of price for vegetable oil have take into consideration. The period of observation is range from year 1983 until year 2000. The currency used in measuring those kinds of data is in the form of America dollar. The methodology used here are forward neural network and propagation algorithm. As a conclusion, technique of neural network can be used as alternative in analyzing the data that involve multicolinearity. Azmi and Shamsul (2004) have conduct a research relating to the price relationship between futures and spot prices of crude palm oil contracts traded in Malaysian Derivatives Exchange. Among the data that employed in this study consists of spot month and 3 month futures prices for crude palm contract within 15 year period from year 1988 to 2002. In this research, the authors has using a model which developed by Longstaff (1995) for the purpose of approximating the convenience yield. As a result, the authors concluded that the application of model developed by Longstaff (1995) has better prediction capability than the simple cost of carry model. h3: Crude Palm Oil Price is positively related to plantation company stock price.
Twite (2002) has using data’s from 12 gold-mining firms from the period 1985 to 1998 with an intention to study the effect of gold price movement toward gold mining company stock price in Australia, A single and multi-factor market models has used to determine the stock price movement, gold price movement and the regression relationship among them. At the end of this research, the authors suggest that the changes in gold price have significance effect towards stock price for gold mining company. Where 1% change in gold price will cause 0.76% change in gold mining company stock price. Clare, Seaton, and Thomas (2008) have shows intention In order to exploring the relationship between the relationship between gold price and gold stock return. They have using 2 gold related indexes in North American namely Philadelphia Stock Exchange Gold and Silver Index (XAU) and American Stock Exchange Basket of Unhedged Gold Stocks (HUI). The authors have employed the market model that has employed before by Tufano in 1998 in calculating the returns on HUI index. Besides that, the authors also using HUI versus gold ration explaining HUI returns. As a conclusion, this study discovers that variation of gold stock towards gold price is not on a constant amount. After that, authors also note that the relationship between gold price and gold stock return become weaker and weaker in recent years. Borenstein and Farrell (2006) have done an investigation that consists of 17 gold-mining firms and weekly observation from year 1977 to 2004. This study aim to examine how the gold price may influence the stock market valuations of gold mining companies, in the study, the author has first test the relationship using Capital Asset Pricing Model (CAPM) market model of equity returns. Besides that, an econometric technique call Generalized Least Squares (GLS). As a conclusion, this research discovers that increase in gold prices will cause the increases in stock market values of many firms. diBartolomeo (1993) has conduct a research with an attempt to explain the behavior for stock price of gold mining companies in responds to the movement in gold prices, has employed the data ranging from monthly movement in stock price and J&J Precious Metals Mutual Fund Index that represent for gold stock price. The methodology used in this research are ordinary least squares regressions, At the end of the study, the results suggest that the gold stock return is significance in accordance with the change in gold price. Kim, Nam, and Wynne (2009) have conducting a research relating to the influence of changes in gold price on hedged and unhedged gold companies. This research aim to examine the hypothesis develop regarding the sensitivity of gold mining company stock towards the change in gold price, The data employed in this research are daily stock price for gold company from July 1998 to December 1999. Besides that, a total amount of 83 companies has been selected in this study. Nevertheless, the model use in this research is call as Seemingly Unrelated Regression (SUR). In results part, it shows that the influence of gold price movement towards stock price is relatively low for the companies that already hedge their risks in gold derivatives. However for those unhedged gold companies, the movement of gold price causes a greater effect for them. Jin and Jorion (n.d) has conducted a research towards North American Gold Mining Industry to determine the sensitivities of gold company stock return towards gold price. The selected sample in this research consists of 44 gold mining companies in United State and Canada in the period of year 1991 to 2000. In order to measure the firm value, the authors has employed methodology call Tobin’s Q where it is represent as market value of assets over the book value of assets. At the end of the research, the results suggest that gold hedging has reduced the exposure of gold mining company stock towards volatility in gold price. Last but not least, the results also suggest that hedging in gold price is inversely related to firm value. Callahan (2002) has shows an attempt to examine the gold mining companies’ hedging practice and their stock performance. He has first identified the regression alphas for 20 gold mining companies. Then, he examines the how stock price volatility influence stock returns. Next, he determine the how is the relationship between alpha and hedging. Last but not least, the author test how hedging influence stock price volatility. As a conclusion, there is an existence of the significant relationship between the extent of hedging activity and the movement of stock price. Blose and Shieh (1995) have employed the monthly data from 1981 to 1990 to determine the level of elasticity for gold mining stock towards the movement in gold price. The unit of analysis for this study consists of 23 public listed gold mining companies in US. In the beginning of the research, the authors have employed the theory special used for gold mining stock valuation. First, the authors identify the gold mine value and gold mining stock return. Then, the authors has done through 3 different empirical test, those 3 test are testing for value of firm, testing for elasticity of gold stock, and testing for gold price sensitivity. From the results, it shows that the elasticity of gold mining stock towards gold price is larger than 1. McDonald and Solnik (1974) have conduct a research to identify the returns of gold mining companies stock towards the changes in price of gold bullion in London and United states. In this research, they have used the model that link the expected return on gold stocks towards the return of gold and aggregate return in stock market. At the end of the study, the results suggest that at a higher gold price level that increase gold companies profitability, gold companies stock are positively related with the overall stock market return. H3: Gold Price is positively related to gold company stock price.
This chapter briefly explain the research methodology that used by the researcher in this study. Overall, this research focused on the relationship between commodities price and commodities base company stock performance. In the beginning of this chapter, Section 3.1 illustrates the theoretical framework designed for this study. Follow by Section 3.2 defines the independent and dependent variable incur in this study. Section 3.3 explains the development of hypothesis. Section 3.4 explains about the sources of data, where and how’s it come from. Section 3.5 shows how the data required in this study is collected. Section 3.6 explain the population and sampling in this study. At the end of this chapter, section 3.7 explains the methodology that need to employ in this study.
As shown in chapter 1 and 2, there is no doubt that the main interest of this research is to investigate the relationship between commodities price and commodity based company stock performance. Thus, Figure 3.1 has provided a diagrammatically illustration for the relationship between independent and dependent variables in this research. In this study, it is assumed that commodities prices have an influence towards the commodities company stock performance. Whereby, the higher the commodities prices, the better the performance of the commodities base company stock prices. In the research, there are 3 different independent variables as represent for commodities prices which are Crude oil (light sweet) price, Crude palm oil price and Gold (100oz) price. While for dependent variables, there are total 9 companies being selected in this study whereby 3 companies for each kinds of commodities. The 9 companies selected are related with oil, crude palm oil, and gold production. The relationship between independent and dependent variables are clearly label and be illustrated in figure 3.1.
Dependent Variables Independent Variable Dependent Variables Independent Variable Dependent Variables Independent Variable
In order to have a clear picture for the whole research, it is crucial to identify both the independent and dependent variable in the research. In facts, variables can be defined as anything that able to take on differing or varying values (Sekaran, 2003). Commonly, 2 major types of variables are independent and dependent variables. Independent variables are the one that affect the dependent variable in either a positive or negative way (Sekaran, 2003). While dependent variables are the variable of main interest to the researcher, whereby the goal of researcher is to understand and describe the dependent variables (Sekaran, 2003).
Commodity prices are represented as unit prices to enable easy and quick comparisons. The numerator of a unit price is a form of currency or other measurement of value, such as US dollars, and the denominator is a unit of the item being priced. Examples include price per piece, price per barrel, price per yard, price per gallon, and price per bushel. Financial assets or claims on physical assets have more or less similar unit prices (coleman, 2006).
Light Sweet Crude Oil (Physical) futures are an outright crude oil contract between a buyer and seller. The contracts also serve as a key international pricing benchmark. The contract size will be 1,000 barrrels, price quotation will be on U.S Dollars and Cents per barrel. The minimum fluctuation will be USD 0.01 per barrel. (CMEgroup, 2009)
Bursa Malaysia’s Crude Palm Oil Futures contract has been the global price benchmark for the Crude Palm Oil market since October 1980. The FCPO is a deliverable contract which is traded electronically on Bursa Malaysia platform. The contract size is 25 metric tons. Price is quote in Ringgit Malaysia and cent. Minimum Price fluctuation is RM1 per metric ton. (Bursa Malaysia, 2009)
Gold futures are hedging tools for commercial producers and users of gold. They are providing global price discovery and opportunities for portfolio diversification. The contract size is 100 troy ounces, Price Quotation in U.S. Dollars and Cents per troy ounce. The minimum price fluctuation is $0.10 per troy ounce. (CMEgroup, 2009)
Tansuchat, McAleer, Chang (2009) view that the value of stock prices in a popular equity pricing model theoretically equals the discounted earning expectation of companies in future or in other words future cash flows. The commodity base company mention here are those company with their principal business is deal with commodity. For example, Plantation Company, oil and Gas Company and gold jewel company. The Information of principal business for a company is get from company annual report available at Bursa Malaysia web site.
Hypothesis can be defined as a logically conjectured relationship between two or more variables which deliver in the form of a testable statement (Sekaran, 2003). In order to identify the relationship between commodities price and the commodities based company stock price performance, various hypothesis have been developed. The hypothesis developed should be tested in this study. Those hypotheses are created based on the literature survey that done on chapter two.
Crude Oil takes an important role in country development; it serves as the resource for many industries ranging from transportation industry to oil refinery industry. Commonly, the appreciation in crude oil price will enhance the revenue and profits of Oil Company. On the other hand, those companies like transportation service operator and plastic making company will suffer for the higher costs incur which reduce the profitability of business. As one of the main interests of this research, the relationship between crude oil price and oil company stock performance is discover. The following are the outcome and conclusion from previous research. First, Sadorsky (2001) found that there is an existence of significant positive relationship between the price of crude oil and oil and gas equity index. Then, Huang et al. (1996) reported that shocks to the oil price would positively affect the oil index. Next, Nandha and Faff (2007) found that oil price rises have a negative impact on equity returns for all sectors except mining, and oil &gas industries. Furthermore, Faff and Brailsford (1999) reported significant positive oil price sensitivity of Australian oil and gas, and diversified resources industries. H0: Crude Oil (Light Sweet) Futures Price is negatively related to oil company stock price. H1: Crude Oil (Light Sweet) Futures Price is positively related to oil company stock price.
Crude palm oil takes an important role in Malaysia context. Appreciation in crude palm oil price will enhance the profit margin and earnings for Plantation Company. As one of the main interests of this research, the relationship between crude palm oil price and plantation company stock performance is discovering. The following are the outcome and conclusion from previous research. Firstly, Warren Bailey (n.d) suggests that spot palm oil price is positively correlated with Singapore All- Share Index. H0: Crude Palm Oil Futures Price is negatively related to plantation company stock price. h3: Crude Palm Oil Futures Price is positively related to plantation company stock price.
Gold take an important role nowadays as an instrument in store of wealth. Appreciation in Gold price will undeniably allowed gold companies to charge more for the gold product that offer. Thus, the stock price behavior of gold company will perform better. As one of the main interests of this research, the relationship between gold price and gold company stock performance is discovering. The following are the outcome and conclusion from previous research. Twite, (2002) says 1% change in gold price will cause 0.76% change in gold mining company stock price. Then, Tufano (1998) found that they expect a 1% increase in gold to lead a 3% to 10% increase in their stock returns. Next, McDonald, Solnik (1974) suggest that higher gold price level that increase gold companies profitability, gold companies stock are positively related with the overall stock return. Furthermore, Shieh (1995) states that gold price sensitivity of a mining stock is greater than one. H0: Gold (100oz) Spot Price is negatively related to gold company stock price. H3: Gold (100oz) Spot Price is positively related to gold company stock price.
The sources of data in this research comprised only secondary data. According to (Sekaran, 2003), secondary data refer to information taken from sources that already existing. There are several sources of secondary data which consist of database, annual report of companies, government statistics, and so on. By employing secondary data in the research, time and costs of requiring information can be saved besides the data are readily available.
Data collection procedure is the important step in any research whereby it will directly affect the validity and relevancy of the research. In this research, most data are collected from Thomson DataStream and Yahoo Finance. Among the data collected are Crude Oil (Light Sweet) Futures Price, Gold (100oz) Spot Price, Crude Palm Oil Futures Price, and stock price for selected Malaysian commodity based company. The data are collected on time series basis (daily data) from year 2004 to 2009. Besides that, company information such as financial data and principal activities are collected from annual report which available at Bursa Malaysia web site. Data collected from annual report used to assist the main interest of this research.
As shown in the selection of variables section, the dependent variable of this study comprise of stock price for 3 kinds of company which consists of oil, plantation and gold company. In this study, 3 companies which are represent able for the whole industry is selected. For Oil Company, the companies selected are Petronas Dagangan Berhad, Shell Refining Company (FOM) Berhad, and Esson Malaysia Berhad. For Plantation companies, the companies selected are IOI Corporation Berhad, Kuala Lumpur Kepong Berhad, and Kulim (Malaysia) Berhad. For gold companies, the companies selected are Poh Kong Holdings Berhad, TOMEI Group, and Habib Corporation Berhad. To identify those companies selected as commodity based companies, the information regarding the principals activities of those companies are getting from annual report.
In order to effectively identify the relationship between commodity price and commodity based company stock performance, several kinds of data analysis technique are employed in this research. With the assist of statistical software E view, the testing for hypothesis can be done. Among the data analysis technique used are Pearson Correlation Analysis, Augmented Dickey Fuller Unit Root Test, Johansen Juselius Cointegration Test, and Granger Causality Test. The results from statistical testing will indicate which hypothesis has to be accepted and which one has to be rejected.
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