Relationship Between Economic Variables And Sub Sector Price Finance Essay - Free Essay Example

This chapter provides an outline of the research process designed to investigate the relationship between economic variables and Sub-sector price index. 3.1 The Data In this section, we will summarize our models data and present the methodology of our model. The daily data for interdependent and dependable variables e.g. FBM KLSE (Kuala Lumpur Composite Index), T-Bill band 4, Crude oil WTI (West Texas Intermediate) price, Gold Bullion LBM (U$ Troy Ounce) price, T-bill band 4, Kuala Lumpur Composite Index (KLCI) price index, and Sub-sector Price Index are collected from the DataStream and cover from period 17/04/2000 to 18/04/2011. There are 2610 daily observations obtained from DataStream. The data set is given in the Appendix of this paper. In relation on this, dependable variable are consists of ten (10) majors price index e.g., Consumer Product, Plantation, Finance, Trading and Services, Industrial, Industrial Products, Construction, Mining, Properties, and Technology. As can be seen from figure 1, there is an increasing trend on global gold price and reached its the highest point, $ 1,492.06, on April, 2011. The gold price was tending to increase since year October, 2008. We believe this trend will continues increasing due to strong demand and short supply gold in the commodities market. Moreover, some expertise research firms like GFMS, a leading global precious metals consultancy, released its 2011 Gold Survey and GFMS expects that gold will reach $1,600 by the end of 2011. Another independent variable, Crude oil WTI (West Texas Intermediate) price known as Texas light sweet, is a type of crude oil used as a benchmark in oil pricing. As refer to figure 2, the oil price increase significantly during year 2007 and the reasons behind can be explained by the Asian growing demand on oil to sustain their economy growth. The past researchers also been reported, that oil consumption in India was increased approximately 8.7% according 1998 and 6.5% according to 2006. Mehmet Eryigit (2009) has studied and found that in year 2007, USA has been consumed the 23.9% of the total oil, however total share of the world oil cons umption for China, India and Turkey in 2009 is only accounted 13.4% (China consumed 9.3%, India consumed 3.3%, and Turkey consumed 0.8%). Meanwhile, back to middle of year 2008 Sub-prime crisis was happened in U.S financial system and the crude oil price has reached to a minimum price $31, that is a minimum last trader price was reported since year 2004. After decreasing trend along the year 2008, early of 2009 crude oil price are in recovery stages and maintained a reasonable price between $ 65 -$ 100 per barrels. We expect the crude oil will continue increasing. The next independent variable is Market returns FBM Kuala Lumpur Composite Index (KLCI). The Kuala Lumpur Composite Index (KLCI) is used as a proxy for the performance of the Kuala Lumpur Stock Exchange and comprises the largest 30 companies listed on the Main Board by full market capitalization. The last independent variable is T-Bill band 4. T-Bill band 4 is type of money market instrument. The Malaysian Treasury B ills (MTB) issued by the Central Bank of Malaysia Are tradable on yield basis (discounted rate) based on bands of remaining tenure (e.g., Band 4 = 68 to 91 days to maturity). This instrument are represents the short-term interest rate in the Malaysia money market. The high or low interest rate will make bonds look more attractive than stock and consequently impact the stock price return. Figure 1: Gold Bullion LBM (U$ Troy Ounce) Price Figure 2: Crude Oil WTI (West Texas Intermediate) Price 3.2 Conceptual Framework 1. Crude Oil WTI 2. Gold Bullion LBM (U$Troy Ounces) 3. KLSE (Kuala Lumpur Composite Index) 4. T-Bill Band 4 Sub Sector Price Index Consumer Product, Plantation, Finance Trading and Services, Industrial, Industrial Products, Construction, Mining, Properties, and Technology.The conceptual framework of this study was derived from literature review where proven macroeconomic variables that effect FBM Kuala Lumpur Composite Index (KLCI) are used as independent variables, Crude oil WTI (West Texas Intermediate) future contract price, Gold Bullion LBM (U$ Troy Ounce) price, and T-bill band 4 had been widely used in evaluating relationship between macroeconomic variables and Sub-sector price index. Further to that, crude oil price is also proven to be a macroeconomic variable that direct impact to the conditional of the stock market. In fact, oil price can affect prices directly by impacting future cash flows or indirectly through an impact on the interest rate used to discount future cash flows. 3.3. Design of Study The Arbitrage Pricing Theory (APT) is an expansion model of Capital Asset Pricing Model (CAPM) Single -factor model. That is, it specifies risk as a function of only one factor, the securitys beta coefficient. In a reality, the risk / return relationship is more complex, with a stocks required return a function of more than one factor. For example, CAPM method is not suitable on this research because there are a various interdependent variables effect the dependent variables. Thus, we should adopt the APT (Arbitrage Pricing Theory) model to define and analyses these factors. A statistical technique that simultaneously develop a mathematical relationship between a single depend variable and two or more independent variables. With the four independent variables the prediction of Y is expressed by the following equation: Regression equation is; Multi-factor Model: Rit = ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€šÃ‚ + BetaMRtMRt + Betaoil Oilt + BetaGoldGoldt+ BetaT-billT-billt (1) Indicators: ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€šÃ‚  = Intercept / Alpha Rit = Return on major sub sector MRt = Market Returns Oilt = Oil Returns Goldt = Gold Returns T-billt= T-bill Returns Where the Sub sector price index is a dependent variable and it shows the return on the Sub sector price index. Beta is constant term and we have four (4) independent variables; Gold price, Oil price, Market returns, and short-term interest rate respectively. We used Ordinary Least Squares (OLS) method to evaluate the relationships between the Gold price, Oil price, Market returns, and short-term interest rate against the ten (10) sub sector price index. The market return was benchmark to the FBM Kuala Lumpur Composite Index (KLCI) composite share price index. Time series of short-term interest rate taken over the T-bill band 4, which is considered to be the short-term interest rate (risk-free interest rate). The first steps, we required to find the return of each independent and dependent variables using below formula: Daily return formula is calculated using as per below: Ri,t = (Pi,t Pi, t-1)/ (Pi, t-1) (2) Where; Ri,t is the price return of ith variable on time t Pi, t is the closing price of day t for variable i. Pi, t-1 is the closing price previous of day t for variable i. Then daily returns are aggregated that are our preliminary input to run regression analysis. The sample period for our study extends from periods 17/04/2000 to 18/04/2011. Then after, used the input and the multi-factor model to run the regression analysis on each interdependent and dependent variable to examine whether each of them have any significant relationship. In additional, sub-part of the analysis section will examine the Gold Oil ratio analysis, the purpose is to determining whether the current Gold Oil ratio is below th e benchmark ratio is either too cheap, or crude oil is too expensive otherwise when ratio is greater than benchmark, oil is either too cheap or gold. Sub-parts of the session will analysis on Gold ratio trend from period 17/04/2000 to 18/04/2011. The mean of gold oil ratio as an indicator for investor to decide whether the gold price is expensive, crude oil prices is cheap or the gold price is cheap, crude oil price is expensive. Using below formula: Gold Ratio = Gold Price0, t / Crude oil Price0, t (3) Where; Gold Price0, t is the closing price of day t for Gold. Crude oil Price0, t is the closing price of day t for Crude oil. CHAPTER 4 FINDINGS AND DISCUSSION This chapter presents the findings of the study and provide a through discussion and analysis of the findings. 4.1 Data Analysis To observe the effect of crude oil price, gold price, market returns, and short-term interest rates, the regression is calculated by using Ordinary Least Square (OLS) estimation procedure. Results are presented in Table 1. Referring to the result obtained from Ordinary Least Square (OLS) analysis, the result found that gold and market return have a positive significant statistical relationship with consumer price index at 5% significant level. These also make a same result for plantation price index. The result implies that gold and market return have a positive significant statistical relationship with plantation price index. Between, the trading and services index shows positive significant relationship with market returns but negative statistical relationship with gold. It implies, when the trading and service price index increase 1% the gold price will decrease 0.011%. Moreover, the regression model is statistically useful in explaining the variation in the Finance, mining, and technology price index with 95% confidence level. The result shows positive significant relationships with market returns. In additional, the industrial, industrial product, and properties price index regression model analysis results shows that market returns have a positive significant statistical relationship with three sub-sector price index. On the other hands, the industrial price index show negative significant statistical relationship with crude oil price at 5% significant level but the industrial product and properties have a positive significant statistical relationship with crude oil price. Finally, from the regression model analysis result found that, only the construction price index has a negative significant statistical relationship with t-bill at 5% significant level and others sub sector price index dont have any statistical relationship with the T-bill. 4.2 Subpart Analysis Gold/ Oil Ratio Gold Oil Ratio is an expressed mathematically as the per-ounce price of gold divided by the cost of a barrel of crude oil, the ratio was telling us how many barrels of oil can be bought with an ounce of gold. Even though oil and gold are thought to be hedging on inflation, their price movements arent in lockstep. Since the 2001 launch of the current bull cycle, the correlation between U.S. benchmark West Texas Intermediate (WTI) crude oil and the London morning gold fix is only 23 percent. In fact, its the lack of a tight correlation that makes the gold/oil ratio meaningful. The ratio can fluctuated over time; since 2002, one ounce of gold could have bought between 11 and 16 barrels of oil. In midyear 2008, as oil prices surged, gold scraped a historic low at a 6x multiple (a 6-to-1 ratio). After half year later, the ratio had shoot to the 23x level after massive de-leveraging sent oil prices down $100 a barrel. Over the longer term-say, the past four decades-the average m ultiple has been 15x. Signals: The gold-oil identifies: Buying opportunities (for gold) when the gold-oil ratio turns up at/below 7 barrels/ounce; and Selling opportunities when the gold-oil ratio turns down at/above 12 barrels/ounce. Table 1: Minimum and Maximum Gold Oil Ratio Record during the Period.  2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Max 15,18 15,74 13,85 11,67 8,94 11,08 12,54 23,11 28,05 17,55 16,29 Min 9,14 10,56 9,35 11,67 6,96 8,22 8,33 6,52 13,15 13,69 13,98             Table 2: Summary Table  Consumer Product Plantation Finance Trading services Industrial Industrial Product Construction Mining Properties Technology Market return ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ Oil ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ'Æ’- Gold ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ'Æ’- ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- T-Bill ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ'Æ’- ÃÆ' ¢Ãƒâ€¹Ã¢â‚¬  Ãƒâ€¦Ã‚ ¡ = Significant at 5% ÃÆ'Æ’- = No significant at 5% Table 3: ANOVA Table: Components Consumer Product Plantation Finance Trading services Industrial Coefficient Intercept 0,0002420 0,0003258 0,0000982 (0,0000444) 0,0000733 KLCI PRICE INDEX 0,5623974 0,9784759 1,0645010 0,9994746 0,7729328 Crude oil (0,0054988) (0,0018498) 0,0025010 0,0026129 (0,0109819) Gold 0,0158866 0,0441310 (0,0037211) (0,0112407) 0,0098721 T-bil (0,0034387) (0,0048518) (0,0059951) 0,0023219 (0,0004433) Adjusted R Square 0,5606859 0,5041736 0,8081372 0,8927299 0,6798043  P-value Intercept 0,00310016 0,04191723 0,24917804 0,43452323 0,39876364 KLCI PRICE INDEX Crude oil 0,0931 0,7729 0,4634 0,2512 0,0016 Gold 0,0258 0,0016 0,6160 0,0233 0,1922 T-bil 0,4479 0,5845 0,2042 0,4613 0,9267 Components Industrial Product Construction Mining Properties Technology Coefficient Intercept (0,0000330) (0,0001192) 0,0006207 (0,0000617) (0,0006292) KLCI PRICE INDEX 0,7928138 1,1884864 0,8354046 0,9573352 0,9419663 Crude oil 0,0092151 0,0029884 (0,0115321) 0,0112074 0,0049796 Gold 0,0145574 0,0093185 (0,0493598) 0,0059426 0,0372188 T-bil (0,0030311) (0,0202644) 0,0016072 (0,0024516) (0,0004453) Adjusted R Square 0,6357414 0,6109031 0,0462843 0,5468360 0,3246577  P-value Intercept 0,73923273 0,44480430 0,30905151 0,66749650 0,00515217 KLCI PRICE INDEX 0,000000 0,000000 Crude oil 0,0203 0,6323 0,6369 0,0515 0,5801 Gold 0,0918 0,4929 0,3531 0,6349 0,0574 T-bil 0,5810 0,0191 0,9621 0,7582 0,9715