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The Relationship Between Macroeconomic Variables and FTSE Bursa Malaysia Kuala Lumpur Composite Index

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The Relationship Between Macroeconomic Variables and FTSE Bursa Malaysia Kuala Lumpur Composite Index ISSN (Print) : 0974-6846 Indian Journal of Science and Technology, Vol 10(12), DOI: 10.17485/ijst/2017/v10i12/112974, March 2017 ISSN (Online) : 0974-5645 The Relationship between Macroeconomic Variables and FTSE Bursa Malaysia Kuala Lumpur Composite Index Nur Ainina Awang, Siti Aida Sheikh Hussin and Zalina Zahid Department of Statistics and Decision Sciences, Universiti Teknologi MARA, Shah Alam, Malaysia; [email protected], [email protected], [email protected] Abstract This study aims to examine the relationship between top ten constituents in FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBM KLCI) with a set of macroeconomic variables and industrial production using Johansen co-integration test. This study also analyzes the respond of each macroeconomic variable on the stock indices using Impulse Response Function with macroeconomic variables and that the shocks of stock indices on its own shock contribute the largest portion followed by(IRF) money and forecastsupply. In error addition, decomposition. we apply GARCH The findings (1, 1) showmodel a to long-run determine relationship which macroeconomic between each affectsstock index volatility in FBM of stockKLCI indices. The result shows that macroeconomic volatility does not affect much on Genting and IHH Healthcare, but Public Bank Bhd, Tenaga Nasional, Malayan Banking, CIMB Group Holdings, Axiata Group Bhd, Petronas Chemicals Group Bhd are affected by the volatility of macroeconomic variables. Keywords: Forecast Error Decomposition, Impulse Response Function, Johansen Co Integration Test 1. Introduction Malaysian composite index, however the macroeconomic variables on stock indices may give different out comes Equity prices, considered as the most firmly watched as compared to the broader market index. Thus, this prices of companies’ assets, can easily fluctuate throughout is the motivation to perform this research where the trading days as they are very susceptible to changes interrelation between macroeconomic variables that in the stock market. Factors such as high volatility or are exchange rate, interest rate, inflation rate, money irregular developments can cause adverse implications supply and industrial production and the stock indices for the economy while uncontrolled volatility may keep in FBM KLCI. This paper also analyses the respond of the smooth working of financial market and unfavorably each of the stock indices in FBM KLCI to each of selected influence the performance of the economy7. According macroeconomic variables and determine the volatility of to10, stock market volatility rises during financial crisis macroeconomic variables that influenced volatility in the and causes stock prices to plunge especially in developing stock indices in Malaysia. markets. Malaysian stock market under Bursa Malaysia 2. Literature Review represents the largest 30 organizations in the main market by full market capitalization which turns into the factor Many research reported contradicting results on the link for the execution of the Malaysian stock market FBM between macroeconomic variables and stock market. KLCI. 17Applied Vector Error Correction Model (VECM) to Most of the previous researches focus on the see the repercussion of four macroeconomic variables association of various macroeconomic variables and the that are consumer price index, industrial production * Author for correspondence The Relationship between Macroeconomic Variables and FTSE Bursa Malaysia Kuala Lumpur Composite Index interest rates and inflation rates on New York stock 3. Methodology exchange (NYSE) for the duration from March 1964 to June 2010. The outcomes show that size has a concussion 3.1 Data on equities returns, while interest rate and inflation has The dependent variables are the top ten constituents an unfavorable interrelation with stock prices. This study in FBM KLCI while the independent variables chosen shows that macroeconomic activities predominance the are interest rate, money supply, exchange rate, inflation equities positively. rate, and industrial production. The monthly data of the 14 Investigated the interrelationships between BSE variables were obtained from Data Stream for the period Sensex index which is the Indian stock market indicator from July 2012 to December 2015. with a set of macroeconomic variables comprising of Basically there are ten models. Model 1 represents industrial production index, exchange rate, money supply, Public Bank Bhd, Model 2 for Tenaga Nasional, Malayan treasury bills rate, and wholesale price index by applying Banking is represented by Model 3. Model 4, Model Johansen’s co-integration and VECM. The results reveal 5, Model 6, Model 7, Model 8, Model 9 and Model 10 that the stock prices are changing in the same direction represent Sime Darby Bhd, CIMB Group Holdings, Axiata to the amount of money supply and industrial production Group Bhd, PETRONAS Chemicals Group Bhd, Genting, macroeconomic variables. IHH Healthcare and PETRONAS Gas respectively. Granger causality test shows no evidence in the short- run analysis or in other words macroeconomic variables cause the equities prices only in long-run. However, there 3.2 Analysis on the Relationship between is a two directional influences that exist between equity Macroeconomic Variables and Stock prices and industrial production, while one directional Indices influence between interest rates to stock prices, money We apply Johansen and Juselius co-integration test to supply to stock price, and stock price to inflation. estimate the long-run relationship among the variables, 7Applied the exact model as14 in order to inspect with reference to the methodology by7. and analyses the long term dynamic interrelationship among equity prices and monetary variables (money 3.3 Analysis on the Measures for Volatility supply, Treasury bill rates, foreign exchange rates and the According to18, most of the existing studies on volatility consumer price index) in Pakistan. The results reveal that used GARCH model as the model is capable to capture there is a long-term dynamic relationship between the not only volatility clustering but also unconditional return Pakistani equity market and monetary variables and this distribution with heavy tails. 14 is consistent with the results reported by . The conditional mean equation that adopted AR (1) 1 Similarly, Also used multivariate Johansen co- is as follows: integration test to study the character of macroeconomic =+ll + e variables that are inward foreign direct investment, ytt01 AR(1) Treasury bill rate, the consumer price index and exchange yt denotes the monthly return of top constituents in rate on equity prices development in Ghana. Their FBM KLCI, AR (1) represents the pure autoregressive investigations revealed co-integration exist between components. The conditional variances in stock macroeconomic variables and equity prices in Ghana in prices is hypothesized and determine by the chosen long-term relationship. Besides, the study reveals that macroeconomic variables that are money supply, inflation rate is certainly representative to the equity exchange rate, inflation rate, interest rate, and industrial prices. production. Therefore, the conditional variance equation 12 Examined the relationship between stock indices of applied in this study is as follow: the Bombay Stock Exchange against industrial production, 2 2 2 σ = ϕ + α ε + β σ + ω LNEX + balance of trade, foreign exchange reserves, money supply t 1 t −i 1 t − j 2 and exchange rate. They found that industrial production, ω3LNBLR + ω4 LNMS + ω5LNCPI + ω6 LNIP exchange rate, foreign exchange reserves has significantly ϕ α Where denotes the constant, 1 is the coefficient contradict towards the sector indices of The Bombay Stock of the lagged squared residuals based on ARCH terms, Exchange while significantly positive on money supply. β1 is the coefficient for the GARCH terms and ωi 2 Vol 10 (12) | March 2017 | www.indjst.org Indian Journal of Science and Technology Nur Ainina Awang, Siti Aida Sheikh Hussin and Zalina Zahid where i = 2, 3, 4, 5 and 6 is the coefficient for the selected Chemicals Group Bhd (PETC), Genting (GENT), IHH macroeconomic variables. Healthcare (IHH) and PETRONAS Gas (PETG) and macroeconomic variables in a long-run equilibrium. 4. Findings and Discussions The results on the long run relationship in this study are consistent with most of the existing studies such as1,4,5,9,14 Table 1 displays the results of the descriptive statistic. Afzal and Hossain (2011), Ali and Akujuobi (2014). All the variables have positive mean return value. Based Based on the results shown in Table 3, exchange rate on the standard deviation values, the table shows that (LNEX) shows a negative relationship with all stock Tenaga Nasional (TNB) and IHH Healthcare (IHH) are indices in FBM KLCI except with PETRONAS Chemicals more volatile compared to Public Bank BHD (PB), CIMB Group Bhd (Model 7) and IHH Healthcare (Model Group Holdings (CIMB) and Genting (GENT). The rest 9). The negative link between exchange rate and stock of sector indices show a low volatility. Besides, Table 1 also indices can be explained because the depreciation in shows that all the stock indices except Sime Darby Bhd Malaysian Ringgit (MYR) would cause more investors do (SIME) are skewed to the left and has an excess kurtosis not interested to invest in Malaysian market. since they deviated from three2. Meanwhile, inflation rate has a positive relationship Table 2 shows the summary of co-integration
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