An empirical analysis of sectoral indices movement in Malaysian stock market

Abstract

The aim of this study is to investigate the dynamic movement between sectoral indices in the Malaysian Stock Market and the three macroeconomic variables, namely oil price (OP), gold price (GP), and exchange rate (ER) during the period 1995-2014. Using the Augmented Dickey-Fuller and Phillip Perron unit root test, the underlying series are tested as non-stationary at the level but stationary in first difference. The use of Johansen-Juselius (1990) Multivariate Cointegration and Vector Error Correction Model indicate that there is long run linkages between macroeconomic variable and sectoral indices specifically in Technology sector. Meanwhile, the analysis based on Vector Auto regression Model technique indicates that there are short run linkages between macroeconomic variable and sectoral indices namely Financial, Industrial, Consumer Product, Industrial Product, Properties and Trade and Service.

The impacts of global economic policy uncertainty on stock market returns in regime switching environment: Evidence from sectoral perspectives

“…Thus, this finding is conformity with the hypothesis of the market model and CAPM. This finding is also in line with findings of the extant studies that related to Malaysian sectoral equity analysis (Jafarian & Safari, ; Law & Ibrahim, ; Pyeman & Ahmad, ).…”

Modeling Long-Term Relationships in Philippine Stock Market (PSE) Indices: A Cointegration Analysis

“…These results are similar to those in the study on the Indian stock market, in which Minimol and Makesh (2017) found that the main indices, BSE Sensex and CNX Nifty, were stationary at first difference. Moreover, other sectoral indices in the NSE (India) market were also stationary at the first difference (Pyeman & Ahamad, 2017). Table 4 exhibits the results of the Johansen cointegration test between the PSEi and the six sectoral indices.…”

“…Fama (1970) shared his work on unpredictability when he investigated the daily price changes of the Dow Jones Industrial Average in the US during the period 1957-1962. Over the past few decades, several academic scholars and financial market experts have been focusing their attention on modelling stock movements, particularly through stock indices. Generally, studies link stock indices with macroeconomic variables (Basci & Karaca, 2013;Pyeman & Ahamad, 2017). Forecasting the movement of stock prices is deemed to be one of the main problems of every investor and fund manager.…”