Straits Times Index Research Articles

Analysis of Cointegration and Causality Relationship among Selected Stock Market Indexes in the World and Indonesia Stock Exchange Composite Index (IHSG) for the Period 2005-2017

This research aims to analyze the cointegration and causality relationship among selected stock market indexes in the world and Indonesia Stock Exchange Composite Index (IHSG) for the period 2005 until 2017. The stock market indexes are selected based on the trading relationship between Indonesia and other countries in the non-oil and gas sectors. The selected stock market indexes are Dow Jones Industries Average, Bombay Stock Exchange Sensex, Kuala Lumpur Stock Exchange, Nikkei, Korea Stock Exchange, Stock Exchange of Thailand, Shanghai Composite, Straits Times Index, and Indonesia Stock Exchange Composite Index (IHSG). This research is a time series research which uses monthly data from January 2005 until December 2017 and Augmented Dickey-Fuller Test, Lag Optimum, Johansen Cointegration Test, Granger Causality Test, Vector Error Correction Model (VECM), Variance Decomposition, and Impulse Response Function. The results of the research show that there is cointegration among selected stock market indexes and Indonesia Stock Exchange Composite Index (IHSG) and there is causality among selected stock market indexes and Indonesia Stock Exchange Composite Index (IHSG).

CO-MOVEMENT AND CAUSAL RELATIONSHIP BETWEEN STOCK MARKET AND MACROECONOMIC VARIABLES: LATEST EVIDENCE FROM MALAYSIA

Previous studies pertaining to the co-movement and causal relationship between Malaysian stock markets and domestic macroeconomic variables are by now quite well documented. Nonetheless, to the best of authors’ knowledge, there is a void in the literature about foreign macroeconomic variables. Therefore, this paper aims to examine co-movement and causal relationship between FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) with foreign macroeconomic variables namely world crude oil price, gold price, and five world major stock market indices; Singapore’s Straits Times Index (STI), Chinese Shanghai A-Share Index (SHAI), the US’s Dow Jones Industrial Average (DJIA), Hong Kong’s Hang Seng Index (HSI) and Japanese Nikkei 225 Index (NIK). We also include domestic macroeconomic variables namely private sector domestic credit, gross international reserves and foreign currency assets, and an exchange rate of Malaysian ringgit (MYR) to the US dollar (USD) in this study. Using 9-year monthly data series from 2010 to 2018, the Augmented Dickey-Fuller (ADF) test reveals that data series have unit root in level order, but become integrated when converted into the first difference. The t-statistics of the Trace test suggests that FBMKLCI co-moves with Malaysian gross international reserves and foreign currency assets, world gold price and STI in the long run, respectively. Further, the VECM notes the absence of long-run or short runs causal relationships except Singapore’s STI to FBMKLCI in the short run. The pairwise Granger causality test indicates a one-way causal relationship running from FBMKLCI to gross international reserves and foreign currency assets. The findings benefit stock market investors, diversified portfolio fund managers, market regulators, and policymakers besides enriching the existing literature.

Keterkaitan Antar Bursa Efek Dunia (Studi Kasus pada Bursa Efek Negara Maju dan Negara Berkembang)

This research analyzes the correlation between stock markets worldwide. Developing countries stock exchanges are represented by China and Indonesia, whereas developed countries stock exchanges are represented by Germany, Japan, Australia, Singapore, and the United States. Using stock’s daily close prices as data, then assessed with Vector Error Correction Model and Granger Causality. Analyzed indexes are Shanghai Stock Exchange Composite (SHCOMP), Indeks Harga Saham Gabungan (IHSG), Dow Jones Industrial Average (DJIA), Nikkei225 (NKY), Deutscher Aktien Index (DAX), All Ordinaries Index (AOI), and Strait Times Index (STI). Stock data grouped into two periods, the first period is the Asian Financial Crisis in 1 January 1998-31 December 2003, while second period is the Subprime Mortgage crisis in 1 January 2008-31 December 2013. Research results show correlations between analyzed stock indexes in both long run and short run relationship in the firstperiod as well asthe second period, however the correlation between Singapore’s and Indonesia’s stock exchange in second period is unproven.

Quantifying the correlation and prediction of daily happiness sentiment and stock return: The Case of Singapore

In this paper, with the newly emerged Twitter happiness index, we employ the VAR regression, linear, and nonlinear Granger causality tests to investigate the predictive correlations between daily happiness sentiment (DHS) and Singapore Straits Times Index (STI) stock performance indicators. The empirical results reveal that DHS presents significant predictability with future STI return. While, for the realized volatility, no compelling forecasting powers are detected. We also perform another two subsample tests as robustness checks. In general, the subsample results are in line with those of the full sample.

DETERMINAN TINGKAT SUKU BUNGA, INDEKS DOW JONES, NIKKEI 225, DAN STRAITS TIME TERHADAP ISSI

<p><em>Islamic financing is a kind of investment that has system and operational based on sharia principles. Islamic financing is supervised by the Sharia Supervisory Board (DPS). This is to safeguard that there are no commercial involved such as gambling, usury, and prohibitedproducts. The indexfluctuation in the capital market of a country is influenced by world capital market indices. The first Islamic index in world is the Dow Jones Islamic Market Index (DJIM). Based on the discussion about the influence of Interest Rate variables, Dow Jones Islamic Market, Nikkei 225 Index, and Straits Times Index on the Indonesian Sharia Stock Index variable for June 2012 until March 2017 the conclusions are as follows: Interest Rate has a negative effect on the Indonesian Sharia Stock Index, Dow Jones Islamic Market has a positive effect on the Indonesian Sharia Stock Index, the Nikkei 225 has a negative effect on the Indonesian Sharia Stock Index, the Straits Times negatively affects the Indonesian Sharia Stock Index</em></p>

Big 5 ASEAN capital markets forecasting using WEMA method

ASEAN through ASEAN Economics Community (AEC) 2020 treaty has proposed financial integration via capital markets integration in order to aim comprehensive ASEAN economic integration. Therefore, the need to have a proper prediction of ASEAN capital market becomes a major issue. In this study, we took big 5 ASEAN capital markets, i.e. Straits Times Index (STI), Kuala Lumpur Stock Exchange (KLSE), Stock Exchange of Thailand (SET), Jakarta Stock Exchange (JKSE), and Philippine Stock Exchange (PSE) to be forecasted using WEMA method. Weighted Exponential Moving Average (WEMA) is a new hybrid moving average method which combines the weighting factor calculation in Weighted Moving Average (WMA) with the procedure of Exponential Moving Average (EMA). WEMA has successfully been implemented and used to forecaste discrete time series data, but never being used to forecast ASEAN capital markets. In this study, we took further action by implementing the WEMA method with brute force approach for scaling factor tuning on big 5 ASEAN capital markets. From the experimental results, we found that WEMA has successfully forecasted all those exchanges. By looking at the forecast error measurement, it gives the best performance on PSE and worst performance on SET dataset among all datasets being considered in this study.

ANALISIS PENGARUH INDEKS HARGA SAHAM GABUNGAN REGIONAL ASIA TERHADAP INDEKS HARGA SAHAM GABUNGAN INDONESIA

ABSTRACTThe aims of this research is to analyze the influence of NIKKEI 225 Index (^N225), HANG SENG Index (^HSI), KOSPI Index (^KS11), Strait Times Index (^STI), and Kuala Lumpur Stock Exchange (^KLSE) simultaneously and partially in Jakarta Composite Index (^JKSE) during 2009 to 2017. Method of multiple linier regression with significant level 0,05 using STATA 10 program. The populations and samples was used this research is stock index on ASIA regional (NIKKEI 225 (Japan), HANG SENG Index (Hongkong), KOSPI (South Korea), Strait Times Index (Singapore), Kuala Lumpur Stock Exchange (Malaysia), and Jakarta Composite Index (Indonesia)) was conducted during January 2009 to May 2017. Results of this research simultaneously model for all independent variables are influence to dependent variable. However, parcially model ^N225, ^KS11 and ^KLSE variables positive and significant influence to ^JKSE variable. Whereas ^HSI and ^STI variable are not effect to ^JKSE variable during January 2009 to May 2017.Keywords: JKSE; N225; HSI; KS11; STI; KLSE.

Pengaruh Kurs, Suku Bunga BI, Indeks STI, Indeks KLSE dan Indeks MC Terhadap Indeks Harga Saham Gabungan Di BEI Periode September 2014-Desember2015

The aims of this research are to analyze the influence of Strait Times Index, Kuala Lumpur Stock Exchange index, and Manila Composite index on strengthening or weakening relation of exchange rate and BI rate against Jakarta Composite Index from September 2014-December 2015. This research used secondary data and a quantitative research . The type of research used is explanatory research ,the population are stock price indices in Bursa Efek Indonesia and sample used is Jakarta Composite Index which shows daily prices fluctuation of all stocks. Analysis methode used is moderated regression analysis. The results showed Strait Times Index able to strengthen exchange rate with Jakarta Composite Index and unable to strengthen BI rate with Jakarta Composite Index, Kuala Lumpur Stock Exchange index able to strengthen exchange rate and BI rate with Jakarta Composite Index, last Manila Composite index unable to strengthen exchange rate with Jakarta Composite Index and able to strengthen BI rate with Jakarta Composite Index.
 Keywords: Strait Times Index, Kuala Lumpur Stock Exchange, Manila Composite, Indeks Harga Saham Gabungan, Moderated Regression Analysis.
 

PENGARUH VARIABEL MAKROEKONOMI DAN HARGA SAHAM ASING TERHADAP INDEKS HARGA SAHAM GABUNGAN

Abstract : This study aimed to analyze the effect of macroeconomic variables and foreign stock price on Jakarta Composite Index (JCI) in Indonesia Stock Exchange covering the data period from January 2008 to December 2015. The methodology applied initially used the standard time series techniques, Vector Autoregression (VAR). The result showed that JCI are influenced with the selected macroeconomic and foreign stock price. Increasing in industrial production index and inflation will increase JCI, but exchange rate (Rp/USD) will decreases it. Money supply (M2) and interest rate is found insignificant on JCI. Strait Times Index, Philippines Stock Exchange Index and Dow Jones Industrial Average are found positively and significantly influenced JCI. However, Nikkei 225 and Shanghai Composite Index negatively and significantly influenced JCI. Kuala Lumpur Composite Index and stock Exchange of Thailand insignificant influenced JCI. Our finding suggest that JCI can be influence by macroeconomic variables and stock price in develop country and countries that are in the same region. DOI : https://doi.org/10.26905/jbm.v5i1.2321

Predictability of Technical Analysis on Singapore Stock Market, Before and After the Asian Financial Crisis

We investigate the predictability of technical analysis applied to the Singapore Straits Times Index. There are three trading rules – the Simple Moving Average, the Dual Moving Average and Trading Range Breakout with and without a one percent band – which are applied to undertake the prediction. Our findings conclude that the three indicators with and without the one percent band applied generate significantly positive returns for both the buy and sell signals in the periods before and after the 1997-98 Asian Financial Crisis coving bull run and bear markets and mixed markets. Our findings conclude that Singapore stock market is not as efficient as US stock market.

A Singaporean Study on Macroeconomic Variables Impacting Stock Returns

Stock market returns has increasingly become a leading indicator of a country’s economic performance. This explains academia’s growing interest in determining factors affecting stock returns. A majority of recent studies on Singapore’s economic performance focused centrally around policy impact or property prices, and not specifically on stock returns. This study aimed to fill this gap, by examining if, and how, historical movements in the Straits Times Index (STI) were explained by the S$NEER, Monetary Supply, CPI, Balance of Payments, Crude Oil Prices, Electricity Generated, GFCF, Industrial Production, Merchandise Trade, or Labour Cost. By utilizing a Structural Vector Auto regression (SVAR) Model, approximately 48% of the STI’s variance was collectively attributable to these ten macroeconomic variables, all of which had short-term impact on the STI. Looking forward, further research could be conducted examining the impact of said variables on individual sectoral stock indices, for greater insight on the dynamics of their relationships.

Day-of-the-Week (DOW) and Intraday Effects on Stock Returns: Evidence from the Selected Countries covering the Asia-Pacific Rim

The paper tries to analyze the conditional and unconditional market risk factors to examine the day of the week and intraday effects on stock returns of some selected countries covering the Asia-Pacific Rim. The paper takes into account six stock indices, namely, Hang Seng, Jakarta Composite Index, Kualalampur FTSE Bursa, Strait Times Index, TSEC Weighted Index and NSE Nifty. In order to fulfill the objectives of the paper, five models are estimated. In each model risk factors are allowed to vary. The study covers the period from 02- 04-2001 to 31-03-2015. However, the results suggest that for most of the indices, Monday suffers from maximum volatility. However, for all the indices, there exists significant day of the week effect at least in one of the five estimated models. Moreover, for most of the indices, the market risk factor is statistically significant in explaining variation in the intraday as well as interday stock returns.

Performance of technical trading rules: evidence from Southeast Asian stock markets.

This paper examines the profitability of technical trading rules in the five Southeast Asian stock markets. The data cover a period of 14 years from January 2000 to December 2013. The instruments investigated are five Southeast Asian stock market indices: SET index (Thailand), FTSE Bursa Malaysia KLC index (Malaysia), FTSE Straits Times index (Singapore), JSX Composite index (Indonesia), and PSE composite index (the Philippines). Trading strategies investigated include Relative Strength Index, Stochastic oscillator, Moving Average Convergence-Divergence, Directional Movement Indicator and On Balance Volume. Performances are compared to a simple Buy-and-Hold. Statistical tests are also performed. Our empirical results show a strong performance of technical trading rules in an emerging stock market of Thailand but not in a more mature stock market of Singapore. The technical trading rules also generate statistical significant returns in the Malaysian, Indonesian and the Philippine markets. However, after taking transaction costs into account, most technical trading rules do not generate net returns. This fact suggests different levels of market efficiency among Southeast Asian stock markets. This paper finds three new insights. Firstly, technical indicators does not help much in terms of market timing. Basically, traders cannot expect to buy at a relative low price and sell at a relative high price by just using technical trading rules. Secondly, technical trading rules can be beneficial to individual investors as they help them to counter the behavioral bias called disposition effects which is the tendency to sell winning stocks too soon and holding on to losing stocks too long. Thirdly, even profitable strategies could not reliably predict subsequent market directions. They make money from having a higher average profit from profitable trades than an average loss from unprofitable ones.

Catching the Behavior of Stock Market: Numerical Approach to Estimate the Catalytic Chemical Model Parameters

This research proposes a numerical approach in estimating the trend of behavior of this market. This approach is applied to a model that is inspired by catalytic chemical model, in terms of differential equations, on four composite indices, New York Stock Exchange, Hong Kong Hang Seng, Straits Times Index, and Jakarta Stock Exchange, as suggested by Caetano and Yoneyama (2011). The approach is used to minimize the difference of estimated indices based on the model with respect to the actual data set. The result shows that the estimation is able to capture the trend of behavior in stock market well.

Forecasting stock returns based on information transmission across global markets using support vector machines

This paper provides evidence that forecasts based on global stock returns transmission yield better returns in day trading, for both developed and emerging stock markets. The study investigates the performance of global stock market price transmission information in forecasting stock prices using support vector regression for six global markets--USA (Dow Jones, S&P500), UK (FTSE-100), India (NSE), Singapore (SGX), Hong Kong (Hang Seng) and China (Shanghai Stock Exchange) over the period 1999---2011. The empirical analysis shows that models with other global market price information outperform forecast models based merely on auto-regressive past lags and technical indicators. Shanghai stock index movement was predicted best by Hang Seng Index opening price (57.69), Hang Seng Index by previous day's S&P500 closing price (54.34), FTSE by previous day's S&P500 closing price (57.94), Straits Times Index by previous day's Dow Jones closing price (54.44), Nifty by HSI opening price (60), S&P500 by STI closing price (55.31) and DJIA by HSI opening price (55.22), and Nifty was found to be the most predictable stock index. Trading using global cues-based forecast model generates greater returns than other models in all the markets. The study provides evidence that stock markets across the globe are integrated and the information on price transmission across markets, including emerging markets, can induce better returns in day trading.

Demutualization in Developing and Developed Country Stock Exchanges

This study considers seven different stock exchanges in order to measure the impact of demutualization announcements on stock market return volatility. This is measured based on the daily index prices of all seven indices: the Toronto Stock Exchange (TSX) in Canada, the FTSE 100 in the UK, the Straits Times Index (STI) in Singapore, the Nikkei 225 in Japan, the Kuala Lumpur Composite Index (KLCI) in Malaysia, the SENSEX in India, and the Hang Seng Index (HSI) in Hong Kong, China. A dummy variable is used to differentiate between pre- and post-event data. We use the augmented Dickey–Fuller test, the ARCH LM test and GARCH (1, 1) methodology to measure return volatility due to demutualization announcements. The results show that the decision to demutualize did not affect the UK, Singapore, and Indian stock markets, where volatility is explained by other factors. It did, however, affect the Canadian, Japanese, Hong Kong, and Malaysian stock markets. Moreover, the Canadian and Malaysian market swere negatively affected, while the Hong Kong and Japanese markets reacted positively to the demutualization announcements.

Are South East Asia Countries Capital Markets Characterized by Nonlinear Structures? An Investigation from Indonesia, Philippine and Singapore Capital Market Indices

This research paper tries to detect the nonlinear structure in the South East Asia Countries Capital Markets. The capital markets of three South East Asia Countries are chosen: Indonesia, Philippine, and Singapore. Daily return data of Capital Markets composite indices are observed: Straits Times Index (STI) of Singapore Exchange from January 04, 1985 to December 31, 2007, Pilipino Stock Exchange Index (PSEi) of Philippines Stock Exchange from March 1, 1990 to December 31, 2007 and Jakarta Composite Index (JCI) of Indonesia Stock Exchange from January 05, 1988 to December 31, 2007. Should nonlinearity be found, the outcomes of each observation are compared to analyze the implications of each country in global, regional and local position of their competition in the continuously changing world of interdependency environment. The implications of nonlinearity finding in the three ASEAN countries capital markets to the current issues of AFAS on Financial Services, Harmonization among ASEAN countries capital markets in the ASEAN region and ASEAN integration and liberalization on Financial Services are analyzed. BDS statistic and R/S Analysis as our tools for nonlinearity testing are applied. Nonlinearity evidences in Jakarta Composite Index, Pilipino Stock Exchange Index and Straits Times Index are found.

PENGUJIAN MONDAY EFFECT PADA BURSA EFEK INDONESIA DAN BURSA EFEK SINGAPURA

The study attempts to examine the influence of Monday effect on stock return. The Monday effect is an example of a seasonal anomaly that is when the stock return is significantly negative on Monday. The variable used is the return index. The population in this study is the Indonesian Stock Exchange and the Singapore Stock Exchange. The samples used were LQ45 and the Straits Times Index (STI) in the period January 2010 - December 2012. Statistical methods were used to test the hypothesis covering ANOVA, multiple regression, linear regression. First, it can be concluded that there is no effect on the phenomenon Monday LQ45 and STI during the period 2010-2012. Second, it can also be concluded that the returns on Monday in LQ45 and STI are not concentrated at week 4 and week 5 during the period 2010-2012. The third results in this study it can be concluded that the LQ45 index returns and STI on Monday systematically unpredictable based on market conditions Friday the previous week during the period 2010-2012.

Building an innovation-driven economy – the case of BRIC and GCC countries

Purpose – The purpose of this paper is to undertake an analysis of the attempts of Gulf Cooperation Council (GCC) and Brazil, Russia, India and China (BRIC) countries to catch up in their national development to build an innovation-driven economy on which to base future growth and wealth. We conducted an analysis of GCC and BRIC countries to show the different strategies leaders have taken to try and achieve this aspiration. This paper analyses the various aspects of national innovation systems of BRIC and GCC countries, highlights similar and different approaches and attempts to quantify their success. For example, GCC countries spend extensively on research and development (R&D), but have so far achieved less than meaningful results. Brazil, China and India are catching up to the acknowledged world leaders in innovation, but Russia is lagging. Design/methodology/approach – Our comparison was based mostly on secondary data from sources and institutions that use statistical data to build country rankings, such as the Global Competitiveness Index (GCI) produced by the World Economic Forum. BRIC and GCC countries were analyzed over 1996-2011 because most of the indicators data are only available from 1996. Data related to intellectual property rights have been collected since 1999 or 2000. The data available for the number of researchers proved problematic for both BRIC and GCC countries. For instance, some data for the GCC countries was missing. To not leave a gap, we extrapolated in line with the overall trend; using the least squares method to approximate a straight line for the missing data based on what had already been reported. Findings – Counter-intuitively, we will argue that the push toward an innovation-based economy is actually not dependent on total expenditure on R&D, but rather relies on the efficient allocation of investments and the rigorous implementation of innovation strategy. And, we will demonstrate this by showing our ideas in relation to both BRIC and GCC countries. This analysis raises fascinating points of discussion for those looking to build an innovation economy in other countries and has practical implications for policy-makers and policy implementers in all countries. Originality/value – First analysis of the correlation of gross expenditure on R&D (GERD) with gross domestic product (GDP) growth and Straits Times Index (STI) policy measures.

Applying Generalized Autoregressive Conditional Heteroscedasticity Models to Model Univariate Volatility

This paper aims to model volatility of daily index returns for four Asian markets namely; Kuala Lumpur Composite Index of Malaysia, Jakarta Stock Exchange Composite Index of Indonesia, Straits Times Index of Singapore and the Stock Index of Korea over the period 03/01/2007 – 31/07/2013 excluding the public holidays. We utilized generalized autoregressive conditional heteroskedasticity models as these models are particularly suitable for high frequency financial time series such as the daily stock returns which has a time-varying variance. Unlike the linear structural models, these models are found very useful in explaining the most stylized facts about index returns such as leptokurtosis, volatility clustering and asymmetric or leverage effects. The key results of this study are as follows. Firstly, the conditional variance process is highly persistent in all markets. Secondly, the relationship between the expected risk and the expected return is positive as expected but the relationship is not statistically significant for all markets except Indonesia. For Indonesian market which is found to be more volatile than the other three markets, the estimated coefficient of risk premium appeared to be statistically significant indicating that increased risk leads to a rise in the returns. The risk-premium coefficients for other three markets are although positive but not statistically significant suggesting that increased risk does not necessarily produce higher return for those three markets. Finally, the asymmetric effects is exist in all cases signifying that negative shock produces higher impact on future volatility than the positive shock of the same magnitude.