Analyzing The Impact of Macroeconomic Factors on Stock Market Performance in Asean-5 Countries

The study explores the relationship between macroeconomic factors and stock market performance in five ASEAN countries (Malaysia, Indonesia, Singapore, Thailand, and the Philippines) from 2012-2022, a period encompassing the COVID-19 pandemic. Existing research predominantly focuses on developed economies, leaving a gap in understanding emerging markets' dynamics. The study aims to fill this gap by examining the impact of interest rates, consumer price index (CPI), exchange rates, and industrial production index (IPI) on stock market indices. The researchers hypothesize that these macroeconomic variables significantly influence the ASEAN-5 stock market, particularly during periods of crisis like the COVID-19 pandemic. The importance of this research lies in its potential to guide investment decisions and inform economic policymaking in the region, offering insights into managing investments effectively during economic uncertainty.

The literature review examines previous research on the correlation between macroeconomic variables and stock market performance. Studies have shown varied relationships, with some indicating negative correlations between interest rates and stock prices, and others demonstrating positive relationships between economic activity (industrial production) and stock market performance. The impact of the COVID-19 pandemic on stock markets has also been a subject of interest, with some research suggesting negative impacts while others point to more nuanced relationships. The review highlights the need for further research, particularly in emerging markets, to better understand these relationships. Specific studies cited include those examining the impact of macroeconomic variables on stock markets in Indonesia, Malaysia, and other ASEAN countries, along with investigations of the effects of the COVID-19 pandemic and previous crises, such as the SARS pandemic, on various economies and stock markets.

The study employs a panel data analysis using monthly data from 2012 to 2022 for the five ASEAN countries. The dependent variable is the stock market index, and the independent variables are interest rates, CPI, exchange rates, and IPI. The Generalized Method of Moments (GMM) estimator is used to address potential endogeneity issues inherent in dynamic panel data models. Before applying GMM, the researchers conduct panel unit root tests (LLC, IPS, ADF, and PP tests) to ensure the variables' stationarity. Both fixed-effects and random-effects models are considered, with the Hausman test used to determine the most appropriate model. Descriptive statistics and correlation analysis are also provided. The study utilizes a two-step system GMM approach, incorporating lagged values of the dependent variable as instruments to address potential endogeneity. Sargan and Arellano-Bond tests are used to assess the validity of the instruments and the absence of autocorrelation in the residuals.

The study's key findings reveal significant relationships between macroeconomic variables and the ASEAN-5 stock market index. The GMM estimations show statistically significant positive relationships between the stock market index and CPI and IPI. This implies that increases in consumer prices and industrial production are associated with increases in the stock market index. Conversely, statistically significant negative relationships are observed between the stock market index and interest rates and exchange rates. Higher interest rates and stronger domestic currencies (appreciation) are negatively correlated with the stock market index. The study's analysis of unit root tests demonstrates that all variables are stationary after applying first-order differencing.The Hausman test suggests the fixed-effects model is more appropriate than the random effects model given the rejection of the null hypothesis that the random effects model is appropriate. The study notes the R-squared value is slightly better for the fixed effects model compared to the random effects model. The model indicates significant statistical significance for the lagged stock market index variable indicating that current values are influenced by prior period values.

The findings suggest that macroeconomic conditions significantly influence stock market performance in the ASEAN-5 countries. The positive relationship between CPI and the stock market index may be attributed to factors like price-setting abilities of certain firms, and the effect of inflation on equity as a hedge against inflation. However, prolonged increases in CPI could signal rising inflation, potentially leading to negative impacts. The negative relationship between interest rates and the stock market index aligns with existing literature and reflects the impact of interest rates on discount rates and borrowing costs for firms. The negative relationship with exchange rates reflects the impact of currency strength on export-oriented companies and import-reliant businesses. The negative relationship with IPI, though statistically significant, needs careful interpretation given the impact of COVID-19 related production disruptions. These findings highlight the importance of considering macroeconomic factors when making investment decisions and underscore the significance of appropriate macroeconomic policies in maintaining stock market stability in the ASEAN-5 region.

This study provides valuable insights into the dynamic interplay between macroeconomic variables and stock market performance in the ASEAN-5 countries during the COVID-19 pandemic. The findings highlight the significant impact of interest rates, exchange rates, CPI, and IPI on the stock market index. The findings provide guidance for investors and policymakers. Investors need to account for the effects of interest rates, exchange rates, and other macroeconomic indicators on the stock market before making investment decisions. Policymakers should implement appropriate macroeconomic policies for stock market stability. Future research can explore more macroeconomic variables and utilize different data frequencies.

The study's limitations include its focus on a specific time period (2012-2022), which may not be fully generalizable to other periods. Also, the use of only four macroeconomic factors might limit a full understanding of the complexities influencing stock market performance. The study also acknowledges the challenges in comparing results across different economies given the various internal factors influencing each one.