Effects of National Macroeconomic Variables and Political Condition on Dhaka Stock Exchange

Abstract

National macroeconomic variables which are determined by economic policies taken by the authority and aggregated economic activities of individuals, has definitive infuence on a country’s stock market. Prime share market of Bangladesh, Dhaka Stock Exchange is also shaped by local macroeconomic situation. Additionally, country’s political condition might affect the market as well because as a developing economy our market face significant political instability. It is observed that the mean point value of the DSE general index was slightly lower for observations when the country goes through political instability than for observations when the political situation was stable. However, this difference was not statistically significant. Our investors seem to be quite indifferent to the country’s political condition and do not turn their back to the market just because the country was observing political unrest. Correlation analysis reveals that all the macroeconomic variables are moderately correlated with DGEN while money supply, remittance and IRS are significantly correlated. Money supply, remittance, inflation rate and exchange rate are positively related with the general index when interest rate spread and political unrest shows negative relationship. This relationship is justifiable by the economic fundamentals. Both money supply and remittance inject cash into the economy, which is supposed to be distributed in all sectors, and thus the stock market would naturally grow. Higher IRS means the banks and other financial institutions are better off by just lending money and would be less interested in investing in the capital markets. Two economic models (linear & binomial) are derived to explain this relationship and estimate the DGEN using the macroeconomic variables. Among the two derived models, the binomial one estimate the general index way better than the linear model (in terms of regression R-square) and is able to explain more than 80% of the fluctuations in Dhaka Stock Exchange where the linear model explains only 25% of the fluctuations. Additionally, another correlation analysis, which is carried out after dropping 5 observations when the market observed unusual ups & downs, shows stronger relationships for all variables. Both estimation models explain more of the fluctuations when derived from the engineered dataset. It can be assumed that external force(s) manipulated the market during that time. However, our study cannot draw any definitive conclusion regarding those 5 months of massive fluctuations because there is always a chance that this happened due randomness which is inherited by the stock market like any other system.