Banking stock price movement and macroeconomic indicators: k-means clustering approach

This study investigates the price movement characteristics of banking issuers listed on the Indonesia Stock Exchange with macroeconomic indicators as an exogenous variable. By using the k-means clustering based on the monthly rate of return, banks are classified into three clusters, lower, middle, and upper clusters, with a cluster rank directly proportional to the average rate of return. Furthermore, each cluster formed is estimated using dynamic panel data regression with the generalized method of moment. This study shows that the price of banking issuers in the middle cluster is more reactive in dealing with interest rates and exchange rates. At the same time, the highest inflation coefficient exists in the upper cluster. The higher beta coefficient creates abnormal returns that allow for higher gains and line with the risk level. Meanwhile, the price effect in the previous period proved to be in line with the cluster level, indicating that higher clusters are more resilient. Therefore, referring to the possibility of abnormal returns and resilience to uncertainty, this study concludes that issuers in the middle cluster are more suitable for a short-term investment, while issuers in the upper cluster are for the long-term