Peramalan Kinerja Perbankan Indonesia Dengan ARCH-GARCH

Abstract

Banking as a form of organization has specific objectives to be achieved. The success in achieving banking objectives is an achievement of management. Performance appraisal or performance of a bank is measured because it can be used as a basis for decision making, both external and internal parties. This study aims to model and predict banking performance. This study uses monthly data from 2012 to 2020 with the Autoregressive Conditional Heteroscedasticity - Generalized Autoregressive Conditional Heteroscedasticity (ARCH-GARCH) method. The data used in this study are Operating Expenses, Operating Income (BOPO), Loan to Deposits Ratio (LDR), Return On Assets Ratio (ROA), and Net Interest Margin Ratio (NIM). The test results from the volatility modeling found that all data have volatility characteristics where several ratios are influenced by the error and volatility returns of the previous period. The forecasting results tend to be stable even though there are spikes that indicate volatility in specific periods.