<![CDATA[Banking companies will have a domino effect when one company fails that causes systemic risk in Indonesia. Moreover, Indonesia has a history of economic crises. This study presents a series of systemic risk measures for Indonesia, the Financial Risk Meter (FRM) with the LASSO-QR model, a novel application within the context of Indonesian data. Then, this study enhances the FRM methodology by incorporating the QRNN method to account for the nonlinear dependencies of return values across different companies, and applies the novel LASSO-QRNN method to measure FRM for Indonesia. This study employs a quantitative empirical approach using secondary financial and macroeconomic time-series data. This study developed LASSO-QR and LASSO-QRNN models applied to log-return data of public banks in Indonesia and macroeconomic variables to measure the FRM. These models captured financial risk characteristics by adjusting LASSO parameters with a moving window approach. The FRM indicated high-risk periods in mid-2020 and the first quarter of 2021 for the LASSO-QR, extending into the third quarter of 2021 for the LASSO-QRNN. This study contributes new insights into risk measures for individual banks and the banking system in Indonesia. Additionally, this offers solutions for measuring daily systemic risk that can account for both linear and nonlinear dependencies among companies.]]>
Copyrights © 2026
