US Top Bank Failures: A GARCH Approach to Analyzing Economic Consequences
Year: 2025
Type: article
Abstract: This study aims to examine the economic consequences of US Top Bank Failures, particularly in Indonesia, with the expectation of providing a predictive model for economic conditions in the event of similar global economic situations. The research employs difference testing and GARCH modeling to analyze investment instruments and the global economy, focusing on the volatility of each instrument's value. Data collection was conducted through secondary sources from websites. The results indicate that stock indices, inflation rates, gold prices, and cryptocurrencies experienced significant value differences as an impact of bank failures. For GARCH analysis, it was identified that the GARCH(1,1) model is optimal for stock indices and exchange rates, the GJR-GARCH(1,1) model is the best for world gold and cryptocurrency, and the EGARCH(1,1) model is most suitable for predicting inflation rates. Based on the findings, the study highlights the importance of developing tailored investment strategies during periods of financial uncertainty. For the Indonesian market, maintaining economic resilience through sound fiscal and monetary policies is critical to mitigating external shocks. Advanced volatility models, such as GARCH variants, can help investors and policymakers anticipate market behavior, optimize risk management, and enhance economic stability during crises.
Authors: Universitas Mikroskil, Jalan M.H. Thamrin No. 140, Medan, North Sumatera, Indonesia, Agustina ., Syafira Ulya Firza, Universitas Mikroskil, Jalan M.H. Thamrin No. 140, Medan, North Sumatera, Indonesia, Litka Tiadoraria br. Ginting, Universitas Mikroskil, Jalan M.H. Thamrin No. 140, Medan, North Sumatera, Indonesia, Fandi Halim, Universitas Mikroskil, Jalan M.H. Thamrin No. 140, Medan, North Sumatera, Indonesia, Mie Mie, Universitas Mikroskil, Jalan M.H. Thamrin No. 140, Medan, North Sumatera, Indonesia
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4408482888