Systemic Risk in the United States banking industry

Abstract

This project examines the Sustainability and Systemic Risk Index (SSRI) as a new macroeconomic index for the United States banking industry. The SSRI measures the aggregate level of risk across all federally insured banks and indicates the industry's sensitivity to systemic events. Since the 2008 recession, the government and the public have searched for ways to analyze elevated levels of risk to prevent future recessions or financial collapses, and this index hopes to address those concerns. The focus of this study was to examine the SSRI as a leading indicator of banking risk and determine the index's relationship with other macroeconomic variables. The SSRI has been compiled for every quarter since 1984, so time series analyses were performed. Additionally, simple and vector autoregressive models were created to assess the relationships between the SSRI and economic indicators. Finally, hidden Markov models were created to examine how relationships changed during different states of the economy, particularly in conditions pre-and post-2008. A two state hidden Markov approach provides the most revealing and intuitive model to interpret changing market risk. The results of these comparisons yielded a statistically significant ability to detect risk. The preliminary simple and vector autoregressive models show that the SSRI is significantly correlated with factors such as 90-day Treasury bill rates, unemployment, commercial loans, and the consumer price index. The complexity of these modeling techniques presents a barrier to understanding for non-engineers. The team will utilize visualization techniques to present the results in an accessible form for individuals without a background in advanced statistics. These techniques will follow best design principles for clarity of graphics and intuitively explain the underlying models.