Network model and macroeconomics of systemic risk

Abstract

This thesis highlights the importance of a holistic approach to understanding systemic risk. The cost of crises and their effects on the economy are catastrophic, thus necessitating a clearer understanding and proper risk mitigation to lessen future financial crises. In considering economic crises, the Basel guidelines emphasise the size of institutions and have limited reflection on how crises might disperse across the financial system network. This thesis aims to empirically comprehend the connection between the tools used by academics in field and systemic risk studies and the practical guides endorsed by policymakers. This study also explores the risk escalation and direction from or to other financial institutions by employing the network model. Another objective is to propose robust integration of micro and macro data to develop systemic risk monitoring tools for practical use. The missing link in current systemic risk research could be used to assess overall risk endogenously and externally expose systemically important financial institutions. Assessment of systemically important banks (SIBs) employed three theoretical models - conditional value at risk (CoVaR), marginal expected shortfall (MES) and systemic risk measure (SRISK) - and compared the results with the current Basel indicator-based results. Using Indonesia commercial bank datasets for the 2008-2019 period, the findings show that all three theoretical approaches have positive association with the Basel-based results, though the 'best' results vary across models. SRISK delivers more consistent rankings over the sample period, but for inter-theoretical approaches, CoVaR - MES has the highest positive correlation that converted to certain degree of rankings similarity. This finding suggests that scholars can build on or extend the estimation model to include bank balance sheets and economic data to better capture the specific risks of SIBs. This research also explores how capital market data and asset returns can be a good proxy to detect interconnectedness and map risk in the financial system. The sample employs a mixture of Indonesian banks' stock market and prudential data for the 2012-2019 period. This thesis recommends practical integration of risk into the systemic risk assessment framework and its technical calculation to capture the holistic exposure of systemically important financial institutions.

Date of Award	2022
Original language	English