Macroprudential is one of the latest buzzwords in financial economics. Discussions and research on macroprudential policies have been active since the 2008 global financial crisis. However, the historical experience used to measure their effectiveness and calibration is scarce. The measurement and theory of financial fragility and systemic risk of financial systems have not yet been firmly established. Moreover, the scope of financial regulation and the institutional framework for macroprudential policy have not been fully agreed upon. Therefore, more discussion and study on various topics are still needed.
This module focuses on the following topics: First, why do financial crises and defaults occur? Second, what are the limitations of current theories of financial fragility and systemic risk? Third, how can systemic risk be measured and monitored in real-time? Fourth, how can we operate an Early Warning System (EWS) for a financial crisis?
Part of the module content is applied. Using the programming language R or Python and a number of macroeconomic and financial data, case studies will be developed to measure and monitor the systemic risk of financial markets. Through these exercises, students taking this module will improve their understanding of systemic risk and gain skills to develop systemic risk models at the basic level. Students need only basic knowledge of econometrics and statistical theory to learn systemic risk. In lab sessions, the programming language R or Python will be introduced.