Officials from central bank financial stability departments, banking regulatory and supervisory bodies, and ministries of finance.
Participants should have a degree in economics or finance. Experience with financial stability analysis is highly desirable.
This course, presented by the IMF Monetary and Capital Markets Department, provides a comprehensive overview of the theories, tools, and techniques necessary for thorough assessment of financial sector surveillance and banking-sovereign interactions. Among the topics covered are
- extracting information from balance sheets and market information;
- tools for monitoring systemic risk;
- risk-adjusted balance sheets for corporations and financial institutions using contingent claims analysis (CCA);
- how credit risk and funding costs are affected by changes in balance sheets and market risk appetite;
- systemic risk assessment using a variety of models, their pros and cons, and how they are related;
- sovereign-risk-adjusted balance sheet calibration;
- enhanced macro stress testing using CCA;
- macrofinancial risk analysis and joint bank-sovereign stress testing;
- modeling links and feedback between macro variables, and indicators of corporate, banking, household, and sovereign risk;
- analysis of country cases when high-frequency and market data are available; and
- analysis that can be carried out in data-constrained countries (illustrated by country case studies and workshops with spreadsheets).
Upon completion of this course, participants should be able to:
- Explain how to use balance sheet and market information to construct risk indicators for sovereigns and the corporate, household, and financial sectors to measure and monitor sector and systemic risk.
- Describe how to calibrate risk-adjusted balance sheets for corporations, banks, nonbank financial institutions, and sovereigns using CCA and related techniques.
- Summarize the tools and data needed for thorough monitoring of systemic risk.
- Define data inputs, outputs, and applications of several types of systemic risk models, their pros and cons, and how they relate to one other. Among them should be CoVaR, Granger causality, marginal expected shortfall, S-RISK and systemic CCA.
- Build models that relate macro variables to the time series of risk indicators, including CCA indicators (expected default probabilities, credit spreads, expected losses, and contingent liabilities) and be able to carry out:
– enhanced macro stress testing, which complements and supplements traditional macro stress testing for banks with funding cost analysis and supplementary capital shortfall and soundness measures;
– analysis of sensitivities and feedback between macro variables and risk indicators for the banking and corporate sectors, households, and sovereigns, using among other models factor, VAR, FAVAR, and GVAR);
– analysis of risk transmission from banks to sovereigns via contingent liabilities and from sovereigns to banks from both their direct holdings of sovereign debt and the indirect impact on banks of sovereign spreads on bank funding costs; and on joint bank and sovereign macro stress testing.