Financial Engineering Workshops - Alberto Grassi (European Central Bank)

•    Title: MuSE: a multiple macro-financial scenario simulation engine for stress testing
•    Abstract: We design an econometric framework to simulate multiple adverse macro-financial scenarios that can be used in top-down stress tests. First, we create a financial stress index informed by shocks generated via a non-parametric copula estimated on a large dataset of daily financial indicators. Second, we simulate the joint dynamics of macroeconomic indicators conditional on the copula-based financial shocks in a large multi-country Bayesian VAR model. This framework, which we refer to as the Multiple macro-financial stress scenario Simulation Engine, MuSE, allows us to replicate thousands of macro-financial stress scenarios where adverse shocks generated in the financial sector propagate into the overall economy, triggering significant macroeconomic fluctuations. We demonstrate its functionality by generating a large number of scenarios inspired from past crises capturing stress stemming from financial markets, sovereign debt, and geopolitical tensions. Using a top-down solvency stress test model, based on recent EU-wide stress tests, we project the capital depletion for euro area banks and find that adverse scenarios triggered by stock market and sovereign shocks appear to threaten the resilience of the euro area banking sector the most at this juncture.
•    Affiliation: European Central Bank, Directorate General Macroprudential Policy and Financial Stability, Stress Test Modelling division.
•    Bio: Alberto Grassi is a financial stability expert at the European Central Bank, where he works in the Directorate General Macroprudential Policy and Financial Stability. With eight years of experience in the Stress Test Modelling division, his work focuses on scenario design, liquidity and market risk, and contagion models for networks of banks and non-bank financial institutions. He has an educational background in economics from Bocconi University and his research interests include financial risk modelling, financial economics, and time series econometrics.

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