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Nicolas Syrichas

12 February 2021
Net trading income is an important but volatile source of revenue for many euro area banks deemed to be highly sensitive to changes in financial market conditions. We propose a two-step econometric approach to quantify the downside risk of financial shocks on the banks’ trading revenues. First, we estimate the parameters of a fixed-effects quantile autoregressive model conditional on exogenous macro-financial shocks and bank characteristics. In the second step, we approximate the entire empirical conditional distribution of net trading income across all banks and time horizons by interpolating between the estimated quantiles. Based on the estimated distribution function, we derive two key metrics that summarize conditional left tail risks: i) conditional shortfall, ii) material loss probability. These measures are relevant in a stress test exercise whose aim to gauge CET-1 capital depletion under an adverse macro-financial scenario. We apply our methodology on supervisory data for a representative sample of European banks over the period spanning from the first quarter of 2015 to the last quarter of 2020. We find that the lower quantiles of net trading revenue distribution are significantly impacted by deteriorating financial conditions, whereas the upper quantiles seem to be stable over time.
JEL Code
C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation