Determining the Banking Solvency Risk in Times of COVID-19 through Gram-Charlier Expansions

Abstract

This paper proposes risk measures for bank solvency by accurately measuring the solvency risk components. These measures consider the minimum regulatory solvency levels and banks’ risk appetite level and risk profile. For this purpose, we used semi-nonparametric statistics to model stylized facts of the risk distribution, particularly the high-order moments of the Solvency Decline Rate, the Tier Decline Rate, and the Portfolio Growth Rate variables. Additionally, these risk measures can be used to measure the risk of regulatory intervention and to define policies that establish the minimum solvency levels required by banking regulators by estimating the Quantile Risk Metrics. As a case study, we collected data on the solvency indicators of the Colombian banking system, which adapts to the standards established by the Basel Committee. According to the results, the liquidity injection measures implemented in response to the needs generated by the COVID-19 pandemic led to an increase in the levels of the risk portfolio in the Colombian banking system, which exceeded the 99th percentile of the probability distribution of monthly portfolio value changes.

Keywords: Solvency risk, Quantile Risk Metrics, Semi-nonparametric approach, Gram-Charlier expansions, COVID-19

JEL Classification: C14, C22, C54, G21, G28