Liquidity Stress-Tester: A Model for Stress-testing Banks' Liquidity Risk

Abstract

This paper presents a stress-testing model for liquidity risks of banks. It takes into account the first and second round (feedback) effects of shocks, induced by reactions of heterogeneous banks, and reputation effects. The impact on liquidity buffers and the probability of a liquidity shortfall is simulated by a Monte Carlo approach. An application to Dutch banks illustrates that the second round effects in specific scenarios could have more impact than the first round effects and hit all types of banks, indicative of systemic risk. This lends support policy initiatives to enhance banks' liquidity buffers and liquidity risk management, which could also contribute to prevent financial stability risks.

Factors affecting sensitivity of commercial banks to bank run in the Visegrad Countries

“…This means that Czech banking sector as a whole should be well prepared for a bank run, simulated by a withdrawal of 20% of client deposits. Of course, individual banks in individual years could have problems coping with such a crisis; noteworthy in this regard are Equa bank in 2011-2014, Česká spořitelna in 2006-2008and 2014, ČSOB in 2006-2008, GE Money Bank in 2007, J&T banka and Expobanka in 2012-2014, or Raiffeisenbank in 2010-2013. Also Hungarian banking sector seems to be quite resilient which is refl ected in the positive median values of the stressed liquid asset ratio.…”

“…There are also numerous empirical studies focusing on the risk of contagion through the interbank market (e.g., Allen & Gale, 2000;Blavarg & Nimander, 2002;Memmel & Sachs, 2013;or Wells, 2004), on the determinants of bank liquidity risk (such as Aspachs et al, 2005;Bunda & Desquilbet, 2008;Dinger, 2009;Lucchetta, 2007;Moore, 2010;or Rauch et al, 2010) or on the sensitivity of banks to various liquidity shocks (e.g., Boss et al, 2007;Negrila, 2010; or Van den End, 2008). However, to the best of our knowledge, there is no empirical study focusing on the determinants of bank vulnerability to a bank run.…”

Liquidity Risk Sensitivity of Czech Commercial Banks

“…Banks' liquidity positions are modeled in three stages: a er the fi rst round eff ect of a scenario (where the shocks to market and funding liquidity risk factors lead to decrease in liquidity buff er), a er the mitigating actions of the banks (where banks try to improve their liquidity by operations in the market which results in the improved liquidity buff er) and a er the second round eff ects (where the reactions of banks cause the second round eff ects of the scenario 1 which again decreases the liquidity buff er). Van den End (2008) applied his model on data of all Dutch banks in July 2007 and investigated impact of banking crisis scenario on bank liquidity. On average, the fi rst round eff ect erased 8% of the initial liquidity buff er (however, some small banks would be faced even with a negative liquidity buff er a er the fi rst round of the scenario).…”

“…Komárková et al (2011) described the model which is used by Czech National Bank (CNB) for stress testing of both market and funding liquidity risk. The model follows the methodology of Van den End (2008) but there are some diff erences. They applied the CNB's model on data provided by banks operating in the Czech Republic in 2011 by the supervisory liquidity report.…”

Linking U.S. CDS Indexes with the U.S. Stock Market: A Multidimensional Analysis with the Market Price and Market Volatility Channels

“…contagion risk) and model stress testing as well as related scenario analysis have been highlighted by the Basel Committee on Banking Supervision under the Basel 3 framework (Basel Committee on Banking Supervision, 2010). With regard to liquidity, various liquidity measures coupled sometimes with a stressed scenario analysis are proposed at both the level of financial assets and the bank level in in-and off-balance sheet prospects (BlundellWignall and Atkinson, 2010;Lumsdaine, 2011;Van Den End, 2011). On the correlation viewpoint, the risk of correlation between risks (e.g.…”