Efficiency and risk in European banking

Fiordelisi, Franco; Marqués-Ibáñez, David; Molyneux, Philip

doi:10.1016/j.jbankfin.2010.10.005

Cited by 547 publications

(455 citation statements)

References 38 publications

Supporting

Mentioning

395

Contrasting

Unclassified

Order By: Relevance

“…Finally, we examine the impact of income diversification on bank performance as has been used in recent studies (Laeven and Levine, 2007;Fiordelisi and Molyneux, 2010). 9 In terms of country macroeconomic variables, we use GDP per capita as a wealth measure (Dietsch and Lozano-Vivas, 2000;Maudos and Guevara, 2007;Maudos and Solis, 2009;Fiordelisi et al, 2011). Empirical evidence and theory point in different directions concerning the impact of GDP per capita on bank performance.…”

Section: Data and Variablesmentioning

confidence: 99%

What drives investment bank performance? The role of risk, liquidity and fees prior to and during the crisis

Mamatzakis

Bermpei

2014

International Review of Financial Analysis

View full text Add to dashboard Cite

This paper examines factors that affect the performance of investment banks in the G7 and Switzerland. In particular, we focus on the role of risk, liquidity and investment banking fees. Panel analysis shows that those variables significantly impact upon performance as derived from stochastic frontier analysis (SFA). Given our sample also comprises the financial crisis, we further test for regimes switches using dynamic panel threshold analysis. Results show different underlying regimes, in particular over the financial crisis. In addition, a strong positive effect of Z-Score on performance for banks in the regime of low default risk is reported, whilst fee-income ratio has also a positive impact for banks with low level of fees. On the other hand, liquidity exerts a negative impact. Notably, there is a clear trend of mobility of banks across the two identified threshold regimes with regards to risk a year before the financial crisis. Our results provide evidence that recent regulation reforms regarding capital adequacy and liquidity requirements are on the right track and could enhance performance.

show abstract

Section: Data and Variablesmentioning

confidence: 99%

What drives investment bank performance? The role of risk, liquidity and fees prior to and during the crisis

Mamatzakis

Bermpei

2014

International Review of Financial Analysis

View full text Add to dashboard Cite

show abstract

“…The Z-Score, discussed in next section, is by far the most widely used accounting ratio in the literature Boyd et al [2006], Mercieca et al [2007], Laeven andLevine [2009], Fiordelisi and Mare [2014], Bolton et al [2015]. Other accounting ratios, such as non-performing loans to total loans or the level of provisioning Houston et al [2010], Fiordelisi et al [2011, are also used to capture different risk dimensions although the focus is on specific narrower aspects such as credit risk, operational risk, liquidity risk and market risk. Marketbased measures include observable market prices (equity prices, debt prices, credit default swap spreads, bond yield spreads) that allow to capture forward-looking information by incorporating market expectations.…”

Section: Measures Of Bank Stabilitymentioning

confidence: 99%

“…Banking financial stability has been investigated in relation to a broad variety of determinants such as corporate governance Laeven and Levine [2009], competition Fiordelisi and Mare [2014], efficiency Fiordelisi et al [2011], the diversification strategy of shareholders García-Kuhnert et al [2013], creditor rights and information sharing Houston et al [2010]. It is paramount both under the regulatory and supervisory perspectives because it drives policy choices to assure the resilience and the functional working of the banking sector, along with optimal social welfare and economic growth.…”

Section: Introductionmentioning

confidence: 99%

Nonstationary Z-Score measures

Mare

Moreira

Rossi

2017

European Journal of Operational Research

View full text Add to dashboard Cite

In this work we develop advanced techniques for measuring bank insolvency risk. More specifically, we contribute to the existing body of research on the Z-Score. We develop bias reduction strategies for state-of-the-art Z-Score measures in the literature. We introduce novel estimators whose aim is to effectively capture nonstationary returns; for these estimators, as well as for existing ones in the literature, we discuss analytical confidence regions. We exploit moment-based error measures to assess the effectiveness of these estimators. We carry out an extensive empirical study that contrasts state-of-the-art estimators to our novel ones on over ten thousand banks. Finally, we contrast results obtained by using Z-score estimators against business news on the banking sector obtained from Factiva. Our work has important implications for researchers and practitioners. First, accounting for the degree of nonstationarity in returns yields a more accurate quantification of the degree of solvency. Second, our measure allows researchers to factor in the degree of uncertainty in the estimation due to the availability of data while estimating the overall risk of bank insolvency.JEL-Classification: C20, C60, G21

show abstract

“…The Herfindahl-Hirschman index (HHI) measures the market power of the local credit market (computed in terms of bank branches) at province level of firms. Following Fiordelisi et al (2011), it is calculated as the as the sum of banks squared market shares in loans granted in each one of the Italian provinces in year 2010.…”

Section: Variablesmentioning

confidence: 99%

Relationship Lending and Credit Quality

2013

Self Cite

View full text Add to dashboard Cite

We analyze if the relationship lending reduces the borrower's probability of borrowers' default and if this beneficial effect operates also for those borrowers who are more exposed to the economic downturn. By using unique, matched data of 43,000 firms and their lending institutions between 2008 and 2010, we document that the probability that a firm becomes distressed decreases when the creditor concentration is high and the duration of bank-firm relationships is long. While these results seem to support the beneficial effect of the relationship lending practices, we note that the organizational distance of banks and collateral also matters both as determinants of loan distress and as determinants of loan downgrading. The results are stronger for smaller firms.JEL classification: G21

show abstract

Efficiency and risk in European banking

Cited by 547 publications

References 38 publications

What drives investment bank performance? The role of risk, liquidity and fees prior to and during the crisis

What drives investment bank performance? The role of risk, liquidity and fees prior to and during the crisis

Nonstationary Z-Score measures

Relationship Lending and Credit Quality

Contact Info

Product

Resources

About