1,720,968 research outputs found
Corporate governance and market performance of European banks: Analysing differences and similarities between one-tier and two-tier models
No full textDue to the relevant role of banks in economies, the subject of corporate governance of banks is attracting growing attention by researchers worldwide. They generally focus on the relationships between board structure and bank performance and risk level. Unfortunately, the results of the studies are somehow contradictory. Thus, this is calling for further investigation on this topic. We have tested the effects of several corporate governance variables (board size, women size, average age and board duration) on bank performance of 46 European banks with one-tier and two-tier corporate governance models. The results show differences and similarities within the two subgroups of banks (i.e., relating to board size, independence and number of female directors). Findings are presented and commented for inspiring policy makers and regulators as well as for driving the management strategy to foster profitability. 2021 Inderscience Enterprises Ltd
Better safe than sorry. Bank corporate governance, risk-taking, and performance
No full textConventional wisdom leads to assert that good governance may underpin bank performance while bad governance destroys stability and soundness. We run a factor analysis to synthesize 23 bank board characteristics of the Eurostoxx banks into seven key features: independence, size, dedication, tenure, corporate governance quality, external perspective, competence, and diversity. We then use multiple regression and find that independence and board and committees size are the most relevant characteristics for banks risk-taking and in line with the agency theory, our results show that independence increases the solvency of banks, and size reduces it
Systemic risk measurement: bucketing global systemically important banks
No full textThe general consensus on the need to enhance the resilience of the financial system has led to the imposition of higher capital requirements for certain institutions, supposedly based on their contribution to systemic risk. Global Systemically Important Banks (G-SIBs) are divided into buckets based on their required additional capital buffers ranging from 1% to 3.5%. We measure the marginal contribution to systemic risk of 26 G-SIBs using the Distressed Insurance Premium methodology proposed by Huang et al. (J Bank Financ 33:2036–2049, 2009) and examine ranking consistency with that using the SRISK of Acharya et al. (Am Econ Rev 102:59–64, 2012). We then compare the bucketing using the two academic approaches and supervisory buckets. Because it leads to capital surcharges, bucketing should be consistent, irrespective of methodology. Instead, discrepancies in the allocation between buckets emerge and this suggests the complementary use of other methodologies
Application of the Merton model to estimate the probability of breaching the capital requirements under Basel III rules
No full textIn this paper, we estimate the probability of a financial institution breaching the Common Equity Tier 1 capital under Basel III rules. We do so by applying the Merton model, where balance sheet data and market data are used to match the probability of default implied by the model with the probability of default implied by market quotations for credit default swaps. We provide an empirical analysis for several banks classified by the Financial Stability Board and the Basel Committee on Banking Supervision as Global Systemically Important Financial Institutions, evaluating how the probability of breaching the Common Equity Tier 1 Capital evolved from 2005 to 2015. We find that higher Common Equity Tier 1 Capital ratios do not necessarily imply lower probabilities of breaching capital requirements and vice versa. We also focus on the asset volatility calibrated according to our model and we find that it appears to be a good proxy for the risk-weighted asset density
Assessing Bank Default Determinants via Machine Learning
No full textThe financial sector is very interested in Artificial Intelligence due to the opportunities that it offers, especially those related to methods of machine-learning. The aim of this paper is to employ a variety of machine-learning algorithms to identify the main determinants of bank default and to understand the impact of each variable on it. Bank default is one of themost studied topics in financial literature because of the severity of its consequences on the whole economic system. However, little attention has been paid to the identification of the major determinants of bank failures via machine-learning
pproaches. This paper employs several machine-learning algorithms, including a graph neural network that has never been used in a financial context. Another novelty is the implementation of a balanced dataset by customising the heuristic oversampling method based on k-means and synthetic minority over-sampling technique. This paper also deals with the inclusion of competition among the possible default determinants. The dataset consists of all the banks in the Euro Area in the period 2018–2020. The results obtained are useful from both micro- and macro-economic points of view
May board committees reduce the probability of financial distress? A survival analysis on Italian companies
No full textThe aim of this research was to study the effect of the composition and functioning of board committees on firms’
financial distress. Exponential, Weibull and Cox regression models were used to conduct a survival analysis on a
sample of 273 Italian listed companies for the period 2004–2017, which indicated that the presence of non-
executive members on remuneration and audit committees, and remuneration committees meeting more
frequently may enhance firms’ stability. In contrast, a high frequency of nomination committee meetings seems
to be positively related to the probability of financial distress.
Although we only partially controlled for endogeneity issues, our findings contribute to the literature on
financial distress-prediction models by deepening the importance of the composition and functioning of board
committees (beyond other corporate governance variables and financial ratios). We can also provide firms with
practical suggestions to promote financial stability
Environmental, Social, Governance: Implications for businesses and effects for stakeholders
No full textCan governance help in making an IPO “successful”? New evidence from Europe
No full textThis paper investigates the determinants of a “successful” IPO from a corporate governance perspective upon a representative sample of European listings from 2000 to 2015. We use an extensive dataset of market performance, financial data, and corporate governance characteristics to run the investigation. Differently from previous studies, our analysis embraces both a short-term perspective and a medium–long-term perspective, where the board of directors seems to perform different tasks, moving from a value creation to a value protection strategy. Among the others, we find that board size, board independence, and their qualifications, together with their experience in other boards, are associated with a positive performance of the IPO in a short-term horizon and in the medium–long-term period, although significant differences emerge among those time perspectives
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