An open market share buyback is not a firm commitment, and there is limited evidence on whether firms repurchase the intended shares. Unlike US studies, we use data from unique UK regulatory and disclosure environment that allows to accurately measure the share buyback completion rates. We show that information disclosure and CEO overconfidence are significant determinants of the share buyback completion rate. In addition, we find that large and widely held firms that conduct subsequent buyback programs and have a past buyback completion reputation exhibit higher completion rates. Finally, we assess whether other CEO characteristics affect buyback completion rates and find that firms with senior CEOs who hold external directorships and have a longer tenure as CEO are more likely to complete the buyback programs. In sum, our results suggest there is a clear relationship between information disclosure, CEO overconfidence, and buyback completion rates.

We contribute to the current regulatory debate by examining the wealth and risk effects of the Dodd-Frank Act on U.S. financial institutions. We measure the effects of key legislative events of the Act by means of a multivariate regression model using the seemingly unrelated regression (SUR) framework. Our results indicate a mixed reaction by financial institutions during the various stages of the Act’s legislative process. Further tests reveal that any positive reactions are driven by small and/or low risk institutions, while negative ones are consistent across subsets; except for investment banks. We also find market risk increases for most financial institutions that are dominated by small and/or low risk firms. The cross-section results reveal that large institutions fare better than their smaller counterparts and that large investment banks gain value at the expense of others. Overall, the Dodd-Frank Act may have redistributed value among financial institutions, while not necessarily reducing the industry’s riskiness.

In this paper, we analyze whether regulation reduced risk during the credit crisis and the sovereign debt crisis for a cross section of global banks. In this regard, we examine distance to default (Laeven and Levine, 2008), systemic risk (Acharya et al., 2010), idiosyncratic risk, and systematic risk. We employ World Bank survey data on regulations to test our conjectures. We find that regulatory restrictions, official supervisory power, capital stringency, along with private monitoring can explain bank risk in both crises. Additionally, we find that deposit insurance schemes enhance moral hazard, as this encouraged banks to take on more risk and perform poorly during the sovereign debt crisis. Finally, official supervision and private monitoring explains the returns during both crisis periods.

Ratings issued by credit rating agencies (CRAs) play an important role in the global financial environment. Among other issues, past studies have explored the potential for predicting these ratings using a variety of explanatory factors and modeling approaches. This paper describes a multi-criteria classification approach that combines accounting data with a structural default prediction model in order to obtain improved predictions and test the incremental information that a structural model provides in this context. Empirical results are presented for a panel data set of European listed firms during the period 2002–2012. The analysis indicates that a distance-to-default measure obtained from a structural model adds significant information compared to popular financial ratios. Nevertheless, its power is considerably weakened when market capitalization is also considered. The robustness of the results is examined over time and under different rating category specifications.