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Download Bank Performance, Risk and Firm Financing (Palgrave by Philip Molyneux PDF

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By Philip Molyneux

This article contains a variety of papers that provide cutting-edge insights into bank functionality, danger and enterprise financing publish main issue that have been provided on the ecu organization of college academics of Banking and Finance convention (otherwise often called the Wolpertinger convention) held at Bangor college, Wales, 2010.

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Extra resources for Bank Performance, Risk and Firm Financing (Palgrave MacMillan Studies in Banking and Financial Institut)

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Indd 35 Pjt (1) 5/26/2011 4:53:35 PM 36 Mario Anolli and Elena Beccalli where: EPSjt 5 actual current earnings per share for each bank j for forecast period t; FEPSyjt 5 current earnings forecast of each individual analyst y for each bank j for each forecast period t; Pjt 5 last available stock price for each bank j for period t. Specifically, we employ two measures of the forecast error according to the type of earnings forecasts used: a. Mean forecast error, where the forecast EPS is the mean consensus forecast calculated as the mean value of all individual forecasts available from the day of the previous annual earnings announcement till the day of the present annual earnings announcement (as done in Lang and Lundholm, 1993); b.

4 Determinants of financial stability. 01. All estimations include fixed and time effects. Source: authors’ own work. indd 21 5/26/2011 4:50:22 PM 22 Joaquín Maudos and Juan Fernández de Guevara GDP growth rate, per capita income, the provisions ratio (as percentage of loans), specialization (relative importance of loans in total assets), stock market capitalization (as percentage of GDP) and inflation. In general, the explanatory variables are shown to be significant (from a statistical point of view) when explaining the differences in market power between banks.

With this objective, we calculated what the variation of the Lerner index would be if it were calculated starting from an observation situated at the value of the 25th percentile of each of the independent variables and increasing up to the value defined by the 75th percentile. 3, we find that the greatest effect on market power is generated by size, since the growth from the 25th percentile to the 75th percentile would signify an 83 per cent growth of market power. At the same time, although the elasticity of per capita GDP was the highest, if its sample range of variation is taken into account the impact on the Lerner index is less than the effect of size, representing a fall of 73 per cent in market power in relation to the level of the 25th percentile.

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