The relationship between banking market competition and risk-taking: Do size and capitalization matter?

This paper addresses the effects of bank competition on the risk-taking behaviors of banks in 10 Latin American countries between 2003 and 2008. We conduct our empirical approach in two steps. First, we estimate the Boone indicator, which is a measure of competition. We then regress this measure and other explanatory variables on the banking "stability inefficiency" derived simultaneously from the estimation of a stability stochastic frontier. Unlike previous findings, this paper concludes that competition affects risk-taking behavior in a non-linear way as both high and low competition levels enhance financial stability, while we find the opposite effect for average competition. In addition, bank size and capitalization are essential factors in explaining this relationship. On the one hand, the larger a bank is, the more it benefits from competition. On the other hand, a greater capital ratio is advantageous for banks that operate in collusive markets, while capitalization only enhances the stability of larger banks under high and average competition. These results are of extreme importance when considering bank regulations, especially in light of the recent turmoil in the global financial markets. (C) 2012 Elsevier B.V. All rights reserved.

Relationship of aerobic and neuromuscular indexes with specific actions in judo

Objective. - The aim of this study was to verify the relationship of aerobic and neuromuscular indexes with specific situations in judo. Method. - Eighteen male judokas took part in the study. The following assessments were performed: vertical jump (CMJ) on a force platform; Special Judo Fitness Test (SJFT) to obtain the number of throws and percentage of the maximal heart rate (%HRmax) one minute after the test; match simulation to obtain the peak blood lactate (LACmax) and the percentage of the blood lactate removal (BLR); incremental test to obtain the velocity at the anaerobic threshold (vAT) and peak velocity (PV) reached in the test. Results. - A significant correlation was observed between the number of throws in the SJFT, the vAT (r = 0.60; P < 0.01), PV (r = 0.70; P < 0.01) and CMJ (r = 0.74; P < 0.01). A significant inverse correlation was found between the LACmax and vAT (r = -0.59; P = 0.01). Conclusions. - It can be concluded that the performance in the SJFT was determined by the aerobic capacity and power and the muscle power. Athletes with greater aerobic ability (vAT) presented lower blood lactate accumulation after the match. (c) 2011 Elsevier Masson SAS. All rights reserved.

Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables

A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.