This study examines the impact of changes in the yield curve factors on the Credit Default Swap (CDS) spreads of the U.S. industrial sectors. Stock returns and the crude oil-based volatility index are used in a quantile regression framework to test the validity of Merton's model. The results...

Analyzing the success of movies has always been a popular research topic in the film industry. Artificial intelligence and machine learning methods in the movie industry have been applied to modeling the financial success of the movie industry. The new contribution of this research combined...

We empirically investigate the impact of capital structure on bank profitability using a quantile regression method in the Vietnamese banking system during 2007-2019. Our results suggest that the nonlinear relationship between capitalization and bank profitability is only significant at the 90th...

This paper discusses questions of the gender diversity of corporate boards vis-à-vis firm performance. Typically, researchers have asked if a female presence is associated with improved performance and more transparent governance. The paper's first part reports on several econometric attempts...

This paper analyzes high-frequency estimates of good and bad realized volatility of Bitcoin. We show that volatility asymmetry depends on the volatility regime and the forecast horizon. For one-day ahead forecasts, good volatility commands a stronger impact on future volatility than bad...

This study empirically presents evidence of nonlinearity and heterogeneity relation between intellectual capital and risk-taking for the Vietnamese banking system. We used quantile regression methods on a data set of 30 Vietnamese banks from 2007 to 2019. The results showed that bank insolvency...

Purpose: Zimbabwe experienced hyperinflation (2000-2008) followed by dollarization from 2009 onwards which had implications on dividend policy. In this context, this study isolates the main determinants and examines their behaviour across the distribution of dividend policy....

We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heterogeneity among control variables. We also...

In this study, we investigate the estimation and inference on a low-dimensional causal parameter in the presence of high-dimensional controls in an instrumental variable quantile regression. Our proposed econometric procedure builds on the Neyman-type orthogonal moment conditions of a previous...

This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest a practical two-step estimation procedure, where the generated regressors are computed in the first step. The asymptotic properties of the two-step estimator, namely,...