We analyze the impact of the most recent global financial crisis (GFC) on the seven most important Latin American stock markets. Our mean-variance analysis shows that the markets are significantly less volatile and, in general, investors prefer to invest in the post-GFC period. Our results from...

Davidson and Duclos (DD, 2000) develop the stochastic dominance statistics, T_j(x)(j=1,2,3), to test the hypothesis on statistically significant differences between any two cumulative density functions F and G for assets Y and Z, respectively. The DD test compares distributions at only a finite...

Chow, et al. (2016) use the theory of ascending stochastic dominance (ASD), descending stochastic dominance (DSD) to develop stochastic dominance (SD) tests for richness and poorness. In this paper, we extend their work by applying Markowitz stochastic dominance (MSD) and prospect stochastic...

The traditional linear Granger causality test has been widely used to examine the linear causality among several time series in bivariate settings as well as multivariate settings. Hiemstra and Jones (1994) develop a nonlinear Granger causality test in a bivariate setting to investigate the...

Portfolio selection and risk management are very actively studied topics in quantitative finance and applied statistics. They are closely related to the dependency structure of portfolio assets or risk factors. The correlation structure across assets and opposite tail movements are essential to...

We analyse a sample of funds and other securities each assigned a total rating score by an unknown expert entity. The scores are based on a number of risk and complexity factors, each assigned a category (factor score) of Low, Medium, or High by the expert entity. A principal component analysis...