This paper applies the mean-variance portfolio optimization (PO) approach and the stochastic dominance (SD) test to examine preferences for international diversification versus domestic diversification from American investors’ viewpoints. Our PO results imply that the domestic diversification...

Using the Markowitz mean-variance portfolio optimization theory, researchers have shown that the traditional estimated return greatly overestimates the theoretical optimal return, especially when the dimension to sample size ratio p/n is large. Bai, Liu, and Wong (2009) propose a...

Extending the work of Jobson and Korkie (1981), Lo (2002) and Memmel (2003), this paper applies the technique of the repeated measures design to develop the Multiple Sharpe ratio test statistic to test the hypothesis of the equality of the multiple Sharpe ratios. We also work out the asymptotic...

Using the Markowitz mean–variance portfolio optimization theory, researchers have shown that the traditional estimated return greatly overestimates the theoretical optimal return, especially when the dimension to sample size ratio p/n is large. Bai et al. (2009) propose a bootstrap-corrected...

The technique of ANOVA has been widely used in economics and finance where the observations are usually time-dependent but the model itself is treated as independent in time. In this paper, we extend an ANOVA model by relaxing the assumption of independence in time. We further relax the...

Studying the characteristics of different income distributions, and compare the differences among different income distributions with respect to geographic regions, and changes over time periods is a very important area in economics. In order to compare the differences among different income...

Using the Markowitz mean-variance portfolio optimization theory, researchers have shown that the traditional estimated return greatly overestimates the theoretical optimal return, especially when the dimension to sample size ratio is large. Bai, Liu, and Wong (2006,2009a,b) propose...