The famous Hiemstra-Jones test (HJ test) developed by Hiemstra and Jones plays a significant role in studying nonlinear causality. In the last two decades there are numerous applications and theoretical extensions based on this pioneering work. However, several works pointed out that...

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...

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...

We propose and develop a mean-variance-ratio (MVR) statistics for comparing the performance of prospects (e.g., investment portfolios, assets, etc.) after the effect of the background risk has been mitigated. We investigate the performance of the statistics in large and small samples, and show...

To circumvent the limitations of the tests for coefficients of variation and Sharpe ratio, we develop the mean-variance-ratio statistic to test for the equality of the mean-variance ratios. We prove that our proposed statistic is uniformly most powerful unbiased. In addition, we provide the...

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...

To circumvent the limitations of the Sharpe-ratio statistic on testing small samples, we develop the mean-variance-ratio (MVR) statistic to test the performance among assets for small samples. We provide theoretical reasoning to use MVR and prove that our proposed statistic is uniformly most...

Bai, et al. (2011c) develop the mean-variance-ratio (MVR) statistic to test the performance among assets for small samples. They provide theoretical reasoning to use MVR and prove that our proposed statistic is uniformly most powerful unbiased. In this paper we illustrate the superiority of our...

The traditional estimated return for the Markowitz mean-variance optimization has been demonstrated to be seriously departed from its theoretic value. We prove that this phenomenon is natural and the estimated optimal return is always larger than its theoretic parameter. Thereafter, we develop...

The traditional linear Granger 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 nonlinear...