This paper extends the work of Korkie and Turtle (2002) by first proving that the traditional estimate for the optimal return of self-financing portfolios always over-estimates from its theoretic value. To circumvent the problem, we develop a Bootstrap estimate for the optimal return of...

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...

Levy and Levy (2002, 2004) and others extend the stochastic dominance (SD) theory for risk averters and risk seekers by developing the prospect SD (PSD) and Markowitz SD (MSD) theory for investors with S-shaped and reverse S-shaped (RS-shaped) utility functions. Davidson and Duclos (DD, 2000)...

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...

We derive the limiting process of the stochastic dominance statistics for risk averters as well as for risk seekers when the underlying processes might be dependent or independent. We take account of the dependency of the partitions and propose a bootstrap method to decide the critical point. In...

We derive the limiting process of the stochastic dominance statistics for risk averters as well as for risk seekers when the underlying processes might be dependent or independent. We take account of the dependency of the partitions and propose a bootstrap method to decide the critical point. In...

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 [19] develop a nonlinear Granger causality test in bivariate settings to investigate the nonlinear...