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...

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...

In this paper, we propose a quick and efficient method to examine whether a time series Yt possesses any nonlinear feature by testing a kind of dependence remained in the residuals after fitting Yt with a linear model. The advantage of our proposed nonlinearity test is that it is not required to...

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...

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...