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...

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...

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...

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...

Rounding errors have a considerable impact on statistical inferences, especially when the data size is large and the finite normal mixture model is very important in many applied statistical problems, such as bioinformatics. In this article, we investigate the statistical impacts of rounding...

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...