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The article proposes two alternative dispersion measures consistent with additive shifts that can be used in investment portfolio selection problems. It examines the stochastic dominance of mean-dispersion approach and the properties of the two dispersion measures and compares these measures with the standard deviation and the conditional value at risk benchmark on the U.S. stock market. An analysis of portfolio diversification and turnover of investment strategies is presented.

In this note, we examine the impact of non linear reward and risk measures on portfolio selection. In particular, we compare the ex-post final wealth sample paths of strategies based on the Sharpe ratio and strategies based on non-linear reward/risk measures. As suggested by the recent literature, we model dependencies with an asymmetric t copula estimated on the innovations of the marginals that follow an ARMA-GARCH type model. Therefore, we first simulate future scenarios, on the basis of which allocation decisions are made, and then we compare the ex-post final wealth obtained with non-linear risk and reward strategies and the wealth obtained with classic portfolio strategies. [ABSTRACT FROM AUTHOR]

In this paper; we propose a methodology to value the portfolio choices based on the prediction of future returns where the dependence structure of joint returns and the behavior of single returns are estimated separately. In particular, we assume the marginals evolve as an ARMA(0,2)-GARCH(0,2) model with stable paretian residuals and the joint distribution of residuals is estimated with an asymmetric t-copula. Then, we compare the ex-post final wealth sample paths of different strategies based on reward/risk ratios. Doing so we examine and discuss the impact of the forecasting method with respect to classic myopic portfolio strategies based on the same reward/risk ratios. [ABSTRACT FROM AUTHOR]

In this note, we examine the impact of non linear reward and risk measures on portfolio selection. In particular, we compare the ex-post final wealth sample paths of strategies based on the Sharpe ratio and strategies based on non-linear reward/risk measures. As suggested by the recent literature, we model dependencies with an asymmetric t copula estimated on the innovations of the marginals that follow an ARMA-GARCH type model. Therefore, we first simulate future scenarios, on the basis of which allocation decisions are made, and then we compare the ex-post final wealth obtained with non-linear risk and reward strategies and the wealth obtained with classic portfolio strategies. [ABSTRACT FROM AUTHOR]

In this paper, we propose a methodology to value the portfolio choices based on the prediction of future returns where the dependence structure of joint returns and the behavior of single returns are estimated separately. In particular, we assume the marginals evolve as an ARMA(0,2)-GARCH(0,2) model with stable paretian residuals and the joint distribution of residuals is estimated with an asymmetric t-copula. Then, we compare the ex-post final wealth sample paths of different strategies based on reward/risk ratios. Doing so we examine and discuss the impact of the forecasting method with respect to classic myopic portfolio strategies based on the same reward/risk ratios. [ABSTRACT FROM AUTHOR]

In this paper we describe and apply estimating function theory to evaluate the parameters of parametric distributions uniquely defined by their characteristic functions. We first implement an estimating function model based on the first four moments of a parametric function of the underlying random variables. For instance we propose two parametric functions of the underlying random variables so as to obtain its first moments more easily by the simple knowledge of the characteristic function. Thus we consider the estimates that present the minimal asymptotic variance with respect to the parameter of the function. Then we propose an empirical analysis based on simulated stable Paretian distributions. Using simulated data of stable distributions we evaluate the forecasting power of the proposed methodology comparing it with the analogous maximum likelihood estimates. Moreover we show how to apply the same methodology to some well-known infinitely divisible distributions. [ABSTRACT FROM AUTHOR]

In this paper, we provide further insight into the stock return momentum phenomena by investigating the sources of momentum profits. Applying statistical factor analysis, we identify the most important variables significantly affecting momentum profits: volatility and changes in the currency component of M1. We also document the periodic dynamics of momentum returns that is their inflation at quarter-, month- and year- ends and their deflation at quarter-, month- and year - beginnings. [ABSTRACT FROM AUTHOR]