Optimal portfolio performance with exchange-traded funds

In this paper, the portfolio selection problem in exchange-traded fund (hereafter ETF) markets is considered. Since the ETFs track some market indexes with lower costs than the indexes, their development and popularity is grown enormously in the last decade. Moreover, ETF characteristics also present several advantages for the investors that we briefly examine for the U.S. and European markets of ETFs. In particular, we first introduce a new performance measure consistent with the optimal choices of non-satiable risk-averse investors and then we discuss the optimization of a few performance measures on the U.S. and European ETF markets. Finally, we propose an empirical comparison among the ex-post wealth obtained by optimizing the new performance measure, the Sharpe ratio and the Rachev ratio

DESIRABLE PROPERTIES OF AN IDEAL RISK MEASURE IN PORTFOLIO THEORY

This paper examines the properties that a risk measure should satisfy in order to characterize an investor's preferences. In particular, we propose some intuitive and realistic examples that describe several desirable features of an ideal risk measure. This analysis is the first step in understanding how to classify an investor's risk. Risk is an asymmetric, relative, heteroskedastic, multidimensional concept that has to take into account asymptotic behavior of returns, inter-temporal dependence, risk-time aggregation, and the impact of several economic phenomena that could influence an investor's preferences. In order to consider the financial impact of the several aspects of risk, we propose and analyze the relationship between distributional modeling and risk measures. Similar to the notion of ideal probability metric to a given approximation problem, we are in the search for an ideal risk measure or ideal performance ratio for a portfolio selection problem. We then emphasize the parallels between risk measures and probability metrics, underlying the computational advantage and disadvantage of different approaches.Risk aversion, portfolio choice, investment risk, reward measure, diversification

THE PROPER USE OF RISK MEASURES IN PORTFOLIO THEORY

This paper discusses and analyzes risk measure properties in order to understand how a risk measure has to be used to optimize the investor's portfolio choices. In particular, we distinguish between two admissible classes of risk measures proposed in the portfolio literature: safety-risk measures and dispersion measures. We study and describe how the risk could depend on other distributional parameters. Then, we examine and discuss the differences between statistical parametric models and linear fund separation ones. Finally, we propose an empirical comparison among three different portfolio choice models which depend on the mean, on a risk measure, and on a skewness parameter. Thus, we assess and value the impact on the investor's preferences of three different risk measures even considering some derivative assets among the possible choices.Skewness, safety risk measures, risk aversion, dispersion measures, portfolio selection, investors' preference, fund separation

Portfolio selection with heavy tailed distributions

This paper analyzes portfolio selection models with heavy tailed return distributions. Firstly, we examine investor’s optimal choices when we assume respectively either Gaussian or stable non-Gaussian unconditional distributed index returns. Then, we approximate discrete time optimal allocations assuming returns following an ARMA process. Finally, we describe further autoregressive portfolio choice models