The elaborate proposes a compact alternative methodology to the classical stocks portfolio optimization based on the normal distribution of the returns of the assets named Adaptable - Kurtosis Asymmetry model (A-KA). In the financial theory is well-known that odd-order moments of a distribution describe a particular performance characteristic; on the contrary, the even-order moments tell a precise sense of risk of a distribution of returns. If it is true that, in general terms, minimizing the variance also minimizes the volatility of portfolio return is also true that we should minimize the kurtosis to get away from unpleasant situations in case “Extreme" events occur, especially if negative. The idea behind this paper is to exploit the four moments of return's distributions, optimizing an alternative risk indicator to variance, such as the kurtosis of the final distribution of the portfolio, making constraints on distributive asymmetry, in a dynamic underlying logic.

A-KA Model: an Optimization of the Stock's Portfolio

Mauro Bisceglia;
2020

Abstract

The elaborate proposes a compact alternative methodology to the classical stocks portfolio optimization based on the normal distribution of the returns of the assets named Adaptable - Kurtosis Asymmetry model (A-KA). In the financial theory is well-known that odd-order moments of a distribution describe a particular performance characteristic; on the contrary, the even-order moments tell a precise sense of risk of a distribution of returns. If it is true that, in general terms, minimizing the variance also minimizes the volatility of portfolio return is also true that we should minimize the kurtosis to get away from unpleasant situations in case “Extreme" events occur, especially if negative. The idea behind this paper is to exploit the four moments of return's distributions, optimizing an alternative risk indicator to variance, such as the kurtosis of the final distribution of the portfolio, making constraints on distributive asymmetry, in a dynamic underlying logic.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/280167
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