Mean-Gini portfolio selection: Forecasting VaR using GARCH models in Moroccan financial market

Abstract

This paper focuses on Mean-Gini (MG) method for optimum portfolio selection. The MG framework, introduced by Shalit and Yitzhaki, is an attractive alternative as it is consistent with stochastic dominance rules regardless of the probability distributions of asset returns. Therefore, a MG framework is similar to a corresponding Mean-Variance (MV) framework in that it also uses two summary statisticsthe mean and a measure of dispersion to characterize the distribution of a risky prospect. The goal of this paper is to test MG strategy, based on Moroccan financial market data from turbulent market period of the years 2011, 2012, 2013 and 2014. In addition, those outcomes are explicitly tested in terms of Value-at-risque (VaR). The results show that MG strategy is profitable for investors. Moreover, we consider MG strategy to be safer in turbulent times.

Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model

“…The application of the Gini coefficient extends to finance [ [61] , [62] , [63] ], the Gini coefficient was utilized as an indispensable, multifunctional metric with applicability spanning various forecasting and optimization paradigms. Reference [ 61 ] employed the Gini coefficient as an evaluative metric within the Classification and Regression Tree (CART) algorithm, specifically for node purity assessment to optimizing decision tree attributes.…”

“…Here, the Gini coefficient functions as part of the input for machine learning and logistic regression models. Meanwhile [ 63 ], introduced the Mean-Gini (MG) method as a robust alternative to the traditional Mean-Variance (MV) approach in investment portfolio optimization, particularly within the volatile Moroccan financial market. The study employs the Gini coefficient to measure risk, as opposed to solely relying on variance, thereby offering portfolio managers in emerging markets a more robust risk-assessment tool.…”

Partial Gini Coefficient for Uncertain Random Variables with Application to Portfolio Selection

“…The first portfolio selection problem was proposed by Markowitz [6] using a mean-variance model with random returns. In addition, Konno and Yamazaki [7], Agouram and Lakhnati [8] and Favre and Galeano [9] obtained optimal solutions for random portfolio selection problems using absolute deviation, value at risk, and modified value at risk, respectively.…”

Ownership Structure and Performance of Companies: Exploratory Study via a Systematic Review of the Literature

“…Several researchers have carried out work to highlight the relationship between the ownership structure and the performance of firms. In particular, financial literature has devoted a considerable degree of attention to this relationship (Agouram, Anoualigh, & Lakhnati, 2020;Agouram & Lakhnati, 2015, 2016Agouram., Harabida, Radi, & Lakhnati, 2020;Jamal & Lakhnati, 2015). First, several works study the relationship between the concentration of capital and the performance of firms.…”