A Comparative Study of Mean-Variance  and Mean Gini Portfolio Selection  Using VaR and CVaR

Agouram, Jamal; Lakhnati, Ghizlane

doi:10.4236/jfrm.2015.42007

Cited by 9 publications

(4 citation statements)

References 6 publications

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“…Based on the above indices, investors prefer a model with a large value of diversification index. As another characterization measure, performance ratio was applied to compare the approaches of the different selection models, for more details, see [51][52][53]. The performance ratio was as follows:…”

Section: Portfolio Selection Of Uncertain Returnsmentioning

confidence: 99%

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

Wang,

Gao,

Ahmadzade

et al. 2023

Mathematics

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The partial Gini coefficient measures the strength of dispersion for uncertain random variables, while controlling for the effects of all random variables. Similarly to variance, the partial Gini coefficient plays an important role in uncertain random portfolio selection problems, as a risk measure to find the optimal proportions for securities. We first define the partial Gini coefficient as a risk measure in uncertain random environments. Then, we obtain a computational formula for computing the partial Gini coefficient of uncertain random variables. Moreover, we apply the partial Gini coefficient to characterize risk of investment and investigate a mean-partial Gini model with uncertain random returns. To display the performance of the mean-partial Gini portfolio selection model, some computational examples are provided. To compare the mean-partial Gini model with the traditional mean-variance model using performance ratio and diversification indices, we apply Wilcoxon non-parametric tests for related samples.

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Section: Portfolio Selection Of Uncertain Returnsmentioning

confidence: 99%

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

Wang,

Gao,

Ahmadzade

et al. 2023

Mathematics

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“…The Mean-Gini (MG) approach in finance is used by Bey and Howe [34] in portfolio analysis, Okunev [35] to evaluate the performance of mutual funds, Shalit and Yitzhaki [24] and agouram & lakhnati [36] [37] [38] to obtain optimal portfolio selection, Cheung et al [39] to examine the effectiveness of hedging options and futures contracts, and Berkhouch et al [40] introduced and applied the Tail Extended Gini functional and the Extended Gini Shortfall on daily returns for the MASI index.…”

Section: The Mean-gini (Mg) Modelmentioning

confidence: 99%

An Empirical Comparison of Different Two-Factor Models in the Context of Portfolio Optimisation

2020

Adv. sci. technol. eng. syst. j.

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The crisis linked to the COVID-19 and the uncertainty it generates in the unprecedented health, societal, economic and financial fields have had a strong impact on the stock markets. Indeed, in such a climate of very high uncertainty, it is to be expected that the excessive stock market price movements will continue, with both declines and technical rebounds, and that the resulting volatility will remain particularly high. In order to cope with this crisis, investors and portfolio managers must mobilize all portfolio selection strategies. In particular, portfolio management and construction are based on the concepts of return and risk. This couple has been at the center of all the concerns of managers and investors in portfolio optimization issues since the introduction of the mean-variance model by Markowitz. However, many studies have proposed different measures of risk to overcome the drawbacks of variance. The objective of this paper is to present and compare the portfolio compositions and performance of four different portfolio optimization models using different risk measures, including variance, Mean Absolute Deviation, Gini coefficient and Lower Partial Moments (LPM). The results of this study show that the Mean-Lower Partial Moments (MLPM) model outperforms other models. The Mean-Lower Partial Moments (MLPM) model is suitable for investors during the crisis period (COVID-19) in the Moroccan financial market.

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“…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.…”

Section: Introductionmentioning

confidence: 99%

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

KOUIRI

Agouram

Kadouri

2021

International Journal of Social Sciences Perspectives

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This article aims to understand the general context of research on the impact of ownership structure and performance of firms through a systematic review of references that include the keywords "ownership structure" and "performance" in their titles and that are published in English between 1990 and June 2020. For this purpose, we used articles published in journals indexed in the Scopus database. The uploaded articles are organized by the Mendeley Desktop tool and then transferred to the NVivo10 tool, in order to make a textual analysis of the elements contained in the articles. Data concerning the article, the characteristics of the study population, were collected. Our initial bibliographic search covered 229 articles published in 141 journals registered in more than 30 databases. It was found that the journals have published on this subject belongs to several disciplines related to governance, finance, and management and that they come from Anglo-Saxon countries. Our work can be considered as a support in the study of the scientific literature review related to ownership structure and performance.

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A Comparative Study of Mean-Variance and Mean Gini Portfolio Selection Using VaR and CVaR

Cited by 9 publications

References 6 publications

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

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

An Empirical Comparison of Different Two-Factor Models in the Context of Portfolio Optimisation

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

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