Mean-Gini portfolio optimisation (Excel)

Today we are going to discuss a very unique and not so well-known portfolio management framework: the mean-Gini (MG) optimisation theory developed by Shalit and Yitzhaki in 1984. It utilises the Gini coefficient, a well-known inequality measure from economics, to measure the risk of the portfolio empirical return distribution. We will implement the mean-Gini framework in Excel, discuss its applicability, assumptions, and limitations.

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[sendywinardi]

Hi, thankyou for your video, it is a very interesting material explaining a new method of portfolio optimization (new for me). But I have a question on the Gini coefficient formula. When I look up to the original journal by Shalit & Yitzhaki (1984) the Gini coefficient formula is only covariance between return and its rank. Why did you divide it by mu times n? Is there any reason behind it?

[lukemunkombwe]

Thank you, this is very helpful! Do you have a video on how to construct a mean semi variance efficient frontier. O learnt that the approach is not so exactly with the MV approach due to the endogeneity problem encountered in the ES approach

[TT-eget]

Great work. I wonder if you would consider repeating the work in python ?

[mahnoorfatima]

Can you tell me how construct sized based portfolio by ranking all the firm in the beginning of each year according to their market capitalization and then divide them into five equal quintile group. kindly guide me regarding this it help me alot i shall be very thankful to you for this favour.

[revgro]

Another nice video. Can you produce a video on the Hawkes Process?

[plazmafield]

Hey Savva, mentioning optimization... ehemm.. sorry, the British way, optimisation :P, it would be helpful to cover optimization methodology and processes that are performed behind the scenes for Excel's GRG nonlinear and Evolutionary methods within Solver. While I have a feel for when to do what, I don't entirely understand what happens behind the scenes with each method or input option.