This a reference request for any python notebooks, packages or blogs that teach how to do asset allocation using multivariate copulas. How can copula portfolio optimization actually be implemented in code rather than in theory?
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$\begingroup$ I do not understand why one would be interested in doing mean-variance optimisation with copulas. Isn't the whole point of using variance as a risk measure the fact that in a multivariate normal world it is the only risk measure? And the point of copulas is going beyond multivariate normal? $\endgroup$– g gCommented Aug 24, 2020 at 18:56
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$\begingroup$ distributions don't have to be multivariate normal to have a mean and covariance $\endgroup$– develaristCommented Aug 24, 2020 at 18:59
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$\begingroup$ Of course but the relevance of covariance is greatly reduced if you do not have multivariate normals. $\endgroup$– g gCommented Aug 24, 2020 at 20:53
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$\begingroup$ i've removed the word mean-variance from the question $\endgroup$– develaristCommented Aug 24, 2020 at 20:59
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$\begingroup$ @gg, if the agent is assumed to have quadratic utility, mean and variance are the only two moments that matter in maximization of expected utility -- regardless of the distribution. This is one of the justifications behind mean-variance optimization. $\endgroup$– Richard HardyCommented Aug 27, 2020 at 11:20
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