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I am not a particularly big fan of fPortfolio. My first thought was to estimate a mean and covariance matrix accounting for the missing data (should be discussed several times on this site or other places) and pass that. However, looking at the manual, it looks like the relevant functions only take time series data. Based on that limitation, you have a few ...


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PerformanceAnalytics in R and PortfolioAnalytics in R Here is a tutorial from UW http://faculty.washington.edu/ezivot/econ424/portfolioFunctionsPowerPoint.pdf


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This spreadsheet shows how to implement Konno's Mean Absolute Deviation (MAD) Portfolio Optimization in Excel using LP Simplex methods. For strictly multivariate normal underlyings, the method can be shown to be equivalent to the standard Mean Variance Optimization method of Markowitz et al. The method is based on the paper Further Reduction of the ...


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A friend constructed an equal weight portfolio for a client that was constrained to a certain number of holdings. I don't mean less than 20 (less than or equal constraints are more common) but =20 holdings. He chose an ordinality based (sort) approach and he liked a paper, but I don't remember which one. Until then I hadn't thought about using the approach ...


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since you've assumed that all returns are independent, the covariance matrix, $C,$ is diagonal. In the comments, you are assuming that the investor is a mean-variance investor. It's a general result that every portfolio that maximizes return for a given variance is a tangent portfolio for some risk-free rate, $R.$ Let $e=(1,1,...,1).$ and let $\mu$ be the ...



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