The following lecture talks about the Markowitz Portfolio Optimization problem in convex optimization. Indeed, many variants of this problem exists, but the classical one looks like this

where is an sized vector containing the amount of assets to invest in. The vector is the mean of the relative price asset change and the matrix is the matrix of variance-covariance of assets. The parameter is minimum accepted returns.

The problem is that in some scenarios, the matrix is ill-conditioned and so the solution to the above Markowitz problem, which takes the following form

will give misleading allocation values. This lecture deals with a conditioned Markowitz type problem where a penalty is added as follows

where in the lecture, we show, gives the following solution

Learn more on why the additional penalty term is one way to fix the ill-conditioned disease of matrix .

The source of this solution is given in *Brodie, Joshua, et al. “Sparse and stable Markowitz portfolios.” Proceedings of the National Academy of Sciences 106.30 (2009): 12267-12272.*

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