This afternoon, I will start a crash course on financial portfolio optimization, with application in R. This week, we start with simple things, with the theoretical setup, without and with a risk free asset. We will discuss then the problem of estimating parameters, in a robust way. Then we introduce the idea of consider a more general criteria to quantify risk than the variance (but it means more general distributions… this point will be discussed further next time). The slides are available here, and R codes from there (in a Markdown)
OpenEdition suggests that you cite this post as follows:
Arthur Charpentier (November 14, 2017). Optimal Portfolios #1. Freakonometrics. Retrieved September 8, 2024 from https://doi.org/10.58079/ov8t
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