Sometimes we refer to single-period portfolio optimization as Markowitz portfolio optimization. Our input datasets include the expected returns, the standard deviations, and the correlation matrix between financial assets, and our output will be an efficient frontier formed by those assets. In the rest of the chapter, we will use historical returns to represent expected returns and use the historical correlation in place of expected correlation.
In the following examples, we use an R package called fPortfolio. We use the following code to install the package:
install.packages("fPortfolio")
To load various embedded datasets, we use the data() function (see the following example code):
library(fPortfolio)
data(GCCINDEX.RET)
dim(GCCINDEX.RET) [1] 824 11
The following table lists the embedded datasets:
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#
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Name
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Dimension... |