I am learning how to use the Portfolio Analytics package in R and I am concerned with overfitting the data for the optimization.

The optimize.portfolio.rebalancing() function has 2 parameters that might help with this:

training_period item{training_period}{an integer of the number of periods to use as a training data in the front of the returns data}

rolling_window \item{rolling_window}{an integer of the width (i.e. the number of periods) of the rolling window, the default of NULL will run the optimization using the data from inception.}

There is also some documentation with an example from CRAN. Here is the Link Pg.84

However, I am having a little difficulty understanding exactly what these do. In my script, I am rebalancing monthly and using daily data. I would like to do something like a Walk Forward Analysis - Optimize on 0:60 days and then test performance on 61:70 days.

Would my parameters be set to: rolling_window = 70; training_period = 60 ?



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