I want to run an optimization procedure under certain constraints (for example Markowitz Minimum Variance under the constraint of no short positions).
Regarding my data: Initially, I have a sample of stocks which contains of monthly returns, market cap and book-to-market information per month. I wrote a program that does the typical Fama/French portfolio sorting. The data is structured the following way: For each variable and point in time exists a series object which contains this information for all firms.
After the sorting process I have new series objects, which contain the returns of all firms of one portolio (for example the smallest size decile) for each point in time. Equal-weighting (-> just the mean of the series object) and Value-weighting is easy to implement. But I have no clue how to implement a minimum variance weighting.
Thank you in advance
