If you have followed the earlier messages on this thread, I had started out with an initial problem statement of calculating portfolio standard deviation. Over last couple of weeks my problem statement evolved to identifying optimal weights for a given set of stocks when provided for information about their returns and volatility. With help from the community I was able to build two workflows which solved this problem.
I am attaching the first workflow here "Workflow_01_Weekly Stock Price_Quandl.yxmd" with an embedded macro "Macro_01_Stock Price_Quandl.yxmc". This workflow downloads weekly stock price data from Quandl. You can specify the Quandl codes and will also need to enter your API key for Quandl to be able to make this work for yourselves.
Once you download this weekly stock price data, you need to convert this into weekly returns and input this in the second workflow (Workflow_00_MPT_24Nov18_Upload.yxmd"). Following this you need to enter your constraints in the (ub, lb), in the stream which is connecting to Anchor O of the optimization icon in the workflow. The outputs on the browse tool should give you the optimal stock weights.
This is my first post, so please accept my apologies if my explanation is lacking somewhere. Also credits to the community where these workflows already existed and I merely have deployed it for my personal wealth management usage. Some other conceptual limitations from a finance perspective which Immediately come to my mind are that I have not adjusted for dividends / stock splits and to that extent my analysis will be deficient. Yet to figure out a way / database which gives data corrected for dividends / stock splits. Hopefully this will evolve over time.