Hello financial experts :)
I recently got interested in portfolio optimization. I'm still learning. As I'm familiar with python I started experimenting a little in JupyterNotebooks with riskfolio. I used this tutorial: Hierarchical Risk Parity (HRP) Portfolio Optimization to get the weights. Now I would like to include the market cap as factor. Sadly the docs and the maintainer weren't very helpful / beginner friendly. Maybe some of you are able to help me answer some questions that came up.
I have the market caps like this:
market_cap_weights = np.array([mcap / np.sum(mcaps) for mcap in mcaps])
- Is Black Litterman the right approach to include the market cap? There is an example notebook. It uses pretty complex views though and it seems too advanced / has to much settings for my usage? It would be great if someone could point me on how to use them for simple market cap weights.
- If BL is not the right approach what is?
Grateful for any help. Thank you.