We came up with the idea to estimate the distribution of a given set of assets. This works at the moment in MATLAB and Python, I wanted to implement the code here in Quantopia to combine our model with different factors. The IDE algorithm works, but the it is not stable, due to the time limit in data handle (It works for 14 assets).
Now, I would like to move the code to the pipeline, because their I have no time restrictions.
1) Filters are applied to get the 2% of assets with the best liquidity
2) Calculate the log returns for a given window, where are nan are dropped or set to zero. (reg. returns would work as well, but I would prefer log).
3) Start with our estimation, where the log returns are the input parameter.
The problem is, that I don't know how to handle the isnan filter or apply. There is a schedule attached.