We didn't experience the expected performance improvements. Locally under
unit test there was aboout an order of magnitude throughput increase, but
when run against the history benchmark, this new approach was 60% slower.
We're reverting this for now to perform further analysis and better
understand the performance profiling of the python history stack.
`EqualEeightingPortfolioConstructionModel` (C# and Python) allocates all cash to the stocks who have insights in universe.
- Fixes regression tests to reflect the model logic change
- Fixes imports in python algorithms to use python models when available