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* Filter out small orders based on Setting
- BuyingPowerModel will filter out small orders based on algorithm
setting, a % of PTV, instead of hard coded 1 share value. Addin unit
and regression tests
- Updating regression algorithms to use new setting, reduce order trades
* Update regression algorithms
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* Python research import improvements
- Improve start.py for research env
- Remove unrequired imports
* Centralize algorithm imports
* Add regression test GH action
* Unit test python import clean up
* Join research and main imports
* More python import clean up
* Fix failing skipped regression algorithm
- Adding new `ConfidenceWeightedPortfolioConstructionModel` (C# / Py) that will
generate percent `Targets` based on the latest active `Insight` `Confidence` per
`Symbol`.
- Will ignore `Insights` that have no `Confidence`.(unit tested)
- If the sum of all the last active `Insight` per `Symbol` is bigger than 1, it
will factor down each target percent holdings proportionally so the sum is 1. (unit tested)
- Adding unit tests
- Adding a new regression test framework algorithm (C#/Py)
-**Note**: `ConfidenceWeightedPortfolioConstructionModel` inherits from the `InsightWeightingPortfolioConstructionModel`. Protect method `GetValue` was implemented in `IWPCM` to enable the choice of `Insight` member.
Martin-Molinero