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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
- `SubscriptionSynchronizer` will emit a `TimeSlice.TimePulse` before
performing any universe selection on each time loop. This will advance
`Algorithm.Time` which will allow universe selection data time and
`Algorithm.Time` to be aligned.
- Updating Regression algorithms that were using `algorithm.Time` in the
selection method.
- Coarse selection will start from the algorithms start date (not in the
next day)
- Adding regression algorithm
- We will now check if python selection method returned `Universe.Unchanged`
- Removing `ToList()` call on fine and coarse data before sending it to
the python algorithm
- Adding regression algorithms
Ashutosh