* First draft of the solution
* Add missing changes
* Remove the new KPI's from report
* Fix bugs
* nit change
* Add improvements
* Fix regression tests
* Solve bugs in the regression algos
* Fix regression tests bugs
* Expand unit tests and add minor changes
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* Add Sortino ratio to statistics and report
* Adds Sortino Ratio to Report Key Statistics
* Addresses Peer-Review
Reuse `SharpeRatioReportElement` and change the template.
* Reuse Calculations Across Statistics and PortfolioStatistics
* Adds Sortino Ratio to Regression Algorithms
* Removes Sortino Ratio from Optimization Result Table
---------
Co-authored-by: Alexandre Catarino <AlexCatarino@users.noreply.github.com>
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* Add new Order.PriceAdjustmentMode property
* Minor fix and unit test
* Minor fix and regression algorithms' stats update
* Unit test fixes
* Minor fix
* Set order price adjustment mode to raw always for live trading
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* Refactor alpha statistics
- Refactor alpha statistics, cleaning up and simplifying no longer required calculations and scoring
- Adding new InsightEvaluator abstraction, adding C# & PY regression
algorithms
* Optimization backtest result json converter update
* Address reviews
- Remove IAlphaHandler, move insight storage responsability to IResultHandler
and centralizing insight collection on the QCAlgorithm.Insights to be
reused by the framework models
- Fix portfolio turnover single day backtests and duplicate time
sampling handling. Updating regression algorithms
* Add InsightCollection tests and minor fixes
* Adding more & improved tests
* add data count properties
* 'add history count property
* assert data counts
* update missing override
* consider override/virtual cases
* implement data count
* add message handler for regression tests
* use regression test message handler
* set algorithm manager for regression test message handler
* update data count
* check if stats are present, check if algo manager is not null
* update
* add c# algo
* make same as c# algo
* use new line
* logic shifted to RegressionTestMessageHandler
* cleanup
* auto cleanup
* skip non deterministic data count
* change data count
* use inheritance
* improve stats
* update couht
* add sma indicator to c# and customSMA to python
* call base method before executing further
* skip test
* revert to original
* add duplicate sma
* skip regression test
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* Refactor `GetFilePath()`
Add also useful methods to use with this one
* Nit changes
* Requested changes
* Requested changes
* Restore SaveString()
* Nit changes
* Address self review
* Test improvements
* Adjust example KerasNeuralNetworkAlgorithm
* Minor tweak for KerasNeuralNetworkAlgorithm.py
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
Shows how to read/save object store entires. In this case, it shows a
use case where a potentially time intensive operation's result is saved
in the object store and on subsequent runs the result is pulled directly
from the object store to enable faster run times
Ricardo Andrés Marino Rojas