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* Implement ShortableProviderPythonWrapper.cs
- Modify AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs and ShortableProviderOrdersRejectedRegressionAlgorithm.cs to use ShortableProvider from Security and not from the Brokerage model
- Add SetShortableProvider() overload method in Security.cs to set a custom shortable provider from Python
- Remove AllShortableSymbols() method from LocalDiskShortableProvider.cs
- Remove DefaultShortableProvider class
- Add regresion algorithms in C# to cover the changes done
* Revert "Merge process"
This reverts commit 775a4b8ec18e0f1562b72c27203ec0df84c8f675, reversing
changes made to bcc3e790f66fe744ea6f4cb2083c3e9d1881ea2f.
* Revert "Revert "Merge process""
This reverts commit aa18fb40eec2aa551ab7a81310ba4515270d6c1a.
* Solve bugs
- Solve bugs in DefaultMarkets, CanUpdateOrder() and CanSubmitOrder() methods from BrokerageModelPythonWrapper.cs
- Add regression algos in both Python and C# to cover the changes
* Catch potential errors and add unit tests
* Add more unit tests
* Nit change
* Enhance implementation, add more unit tests
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* Implement ShortableProviderPythonWrapper.cs
- Modify AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs and ShortableProviderOrdersRejectedRegressionAlgorithm.cs to use ShortableProvider from Security and not from the Brokerage model
- Add SetShortableProvider() overload method in Security.cs to set a custom shortable provider from Python
- Remove AllShortableSymbols() method from LocalDiskShortableProvider.cs
- Remove DefaultShortableProvider class
- Add regresion algorithms in C# to cover the changes done
* Revert "Merge process"
This reverts commit 775a4b8ec18e0f1562b72c27203ec0df84c8f675, reversing
changes made to bcc3e790f66fe744ea6f4cb2083c3e9d1881ea2f.
* Revert "Revert "Merge process""
This reverts commit aa18fb40eec2aa551ab7a81310ba4515270d6c1a.
* Solve bug
- Add new constructor overload in OpenInterestFutureUniverseSelectionModel.cs that accepts future chain symbol selector as PyObject
- Add a private static method in OpenInterestFutureUniverseSelectionModel that converts Python lambda function to Func<DateTime, IEnumerable<Symbol>>
- Add a regression algorithm in Python to cover changes. In these case, add Python version of OpenInterestFuturesRegressionAlgorithm.cs
* Nit changes
* Nit change
* Minor docs tweak
---------
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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* Implement ShortableProviderPythonWrapper.cs
- Modify AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs and ShortableProviderOrdersRejectedRegressionAlgorithm.cs to use ShortableProvider from Security and not from the Brokerage model
- Add SetShortableProvider() overload method in Security.cs to set a custom shortable provider from Python
- Remove AllShortableSymbols() method from LocalDiskShortableProvider.cs
- Remove DefaultShortableProvider class
- Add regresion algorithms in C# to cover the changes done
* Implement ShortableProviderPythonWrapper.cs
- Modify AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs and ShortableProviderOrdersRejectedRegressionAlgorithm.cs to use ShortableProvider from Security and not from the Brokerage model
- Add SetShortableProvider() overload method in Security.cs to set a custom shortable provider from Python
- Remove AllShortableSymbols() method from LocalDiskShortableProvider.cs
- Remove DefaultShortableProvider class
- Add regresion algorithms in C# to cover the changes done
* Solve bugs and nit change
* Address review
---------
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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* Solve Report Generation Conversion Rate Error bug (#7183)
* Solve bug
Remove if sentence that checked if Portfolio contained securities that
needed a conversion, like Forex, Crypto or Cfd. It didn't take into
account CryptoFutures so when the backtest result used that kind of
security types it never found a conversion for them. Making a git blame
for Report.PortfolioLooper constructor it was found the if sentence was
not needed so it was removed and then different reports were made for
algorithms that used security types different than Forex,Crypto,Cfd and
CryptoFutures to check everything was still working as expected.
* Solve bug
Remove if sentence that checked if Portfolio contained securities that
needed a conversion, like Forex, Crypto or Cfd. It didn't take into
account CryptoFutures so when the backtest result used that kind of
security types it never found a conversion for them. Making a git blame
for Report.PortfolioLooper constructor it was found the if sentence was
not needed so it was removed and then different reports were made for
algorithms that used security types different than Forex,Crypto,Cfd and
CryptoFutures to check everything was still working as expected.
* Missing Python Version of Crypto Future Algorithms - Issue 7128
* Address reviews
---------
Co-authored-by: hungv <hungv@compatibl.com>
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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* Add dataMappingMode parameter to every history api method overload
* Minor unit tests fixes
* Update regression algorithm stats
* Minor changes
* Minor changes
- Create `SecurityDataFilterPythonWrapper.cs`
- Modifiy `Security.cs` to set a data filter, whether is a C#, Python derivative or custom data filter custom
- Add Python and C# regression algorithms to assert the changes
* Add extendedMarket parameter to every history api method overload
* Rename extendedMarketHours parameter
New name is extendedHours as in the History API to standarize parameters naming
* Update generic history overloads to use every matching subscription
* Update regression algorithms stats
* Centralize period-based history error for tick resolution
* Rename extended market hours parameter to extendedMarketHours
* Minor changes
* Minor changes
* Minor unit tests changes
* Minor unit tests changes
* Minor changes
* Minor unit tests changes
* Minor unit tests changes
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* Implement `OptionExerciseModelPythonWrapper.cs`
- Modifiy `Option.cs` to set the automatic exercise model, even if it's a python custom option model exercise model
- Add `QuantConnect.Orders.OptionExercise` in `AlgorithmImports.py`
- Add regression algorithms in C# and Python showing how to specify a custom option exercise model
* Address required changes
- Remove unnecessary constructor in
´CustomOptionExerciseModelRegressionAlgorithm.cs´
- Change `.Dispose()` in `OptionExerciseModelPythonWrapper.OptionExercise(9` to ´using´ keyword
- Change `Option.SetOptionExerciseModel()` XML docs
* Minor tweaks
* Update CustomOptionExerciseModelRegressionAlgorithm.cs
---------
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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* Add fillForward parameters to every History method
* Remove conflicting Python history method
* Undo removing conflicting Python history method
* Minor changes
* Minor changes
* Minor changes
* Add fillForward and extendedMarket parameters to history request factory
* Minor changes
* Minor changes
* Minor changes
* Minor changes
* Minor unit tests changes
* Rename fillForward parameter in History API
New name if fillDataForward as in the Add*Security API to standarize
parameters naming
* Rename fillForward parameter
Using the shorter fillForward in every API
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* Add Collective2SignalExportClass
Add SignalExportTarget interface
* Collective2SignalExport test working
Add SignalExportManager
Add draft of CrunchDAOSignalExport
* Modify SignalExportManager
Instantiate SignalExportManager in QCAlgorithm constructor
Draft of CrunchDAOSignalExport
* Improve SignalExportManager
- Add regression tests SignalExportDemonstrationAlgorithm in C# and
Python
* Improve SignalExportDemonstrationAlgorithm
Address requested changes in Collective2SignalExport, SignalExportManger and SignalExportTargetTests.cs
* Add CrunchDAOSignalExport.cs
Add CrunchDAOSignalExport unit tests in SignalExportTargetTests.cs
* Add NumeraiSignalExport.cs
Modify SignalExportDemonstrationAlgorithm.cs to test NumeraiSignalExport
Add unit test in SignalExportTargetTests to test NumeraiSignalExport
* Address required changes
- Add BaseSignalExport.cs
- Add SignalExportParameters.cs
- Add PortfolioSignalExportDemonstrationAlgorithm.cs/py
- Improve Error handling in SignalExport provider classes
- Collective2SignalExport now gets the correct number of shares for each holding
- SignalExportManager now computes the correct holding percentage of each portfolio target
- SignalExportManager now takes into account if the algorithm is in live mode
- Demonstration algorithms now are more simple
* Address last required changes
- PortfolioSignalExportDemonstrationAlgorithm.cs/py now inherits from SignalExportDemonstrationAlgorithm.cs/py
- Add more unit tests to assert SignalExportManager gets the correct percentage quantity for each holding
- Change Collective2SignalExport, CrunchDAOSignalExport and NumeraiSignalExport Send() method to return true if there was no error while sending the signals and false otherwise
- Nit changes
* Remove exceptions thrown
- Add more unit tests and more test cases
- Enhance BaseSignalExport.Dispose() method
* Add Collective2SignalExportClass
Add SignalExportTarget interface
* Collective2SignalExport test working
Add SignalExportManager
Add draft of CrunchDAOSignalExport
* Modify SignalExportManager
Instantiate SignalExportManager in QCAlgorithm constructor
Draft of CrunchDAOSignalExport
* Improve SignalExportManager
- Add regression tests SignalExportDemonstrationAlgorithm in C# and
Python
* Improve SignalExportDemonstrationAlgorithm
Address requested changes in Collective2SignalExport, SignalExportManger and SignalExportTargetTests.cs
* Add CrunchDAOSignalExport.cs
Add CrunchDAOSignalExport unit tests in SignalExportTargetTests.cs
* Add NumeraiSignalExport.cs
Modify SignalExportDemonstrationAlgorithm.cs to test NumeraiSignalExport
Add unit test in SignalExportTargetTests to test NumeraiSignalExport
* Address required changes
- Add BaseSignalExport.cs
- Add SignalExportParameters.cs
- Add PortfolioSignalExportDemonstrationAlgorithm.cs/py
- Improve Error handling in SignalExport provider classes
- Collective2SignalExport now gets the correct number of shares for each holding
- SignalExportManager now computes the correct holding percentage of each portfolio target
- SignalExportManager now takes into account if the algorithm is in live mode
- Demonstration algorithms now are more simple
* Address last required changes
- PortfolioSignalExportDemonstrationAlgorithm.cs/py now inherits from SignalExportDemonstrationAlgorithm.cs/py
- Add more unit tests to assert SignalExportManager gets the correct percentage quantity for each holding
- Change Collective2SignalExport, CrunchDAOSignalExport and NumeraiSignalExport Send() method to return true if there was no error while sending the signals and false otherwise
- Nit changes
* Remove exceptions thrown
- Add more unit tests and more test cases
- Enhance BaseSignalExport.Dispose() method
* Fix failing regression tests
* Fix failing unit tests
* Nit changes
* Nit change
* Nit change
* Fix failing unit tests
* Changes required
- Break regression algos `SignalExportDemonstrationAlgorithm.cs/py` nad `PortfolioSignalExportDemonstrationAlgorithm.cs/`y` into three ones, one for each signal export provider
- Change SignalExportManager constructor to receive current algorithm as a parameter
- Fix bug in `SignalExportManager.GetPortfolioTargets()`, now it computes the correct percentage for each holding
- Make `BaseSignalExport.DefaultAllowedSecurityTypes` overrdible
- Handle case were `Collective2SignalExport.ConvertPercentageToQuantity()` returns null
- Clean unnecessary code in `Collective2SignalExport()`, `CrunchDAOSignalExport()` and `NumeraiSignalExport()`
* Nit change
* Nit change
* Minor tweaks after review
* Remove indexes from signal exports
* Required changes
- Change EMA indicators period from 200, 300 to 10,100 in regression algorithms
- Remove Indices from regression algorithms
- Add more XML documentation to regression algorithms
- Change `Log.Error` to `_algorithm.Error` in Signal export providers. Besides, fix error message format
- Change default value for `platformId` parameter in `Collective2SignalExport.cs` constructor
- Solve small bugs in SignalExportProvider when verificating the amount of porfolio targets is greater than zero and each portfolio target is allowed
- Handle case when `PortfolioTarget.Percent()` returns null in `Collective2SignalExport.ConvertPercentageToQuantity()`
- Handle error format message from Collective2 API
- Check every ticker signal is between 0 and 1 (inclusive) in `CrunchDAOSignalExport.cs`
- Modifiy `NumeraiSignalExport.cs` constructor to take into account filename given in the arguments
- Fix small bug with the return value of `ConvertTargetsToNumerai()` method in `NumeraiSignalExport.cs`
- Modify `SignalExportManager.cs` to return true when the algorithm being ran is not in live mode
- Remove indices from CrunchDAO unit tests
* Enhance ´CrunchDAOSignalExport.cs´ implementation
---------
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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* Handle position group margin calls
* Minor changes
* Update regression algorithms
* Minor changes
* Minor changes
* Added regression algorithm
* Peer review
* Peer review
* Peer review
* Peer review
* Minor changes
* Minor changes
* Add unit test
* Allow sufficient buying power when closing position group
* Add unit test
* Improve regression algorithms
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* Update regression test to check number of insights
* Update model to have insight manager ref and cancel insight when signal goes flat
* Update unit tests and regression tests
* Address peer review: using Insights.Clear
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* Invalidate option strategies orders when short selling over margin
When shorting an option strategy with margin requirements that cannot be
met, the order should be invalidated. The buying power model is now able
to detect said situation and result in unssuficient buying power.
The OptionsMarginModel now uses the parameters instance values instead
of the security holdings to compute margin requirements. This fixes the
situation when calculation buying power for a first time position with
no holdings.
* Add and fix unit tests
* Update regression algorithms
* Peer review
* Updates Regression Algorithm to Assert the Number of Insights
* Updates HistoricalReturnsAlphaModel to Cancel Insights Not Emit Flat
We expect fewer insights after this change, but no changes to any regression algorithm.
* Updates Regression Algorithm
Assert the new expected number of generated insights.
* Use InsightCollection Clear Method
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Replaces old `TrailingStopRiskFrameworkAlgorithm` for `TrailingStopRiskFrameworkRegressionAlgorithm` that inherits from `BaseFrameworkRegressionAlgorithm` as a member of the framework regression tests.
* Update regression test
* Update model to expire insights
* Avoid remove insights
* Update regression test
* Use InsightManager Cancel to Expire All Insights
* Update CompositeRiskManagementModelFrameworkAlgorithm
This regression also depends on `MaximumUnrealizedProfitPercentPerSecurity` and `MaximumDrawdownPercentPerSecurity` but `MaximumDrawdownPercentPerSecurity` doesn't close positions.
---------
Co-authored-by: Alexandre Catarino <AlexCatarino@users.noreply.github.com>
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* Remove OnEndOfAlgorithm and update expected trades
* Update models to cancel insights
* Update expected results
There are 3 trades instead of 2 because the PCM does a rebalance
* Remove `Remove` method call
* Update to use the new `Cancel` method
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If we use `.astimezone(dt.tzinfo)`, the new time was convering the timezone from local (e.g. PST) to GMT (dt.tzinfo). In this case, we only want to remove the timezone to enable the operation.
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* Renames and Updates BaseAlphaModelFrameworkRegressionAlgorithm
The `BaseFrameworkRegressionAlgorithm ` will be used for multiple framework regression tests
* Updates and Renames EmaCrossAlphaModelFrameworkAlgorithm
Adds "Regression" to inform that it's a regression algorithm.
* Updates and Renames MaximumPortfolioDrawdownFrameworkAlgorithm
Adds "Regression" to inform that it's a regression algorithm, and use the model name: `MaximumDrawdownPercentPortfolio`
* Adds New Regression Algorithms
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* Adds BaseAlphaModelFrameworkRegressionAlgorithm
`BaseAlphaModelFrameworkRegressionAlgorithm` will be used to validate Alpha Model regression algorithm with the same universe.
- HistoricalReturnsAlphaModelFrameworkAlgorithm
- EmaCrossAlphaModelFrameworkAlgorithm
- MacdAlphaModelFrameworkAlgorithm
- RsiAlphaModelFrameworkAlgorithm
- BasePairsTradingAlphaModelFrameworkAlgorithm
* Addresses Peer-Review
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* Fix fill quantity using group order quantity for combo orders
* Add Order's ComboQuantity property
* Add Order's ComboDirection property
* Minor changes and regression algorithms update
* Minor changes
* Update algorithms stats
* Minor changes and regression algorithms update
* Store the full quantity for each combo order leg in Quantity property instead of the ratio
* Minor changes and regression algorithms update
* A few fixes after pair programming
* Handle grouping position reduction
---------
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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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
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* Adds Regression Test
The new regression test asserts that the total trades is 2.
* Fixes Liquidate Existing Holdings Bug
Liquidate existing holdings before open new postions.
* Addresses Peer-Review
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* Updates the PearsonCorrelationPairsTradingAlphaModelFrameworkAlgorithm
Change the `PearsonCorrelationPairsTradingAlphaModelFrameworkAlgorithm` logic to show that it doesn't remove the consolidators used in the Alpha Model's indicators.
* Fixes `BasePairsTradingAlphaModel`
The `BasePairsTradingAlphaModel` will create indicators with class constructors and register them to consolidators that will be removed when the security is removed from the universe.
* Addresses Peer-Review
* Adds NullBuyingPowerModel
The `NullBuyingPowerModel` considers that we have sufficient buying power for all orders.
Adds example using a bull call spread since a equity buy and hold would not show the impact of this model in the position group buing power model.
* Define NullBuyingPowerModel.GetMaintenanceMargin
The `NullBuyingPowerModel.GetMaintenanceMargin` returns a `MaintenanceMargin` of zero. It means the total margin used is always zero and margin calls will not be triggered.
This feature is inspired on the `ConstantBuyingPowerModel`. We don't inherit from that class, because `ConstantBuyingPowerModel.GetInitialMarginRequirement` gives us very small initial margin that leads to a very large quantity if we use `SetHoldings` or `CalculateOrderQuantity`
* Custom data type history request in python
* Potential solutions
* Minor changes
* Use Slice.Get(Type) for getting python custom data history
* Minor changes
* Add unit tests
* Add unit tests
* Udpdate regression algorithms
* Peer review
* Peer review
* Add research regression tests
* Minor changes
* Minor changes
* Minor tweaks
---------
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
Ricardo Andrés Marino Rojas