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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>
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* Expand Index option support
- Adjust APIs so that the same underlying can be used
for different options, adding support for SPX weekly options. Adding
regression tests
* Fix IndexOption.IsStandard
* Add IndexOption test
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Fixed this error from happening when running this code:
tf.placeholder() is not compatible with eager execution.
at placeholder
raise RuntimeError("tf.placeholder() is not compatible with "
in array_ops.py: line 3341
at NetTrain
xs = tf.compat.v1.placeholder(tf.float32 in /QuantConnect/backtesting/./cache/algorithm/project/main.py: line 57
* Feature combo orders
- Add support for combo orders
* Make fill model wait for all grouped orders to emit fills
* Add ComboFill to model multiple fills for combo orders
* Fill combo limit orders
Add some regression algorithms
* Add fill implementation for combo leg limit orders
* Add IFill as common interface for Fill and ComboFill
* Refactor combo orders removing IGroupOrder interface
Move the group order manager to the base Order class
* Update algorithms
* Handle combo order events atomically
* Refactor brokerage transaction event handler
* Refactor combo fill models
* Process fills in batch
* Combo orders fill model tests
* Combo leg limit orders algorithm
* Regression algorithms cleanup
* Fill and combo fill classes cleanup
* Housekeeping
* Refactor equity fill model to derive from base fill model
* Address review changes request
* Handling the new types of orders in the OrderJsonConverter
* Add regression algorithm to test combo orders update/cancel
* Add regression algorithm to test combo orders update/cancel
* Housekeeping
* Address review changes request
* Minor changes
* Security transaction handler method for setting order request id
* Extend public interface for placing combo orders
* Combo order tickets demo algorithm python version
* Tweaks and updates
* Minor fixes
* Minor changes
* Minor fixes
* Address reviews minor fixes
* Minor fixes
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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* Allows Market-On-Close Orders Outside Buffer Period
Market-On-Close orders can be submitted before and after the buffer period from 15:45 to 16:00 (Tested with TWS) meaning that we can submit MOC when the market is closed and, consequently, use daily resolution data.
* Adds Regression Test with Extended Market Hours
- Removes `nextMarketClose > Time` condition since it's unnecessary. If the algorithm Time is greater than the close of that day, `nextMarektClose` refers to the next day.
* Updates Unit Test
Updates `OrderQuantityConversionTest` because the MOC orders are submitted. They are placed at 7 pm and invalid before this pull request.
* Updates Summary of new Regression Tests
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* Set fill price to zero in OTM exercise orders.
Improved the OTM exercise orders message.
* Update regression algorithms and unit tests
* Add IsInTheMoney property to OrderEvent
* Update SerializedOrderEvent
* Properly setting the option exercise order price to strike price or zero
* Minor changes
* Minor changes
Jhonathan Abreu