* Implement risk free interest rate as an algorithm model
* Use risk free insterest rate model in Sharpe Ratio indicator
* Address peer review
Also added python wrapper
* Take pyobject as interest rate model in Sharpe Ratio indicator
* Minor fix
* Minor fix
* Address peer review
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* Fix using brokerage transaction handler algo befor set
Brokerage open orders are being set before algorithm is set to the transaction handler, so SetPriceAdjustmentMode needs to get the algo to use
* Update unit tests
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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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* Shortable modeling improvements
- Do not limit live trading because of shortable model, will send
algorithm warning
- Add Interactive brokers shortable provider
- Minor LocalDiskShortableProvider API changes
* Fix shorted order update
- Fix shorted order update. Updating regression algorithm
* Minor improvement
* Address reviews
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- Once a security has been delisted or no longer selected by any
universe it will be remove from the main algorithm securities
collection but kept in the new Complete collection, this improves
performance in long running backtests where security collection can
get enumerated in different cases
- Minor refactor for security exchange local time to avoid having to set
it explicitly
* Store traded securities subscription data configs to disk
* Delegate traded subscriptions storage to the data monitor
* Add unit tests
* Address peer review
* Minor changes
* Async universe selection
- Add support for async universe selection, which will happen ahead of
time in the data stack for a performance improvement
* Thrown if using Coarse+Fine Asynchronous Universe selectioon
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* New Fundamental Data
* Minor CIK lookup fix
* Handle live mode & delete unexisting properties
* Minor coarse fundamental adjustment
* Add fundamental history support
* Fix unit tests
* Performance improvements
* Fixes
* Minor regression algorithm fix
* Improvements. Add FundamentalUniverseSelectionModel
* Change default values
* Fix unit test
* Minor tweaks
* Fix unit test
* Minor error handling improvement
* Fix rebase
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* Add ClrBubbleExceptionInterpreter
* Add ClrBubbledExceptionInterpreter tests
* Bump pythonnet version to 2.0.23
* Minor changes
* Minor change
* Minor fix
* Fix failing unit tests
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* Support sourcing custom data from ObjectStore
* Add Python regression algorithm
* Wire engine to pass ObjectStore down to the stream readers
* Minor changes
* Minor unit tests fixes
* Remove unused SetupHandlerParameters.ObjectStore
* Minor changes
* Minor changes
* Support single-file zipped data to be sourced from object store
* Assert object store custom data history requests in regression algorithms
* Add custom object store data live data feed unit test
* Add multi-file object store custom data regression algorithms
* Minor fix
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* Deprecates IAlgorithmSettings.DataSubscriptionLimit
We will let the brokerage check and notify users that they have subscribed to datafeeds beyond their quota.
* Removes Unit Test
Also remove usage in `EmptyEquityAndOptions400Benchmark`.
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* Candlestick charts base implementation
* Series and Candlestick series json serialization
* Some cleanup
* Add AddPlot method for candlestick series to QCAlgorithm
* Remove Values property from ISeriesPoint
* Add candlestick QCAlgorithm.Plot trade bar methods
* Implement candlestick series re-sampling
* Add more SeriesSampler unit tests
* Add examples of candlestick charts usage to exisiting charting algorithm
* Address peer review
* Address peer review
* Derive Candlestick from Bar
* Sampler changes
* Add new series types from the cloud
* Add more candlestick series sampler tests
* Minor cleanup
* Minor changes
* Add trailing stop orders base implementation
* Handle trailing stop order prices rounding
* Implement trailing stop orders fill logic
* Minor fill model changes
* Add ApplySplit to fill model interface for models that might need to be aware of splits.
Filling trailing stop orders require keeping track of min/max prices, which need to be split adjusted.
* Add brokerage order updated event for communicating certain order types prices changes
* Add order update event args class for brokerage side order updates
* Revert IFillModel.ApplySplit
* Add trailing stop orders regression algorithm
* Updated order ticket demo algorithm to include trailing stop orders
* Some cleanup
* Support trailing stop orders in IB brokerage model
* Some cleanup
* Fix failing tests
* Fix failing regression algorithm
* Address peer review
* Add trailing stop price calculation unit tests
* Minor changes
* Minor change
- Minor adjustment not to transition from canceled to invalid order
status, which can happen in some cases in live trading as a race
condition. Adding unit test
- Make sure open order status is set to submitted if none provided,
adjusting existing test
* Changed argument exceptions so that they used the nameof() operator for parameter names
* Update IQSocket.cs
---------
Co-authored-by: John Doe <john@doe>
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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* Contract chain selection improvements
- Adjust contract chain selection behavior for futures and options so we
are sure to use the correct local time when filtering expirations.
Adding unit test reproducing issue
* Update futures regression algorithms
* Address reviews
* Add security dynamic properties unit and regression tests.
These assert that dynamic properties that are instances of python classes that inherit c# classes keep their python object references.
* Minor change
* Bump pythonnet version to 2.0.21
* Fix security dynamic properties cast from PyObject
* Minor change
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* Dynamic security properties for quick objects storage
* Documentation and other minor changes
* Add Security indexer to access custom properties
* Address peer review
* Minor changes
* Improve regression algorithms
* Bumped pythonnet to version 2.0.19
* Bumped pythonnet to version 2.0.20
* Address peer review
* Make statistics available at runtime to algorithms
* Re-calculate statistics on every call
* Housekeeping
* Add regression algorithms
* Address peer review
* Support for custom summary statistics at runtime
* Minor changes
* Address peer review
* Address peer review
* Minor changes
* Minor changes
Martin-Molinero