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* Normalize universe data frames
Universe and (generically BaseDataCollection) data frames are not normalize and unpacked into a data frame, instead of just creating data frames with the universe lists within it
* Fix unit tests and algorithms to expecte new universe dataframe format
* Fixes
* Add PandasConverter.DataFrameGenerator class
* Pandas data frame generator class fixes
* Add comments
* Housekeeping
* Add attributes to mark classes and properties for pandas processing
* Improve pandas properties expanding
Allow and handle duplicate names
* Use PandasData generalization for Lean common data types
* Add points time as column when converting base data collections to data frames
* Cleanup and minor changes
* Minor change
* Pandas data to get type members on demand
* Move Pandas helper classes to their own files
* Minor changes
* Add flatten argument to python history api
This allows users to decide whether they want fully expanded dataframes for universe and other collection data types. Else, master behavior is kept
* Adding missing changes to last commit
* Update Pythonnet version to 2.0.40
* Add flattent argument to algorithm's OptionChain api
* Minor changes
* Housekeeping
* Minor changes
* Bug fix skipping data collection data points
* Add comment
* Set correct exchange time to OptionUniverse instances
* Address peer review and cleanup
* Cleanup
* Minor changes
* Fix pandas converter to handle list of data with different symbols
* Properly convert list of data into dataframe
Take into consideration data for multiple symbols in the same list
* Cleanup
* Index dataframes by symbol object instead of SID string
* Add symbol equality operator to compare against object
* Exclude "ID" from option chain dataframe
* Minor fix
* Add greeks columns directly in option chain dataframe.
Also add pass-through properties for greek values in OptionUniverse
* Some cleanup
* Minor fix
* Add new QCAlgorithm.OptionChains() method
- Use OptionChains as output
- Add DataFrame to OptionChain and OptionChains
- Rename Greeks classes
- Add ISymbolProvider for classes that have a symbol (IBaseData, OptionContract)
* Unify QCAlgorithmOptionChain API
Also refactor OptionContract to handle: (1) Actual market data and option price model data, and (2) OptionUniverse data
* Pass symbol properties to OptionUniverse option chain from algorithm
* Format OptionContract for dataframe
* Minor fix
* Add multiple option chains api regression algorithms and other minor changes
* Address peer review
Add NullGreeks class: keep ModeledGreeks as internal as possible
* Minor fix and add PandasConverter unit tests
* Peer review: Non-thread-safe Lazy for Python
* Handle Greeks unwrapping by PandasData
* PandasData cleanup
* Add data and other minor changes
* Unit test fix
* Update Pythonnet to 2.0.39
* Cleanup
* PandasData handling children class members
Address peer review
* Fix: indexing symbol conversion in pandas mapper
* Fix pandas mapper to convert string keys to symbol only when necessary
* Cleanup
* Cleanup
* Add PandasColumn python class to handle proper indexing
This allows propery hash and equality between Symbols, C# strings and Python strings
* Minor fixes
* Symbol cache improvements
* Minor fix for cache miss
* Revert PandasMapper reserved names and improvements
* Minor fix
* Revert reserved names
* Minor fix for Symbol equality operators
---------
Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
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* Enhance command support
- Enhance command support, adding link helper methods. Adding and
expanding new tests
- Minor improvement for command str representation
* Minor test fix
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* Option universe improvements
- Improvement for resolution handling of option universes, affecting
performance in live mode. Adding regression algorithm
* Minor fix for research test
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* Add new QCAlgorithm.OptionChain method to get full data option chain
* Add extension method to get canonical symbol
* Support future options in new OptionChain method
* Replace option chain provider with OptionChain method in some regression algorithms
* Add new regression algorithms for OptionChain method
* Replace option chain provider with OptionChain method in some regression algorithms
* Minor
* Cleanup
* Minor changes in regression algorithms
* Minor adjustments
* Adds Overload to AddIndexOption
Simplify usage. We don't need to create/add the underlying explicitly, see AddIndexOption(string, Resolution, string, bool) overload.
* Addresses Peer-Review
- Default market is `null` instead of `Market.USA` allowing for `BrokerageModel` setup.
- `AddIndexOption` and `AddIndexOptionContract` methods now return `indexOption` objects.
* Fixes Logic Bug
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* Default daily precise end times
- Enable by default daily precise end times. Updating stats
- Minor fix for algorithm manager consolidator updates, adding new regression test
asserting behavior and updating others
- Minor fix for SubscriptionData creator avoid round down on warmup if
not appropiate
- Adjust consolidators to emit on daily strict end times if requested
daily resolution and setting enabled
- Updating regression algorithms
* Skip daily data on extended market hours
* Some cleanup and self review
* Revert unrequired change
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* Minor api improvements
- Adding Universe.Selected to hold the current set of selected symbols.
Adding regression tests
- Adjusting TimeRules and DateRules to fallback to the MHDB if the
security hasn't been added. Updating existing regression tests
* Expand regression test assertion
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* Adding new algorithm data handling options
- Adding new QCAlgorithm data handling method options to override.
Adding Py/C# regression tests
- Removing old OnData Type specific invoker methods
* Address reviews. Remove old OnData C# only methods
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* Improve consolidator scan
- Improve consolidator scan to be triggered even if no data is present.
Adding new regression test, updating existing
* Adding more tests & minor tweaks
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* Implement backtest self-naming and self-tagging
* Minor unit test fix
* Minor api changes
* Minor changes
* Send packet messages when algorithm's name or tags are updated
* Minor fixes
* Address peer review
* Backtest name and tags API calls
Plus, first version of CI for API tests
* Add endpoint to update a backtest set of tags
* Minor GH actions change
* Address peer review
* Add algorithm naming and tagging unit tests
* Minor backtest API changes
* 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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* 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
* 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
* 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>
* 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
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* Add SetAccountCurrency overload
- Add SetAccountCurrencyOverload to allow the user to set also account
currency quantity
- Add regression and unit tests to cover the changes
* Add regression algos
* Simplifiy SetAccountCurrency implementation
* Minor changes
* Minor changes
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* Implement Trailing FreePortfolioValue
- Implement Trailing FreePortfolioValue by default, users will be able
to set it to a fixed number if desired. Adding regression algorithm
- Setting the default 'MinimumOrderMarginPortfolioPercentage' from 0 to
0.1% of the TPV to avoud tiny trades by default
* Update existing regression algorithms
* Address reviews
- Send warning message to the user if a trade does not happen due to the
default setting of the minimum order margin percentage value
* Address reivews
* Rename TotalPortfolioValueLessFreeBuffer
* Update new regression algorithm
* Minor fix CrunchDao Symbology
- Minor fix for CrunchDao Symbology. Updating existing tests
* Add missing symbol mapping
- Add IAlgorithm.Ticker(Symbol) functionality which will return the
latest ticker for the requested symbol at the current algorithm time
- SignalExporters will use Ticker to get the current symbol ticker
* Rename SecId GetTicker to Ticker
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* Add forward data only fill model example
- Add forward data only custom fill model C# & PY example.
- Minor adjustment for 'MarketOrderFillTimeout' to be zero always in
backtesting
* Address reviews
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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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* 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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* 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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* 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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* WIP
* Add base currency cash
* Symbol properties and data processing
* Add basic template algorithm
* Add hourly crypto future algorithm
* Minor fixes after live trading testing
* CoinApiDataQueueHandler CryptoFuture support
* Address reviews
* Fix regression algorithms after update
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* Normalize time in universe behavior
- Normalize Option & Future chain universe behavior regarding their
assets time in universe. They will now respect the universe settings
time in universe value. Adding new regression algorithms asserting the
behavior
* Address reviews & cleanup
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Use `SetEndDate` to set `EndDate` in `QCAlgorithm` constructor. It will ensure that the `EndDate` is independent of the time the algorithm is executed if `SetEndDate` is not called in `Initilaize`.
Some users don't implement `SetEndDate` to run the algorithm to the latest datapoint, but this is not true if we run the algorithm during the day as the latest datapoint will be 24 hours before the execution time while there is data until the current day midnight.
Martin-Molinero