- Reduce MinimumVariancePortfolioOptimizar precision goal so that both
CSharp and Py MeanVarianceOptimizationFrameworkAlgorithm return the same
results
- Limit factor file dates in factor file generator unit test
Implements `PortfolioBias` in EWPCM, CWPCM and IWPCM. With this new feature, these PCM will ignore insights that do not respect the desired bias. E.g. for `PortfolioBias.Long`, on Insights with `InsightDirection.Up` will be converted into `PortfolioTarget.Quantity` greater than zero and other `InsightDirection` will result in `PortfolioTarget.Quantity` of zero.
- Adding new unit test for python PCM implementations, asserting each
method is correctly called
- Reverting some unrequired changes in the
`MeanVarianceOptimizationFrameworkAlgorithm`
- Refactor shared logic from `EqualWeightingPortfolioConstructionModel`
into base `PortfolioConstructionModel` implementation
- `MeanVarianceOptimizationPortfolioConstructionModel` will respect
rebalancing period and will use all active inisights, not just the last
- Refactor AccumulativeInsightPortfolioConstructionModel to inherit from
the EWPCM, reducing code duplication and adding support for rebalancing
period
- Fixing bug where only 1 new insight per symbol was processed per loop
- Adding unit tests
- Updates `DropboxUniverseSelectionAlgorithm` and `DropboxBaseDataUniverseSelectionAlgorithm` with new links to Dropbox files and date range to match the dates in the files.
- Adds copy of files in `TestData` folder.
* Updates TradingEconomics algorithms to use new event definition
* Separated Calendar and Indicator definitions into partial class
* Refactors portions of TradingEconomicsCalendar
* Makes TradingEconomicsCalendar.GetSource return RemoteFile for live
* Fixes bugs in TradingEconomicsEventFilter
* Fixes bugs in StreamReaderExtensions (thanks Martin :))
* Adds new unit tests to cover changes
- Remove unrequired `GetBuyingPower`
- Making `BuyingPowerModel.GetMaintenanceMarginRequirement` protected
instead of public
- Adding `GetMaximumOrderQuantityForDeltaBuyingPower` to replace
public `GetMaintenanceMarginRequirement` and improve API experience for
consumers like the `DefaultMarginCallModel`
- Adding new unit tests
- Remove unused `OptionChainUniverseDataCollectionAggregatorEnumerator`
- Refactor `BaseDataCollectionAggregatorEnumerator` and
`OptionChainUniverseDataCollectionEnumerator` to avoid emitting invalid
data points
- Updating regression tests statistics
- Adding unit test
event names
* Adds unit test for new filter method
NOTE: This is a breaking change for Trading Economics calendar events
property. Any previous string matching might result in a mismatch if
results were not previously being normalized.
- After https://github.com/QuantConnect/Lean/pull/4000
CoarseFineFundamentalRegressionAlgorithm started using `MarketCap`, but
this value was always 0 in existing data, so it caused undeterministic
results. Adding new data and update expected result.
- `AccumulativeInsightFrameworkAlgorithm` expected statistic were not
correct, updating.
* OnEndOfDayRegressionAlgorithm - Since the EndTime of the hourly benchmark is during the day,
the OnEndOfDay method gets called one less time than usual. Updates statistics
* CustomUniverseWithBenchmarkRegressionAlgorithm.cs - modified algorithm so
that it works with hourly benchmark. Previously only tested for Daily benchmark
* BasicTemplateAlgorithm.py - Modified resolution to be
Resolution.Minute, just like it is in C#
* CustomDataRegressionAlgorithm.py - Remove warmup call from Initialize
* IndicatorSuiteAlgorithm.py - Adds PythonQuandl import to fix import error
- BacktestingResultHandler will send a maximum of 50 orders per update
packet and will check `LastFillTime` and `LastUpdateTime` too
- Fix invalid linked file
`AccumulativeInsightPortfolioRegressionAlgorithm`
Adds `MarketCap` member to `FineFundamental` class that represents the aggregate market value of a company represented in dollar amount.
Changes `CoarseFineFundamentalRegressionAlgorithm` (C# and Python) to select securities based in its market capitalization. Same result as selecting by P/E ratio.
In `PeriodCountConsolidatorBase`, differentiate the type of the `PyObject` and create an `IPeriodSpecification` accordingly. If the `PyObject` is a C# `Func<DateTime, CalendarInfo>` or a convertable Python method, we create a `FuncPeriodSpecification` with it as a parameter. If the `PyObject` is a `datetime.timedelta`, we create a `TimeSpanPeriodSpecification` with it as a parameter after a conversion to `TimeSpan`.
- Adds example in `DataConsolidationAlgorithm`
- Adds unit test for `timedelta` overload.
In the Coarse Universe Selection of the following algorithms
- ContingentClaimsAnalysisDefaultPredictionAlpha
- GreenblattMagicFormulaAlpha
- PriceGapMeanReversionAlpha
- SykesShortMicroCapAlpha
Universe.Unchanged is now used when the universe is not changed instead of saving a list of symbol and returning it.
Other minor refactoring.
* Write files by `UpdatedAt` date instead of the `CreatedAt` date
* Added ability to append to compressed files if file does not exist
* Cleaned up code as per review
* misc. documentation changes
* RSS converter now lives at: https://gist.github.com/gsalaz98/b87992cd5a5a214d01c63dbbefbbf12c
* Removed BenzingaNewsFactory as it is no longer needed
* Cleaned up code as per review to make this more maintainable
* Included new documentation
* Filter articles with no Symbols from being written
* General code improvements (duplication reduction, etc.)
- Renaming `PreSelected` to `Constituents`
- Adding base `ConstituentsUniverse`
- Adding Py and C# regression algorithm
- Fixing bug in `UniverseSelection`, it wasn't removing pending to be
removed securities unless the universe selection changed
- Adding test data
* Make Benzinga News Converter more efficient (and cleaner!)
* Implement JSON converter for serialization/deserialization process
* Fix bug where duplicate symbols would be added to news.Symbols
* Modify algorithm strategies
Alexandre Catarino