- Adding new `ConfidenceWeightedPortfolioConstructionModel` (C# / Py) that will
generate percent `Targets` based on the latest active `Insight` `Confidence` per
`Symbol`.
- Will ignore `Insights` that have no `Confidence`.(unit tested)
- If the sum of all the last active `Insight` per `Symbol` is bigger than 1, it
will factor down each target percent holdings proportionally so the sum is 1. (unit tested)
- Adding unit tests
- Adding a new regression test framework algorithm (C#/Py)
-**Note**: `ConfidenceWeightedPortfolioConstructionModel` inherits from the `InsightWeightingPortfolioConstructionModel`. Protect method `GetValue` was implemented in `IWPCM` to enable the choice of `Insight` member.
- Creates `CustomUniverseSelectionModel` that mimics `QCAlgorithm.AddUniverse(String, Func<DateTime, IEnumerable<string>>)`
- Replaces `BaseETFUniverse` for `InceptionDateUniverseSelectionModel` that inherits from `CustomUniverseSelectionModel`
- ETF Basket USMs inherits from `InceptionDateUniverseSelectionModel`
Adds `BaseETFUniverseSelectionModel` that handles the common universe selection logic for all ETF Basket.
Adds the following ETF Baskets:
- Energy
- Precious Metals
- S&P500 Sectors
- Technology
- US Treasuries
- Volatility
Adds static methods of the form Parse.<TypeName>(string str) that use
CultureInfo.InvariantCulture. These are to be used when parsing strings.
It's still safe (from the CA1304/CA1305 perspective) to use the ToDecimal
extension method for decimals.
Adds string extension methods for common operations that will now require
CultureInfo.InvariantCulture. These are to be used when converting values
to strings, such as ToStringInvariant()/ToStringInvariant(format), but also
useful for searching within strings, StartsWithInvariant, EndsWithInvariant
and IndexOfInvariant.
FxCop has various rulesets for enforcing things within our codebase.
For this particular issue, we'll be enforcing CA1304 and CA1305 to
ensure we're always using an IFormatProvider or a CultureInfo where
applicable.
Linked Issue: #3045
- Adding new `InsightWeightingPortfolioConstructionModel` that will
generate percent `Targets` based on the latest active `Insight` `Weight` per
`Symbol`.
- Will ignore `Insights` that have no `Weight`.
- If the sum of all the last active `Insight` per `Symbol` is bigger than 1, it
will factor down each target percent holdings proportionally so the sum is 1.
- Adding unit tests
- Adding a new regression test framework algorithm
- Note most of the code, including tests, are reused from the
`EqualWeightingPortfolioConstructionModel`
- Updates PythonNet to 1.0.5.17
- Improve performance by adding new `interop` `type` cache holding a `bool`, true if its an `exception`. And adding a `setter` and `getter` cache for the `propertyobject`. Closes#2925.
- Decimal parsing allows numeric string in exponential notation. Closes#2918#2919.
Closes#2929
- Requires a new PythonNet 1.0.5.15 package where the different `.dll` are in a
specific folder: `\win` `\linux` and `\osx`
- Removed not present `decimal.py` from `Algorithm.Python` project. It
was moved into `Common`.
- Replace `xbuild` for `msbuild` required for using the `System.Runtime.InteropServices`.
Also note the `xbuild` on travis prints:
> >>>> xbuild tool is deprecated and will be removed in future updates, use msbuild instead <<<<
In the new package:
- C# decimal conversion will use C# double and python float due to the big performance impact of converting C# decimal to python decimal;
The C# version was supposed to handle python modules, but when they inherit from a C# module, pythonnet send them as C# objects. Consequently, they are not wrapped and cannot be used. The python version of `CompositeRiskManagementModel` solves the issue.
- Implements python version of `MaximumUnrealizedProfitPercentPerSecurity`
- Updates `CompositeRiskManagementModelFrameworkAlgorithm` in order to use python risk model.
Restructured
Update message
Added removal of trailing highs for unnecessary securities
Add logging message
Improvements
Rename
Add regression Algorithm
Changed to use TradeBar values instead of only current price
Cleaned msg layout
Update Regression test
This is the inverse of the MaximumDrawdownPercentPerSecurity risk model.
It's goal is to liquidate holdings for a security when the unrealized profit
passes a specified threshold. This can viewed as a 'take the money and run'
risk model.
Add a multi-dimensional array of double representing the covariance. Some models, e.g., Black-Litterman may want to optimize a covariance that is different from the historical one.
Adds UnconstrainedMeanVariancePortfolioOptimizer: a simple optimizer that has a solution, therefore no numerical optimization method is required.
This algorithm shows how to implement a futures strategy in a framework algorithm.
`FutureUniverseSelectionModel` portfolio selection model was implemented to provide a base class to help create other futures universe selection models.
Stefano Raggi