The composite model combines multiple alpha models into a singular model and
properly sets each insight's SourceModel property to the name of the model that
generated the insight
Alpha models can choose to implement the Name property, if not, the system
will use the model's type name as the Insight.SourceModel.
Existing tests were updated to also assert expected model names
Implements `Insight.Price` method to make it easier to create new instances of `Insight` of `InsightType.Price`.
Standardize the parameter order to `Symbol`, `TimeSpan`, `InsightType`, `InsightDirection`, `Double`, `Double`.
Three methods were added to enable easier consumption of an enumerable
of slices returned from a history request. The dictionary version is
most likely to be used by python, while the functional versions allow
for lots of flexibility in how you'd like to consume the stream of slices.
VWAP will submit market orders while the current price is more favorable than VWAP.
STD will submit market orders while the current price is a configured number of
standard deviations away from the mean in the favorable direction.
1. `HistoricalReturnsAlphaModel`:
1. Adds lookback period for return calculation
2. Adds return-depend direction to insights
3. Refactors indicator history warm-up
2. `MeanVarianceOptimizationPortfolioConstructionModel`:
1. Adds lookback period for return calculation
2. Adds exception for null magnitude
3. Refactors indicator history warm-up
3. Other minor fixes:
1. Default target return was 2 instead of 0.02 (2%)
2. Proper removal of consolidator subscriptions
This framework algorithm alpha model is HistoricalReturnsAlphaModel and the portfolio construction model is MeanVarianceOptimizationPortfolioConstructionModel.
This examples implements an algorithm that rebalances the portfolio according to modern portfolio theory.
This method is misleading at best and incorrect at worst.
Insight objects should use reference equality or compare ids to
perform equality checking. The only usage, in MacdAlphaModel,
was easily converted to not relying on this method.
Adds method overload that accept a `PyObject` to `SetAlpha`, `SetExecution`, `SetPortfolioConstruction`, `SetPortfolioSelection` and `SetRiskManagement`. In these methods, a custom model written in python will be wrapped around the respective `PythonWrapper`.
The term 'alpha' is used to describe the entire algorithm. Therefore, 'alpha'
produces insights. From this we have things like IAlphaModel, which is the model
defining how insights are produced. We have IAlphaHandler, which defines how the
insights from a single 'alpha' (the algorithm) are managed, analyzed, and stored.
Types closer to the individual prediction level, such as InsightDirection, or
InsightScore relate directly to exactly 1 insight. The distinction between the
two became more clear as we developed the insights API, and from that effort it
was decided to harmonize alpha/insight terminology across the various QC systems.
Michael Handschuh