- Adding `FreePortfolioValue` to be set after algorithm initialize based
on the `TotalPortfolioValue` and the `FreePortfolioValuePercentage`
- Updating regression tests
- Adding new regression test
- Adding check for minimum order value at `BuyingPowerModel`
- Removing `using QCAlgorithmFramework = QuantConnect.Algorithm.QCAlgorithm`
- Removing `QCAlgorithmFrameworkBridge`
- Removing `IsFrameworkAlgorithm`
- Making `EmitInsightBasedOnFill` private. Adding new
`IOrderEventProvider` exposing an `event` to which `QCAlgorithm` will
subscribe.
- `AccountType.Cash` algorithms will be allowed to manually trade and
emight insights manually or with alpha model.
Fixes a bug where we were using the security's data resolution to compute
the insight's close time. This led a case such as insight.Period == 20days
to step 20days worth of tradable minutes (assuming minute data resolution),
yielding a close time that was very far in the future.
We also add different means of specifying an insight's period/close time:
1. Specify insight period as a TimeSpan and we compute close time
2. Specify insight period and a resolution and bar count and we compute close time
3. Specify insight close time local directly and we compute the insight period
The key here is maintaining consistency between the three different approaches
which is heavily validated with the corresponding unit tests.
Edits also made to trust the insight's close time as the analysis end time in
the case where the analysis period == insight period (extra analysis period = 0).
Given the current setup (extra analysis period == 0), this guarantees that close
and analysis end times are equivalent.
Regression statistics were updated and expectedly we get many more insights that
have completed analysis, and as such, average scores have also changed.
This flag indicates whether or not the local regression test system,
via RegressionTests.AlgorithmStatisticsRegression should run a given
IRegressionAlgorithmDefinition
It's important that we keep the factor files consistent with respect to
the date that they were generated. This enables us to run the regression
algorithms in the cloud and get the same results by using the factor files
from the correct date.
A mechanical refactoring was performed to make algorithms currently used in
regression algorithms to implement IRegressionAlgorithmDefinition, which allows
algorithms to define their own expected statistics and what languages should be
run as part of regression. The type name of the C# type is used to determine the
file/model name for python. This was for simplicity, but if needed, could later be
refactored to expose more information, but for now the convention of keeping names
the same makes sense and just works easily.
Provides demonstration algorithm showing the steps required to convert a
QCAlgorithm into the framework with minimal code changes.
1. Subclass QCAlgorithmFrameworkBridge
2. Add EmitInsights calls to where orders are placed
3. Profit :)
Martin Molinero