- Update regression algorithms stats after making SecurityCache ignore
QuoteBars for equity for OHCL values and GetLastData(). They were
affected since the `BenchmarkSecurity` used `.Price` which was QB for
equities. Order list hashes changed because SubmissionLastPrice will
now be TB instead of QB
When new securities are added to the universe, the `ReturnsSymbolData` is warmed up with historical data that may not have the same timestamp causing an index mismatch that leads to a rejection to several valid data. In this case, we will assume that there is a time correspondence similar to what is done in Python. Unit test was added.
`BlackLittermanOptimizationPortfolioConstructionModel` will consider a new view only if there is a new last active insight by updating the `ReturnsSymbolData` with the `Insight.GeneratedTimeUtc` instead of the `IAlgorithm.Time`. Consequently, the timestamp of the historical data is converted to UTC for consistency.
`BlackLittermanSymbolData` now rejects duplicate keys like its C# version: `ReturnsSymbolData`.
Finally, `BlackLittermanPortfolioOptimizationFrameworkAlgorithm` statistics was updated because of the bug fixes.
- 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`
- `SubscriptionSynchronizer` will emit a `TimeSlice.TimePulse` before
performing any universe selection on each time loop. This will advance
`Algorithm.Time` which will allow universe selection data time and
`Algorithm.Time` to be aligned.
- Updating Regression algorithms that were using `algorithm.Time` in the
selection method.
- Coarse selection will start from the algorithms start date (not in the
next day)
- Adding regression algorithm
- 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.
1. Apply the pattern used in `EqualWeightingPortfolioConstructionModel`
2. Change the logic to compute the views from the insights.
3. Change the logis to compute the posterior mean and covariance
Use `UnconstrainedMeanVariancePortfolioOptimizer` in `BlackLittermanPortfolioOptimizationFrameworkAlgorithm` to bypass the difference in regression tests with `IPortfolioOptimizer` that rely on different algorithms in C# and python.
Adds unit tests for BLOPCV to test the implementation against Black and Litterman 1999 paper.
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.
- Changes `ExpectedStatistics` in MVOFA
- All regression tests now
- Removes unnecessary constructor arguments in `ReturnsSymbolData`
- Tide up code and add method summaries.
Martin Molinero