- AlgorithmPythonWrapper will directly call base OnFrameworkData()
implementation skipping going through python and it's overhead
- Small performance improvement for adding Tick data points into a Ticks
collection
- For python always wrap slice with PythonSlice, so that slice.Get()
works even when no custom data is present, adding test.
- WarmupIndicator will be able to determine the correct type to use
- Fix bug in `History.GetMatchingSubscriptions()` which would use the
same TZ for exchange and data. Covered by regression algorithm.
- Consolidate will only infer `TickType` from `T` is not abstract
- Adding regression algorithm
- Slice will expose `Get(Type)` to get data by type, adding unit tests
- Remove unrequired symbol check
- Dispose of `ZipDataCacheProvider` used in unit tests.
To avoid issues with other tests since zip files could remain open.
- Make `GetSubscription` private and remove unrequired overload
- Add warning message when trying to warm up an indicator which does not
have a warm up period
- Fixes for C# RegisterIndicator API methods which were ignoring provided
type of T
- Fixes for Py RegisterIndicator API methods which was not using the
provided 'selector' method
- Adding C# and Py regression algorithm
Update test to the new crypto and equity subscriptions rules:
- Only consolidates trades
- Low resolution data are only trades.
Update and fix tests
Add missing minute sample files
Update Regression algorithms statistics
Crypto and Equities will consolidate trades by default
Daily and hourly resolution will return only trades for crypto and equities.
Update equity TAQ regression test
Add minute sample files
Updating regression algorithms
Update SpotMarket test cases
Add regression test for equity trades and quotes
- History request.
- Trades and quotes pumped into OnData.
- Subscriptions are added correctly.
Add sample data
Checks low resolution only subscribes to trade bars
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
- Adding new `Func<DateTime, DateTime?>` that allows PCM to return null
if the next rebalance time is null, in which case the function will be
called again in the next loop.
- Adjusting PCM next rebalance time check to perform rebalance once the
time is reached
- Adding new regression test. Updating existing
- Moving InsightCollection into base `PortfolioConstructionModel`
- Will call `InsightCollection.GetNextExpiryTime()` on each check, and
for performance `InsightCollection` will keep track of next insight
expiry time
- Removing need for PCM base classes having to call `RefreshRebalance`
- Some refactor clean up at base
PortfolioConstructionModel.IsRebalanceDue()
AlexCatarino