- Adding new `AlgorithmSettings` Min and Max absolute portfolio target
percentage
- Adding new `PortfolioConstructionModel.FilterInvalidInsightMagnitude()`
helper method that will be used by the `BlackLitterman` and
`MeanVariance` optiomization portfolio construction models to skip
insights with extreme magnitudes that will cause exceptions
- `PortfolioTarget.Percentage()` will now verify requested percent is
withing the settings values
- `Alpha Assets` chart will only store last data point
- Adding new `JsonRoundingConverter` that will round to 4 (number of
digits currently used for comparing alpha statistics) fractional
digits.
- Will be used for `Insights` and `ChartPoint`
- 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`
This model was assuming that the history request used to warm up the indicators contains the 'close' column which is only valid for Equity.
The models were also refactored to update the indicators without a consolidator since the last data point from the history request was not pushed throught the indicators.
Adds unit tests for UniverseSelectionModel's that can be used to create new models with inheritance:
- ManualUniverseSelectionModel
- FundamentalUniverseSelectionModel
- Adding new `CompositeAlphaModel.AddAlphaModel()`
- Adding C#/Py regression algorithms using the new `QCAlgorith.AddAlphaModel()`
- Improving exception message
- Add python version of `QCAlgorith.AddAlphaModel()`
- 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.
Implement a new overload to `Insight` constructor that accepts a `Func<DateTime, DateTime>` that is used to compute the `CloseTimeUtc` and `Period` after the `Insight` object is emitted (`SetPeriodAndCloseTime` method).
Adds the static Expiry class with functions that can be used to compute a future date/time (expiry) given a date/time.
Closes#3038
- Classic Algorithms will emight insights based on order fills.
- To be able to update generated insights closed time, we will not
clone emitted insights.
- `InsightAnalysisContext` will update `AnalysisEndTimeUtc` when the
Insight period is closed and the period is `EndOfTimeTimeSpan`
- Adding new regression algorithm asserting on the new emitted insights
- Adding unit tests
- `LiveTradingResultHandler` will store `AlphaRunTimeStatistics`
- Making `DefaultAlphaHandler.ProcessAsynchronousEvents` virtual to
facilitate cloud changes
- `CashBook[NullCurrency] { get; }` will throw an exception
- Revert `Currencies.USD` changes in user facing algorithms
- Improve some documentation
- Revert some format changes
- Adding more asserts for regression test
- Adding new regression tests using a custom fee model which returns
`OrderFee.Zero`
- Adding a non-usd account currency test to the cash book tests
- Adding some unit tests for `NullCurrency` and `OrderFee.Zero`
- Removing `AccountCurrency` from `Cash` and `Brokerage` classes.
`ICurrencyConverter` will now provide the `AccountCurrency`
- Adding new static `OrderFee.Zero` which will return a 0 order fee in
`NullCurrency`
- Adding static `Currencies.USD` value, replacing all "USD".
- Addin new static `Currencies.NullCurrency`
- Updating Bitfinex `FeeModel` so it return fees in quote currency.
Adding unit tests
- Adding new `IAlgorithm.AccountCurrency { get; }` that will point to the
`Portfolio.CashBook.AccountCurrency`. Setter will be added in a
following PR.
- Base `Brokerage` class will now have a `AccountCurrency { get }`
pointing to the `IAccountCurrencyProvider`. Will be used by the different
brokerages implementations.
> This PR is a mechanical refactor, no behaviour changed
- Obsoleting `IsFillDataForward`, `Resolution`, `IsExtendedMarketHours`
`Security` configuration properties. Replacing there usages by
requesting the `SubscriptionDataConfigs` to the new
`SubscriptionDataConfigService`
- Removing unneeded `CashBook` instance to create a new `TimeSlice`
- Adding new `TimeSliceFactory`, an instance base class that will
provide methods to create a new `TimeSlice`. Will own the `DateTimeZone`
property.
- Adding new `ISecurityPrice` and `IOptionPrice` that will provide a
reduced interface for accessing price properties and methods used when
creating a new `TimeSlice`
- Removed usages of algorithm.Securities.key as a parameter for the
`ManualUniverseSelectionModel()` since those securities, added through
`AddXXXX` calls will be managed by the `UserDefinedUniverse`. This was
causing for Universes to try to add the same subscription requests
- Adding new empty constructor for ManualUniverseSelectionModel,
required for Python
- ManualUniverse will return any existing SDC for the
symbol. This is for maintaining existing behavior and
preventing breaking changes: Specifically motivated by usages of
Algorithm.Securities.Keys as constructor parameter of the
ManualUniverseSelectionModel, since those Symbols added by Addxxx()
calls will already be managed by the UserDefinedUniverse
- Making some format modifications to aling with used Lean formatting
Security instances will require private access to this value in order to
compute close profit.
NOTE: The extent of these changes for simply adding a constructor argument
insinuates that we're missing an abstraction to manage the construction of
these objects, such as a factor object for Security. This will need some
careful TLC in the near future.
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.
- When there are or aren'tt new insights, the EqualWeightingPortfolioConstructionModel will creates a target to flatten delisted securities from the universe of expired insights.
- Helper methods were added to deal with removing expired insights and getting active ones and used in `EqualWeightingPortfolioConstructionModel`
- Adds unit test
- Updates framework algorithms
Martin Molinero