In order to add support custom python indicators for `QCAlgorithm.PlotIndicator`, we created a `PythonIndicator` class that wraps the custom python indicator. In `QCAlgorithm`, the reference of the wrapper is saved into a dictionary keyed by the python indicator handle.
- Adding `IRealTimeHandler.OnSecurityChanged()` will be used to update
the `OnEndOfDay` security related scheduled events
- Adding `BaseRealTimeHandler.cs` to reduce code duplication in the
`Backtesting` and `LiveTrading` `RealTimeHandlers`
- Adding CSharp and Python regression tests
- Deprecating `OnEndOfDay()` callback because of two reasons, mainly
because Python does not support two methods with the same name, but also
because different assets have different market close times.
- `ScheduledEvents` set at the same time will now be deterministic
- Adding `LazyToUpper()` implementation, that will avoid the call to
`ToUpper` if the string is already upper.
- Reduce the timezone conversions at `Time.EachTradeableDayInTimeZone`
- `TotalPortfolioValue` will iterate over all securities once
- Adding new `SecurityIdentifier` cache, significant impact for
algorithms using coarse/fine data
- `TimeSliceFactory` will avoid creating empty collections
- `ExecutionModels` will check target collection count before trying to
enumerate
- Reduce calls to .`TotalPortfolioValue`
- `SecurityValues` will only be created when required
- `TimeKeeper` will use TimeZone unique Id as dictionary key. The
TimeZone hash is expensive.
- `AlgorithmManager` will avoid calling `DateTime.UtcNow`,
`ConvertFromUtc()` and `RoundDownInTimeZone()`
- 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
- Consistently use QuantConnect/Lean naming convention for method variables;
- Use `IND(PARAM1,PARAM2, ..., PARAMN)` format for indicators. Indicators that are created by a helper method become: `IND(PARAM1,PARAM2, ..., PARAMN, SYMBOL_res)`.
- Fixes `RegressionChannelTest`.
- Implements `IIndicatorWarmUpPeriodProvider`;
- Refactors `IchimokuKinkoHyo`;
- Fixes sub-indicator computations: the `Delay` sub-indicators were accepting input from indicators that were not realy;
- Adds `Chikou` indicator (closes#919);
- Indicators with name starting with A;
- `Maximum`. `Minimum` and `MACD`;
- Adds new unit test method to `CommonIndicatorTests`: `WarmsUpProperly`;
- Indicators unit tests inherit from `CommonIndicatorTests`.
Remove usage of DateTime.UtcNow in buying power models
In PR#3013 we added support for fee models with history, so the new changes to the GDAXFeeModel exposed this bug, breaking a couple of regression tests (issue #3044)
Update regression stats for EmitInsightCryptoCashAccountType
* Fix typos
Add missing time keeper in CashBuyingPowerModelTests
- `FactorFile` will keep an ordered reversed list with the dates.
Calling `Reverse()` on the `SortedList` is expensive.
- `MapFiles` will keep first and last date, so we don't need to call
`First()` and `Last()` multiple times.
- `Liquidate` will go through all the algorithms securities only if
necessary
- `TradeBar` parsing will not call `new T` for pure `TradeBar` which is
expensive
- Removing `Lazy` hash code and security type for the
`SecurityIdentifier`, replacing for direct initialization. Accessing the
`Lazy` value adds an overhead.
- Replacing `Enum` to string for hardcoded switch statement. `Enum.ToString` is expensive.
- `DataManager` will be lazy for counting the subscriptions for
determining if its above the limit
- Adding `AlgorithmSecurityValuesProvider.GetAllValues()`, removes the
need to fetch all the security keys twice.
- During universe selection, will not try to re add already added symbol
- Removes `UniverseSettings.DataNormalizationMode` (it will ne addressed in a dedicated issue: https://github.com/QuantConnect/Lean/issues/3082)
- Adds examples/tests for Tick resolution, Forex (QuoteBar data) and Custom data.
- Tick resolution is not allowed: logs a message
- Custom data example/test added in `CustomDataNiftyAlgorithm`
- Adds support for ATR and VWAP since they are, respectively, a bar and a trade bar indicator.
- Adds consolidators to handle difference between data resolution and indicator resolution.
This helper method can be used to warm up indicators individually whether it is created after the security has been added to the universe or before (universe selection scenario).
- Fix the subscription addition to `SubcriptionManager` when a History request is made before the security is created, since it should be not added.
- `IndicatorBase.Update` does not throw when an input is older than the last update. We only log (adds QuantConnect.Logging dependency to QuantConnect.Indicators) the error and discard the addition. Removes unit test for that exception.
- Using `Aggregate(lambda)` vs `Sum(lambda)` since the later is slower
due to performing an extra `Select`
- For `QCAlgorithm.Framework.OnFrameworkData()` will avoid calling
`ToArray()` on empty `Enumerables` due to its cost * the number of
calls. If the `Enumerable` is the empty instance, which is static,
will create a new empty array and return it instead.
- Replacing `SecurityIdentifier` `SecurityType` and `GetHashCode`
implementations for `Lazy` versions, that are performed just once, since
these values do not change and are used multiple times.
- For the different `DataDictionary<T>` implementations adding `this[
Symbol] get; set` since existing overload `this [string]` produces an
extra round operations `Symbol->string->Symbol` with a significant
impact.
- Adding `PortfolioTargetCollection.AddRange()` overload using an array
to avoid unnecessary convertions.
- Adding _some_ of the missing PyObject.Dispose calls. In the cases
where C# is calling the Python side.
- Note that Python calls to C# code is correctly handling the
disposure of resources.
Replaces Enum `CalendarType` for static class with the same name. This class defines two properties (`Weekly` and `Monthly`) that can be used to define the previous calendar date (Monday or 1st of current month) which will correspont to the `Time` of a `IBaseData` object.
Refactor `PeriodCountConsolidatorBase` to define use `GetRoundedBarTime` based on a period specification that depends on the constructor overload: `integer`, `TimeSpan` or `Func<DateTime, CalendarInfo>`. The last one can be set with the `CalendarType` properties.
- Implementing `QCAlgorithm.AddUniverseSelectionModel`
- Adding C#/Py regression algorithms using the new API
- Modifying `ManualUniverSelectionModels` symbol, adding hash of
the selected `Symbol.Values`
- Modifying `Coarse` and `Fine` symbol, adding random GUID
- Adding `NullUniverseSelectionModel`
- 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.
- 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