- Adding new SerializedOrderEvent and SerializedOrder with new
JsonConverters
- Specifying OrderEvent json converter when storing, streaming data
- Adding unit tests
- 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()
- Refactoring some PCM methods to be `protected` since they are not required
to be public
- Adding new `PortfolioConstructionModel.RebalanceOnInsightChanges`
flag, that will allow avoiding new insights or insight expirations to
trigger a rebalance
- Updating unit tests
- Fix for the MeanVarianceOptimizationPortfolioConstructionModel that
was skipping, in some cases, 0 magnitude insights
- Adding `SecurityCacheProvider` this class allows for two different
`Security` to share the same data type cache through different instance
of `SecurityCache`. This is used to directly access custom data types
through their underlying in a peformant maner
- Some small improvements
The `NullReferenceException` type is intended to only be thrown by the CLR.
In most cases, it should be converted to an `ArgumentException` or an
`InvalidOperationException`, depending on if the null value is a parameter
to the current method or not.
The `Exception` type should never really be thrown as it doesn't provide any
additional information or hints as to the issue. It also forces users that
would like to handle expected exceptions to catch all exceptions. These are
converted to an exception type that more accurately describes the reason for
raising the exception: `KeyNotFoundException`, `InvalidOperationException`
- `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
- `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`
- `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
- 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.
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
- 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
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.
The insight itself defines when it closes via the algorithm framework
and properly takes into account weekends and out of market hours. The
insight analysis was not respecting the insight's stated close time,
but instead was simply doing generated time + period, which doesn't
properly take into account market hours. This causes the number of
closed insights to decrease and due to the extra time for each insight,
the values of the insights have also increased.
This identifier is used to determine the alpha model that generated.
This is NOT ideal, since it requires users to specify the value, more
thought will be givent to how we can resolve this value automatically
Adds test for surviving roundtrip copy operation.
Provides a collection type for managing insights. Internally it uses
a dictionary Symbol->List<Insight> but does NOT implement the dictionary
interface due to potentially unexpected behavior when enumerating, i.e,
different behavior when enumerating if statically known as list vs statically
known as dictionary -- not sure how python would resposne to the ambiguity,
so best to leave well enough alone :)
Adam May