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* Default daily precise end times
- Enable by default daily precise end times. Updating stats
- Minor fix for algorithm manager consolidator updates, adding new regression test
asserting behavior and updating others
- Minor fix for SubscriptionData creator avoid round down on warmup if
not appropiate
- Adjust consolidators to emit on daily strict end times if requested
daily resolution and setting enabled
- Updating regression algorithms
* Skip daily data on extended market hours
* Some cleanup and self review
* Revert unrequired change
* Dynamic spdb
* Minor changes and unit test
* Get MHDB and SPDB refresh period from config
* Add databases refresh period to algorithm settings
* Address peer review and add unit test
* Daily data Time & EndTime Improvement
- Adjust daily data Time & EndTime to actually reflect the time of the
data used, for example US Equity from 9.30 to 4PM. Adding new unit and
regression tests
* Refactor solution to use enumerator
- Refactor daily strict end times solution to be through enumerator
usage, so it applies for history providers too
* Minor fixes
* Revert fill forward enumerator change
- Revert FillForward enumerator causing stats changing, enhancing unit
tests
* Some cleanup
* Improve handling of live trading FF enumerator
- Improve handling of live trading FF enumerator, by adding support for
bars to arrive with a delay so we can handle auction close/option
prices or data providers which might have some delay making the data
available. Adding new unit tests asserting the behavior
* feat: new `TradingDaysPerYear` prop in IAlgorithmSettings
* feat: getTradingDayPerYear by BrokerageModel
feat: init algo tradingDaysPerYear in brokerage|BacktestingSetupHandler
refactor: nullable `TradingDayPerYear`
* remove: hardcoded value:252 in statistics
* test: `algorithm.Settings.TradingDaysPerYear` for different brokerage
fix: tests calculation of `AnnualPerformance()`
* fix: Report generator by tradingDayPerYear
* fix: hardcoded value in PortfolioStatisticsTests
* fix: tradingDayPerYear in AnnualPerformanceTest
remove: extra spacing
* feat: backwards compatibility for TradingDaysPerYear
* feat: several UTest for AlgoSetting's TradingDaysPerYear prop
* fix: existed algo + test
* feat: regression algo with checking of tradingDayPerYear in OnEndOfAlgorithm()
* refactor: GetBrokerageTradingDayPerYear -> SetBrokerage... in BaseSetupHandler
refactor: carry out tradingDayPerYear at the top level and pass variable
* remove: default valuine in test param
remove: extra comment.
* fix: missed init TradingDaysPerYear in report.portfolioAlgo
fix: hardcoded value to tradingDaysPerYear
* fix: nullable TradingDaysPerYear in AlgorithmConfiguration
feat: UTest for PortfolioLooperAlgo
feat: add advanced description
* feat: test PortfolioStatistics with different tradingDaysPerYear
* revert: PortfolioLooper with TradingDaysPerYear implementation
* revert: nullable TradingDaysPerYear in AlgoConfiguration
remove: SetBrokerageTradingDayPerYear in BaseResultHandler
* style: remove empty row
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* Deprecates IAlgorithmSettings.DataSubscriptionLimit
We will let the brokerage check and notify users that they have subscribed to datafeeds beyond their quota.
* Removes Unit Test
Also remove usage in `EmptyEquityAndOptions400Benchmark`.
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* Implement Trailing FreePortfolioValue
- Implement Trailing FreePortfolioValue by default, users will be able
to set it to a fixed number if desired. Adding regression algorithm
- Setting the default 'MinimumOrderMarginPortfolioPercentage' from 0 to
0.1% of the TPV to avoud tiny trades by default
* Update existing regression algorithms
* Address reviews
- Send warning message to the user if a trade does not happen due to the
default setting of the minimum order margin percentage value
* Address reivews
* Rename TotalPortfolioValueLessFreeBuffer
* Update new regression algorithm
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* Respect warmup resolution given
- The data feed will respect the warmup resolution given and override
the resolution used by the algorithm when adding a subscription.
Updating regression algorithm to keep previous statistics. Adding new
regression algorithm asserting the desired behavior
* Testing improvements
- Add more unit tests and regresion test
- Add missing data for crypto
- Fix bug with FFed data crossing after the end time of the warmup
request
* Add more Warmup resolution regression algorithms
- Adding more warmup resolution regression algorithms, using
Settings.WarmupResolution and an option selection case
* Add more warmup regression tests
- Adding more warmup regression tests.
- Will no longer skip universe selection subscriptions from warmup
resolution enforcement. Updating regression algorithms data points
* Fix bug with data rounding
- Fix data rounding bug when warmup resolution is set to a different
value than the original configuration. Updating regression algorithms
to assert the expected behavior
* Address reviews
- Revert regression algorithms changes to use Resolution during warmup.
Updating their stats.
- Adding new regression algorithms asserting the behavior warming up
using a timespan and no warmup resolution
- Fix bug where data used to warmup the 'normal' enumerator will make it
through into the warmup time span. Updating tests
* Address reviews
- Add missing comments, explaning warmup algorithms time span
calculations.
- Revert changes in existing `WarmupOptionTimeSpanRegressionAlgorithm`
to reduce diff to minimum
- Adding new warmup unit tests asseting algorithm warmup start time, for
different combinations of bar count, timespan, resolution
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* Filter out small orders based on Setting
- BuyingPowerModel will filter out small orders based on algorithm
setting, a % of PTV, instead of hard coded 1 share value. Addin unit
and regression tests
- Updating regression algorithms to use new setting, reduce order trades
* Update regression algorithms
- 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`
- 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
The market fill warning introduced in #2869 was considering any price older than the fill time as stale (even if only a few seconds older), causing many false alerts.
This is being changed now by adding a new configurable algorithm setting: StalePriceTimeSpan (with a default value of one hour).
Jhonathan Abreu