* add data count properties
* 'add history count property
* assert data counts
* update missing override
* consider override/virtual cases
* implement data count
* add message handler for regression tests
* use regression test message handler
* set algorithm manager for regression test message handler
* update data count
* check if stats are present, check if algo manager is not null
* update
* add c# algo
* make same as c# algo
* use new line
* logic shifted to RegressionTestMessageHandler
* cleanup
* auto cleanup
* skip non deterministic data count
* change data count
* use inheritance
* improve stats
* update couht
* add sma indicator to c# and customSMA to python
* call base method before executing further
* skip test
* revert to original
* add duplicate sma
* skip regression test
* Refactor error message for reproducability
* WIP Refactor GetMaximumOrderQuantityForTargetBuyingPower
* Additional tweaks and tests
* Address shorted margin case
* Reinstate tests with new modified function
* Update regression
* Some cleanup
* Expand test set
* Refactor solution
* Address review
* Final adjustments and cleanup
* Expand error message for GetAmountToOrder for safety and reproducibility
* Address reviews
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Implement scheduled event sampling solution
* Use UTC time, only update daily portfolio value once a day
* For daily resolutions sample chart always
* Cleanup
* Drop resample daily all together
* Force final sample
* Regression updates
* FIx LiveResultHandler to update portfolio and benchmark values outside of sampling event
* Name the daily sampling event
* Address review pt 1
* Drop force and use reference wrapper
* Adjust tests
* Fix warning for Benchmark Timezone Misalignment and also add test
* Fix for daily resolution orders and test adjustments
* Also warn on universe settings with daily resolution
* Update missed regression
* Fix reference wrapper use
* Update regression after rebase
* Add values back in for Daylight Algo
* Have statistics builder skip day 1 performance
* Regression adjustments
* Test adjustments
* Update regression unit test
* Adjust some regressions starts to show performance values
* Add hourly algorithm for beta comparison
* Address missing Python regression changes
* Remove null comment
Build & Test Lean / build (push) Has been cancelled
* Add property for capacity. Remove unused variable
* Move SymbolCapacity and CapacityEstimate to common, passed through Symbol to runtime statistics
* Add null checks
* Remove uninvested and untradable assets from capacty calculations
* Add SymbolCapacity influential period
* Updates Regression Tests
- DelistingEventsAlgorithm
- Allows additional contributions from delisted AAA.1
- DelistingFutureOptionRegressionAlgorithm
- Removes DC01H12 contributions one month later
- FutureOptionBuySellCallIntradayRegressionAlgorithm
- Allows additional contributions from future after expiry replacing the contribution of the next contract option
- DelistedFutureLiquidateRegressionAlgorithm
- FutureOptionCallITMExpiryRegressionAlgorithm
- FutureOptionCallITMGreeksExpiryRegressionAlgorithm
- FutureOptionPutITMExpiryRegressionAlgorithm
- FutureOptionShortCallITMExpiryRegressionAlgorithm
- FutureOptionShortPutITMExpiryRegressionAlgorithm
- FuturesAndFuturesOptionsExpiryTimeAndLiquidationRegressionAlgorithm
- Allows additional contributions from future after expiry
- FutureOptionCallOTMExpiryRegressionAlgorithm
- FutureOptionPutOTMExpiryRegressionAlgorithm
- FutureOptionShortPutOTMExpiryRegressionAlgorithm
- IndexOptionCallITMGreeksExpiryRegressionAlgorithm
- IndexOptionCallOTMExpiryRegressionAlgorithm
- IndexOptionShortCallOTMExpiryRegressionAlgorithm
- Allows additional contributions from option after expiry
- MACDTrendAlgorithm
- Removes contribution when SPY is not invested for over one month
- UniverseSelectionRegressionAlgorithm
- Allows additional contributions from delisted GOOAV replacing GOOG (new symbols)
* Adds Lowest Capacity Asset to Regression Tests
* Normalize expected value -0, because -0 is also written to file if updated
* Write Symbol.Value for lowestCapacitySymbol or empty string for empty Symbol
* Update Regressions
* Update 'Lowest Capacity Asset' to Symbol.ID
Co-authored-by: Jared Broad <jaredbroad@gmail.com>
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
Co-authored-by: Colton Sellers <Colton.R.Sellers@gmail.com>
* Adds CapacityEstimate and SymbolCapacity
The capacity estimation has been moved from
the report generator and wired directly into
Lean via the ResultHandler. In addition,
the capacity estimation strategy has changed
to account for errors in the previous iteration
of the capacity estimation.
Many many thanks to Jared for being much of the
mastermind behind this project. It would have
been harder to complete without him to bounce ideas
off of.
* Moves old tests to regression algorithms
* Adds Estimated Capacity statistic
* Removes old capacity estimation tests
Final report capacity estimation. Pushing to save state
* Fixes bugs, cleans up code and adds comments
* Adds forced sampling to Capacity Estimation
* Misc. bug fixes for daily data
* Updates capacity test cases' Estimated Strategy Capacity statistic
* Adds Capacity Estimate to all regression algorithms
* Removes Report's StrategyCapacity class and fixes bug in tests
* Adds null check in BacktestingResultHandler to fix
BacktestingTransactionHandler failing tests
* Deletes old capacity estimation classes
* Retrieve capacity estimates from backtest statistics results
instead of calculating at runtime
* Make $0.00 capacity return as "-" and Result = 0 in report
* Adds capacity to runtime statistics
* Converts capacity to number denoted by financial figures in RuntimeStats
* Addresses review: code cleanup for Capacity and adds comments to regression tests
* Update OrderListHash to use MD5 as hash instead of hash code
* Update regression algorithm OrderListHash statistic
* Use full MD5 hash as OrderListHash, update regression statistic
* Fixes failing regression tests
- Remove unrequired `GetBuyingPower`
- Making `BuyingPowerModel.GetMaintenanceMarginRequirement` protected
instead of public
- Adding `GetMaximumOrderQuantityForDeltaBuyingPower` to replace
public `GetMaintenanceMarginRequirement` and improve API experience for
consumers like the `DefaultMarginCallModel`
- Adding new unit tests
- 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`
This flag indicates whether or not the local regression test system,
via RegressionTests.AlgorithmStatisticsRegression should run a given
IRegressionAlgorithmDefinition
It's important that we keep the factor files consistent with respect to
the date that they were generated. This enables us to run the regression
algorithms in the cloud and get the same results by using the factor files
from the correct date.
A mechanical refactoring was performed to make algorithms currently used in
regression algorithms to implement IRegressionAlgorithmDefinition, which allows
algorithms to define their own expected statistics and what languages should be
run as part of regression. The type name of the C# type is used to determine the
file/model name for python. This was for simplicity, but if needed, could later be
refactored to expose more information, but for now the convention of keeping names
the same makes sense and just works easily.
In order to test the GDAX FillModel and FeeModel that respects both lot size, the fractionalQuantityRegressionModel was changed to use the GDAX Brokerage. This drastically changed the regression statistics for the regression test. These statistics have been updated
Decreasing the fractional quantity of the gdax lot sizes required test corrections for BrokerageTransactionHandlerTests specifically RoundOff_LessThanLotSize_Fractional_Orders, RoundOff_Short_Fractional_Orders, RoundOff_Long_Fractional_Orders order. The quantity of the test orders needed to be reduced in order to comply with the updated lot order sizes
Also needed to change the FractionalQuantityRegressionAlgorithm - which is supposed to have one order fail because the quantity is too small. This order needed a smaller quantity in order to fail with the new lot sizes
Updated FactionionalQuantityRegressionAlgorithm tests
- Update quantity to decimal in OptionExerciseOrder
- Update FractionalQuantityRegressionAlgorithm to use QuoteBarConsolidator
- Update FractionalQuantityRegressionAlgorithm stats
- Truncate order quantity to int in IB exerciseOptions
- Truncate order quantity to int in FuzzyInferenceAlgorithm
Ronit Jain