* 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
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* Fixes Market On Open Fill of Equity Fill Model
Only use trade data (Tick with Trade type or TradeBar) to get the open price, since MOO is filled with the opening action price. Ensure that this method doesn't use trade data from before the market opens for high-resolution data case.
Fix unit tests to show that the new implementation only fills with trade data from the current open market.
Change regression tests to reflect the bug fix.
In the `ExtendedMarketHoursHistoryRegressionAlgorithm`, MOO was filled with extended market hours.
* Fix Bug for Tick Resolution Case
For tick susbcription, the tick with the open price information is the the first valid (non-zero) tick of trade type from an open market.
Addresses peer-review by moving the if-condition for data belonging to the open market where the subscriscribed types are checked.
* Fix Bug for Low Resolution Edge Case
For the edge case where the order is placed after the trade bar is open, for example, order places at 1 pm with daily-resolution data. The fill model will not use the open of the bar that will close at midnight, since this value is prior to the order.
Adds unit test.
Change regression tests to reflect the bug fix.
In the `RegressionAlgorithm`, MOO was filled with open prior to the order. The algorithm now has one order less, since the last MOO would need to wait another day to be filled.
* Implements SaleCondition and Exchange Check For Tick
- Adds additional unit tests for MOO
* Fixes Regression Test in DataConsolidatorPythonWrapperTests
* Addresses Peer-Review
- Adds new unit test cases.
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* Implement solution with lightest changes possible
* Update regressions v1
* Adjust AlgorithmTradingTests
* Adjust PatternDayTradingMarginBuyingPowerModel tests
* Drop need to loop twice
* Adjust last unit test, with calculations included
* nit - comment fix
* Break out adjustment calculation to static function; add unit test
* Update Py regression
* Upgrade adjustment calculation to be smart enough to get us to target always
* nit - cleanup GetAmountToOrder
* Add license to test
* nit - comment fix
* cleanup GetAmountToOrder further
* Add additional test cases
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* Updates Equity Market Data
* Updates Unit Tests
* Updates Regression Tests
In this commit we include regression tests with small changes (slightly different CAGR, Alpha, etc, but same number of trades) due to the data update.
* Updates Regression Tests 2
The following regression tests were adapt because of verification of hard-coded market data values:
- `AdjustedVolumeRegressionAlgorithm`
- `HistoryWithSymbolChangesRegressionAlgorithm`
- `OptionRenameRegressionAlgorithm`
- `RawDataRegressionAlgorithm`
- `SwitchDataModeRegressionAlgorithm`
The following regression tests have more trades since adjusted prices allowed more 1-2 shares trades that were rounded down to zero before:
- `AddUniverseSelectionModelCoarseAlgorithm` 23 -> 35
- `MeanVarianceOptimizationFrameworkAlgorithm` 12 -> 14
- `PortfolioRebalanceOnDateRulesRegressionAlgorithm` 298 -> 324
- `PortfolioRebalanceOnInsightChangesRegressionAlgorithm` 83 -> 86
- `ScheduledUniverseSelectionModelRegressionAlgorithm` 86 -> 90
- `SectorExposureRiskFrameworkAlgorithm` 17 -> 22
- `SetHoldingsMultipleTargetsRegressionAlgorithm` 8 -> 9
- `StandardDeviationExecutionModelRegressionAlgorithm` 196 -> 199
- `UniverseUnchangedRegressionAlgorithm` 11 -> 17
- `VolumeWeightedAveragePriceExecutionModelRegressionAlgorithm` 237 -> 238
Especial cases:
- `BlackLittermanPortfolioOptimizationFrameworkAlgorithm` 18 -> 17
- BLM model sensibility
- `OptionChainedAndUniverseSelectionRegressionAlgorithm`
The following regression tests have different Capacity because of different volume from lowest capacity asset, except:
- `OptionEquityCoveredCallRegressionAlgorithm` New lowest capacity asset is underlying
- `OptionEquityCoveredPutRegressionAlgorithm` New lowest capacity asset is underlying
* Revert File Update for SPWR and SPWRA
* Fix Regression Tests
Temporarily removes python regression test for `MeanVarianceOptimizationFrameworkAlgorithm` as the `MeanVarianceOptimizationPortfolioConstructionModel` for each version are yeilding different results. If we use C# version in `MeanVarianceOptimizationPortfolioConstructionModel.py`, the results match.
* Changes Optimization Method in MinimumVariancePortfolioOptimizer [Py]
Uses `trust-constr` method.
See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html
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* 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>
* Fixes Double to Decimal Cast in GetAnnualPerformance
`GetAnnualPerformance` raises an exception if the `AnnualPerformance` calculation returns a double that cannot be cast to decimal (smaller than `decimal.MinValue` or bigger than `decimal.MaxValue`).
See `ProbabilisticSharpeRatio` where the same solution was applied.
* Updates SPY Market Data
SPY is a key asset since it is the default benchmark, and any change can lead to different `Alpha` and `Beta`
* Updates Unit Tests to Reflect Data Update
* Updates Regression Tests to Reflect Data Update I
Most of the regression tests change because of updated data (market and factors) of SPY (default benchmark) while the total trade remain the same.
* Updates Regression Tests to Reflect Data Update II
The following regression tests were changed to adapt to adjusted prices and keep the total trades:
- `BacktestingBrokerageRegressionAlgorithm`
- `LimitIfTouchedRegressionAlgorithm`
- `PortfolioRebalanceOnCustomFuncRegressionAlgorithm`
- `SetAccountCurrencySecurityMarginModelRegressionAlgorithm`
- `StopLossOnOrderEventRegressionAlgorithm`
- `TimeInForceAlgorithm`
The following regression tests have more trades since adjusted prices allowed more 1-2 shares trades that were rounded down to zero before:
- `FreePortfolioValueRegressionAlgorithm` 2 -> 3
- `PortfolioRebalanceOnDateRulesRegressionAlgorithm` 291 -> 298
- `TrailingStopRiskFrameworkAlgorithm` 5 -> 7
Especial cases:
- `AutoRegressiveIntegratedMovingAverageRegressionAlgorithm` 65 -> 52
- ARIMA model sensibility
- `BlackLittermanPortfolioOptimizationFrameworkAlgorithm` 18 -> 19
- BLM model sensibility
- `ExtendedMarketHoursHistoryRegressionAlgorithm` 20 -> 18
- Less minute bars before market opens
* Addresses Peer-Review
Fix `BacktestingBrokerageRegressionAlgorithm` to use `CalculateOrderQuantity` and round down `quantity` to an even number to pass a value assertion and update the expected value from 50 to 52.
The quantity calculated by `CalculateOrderQuantity` has changed from 50 to 53 because of factor file update.
* 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
- Update regression algorithms stats after making SecurityCache ignore
QuoteBars for equity for OHCL values and GetLastData(). They were
affected since the `BenchmarkSecurity` used `.Price` which was QB for
equities. Order list hashes changed because SubmissionLastPrice will
now be TB instead of QB
- Adding new `Func<DateTime, DateTime?>` that allows PCM to return null
if the next rebalance time is null, in which case the function will be
called again in the next loop.
- Adjusting PCM next rebalance time check to perform rebalance once the
time is reached
- Adding new regression test. Updating existing
- 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`
- 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.
- 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.
This flag indicates whether or not the local regression test system,
via RegressionTests.AlgorithmStatisticsRegression should run a given
IRegressionAlgorithmDefinition
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.
VWAP will submit market orders while the current price is more favorable than VWAP.
STD will submit market orders while the current price is a configured number of
standard deviations away from the mean in the favorable direction.
Ronit Jain