Build & Test Lean / build (push) Has been cancelled
* Updates Fundamental Data
* Updates Regression Algorithms
- `CoarseFundamentalTop3Algorithm`
- New coarse has higher `DollarVolume` for `FB`
- `CoarseNoLookAheadBiasAlgorithm`
- Change from `SPY` update not included in #5493
- `SectorExposureRiskFrameworkAlgorithm`
- `HasFundamentalData` was false for `GOOG` on 20140401 and 20140402.
* Updates Unit Tests
Minor changes in expected values
* Updates Regression Tests
Should have been included in #5493:
- `OptionsExpiredContractRegression`
- `FuturesExpiredContractRegression`
* Adjusted Quantity By Lot Size in OrderTargetsByMarginImpact
`OrderTargetsByMarginImpact` didn't calculate the order value with the quantity adjusted by order size which less to values that did not reflect the actual order value.
It has a particular affect in `SectorExposureRiskFrameworkAlgorithm` where the Python and C# versions have the same orders but placed in a different sequence because of decimal/double precision.
* Reduce dictionary access x3 on OrderTargetsByMarginImpact
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
Build & Test Lean / build (push) Has been cancelled
* Redefine IsReady and WarmUpPeriod
* Update warm up periods of other indicators to account for ROC warmup change
* Update regressions affected by this change (because of HistoricalReturnsAlphaModel using ROC)
* Add simple unit test for issue #5491
* Cleanup warmup period math and add comments
Co-authored-by: Colton Sellers <Colton.R.Sellers@gmail.com>
Build & Test Lean / build (push) Has been cancelled
* Reconcile and consolidate SetupHandlers
* Centralize GetConfiguredDataFeeds()
* nit - extra space
* Check for null, also allow null to be passed back if no config value
* Fix breaking test
* Cleanup
* fix return var
* remove unneeded if/else
* Minor changes
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
Build & Test Lean / build (push) Has been cancelled
* Use UniverseSettings.DataNormalizationMode for securities added in Algorithm
* Stop SubscriptionUtils from forcing Adjusted mode
* Return behavior to original and add comments
* nit typo
* Add regression
* Add unit test that verifies DataNormalizationMode can be altered manually by security
* Cleanup and add Py version of regression
* Update projects to use .NET 5.0, the successor to .NET Core
* Fix ambiguous errors. Add IBAutomator net5
* Remove FXCM
* Upgrade IBAutomater to v1.0.51
ignored, and an empty message aborts the commit.
* Fix rebase
- Fix ambiguous Index
- Remove StrategyCapacity.cs
- Update System.Threading.Tasks.Extensionsy
* Remove unrequired references
* Fixes
- Travis will use dotnet, not nunit nor mono
- Remove mono from foundation image
- Fix python setup in research
- Fix unit tests
* Don't call ReadKey when input is redirected
* Fix ConsoleLeanOptimizer
* Research fixes
* Update comment
* Add vsdbg to Dockerfile
* Fixes
- Revert dockerfile FROM custom changes
- Adjust and fix regression algorithms
- Option assignment will be deterministic in the order
- 'Rolling Averaged Population' is calculated using doubles, updating
expected values.
- Update readme, removing references to mono
- Add missing Py.Gil lock
* Replace ICSharp with .NET Interactive
* Fixes after rebase
* CSharp research fixes
- Adding new Initialize.csx that pre loads all assemblies
- Adjusting template research file
- Moving steps in dockerfilejupyter
- Fix unit tests and regression tests after rebase
Co-authored-by: Gerardo Salazar <gsalaz9800@gmail.com>
Co-authored-by: Stefano Raggi <stefano.raggi67@gmail.com>
Co-authored-by: Jasper van Merle <jaspervmerle@gmail.com>
Build & Test Lean / build (push) Has been cancelled
* Add unit test
* Make test cover issue case
* Filter out times before startTimeUtc
* Refactor solution, fixes missing first date
* Fix case where none is expected
* Cleanup tests, add TriggerTimesNone
* Drop unused imports
* Add missing dipose call
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
* Refactor HasSufficientBuyingPowerForOrder implementations
Adds Sufficient and Insufficient helper methods to HashSufficientbuyingPowerForOrderParameters
enabling syntax like:
return paraeeters.Sufficient()
returnparameters.Insufficient(reason)
The next change will add the initial margin required which will simply require
updating both of these helper methods to accept the value.
* IBuyingPowerModel: Add margin functions Maintenance/Initial/ForOrder
These were originally hidden in an effort to only expose what's necessary
for the engine to perform its work. Additionally, we encapsulated all of
the method arguments into parameters classes to prevent having to break
anyone in the future. Not including these foundational methods turns out to
be an oversight. These methods are not required by the engine, but rather by
other models. Another possible solution here is to add an additional abstraction
and include these methods on this new abstraction. BuyingPowerModel would then
explicitly implement these methods and models that depend on them would require
two code paths, one for when the buying power model implements this interface
and another for when it doesn't.
Tests were additionally updated to remove test model implementations created for
the sole purpose of exposing these private methods.
* Add ConstantBuyingPowerModel
Provides an implementation of IBuyingPowerModel that returns the same
constant value
* Update BuyingPowerModelPythonWrapper to use reflection for method names
Having a bunch of hard-coded strings is a sure fire way for someone to
overlook when changing methods. This change ensures that noone needs to
remember that this code exists :)
Cleans up the syntax around verifying a python object implements a particular
C# interface via the ValidateImplementationOf<T> method by having it return a
value since the only use cases are in constructors when setting the models.
I was initially going to update ALL python wrappers to validate the passed
in models, but such a change could break many things that are 'working' right
now. Such an effort should be saved for its own dedicated PR.
* Add Parameters/Result types for new buying power model methods
* Support computing maintenance margin for arbitrary quantities
The existing GetMaintenanceMargin function assumes that we're only interested
in the maintenance margin for the entirety of the provided security's holdings.
This makes it impossible to perform what-if analysis or to even ask how much
maintenance margin is devoted to a particular subset of the security's holdings.
This change adds the quantity to the MaintenanceMarginParameters class. Futures
and Options models also depend on holdings cost and holdings value, so they have
also been added to the parameters type. Finally, static factory methods were
added to improve discernment of intent: ForCurrentHoldings provides the existing
behavior and then ForQuantityAtCurrentPrice to support what-if scenarios where
we're looking for the change in maintenance margin if we were to execute an order
for the securiy at the current time step. Obviously a constructor is provided to
set all of the values explicitly, using any price metric the caller desires.
* Address review
- Fix BPM xml documentation
- Fix python unit tests and PythonWrapper validate method
* Add SecurityHolding.QuantityChanged event
Adding event handlers will allow us to orchestrate complex
events from distant parts of the codebase through wiring
them up. If we continue down this path, it will move us away
from the current, very 'mechanical' data flows expressed in
LEAN and towards a more modern, event processing based system.
This is but a baby step in that direction and the initial use
case is using this QuantityChanged event to trigger resolution
of the algoritm's positions groups. This is part of an effort
to improve the fidelity of options margin modeling where we'll
model an OptionStrategy as an IPositionGroup. This will allow
us to compute the margin requirements of an OptionStrategy as
a unit instead of computing margin of each security individually
in isolation.
See #4065
* PortfolioManager: Group fields and remove unused field
This codebase generally places fields as the first members, but
this class had some fields at the top, then some properties, and
then some more fields. This change brings all the fields together
at the top of the file and also removes pointless comments placed
directly above some of the fields. Additionally, an unused field
was removed.
* Remove unused _currencyConverter from Security
Looks like at some point the only code using this member variable was removed
and the necessary clean up was overlooked.
* Add Parse.Enum functions
* Support disabling regression algorithms by language via config.json
Adds 'regression-test-languages' to config.json and filters regerssion algorithms to
run based on this value. When cycling on a particular feature, it's nice to be able
to run the entire regression set while ignoring the python algorithms. Once the C#
algorithms are all passing, one can then go back and run C# and Python in a final run,
since 99% of feature work doesn't impact python specifically.
* Implement IComparable in SecurityIdentitfier
This can be used to deterministically sort securities and symbols
* Add .editorconfig to enforce common formatting for json/sh files
* Fix typo in IBuyingPowerModel.GetBuyingPower xml docs
* Add ListEquals/GetListHashCode and OrderDirection.Closes(PositionSide)
ListEquals and GetListHashCode are designed to be used together as they
complement each other according to C#'s requirements for Equals and
GetHashCode functions.
PositionSide.ToOrderDirection() extension simply converts a PositionSide
to its logical equivalent OrderDirection. Long->Buy, Short->Sell, None->Hold
OrderDirection.Closes(PositionSide) determines if a particular OrderDirection
would have the effect of reducing a position's absolute size. This function
greatly improves the readability of buying power functions that must provide
adjustments when an order/contemplated trade reduces/closes an existing position.
OrderDirection.Buy.Closes(PositionSide.Short)
OrderDirection.Sell.Closes(PositionSide.Long)
All other combinations return false
Adds ToArray/ToImmutableArray convenience functions that combine a call
to Select followed by To(Immutable)Array all in one function call.
* Add decimal.DiscretelyRoundBy extension method
Supports rounding a decimal value by an arbitrarily chosen maximum precision,
or 'quanta'
* Update FutureMarginBuyingPowerModelTests to respect the security's lot size
* Add core position group classes and abstractions
* Add initial/maintenance margin support, buying power model consistency tests
* Add SufficientBuyingPower and GetReservedBuyingPower to position group model
Includes update to BrokerageTransactionHandler to use position group BPM for
sufficient buying power checks.
* Resolve position groups on each fill
We need to update the state of our position groups on each fill so that
we can properly handle multiple orders within the same time step. We
also limit the number of positions sent into the resolver by removing
securities without any holdings.
* fixup! Add SufficientBuyingPower and GetReservedBuyingPower to position group model
* Add GetMaximumLotsFor{Target|Delta}BuyingPower
Instead of computing order quantity, these functions compute the
maximum number of position group lots, which is the position group
quantity, and is guaranteed to be a whole number, for the provided
target/delta buying power parameters.
The SecurityPositionGroupBuyingPowerModel delegates to the security's
IBuyingPowerModel by applying a scaling factor equal to the security's
lot size.
This change also updates references to IBuyingPowerModel.GetMaximum...
to use the new position group model methods.
* Convert remaining IBuyingPowerModel call sites to position groups
* Rename PositionManasger.CreateDefaultGroup -> GetOrCreateDefaultGroup
Better describes its behavior
* Add Position Groups readme.md
* Add Option Strategy BuyingPowerModel
- Adding CompositePrositionGroupResolver and
OptionStrategyPositionGroupResolver
- Adding OptionStrategyPositionGroupBuyingPowerModel handling option
strategies based on IBs margin table. Adding regression algorithms
- Few changes so that option strategies executed by multiple orders are
detected
- Adjust OptionStrategyDefinitionMatch to include equity legs in the
matching result
- Minor tweaks fixing previous rebase
- Minor fixes for existing option strategies definitions, adding new
missing strategies.
- Fixing minor bugs in option strategy matcher. Adding more unit tests
* Address self reviews
- Fixing bug in 'PositionGroupCollection'
- Few minor simplificaitons
- Adding BasicTemplateOptionEquityStrategyAlgorithm
* Address reviews
- Improve regression algorithms margin remaining and used assert logic to be exact. Taking into account spread and fees
Co-authored-by: Michael Handschuh <mhandschuh@gmail.com>
* Refactor to queue up start date changes to log on dispose
* Fix typo in warning collection used
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
* Collect and log symbols that had start date adjusted because of factor files
* Only post the message if the set has values
* Modify message to be [Symbol, Date] combo for more information on log
* Set a hard limit on the warning set to keep it from growing unnecessarily large
* Enforce a hard limit and improve message if full
* Enforce limit in log message because of possible threading adding past max
* Cleanup
* Log security mode change once per universe addition process
* Limit max size of the warning queue to 10
* Only allow to emit once per backtest
* Set limit as var, if at limit suggest more
* Always suggest more warnings may exist because we opted to log only once
* Improves greeks configurability and defaults for all option asset types
* Makes `StandardDeviationOfReturns` configurable by users, so that
greeks can be loaded according to user expectations and the series
of returns that they'd like to compute for `n` periods and timespan
of `T`, as well as resolution of the data in live mode.
* Changes resolution to max resolution available for the default
volatility model created for the security. Usually this only applies
to live mode, but if creating an instance of the
`StandardDeviationOfReturns` volatility model and no `updateFrequency`
is provided, the resolution's time span will be used as the default
value. Backwards compatibility for equities is maintained.
* Changes defaults for `StandardDeviationOfReturnsVolatilityModel`
to warmup greeks faster for other derivative asset types
* Improves comments on `StandardDeviationOfReturns` for clarity on how
to use the volatility model for end users
* Fixes bug where TradeBar could not have proper Symbol set when getting
max resolution
* Applies to QCAlgorithm.Universe and StandardDeviationOfReturnsVolatilityModel
* Adds tests to check volatility model is updated at specified config intervals
* Address review: add shared method for (Relative)StandardDeviation
volatility models
* Adjusts logic to determine bar type
* Address review: order by TickType when getting configs inside volatility models
* Allow USDC in cashbook without USDC-USD pair
* Cover more stablecoin cases unique to our crypto brokers
* Add unit test
* Cleanup and expand test cases
* Add USDCEUR and USDCGBP to GDAX Symbols
* Add missing tickers to SPDB
* Cleanup test
- Testing net5 uncovered these algorithms to be undeterministic
- Adjusting AllShortableSymbolsCoarseSelectionRegressionAlgorithm
internal implementation
- Order removal of universe members will be deterministic, when the
entire universe is removed.
* 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.
* Add futures regression reproducing the issue
* Cleanup futures regression
* Add Options regression
* Add IRegressionAlgorithmDefinition
* Add IRegressionAlgorithmDefinition
* Adjust regressions to compare to expiration date; delisting time is not always correct
* Refactor subscription enumerator filtering of AuxData to top of the stack
* Update broken tests to reflect the split/dividends/delisting subscriptions
* Update regression statistics because of Delisting EOD instead of at time
* Let custom data configurations bypass filter
* Adjust expected count, now that we are letting aux data through to history requests
* another small adjustment
* Use ExpectedBarCount in error message
* Add filter test for both cases
* Add some clarifying comments
* Verify we did recieve data in the regressions
* Make _shouldEmitAuxiliaryData private readonly
* Filter out aux data for history requests
* Remove option to not include aux data in subscriptions
* Refactor filtering to be more explicit for each piece of data; fixes universe selection aux data
* Cleanup comments after removed var
* Refactor order of filtering for performance reasons.
`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.
* Add SI
* Add ASI
* Add Swing Index
* Add Accumulative Swing Index
* Fix XML comment
* Add SI and ASI
* Add test data
* Add SI tests
* Add ASI tests
* Convert get only properties to methods
* Fix indicator name
* Replace special characters
* Fix indicator formula
* Replace test data
* Replace test data
* Update QCAlgorithm.Indicators.cs
* Minor format tweaks
Co-authored-by: Jared <jaredbroad@gmail.com>
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
- Fixed GDAXBrokerage missing fills caused by an incorrect assumption of a global counter for order fills (it is actually per-symbol)
- Filtered out rate limit messages in the fill monitor task
* Remove and replace OnEndOfDay() ref
* Restore functionality of obsolete EOD, waiting for deprecation in August 2021
* Cleanup
* Adjustments to only post message when using obsolete EOD
* nit, extra space
* Address review
* Adjust test to reflect new behaviour
* Move GetPythonArgCount to an extension method
* Add unit test
* nit accidental import
* Refactor broken test
* Use Py.GIL() state for extension
* Set _lastEmit before emitting, otherwise _workingBar is always null
* Aggregate bars if the data endTime is past lastEmit
* Add unit test
* Address Review
* Clean up unit tests
* Refactor solution to set consistent _lastEmit behaviour
* Add another unit test
* Make fixture non-parallelizable
* Undo last change, and adjust breaking test directly
Jasper van Merle