* 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
Python Virtual Environments / build (push) Has been cancelled
API Tests / build (push) Has been cancelled
Benchmarks / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Report Generator Tests / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
* fix: download year file data only for hour and daily resolutions for options and index options
* minor fix: index options regression tests expected status
* Minor change
* minor: update regression algorithms stats
* Async universe selection
- Add support for async universe selection, which will happen ahead of
time in the data stack for a performance improvement
* Thrown if using Coarse+Fine Asynchronous Universe selectioon
Regression Tests / build (push) Has been cancelled
Python Virtual Environments / build (push) Has been cancelled
Benchmarks / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
* Apply splits and dividends to volatility models
* Apply splits and dividends to volatility models using history requests
* Add new ScaleRaw data normalization mode
Handling the new mode in the price scale enumerator.
* DataNormalizationMode.ScaledRaw history requests
* Minor changes
* Minor changes
* Disable new normalization mode in AddSecurity methods and other minor changes
* Peer review
* Minor changes
* Peer review
* Minor changes
* Peer review
* Peer review
* Peer review
* Add scaled raw history regression algorithm
* Add more regression algorithms
* Add more regression algorithms
* Add Slice.TryGet unit tests
* Peer review
* Peer review
* Peer review
* Peer review
* Peer review
* Update algorithms stats
* Peer review
* Peer review
Regression Tests / build (push) Has been cancelled
Python Virtual Environments / build (push) Has been cancelled
Benchmarks / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
* Refactor alpha statistics
- Refactor alpha statistics, cleaning up and simplifying no longer required calculations and scoring
- Adding new InsightEvaluator abstraction, adding C# & PY regression
algorithms
* Optimization backtest result json converter update
* Address reviews
- Remove IAlphaHandler, move insight storage responsability to IResultHandler
and centralizing insight collection on the QCAlgorithm.Insights to be
reused by the framework models
- Fix portfolio turnover single day backtests and duplicate time
sampling handling. Updating regression algorithms
* Add InsightCollection tests and minor fixes
* Adding more & improved tests
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
Python Virtual Environments / build (push) Has been cancelled
* Fix index option data timezone
- Fix index option data timezone which was 1 hour late than expected
* Update existing index option tests
- Update existing index option tests.
- Disable index option daily resolution support
Regression Tests / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Added checking if algorithm is stopped in initialize method
* Quit on initialize adjusment
- Minor adjustments to solution. Adding more regression algorithms
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
* 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
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
* Use GC server mode for tests
* Fix daily auxiliary data points emission time
- Due to fillforwarding, in some cases with daily resolution symbol
change events (generically any auxiliary data) would arrive late.
Updating regression test to reproduce the issue. Adding unit test
- Some refactoring and logging improvements
* Address reviews
* Remove old xml docs param
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Python research import improvements
- Improve start.py for research env
- Remove unrequired imports
* Centralize algorithm imports
* Add regression test GH action
* Unit test python import clean up
* Join research and main imports
* More python import clean up
* Fix failing skipped regression algorithm
Build & Test Lean / build (push) Has been cancelled
* Use lean data key as param for request
* key -> filePath rename and some cleanup
* Refactor
* Add Organizations Endpoints
* Add some organization api wrapper objects
* Address namespace issue
* Reorganize Api Test into seperate files using one ApiTestBase
* Add Organization tests
* Use capitalized "API" test namespace to reduce amount of file changes
* Add License to test base
* Update /data endpoint functions and response objects
* Update ApiDataProvider Logic
* Handle deserialization of organization products
* Simplify converter
* Only throw for equity requests when not subscribed to map/factor files
* Add missing header
* Make arguement exception
* Api adjustments
* Add Zip factor and map file providers
- Common project will now reference Compression project and not the other way
round.
- Adding Zip FactorFile and MapFile providers
* Refactor FactorFileProvider to use DataProvider to fetch files
* Use resulting MinimumDate in construction of FactorFile
* Nit FactorFile comments and arrangement
* Refactor MapFileProviders to use DataProvider for fetching files
* Refactor ZipFileProvider
* Clean up
* Refactor Backtesting Future/Option chain providers to use dataprovider
* Fixes for data/ endpoints and test adjustments
* Response objects adjustments/cleanups
* ApiDateProvider fixes and testing
* Add LocalZipFactorFileTests
* Update ApiDataProvider download test to verify stream is not null
* Implement posting of agreement summary and signed time
* Mark all Api related tests as explicit and document details on running
* Clarify default token on ApiTestBase
* Adjust summary
* Update Api responses for QCC, except org products which are sold in USD
* Implement cache expiration for zip MapFile and FactorFiles. Adding unit tests
* Fix multiple markets for ZipFactorFile provider
* Use Symbol as cache key
* Api.cs review
* Dispose of factorFileStream after reading
* Use zip.EntryFileNames
* Address a few reviews
* Few more fixes
* Address Api Review
* Add Job Org id to config
* Minor tweaks
* Compare with invariant culture
* Fixes Option Universe selection
* ZipEntryNameSubscriptionDataSourceReader will use IDataProvider
* Fix research
* Fix null reference exception
* Make duplicate log debug
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
* 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>
* 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>
* Changed variable names of protected members in BaseResultHandler to
match existing variable naming convention
* Changed AlgorithmRunner return type
* Remove AlgorithmResults dictionary from AlgorithmRunner
* Create AlgorithmRunnerResults container class
* Modify Relative Sampling test to accept failure cases
* Misc. updates as a result of changing AlgorithmRunner return type
In order to continue to provide debugging support in the QC cloud, the
scheduled events were moved from inside of a task to the algorithm's
main execution thread. This necesitated a different methodology for
managing timeouts. Instead of raising an exception when attempting to
request additional time when none is remaining, we're now simply allowing
the isolator's limit to be reached by virtue of not incrementing the
additional minutes in the time manager. This uncovered a bug in LEAN
engine where if the isolator terminates an algorithm, then the status
of the algorithm (on the algorithm manager instance) isn't properly
updated to indicate RuntimeError. This is in direct conflict with the
status update that is provided to the api, which is RuntimeError, so
this change remedies that issue as well. One of the regression algorithms
depends on this status value being properly flipped to RuntimeError in
the event that the isolator limit is reached.
See #3319
We restrict each algorithm time loop to a pre-determined amount of time.
Exceeding this limit will cause the algorithm to immediately terminate.
This quickly becomes an issue when considering users running trainable
models that have a long initialization period that exceeds the time loop
maximum.
This change provides a mechanism through which a long-running scheduled
event is permitted to keep running and is permitted to avoid the time loop
permitted by requesting additional time. Requests for additional time are
limited according to a leaky bucket implementation whose parameters are
set via the job's controls structure. The fundamental time unit for the
algorithm is a single minute.
Here's how it works. If a scheduled event takes longer than one full wall
clock second then a request is made to the leaky bucket for one more minute.
If the scheduled event continues to take more time, it will continue to
request additional minutes. Each requested minute will prevent the algorithm's
time loop check from terminating the algorithm. When the bucket is empty and
no more minutes are available to be requested, a TimeoutException is thrown
causing a cascade that ends in the algorithm's termination and status being
flipped to RuntimeError.
Additionally, this applies equally to ALL scheduled events. While some helpers
were added with the naming of Train and TrainNow to the ScheduleManager, these
methods don't do anything special and the infrastructure doesn't otherwise
flag them as different, so this feature becomes part of the core Scheduled
Event feature set.
Further, the live scheduled events were not touched and are still pending
further discussion regarding the value added by enforcing a time restriction
when simulation time and wall clock time are equivalent.
Fixes#3319
- Disabling C# and Py `BasicTemplateIntrinioEconomicData` regression
test. Free user credentials are invalid because Intrinio has now a 30 day trial for free users
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.
This change allows the universe selection model to select different universe
definitions as time proceeds. This enables the definition of a universe model
that, for example, could add option chains for securities selected by a different
universe model.
The BasicTemplateOptionsFrameworkAlgorithm was added to showcase and provide
regression for a universe model that selects different universes.
Adds the concept of universe disposal which is requested by an algorithm
through invocation of UniverseManager.Remove, which is invoked via
algorithm.RemoveSecurity. This instructs the data feed that the algorithm
has requested to completely remove the universe and any child subscriptions
from the feed. Security changes are fired for all removed securities.
Provides demonstration algorithm showing the steps required to convert a
QCAlgorithm into the framework with minimal code changes.
1. Subclass QCAlgorithmFrameworkBridge
2. Add EmitInsights calls to where orders are placed
3. Profit :)
`EqualEeightingPortfolioConstructionModel` (C# and Python) allocates all cash to the stocks who have insights in universe.
- Fixes regression tests to reflect the model logic change
- Fixes imports in python algorithms to use python models when available
Since we start Monday and end on a Friday we aren't properly covering the
edge cases. As it currently stands, if we start on a date then we receive
data for that date, so a daily algo starting on the 8th receives it's first
data point on the 9th at 00:00 (daily bar is 8th 00:00 to 9th 00:00). Like
wise, the requested end date is the 17th and we include data from the 17th,
so the last data point is the 18th at 00:00 (daily bar is 17th 00:00 to 18th
00:00).
Subscribe to daily data instead of minute-resolution to be able to run tests locally. Also, liquidate the position in one of the event handlers to generate more trades.
- Adds regression test for that algorithm.
Martin-Molinero