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* Add indicator for allowed option styles to QL option price models
* Add and update option price model tests
* Update option price models methods sumary to indicate allowed option styles
* Add regression algorithms for option price models for different option styles
* Update OptionPriceModel regression algorithms to use Lean local data
* Add Python regression algorithms for option price models for different option styles
* Update OptionPriceModel regression algorithms to assert that greeks are valid
* Address changes request
* Address changes request
* Update OptionPriceModel regression algorithms to check both call and put contracts
* Update OptionPriceModel regression algorithms to use correct test data
* Update OptionPriceModel regression algorithms to throw in OnData
* Address changes request
* Update OptionPriceModel regression algorithms to assert greeks are not all zero
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Since there is `UpdateStopPrice`, `UpdateLimitPrice`, `UpdateQuantity` and `UpdateTag` method to make it easier to update the `OrderTicket`, we include `UpdateTriggerPrice` to cover the `LimitIfTouched` case.
Also, updated the docs or the arguments for these methods.
Updates LimitIfTouchedRegressionAlgorithm:
- Adds `UpdateTriggerPrice` call that rounds down the `TriggerPrice`.
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* Add missing stablecoins
* Fix bugs
* Remove MIMUSD stablecoin pair
That pair is already in the SPDB
* Add more stablecoins pairs
- Add SUSD and IDRT
* Fix bug
* Requested changes
The algorithm posted in the GH was failing because when finding a conversion between currencies BTC to USD, it wasn't taking into account BTCUSDT and that USD = USDT because is a stablecoin
* Solve bugs
* Nit changes and more tests
* Requested changes
* Nit changes
* Requested changes
* Nit change
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* 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>
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* Add requested History overload
* Add more regression tests
* Revert "Add more regression tests"
This reverts commit 71b279e917629c3d5ed577e39aec74149b052afb.
* Add more regression tests
* 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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`WarmUpIndicator` for Python indicators doesn't return the indicator anymore after #6027. So all overloads should return `void`.
Fixes `SmaCrossUniverseSelectionAlgorithm` [C# and Py].
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`CashBuyingPowerModel`, which reflected on `AlphaStreamBrokerageModel`, a margin-only brokerage.
It also didn't consider the account type, so `InteractiveBrokersBrokerageModel` was using the margin model even if `AccountType.Cash` was selected.
Removes `GetBuyingPowerModel` method from other Brokerage Models when their cases are covered by `DefaultBrokerageModel`
Fixes some typoes in `TradierBrokerageModel`
Fixes unit and regression tests. For the regression tests, we have explicitly set the brokerage model.
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* Adding unit tests reproducing issue.
* Fix a couple of minor bugs
- IsMarketOpen will work correctly when used with daily and hourly
resolution.
- slice.Get will work correctly with python custom data
- ExtendedDictionary will be able to dinamically access methods,
required for python and private C# data types
* Refactor solution. Add more tests
* Remove unrequired import statement
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* 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
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* Refactor `GetFilePath()`
Add also useful methods to use with this one
* Nit changes
* Requested changes
* Requested changes
* Restore SaveString()
* Nit changes
* Address self review
* Test improvements
* Adjust example KerasNeuralNetworkAlgorithm
* Minor tweak for KerasNeuralNetworkAlgorithm.py
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
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- GetLastKnownPrices will no longer guess which resolution to use but
rely on other methods implementation/
- Updating basic template future algorithms to warmup contracts and
assert it
- Minor improvements for FunSecurityInitializer and FuncSecuritySeeder
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* add data
(cherry picked from commit 814011d89e5316d150f88ffca5f48d8d5f0ea7d9)
* update market hours for index
(cherry picked from commit edac40732c120eb84d27de00594b59eebb4983f5)
* add index algorithms
(cherry picked from commit b22d27b4fa98172c435f7c26de4a3a297c49a6b7)
* update statistics
* add cash
* Add india market
* add leverage for index
* can subscribe to index
* update format
* fix wrong cash
* fix ticker names
* update data
* update ticker and stats
* update docs
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* Add india market data
* use local data for algo
* Add India market regression algo
* update india market data
* Update readme
* add python algo for BasicTemplateIndiaAlgorithm
* Add India data regression python algo
* data india data files
* update tickers
* Fix algo template
* remove data
* fix stats
* update stats
* remove unused data
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* Continuous Futures Refactor. Live Mappings
- Adding support for live mappings. LiveTradingDataFeed will handle any
symbol mapping at the configuration layer and resubscribe through the
IDQH
- Refactoring continuous futures adding ContinuousFutureUniverse that
will select the currently mapped security
* Minor fixes
- Remove addition of configurations in UniverseSelection step, leave
resposability for universe.
- LiveTradingDF future unit test will only assert slice data for non
internal feeds.
- ContinuousContractUniverse will respect internal option interest
subscription
* Address review
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* Fixes for FutureOptions support in LeanData
* Add CreateCanonicalOption() utility function for Symbol.cs
* Add aggregated Futures/FuturesOptions data to Lean
* Add FutureOptions regressions for daily/hourly data
* Allow Futures to be added with low resolution
* Add Future regressions using hour/daily data
* Nit - Python Class names
* Add reviews
* Add alias into CreateCanonicalOption
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* Move processing of delistings to Brokerage
* Deal with case that exchange is not open on OptionSymbol.ID.Date
* Refactor solution to use DelistingNotification event
* Adjust some regression expected liquidation time
* Mark some todos on deprecated functions
* Update expected liqudation time for Py regressions
* Update regressions that have been validated
* Use HandlePositionAssigned for assignment orders
* Update regressions
* Update some missed unit tests; remove one that is already covered by regression
* Cleanup deprecated backend functions
* nit - small cleanup adjustment
* Post rebase fix
* Address review
* Minor tweak to py regression
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* Create generic writing for LeanDataWriter, + notes on todos
* Make Options Daily/Hourly data store by year
* Refactor Generic Write
* Permit hour and daily resolutions for options
* Refactor writer to merge when needed with other files
* Cleanup redundancies, run write tasks in parallel
* Make needed classes/vars available
* Update tests to reflect new naming convention for daily hourly options data
* Add Byte[] overloads for ZipData functions in compression
* Implemented Store() for ZipDataCacheProvider
* Have LeanDataWriter use a DataCacheProvider
* ZipDataCacheProvider cleanup
* ZipDataCacheProvider tweaks, doesn't support storing non-zips
* Test adjustments
* Update LeanDataWriter to use Write instead of SaveDailyHourly/SaveMinuteSecond
* Implement tests to verify DownloadAndSave behavior
* Nit cleanup on DownloadAndSave tests
* Fix for options daily/hourly underlying equity subscription read
* Add daily/hourly options data and regressions
* Add missing open interest for hourly
* Fix writing of OpenInterest Daily/Hourly data
* Update data
* Fix Date typo in regression
* Use daily algorithm to test delisting
* Revisions part 1
* Expand test for DataCacheProviders; refactor DiskDataCacheProvider
* nit - test adjustments
* ZipDataCacheProvider test setup refactor
* Adjust multithreaded read/write test; fixes for ZipDataCacheProvider
* Move DiskDataCacheProvider to its own file and add write test
* Remove _appendToZips; always overwrite entry or create zip
* Add mapping regression for daily options
* nit - add license to regression
* Fix Tick write case where more than one data point for a DateTime
* Fix data issue
* Address review
* Tweaks for tests
* Stop Store() early if no entry name is given
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* Implement IIndicatorWarmUpPeriodProvider
- Implement IIndicatorWarmUpPeriodProvider in PythonIndicator.cs
- Make a unit test to check whether the WarmUpPeriod is working as expected
- Make a regression test to check the new feature at a system level
* Nit change
* Change Period parameter for WarmUpPeriod parameter
- Change regression test to check if the new parameter keep backwards compatibility with indicators that do not set WarmUpPeriod
* Documentation change
* Fix tests bugs
- In CommonIndicatorTests.cs before finish the test it checks the period.value with the number of samples but for default the period.value was set to -1
* Change names
* Change WarmUp and RegisterIndicator methods
- Lean WarmUp indicator skip custom python indicators that don't define WarmUpPeriod parameter
* Call WarmUpIndicator manually
- Add a new "bridge" method called WarmUpIndicator in QCAlgorithm.Python.cs to set up everything to call WarmUpIndicator in QCAlgorithm.Indicators.cs
- Change the regression algorithm to warm up the indicators manually
* Remove unnecessary code and add more tests
* Nit change
* Revert "Nit change"
This reverts commit da411f59c9e4295d75a11c6c581f615a938dd2c6.
* Fix bugs
* Try fix bugs
* Add C# regression test
- More nit changes
- Fix bugs
* Requested changes
* Remove unnecessary code
* Requested changes
* Nit changes
- Add new Python class to check a custom indicator, which doesn't inherits from PythonIndicator, warms up properly
* Reduce redundant code
* Fix bug and add more unit and regression tests
* - Add more unit tests
* Nit change
* Test cleanup
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
* Implement IIndicatorWarmUpPeriodProvider
- Implement IIndicatorWarmUpPeriodProvider in PythonIndicator.cs
- Make a unit test to check whether the WarmUpPeriod is working as expected
- Make a regression test to check the new feature at a system level
* Nit change
* Change Period parameter for WarmUpPeriod parameter
- Change regression test to check if the new parameter keep backwards compatibility with indicators that do not set WarmUpPeriod
* Documentation change
* Fix tests bugs
- In CommonIndicatorTests.cs before finish the test it checks the period.value with the number of samples but for default the period.value was set to -1
* Change names
* Change WarmUp and RegisterIndicator methods
- Lean WarmUp indicator skip custom python indicators that don't define WarmUpPeriod parameter
* Call WarmUpIndicator manually
- Add a new "bridge" method called WarmUpIndicator in QCAlgorithm.Python.cs to set up everything to call WarmUpIndicator in QCAlgorithm.Indicators.cs
- Change the regression algorithm to warm up the indicators manually
* Remove unnecessary code and add more tests
* Nit change
* Revert "Nit change"
This reverts commit da411f59c9e4295d75a11c6c581f615a938dd2c6.
* Fix bugs
* Try fix bugs
* Add C# regression test
- More nit changes
- Fix bugs
* Requested changes
* Remove unnecessary code
* Requested changes
* Nit changes
- Add new Python class to check a custom indicator, which doesn't inherits from PythonIndicator, warms up properly
* Reduce redundant code
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* 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
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* Rename Renko to ClassicRenko
* Rename WickedRenko to Renko
* Adjust tests and usages
* Backwards support WickedRenkoConsolidator
* Renames for consistency
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- After https://github.com/QuantConnect/Lean/pull/5872 trading API
changes numpy float64 was not converted correctly by pythonNet and
used an int. Reverting API changes and adding regression test. This
should be fixed at pythonNet layer
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* Adds ETF(...) to UniverseDefinitions
* Adds ETF constituents universe framework regression algorithm
for C#/Python
* Address review: adds test cases for ticker/Symbol ETF universe additions
* Fixes bug where null Market would result in null dereference exception
* Address review: add missing Index tests
* Address review: don't hardcode market when creating constituent universe
* Uses Brokerage Model's default markets collection to determine
the market for the given security type
* Address review: restore QC500 and DollarVolume.Top(...)
* Restores algorithms related to both helper universe
definition methods
* Address review: remove copy to output directory for python algos
* Add example algorithms for ETF constituent universes using custom RSI alpha model
* Address review: adjust algorithm to use cache + algo RSI & clean up code
* Address review: make ETF Constituent RSI Alpha Model algo a regression test
* Address review: increase trade count and remove single trade logic
Martin-Molinero