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Author SHA1 Message Date
JosueNina
8123e76e3c Validate inputs for safe logarithm calculation (#8439)
- Ensure both previousPoint and previousPoint2 are non-zero.
- Prevent division by zero and undefined errors.
- Add unit test to verity the new validation logic.
2024-12-03 17:30:07 -03:00
Jhonathan Abreu
a28d1f2ffe Universe data frames improvements (#8433)
* Default Data to null for ETFConstituentUniverses.

The data collection will be assigned only if needed. This allows data column to be filtered from dataframes since it will always be null for all constituents.

* Make base data collection aggregator reader fall back to BaseDataCollection

After instatiating the collection type, fall back to the base BaseDataCollection to aggregate data if the type is not a base data collection.

* Minor change

* Minor change

* Update pythonnet to 2.0.41

* Ignore data column for every flattened universe dataframe

* Filter empty collections columns in data frames

* Allow snake case named attributes in PythonSlice

* Remove PythonSlice Data Python class

Pythonnet handles dynamic objects behavior
2024-12-03 16:19:17 -04:00
Ricardo Andrés Marino Rojas
f4314549c3 Fix warming up bug QCAlgorithm.WarmUpIndicator() (#8431)
* First draft of the solution

* Add regression tests

* Nit changes

* Solve root issue

* Improve regression tests

* Reduce duplication

* Nit change

* Improve implementation

* Address suggestions

* Address requested improvements

* Nit change

* Nit changes

* Nit change
2024-11-29 16:35:37 -03:00
Jhonathan Abreu
d416580456 Adjust lower-resolution fill-forwarded strict end-timed daily bars (#8412)
* Adjust lower-resolution fill-forwarded daily bars when strict end times is enabled

This allows to get fill-forwarded bars with unchanged time stamps

* Minor fixes

* Minor test data changes

* Fixes and comments

* Address peer review and add some fixes

* Minor fix and add regression algorithm

* Minor fix
2024-11-29 09:52:01 -04:00
Jhonathan Abreu
93ce62536f Revert "Fix warming up bug in Stochastic indicator (#8422)" (#8430)
This reverts commit 312392d6ae.
2024-11-29 09:50:30 -04:00
Ricardo Andrés Marino Rojas
312392d6ae Fix warming up bug in Stochastic indicator (#8422)
* First draft of the solution

* Add regression tests

* Nit changes

* Solve root issue

* Improve regression tests

* Reduce duplication

* Nit change

* Improve implementation
2024-11-29 09:49:06 -04:00
JosueNina
01734e1f61 Implement Mesa Adaptive Moving Average (MAMA) Indicator (#8428)
* Initial implementation of MAMA indicator and tests

* Implemented Mesa Adaptive Moving Average (MAMA) indicator

- Implemented the MAMA indicator.
- Created methods with overloads to support custom and default
  fastLimit/slowLimit
- Included necessary logic to calculate the mesa adaptive moving average
  based on John's formula.
- Created unit tests to validate MAMA's behaviour.

* Refactor Mesa Adaptive Moving Average(MAMA)

- Separated the logic into smaller functions for better maintainability.
- Improved variable names to reflec their purpose.
- Updated comments to reflect changes and improve readability.
- Consolidated MAMA method overlaod by using default parameters values.

* Refactor variables and update method parameters

- Renamed variables for better clarity.
- Updated method to use 'IBaseDataBar' instead of 'TradeBar'
- Used 'MAMA({fastLimit}, {slowLimit}) instead of just 'MAMA'
2024-11-27 18:54:59 -03:00
Ricardo Andrés Marino Rojas
124063a2a4 Change Log.Trace() to Log.Debug() (#8429) 2024-11-27 18:27:54 -03:00
Ricardo Andrés Marino Rojas
b99da54d5a Implement Reset() method (#8410)
* First draft of the feature

* Add XML docs

* Fix and improve unit test

* Address suggestions

* Improve unit test

* Improve implementation
2024-11-27 16:53:02 -03:00
Jhonathan Abreu
bc5d51806d Universe data frames normalization (#8385)
* Normalize universe data frames

Universe and (generically BaseDataCollection) data frames are not normalize and unpacked into a data frame, instead of just creating data frames with the universe lists within it

* Fix unit tests and algorithms to expecte new universe dataframe format

* Fixes

* Add PandasConverter.DataFrameGenerator class

* Pandas data frame generator class fixes

* Add comments

* Housekeeping

* Add attributes to mark classes and properties for pandas processing

* Improve pandas properties expanding

Allow and handle duplicate names

* Use PandasData generalization for Lean common data types

* Add points time as column when converting base data collections to data frames

* Cleanup and minor changes

* Minor change

* Pandas data to get type members on demand

* Move Pandas helper classes to their own files

* Minor changes

* Add flatten argument to python history api

This allows users to decide whether they want fully expanded dataframes for universe and other collection data types. Else, master behavior is kept

* Adding missing changes to last commit

* Update Pythonnet version to 2.0.40

* Add flattent argument to algorithm's OptionChain api

* Minor changes

* Housekeeping

* Minor changes

* Bug fix skipping data collection data points

* Add comment

* Set correct exchange time to OptionUniverse instances

* Address peer review and cleanup

* Cleanup

* Minor changes
2024-11-26 16:16:34 -04:00
JosueNina
f3ed5b1206 Fix correlation type (#8426)
- Addressed bug causing mismatch between types of correlations.
- Updated C method to include CorrelationType.
- Created regression test to ensure proper validation.
2024-11-26 14:05:49 -03:00
Ricardo Andrés Marino Rojas
eb6c5d20f5 Fix typos (#8349)
* Fix typos

* Fix bugs

* second try to fix bugs

* Fix typos

* Nit change

* Update enums too

* Fix bugs
2024-11-26 11:36:14 -03:00
Ricardo Andrés Marino Rojas
b70b5bd5fe Add extended market hours option in DateRules.WeekStart() (#8400)
* First potential solution

* Add unit tests

* Address requested changes

* Add unit test reproducing user bug

* Missing update

* Address reviews

* Improve unit test

* Improve unit test

* Nit change

* Nit changes

* Nit changes
2024-11-25 18:09:44 -03:00
Ricardo Andrés Marino Rojas
5ac7d00e24 Normalize Date timezone (#8420)
* First draft of the solution

* Add unit test

* Nit change
2024-11-25 17:44:22 -03:00
JosueNina
469d960f50 Implement Connor's Relative Strength Index(CRSI) Indicator (#8419)
* Add Connors Relative Strength Index(CRSI) Indicator

- Implemented CRSI combining RSI, Streak RSI, and ROC
- Added unit tests for CRSI calculation to ensure correctness and
  reliability.
- Inclued the spy_crsi.csv file for testing purposes and validation of
  CRSI logic.

* Refactor CRSI indicator

- Updated the CRSI logic to use Percent Change of Daily Returns instead
  of ROC.
- Modified the ConnorsRelativeStrengthIndex class:
  - Updated ComputeNextValue to calculate daily returns and relative
    magnitude
- Improved documentation and comments

* Refactor CRSI Indicator:

- Refactored the method that updated the trend streak based on price
  changes.
- Created a new method ComputeTrendStreak.
- Added check for null or 0 value in _previousInput.

* Fix comments from code review

- Add _ to priceChangeRatios
- Move _srsi.Update() to the top to avoid duplication
2024-11-25 15:43:42 -03:00
Jhonathan Abreu
7eea365aa1 Let delistings through for internal subscriptions (#8398)
* Let delistings through for internal subscriptions

Without it, previously mapped continuous future contracts for which a position is open never received a delisting event for them to be liquidated and marked as non-tradable

* Update regression algorithm stats

* Revert/remove transaction handler initialization parameters DTO class

* Cleanup
2024-11-25 11:41:02 -03:00
Jhonathan Abreu
760071a2f7 Fix 0DTE index options selection (#8418)
* Revert parts of GH PR 8395 to fix 0DTE index options

* Add regression algorithms

* Cleanup

* Cleanup
2024-11-20 09:18:11 -04:00
Jhonathan Abreu
fa1ef4f763 Index option chain backwards compatibility (#8395)
* Fix option universe

Set right time using exchange time zone when reading.
Remove OptionUniverse market hours hack in GetEntry extension method.

* Minor change
2024-11-15 17:30:44 -04:00
Roman Yavnikov
f7b012aa11 Feature: Implementation Charles Schwab Brokerage (#8406)
* feat: ExtendedRegularTradingHours property in CharlesSchwabOrderProperties

* feat: BrokerageModel, FeeModel of Charles Schwab

* refactor: CharlesSchwab Fee model
remove: SecurityType.Index in CanSubmit CharlesSchwab

* refactor: CharlesSchwabFeeModel (a little bit simpler)

* refactor: CharlesSchwabFeeModel (more simpler)
2024-11-15 18:17:20 -03:00
JosueNina
725ad73240 Implement Average Range (AR) Indicator (#8404)
* Add Average Daily Range indicator and tests

- Implemented AverageDailyRange indicator
- The indicator uses a Simple Moving Average (SMA)
- Created unit tests for the indicator
- Includes example input data and test file (spy_adr.csv)

* Refactor AverageDailyRange Indicator

- Renamed AverageDailyRange to AverageRage for a more generic approach
- Replaced explicit types with 'var'
- Updated method name in test cases
- Placed AR method in the correct alphabetical order

* Solving minor issues with AR indicator

- Replace TradeBar with IBaseDataBar
- Remove unnecessary override methods
2024-11-15 11:19:55 -03:00
JosueNina
7bbf42f79b Implement Premier Stochastic Oscillator (PSO) Indicator (#8394)
* Implement Premier Stochastic Oscillator (PSO)

- Added PremierStochasticOscillator class with two Exponential Moving
  Averages (_ema1 and _ema2) for double smoothing.
- Implemented PSO computation:
  - Normalized Stochastic (nsk) = 0.1 * (Fast%K - 50)
  - Double-smoothed Normalized Stochastic
- Added XML documentation for public methods and key calculations.

This commit introduces a new indicator.

* Add license header and adjust spacing

* Refactor Premier Stochastic Oscillator (PSO)

- Renamed smoothing variables for clarity
- Integrated PSO logic directly in ComputeNextValue
- Used IndicatorExtensions for streamlined EMA chaining
- Updated tests to match refactored logic

* Refactor PSO

- Changed "STO" to "PSO"
- Removed unused imports
- Updated private fields
- Minor code cleanup
2024-11-14 18:22:46 -03:00
Ricardo Andrés Marino Rojas
f2da037d42 Solve divide by zero exception in McGinleyDynamic indicator (#8397)
* Add SafeDivision() method

* Add assertions

* Nit changes

* Nit change
2024-11-14 18:20:18 -03:00
Ricardo Andrés Marino Rojas
5c5c527252 Use SafeDivision() method to avoid overflow exception in CCI (#8396)
* Use SafeDivision() method to avoid overflow exception

* Nit change
2024-11-14 18:20:00 -03:00
Martin-Molinero
71d09a3567 Private cloud minor improvements (#8409)
* Private cloud tweaks

* Minor tweaks for optimization
2024-11-14 17:22:33 -03:00
JosueNina
085476a222 job_queue: fix typos in comments (#8390)
Corrected minor typos in comments within the JobQueue class to improve
readability

- Verify all comments for further errors
2024-11-01 19:13:49 -03:00
Alexandre Catarino
c78774b99a Adds Country Static Class (#8389)
This class contains all countries and mapping them to their ISO 3166-1 alpha-3 codes.
2024-11-01 19:13:07 -03:00
Ricardo Andrés Marino Rojas
d5b2e4d8cc Make Target.MoveAhead() case insensitive (#8382)
* First draft of the solution

* Try a different approach

* Nit change

* Add unit tests

* Add edge cases

* Address requests
2024-10-24 09:29:16 -03:00
Ricardo Andrés Marino Rojas
828d9238b8 Remove duplicated keys in OpenInterestFutureUniverseSelectionModel (#8365)
* First draft of the solution

* Enhance implementation
2024-10-21 09:43:06 -03:00
Jhonathan Abreu
f2100adb46 Fix price shifts around futures rollover date (#8371)
* Test

* Fix price shift on continuous future rollover

* Keep track of both data and exchange time in subscription data reader

* Fix for daily and hourly resolutions.

Add daily and hour algorithms

* Fixes for emitting new exchange dates at the beginning and end when data is not available

* Cleanup

* Minor fix

* Minor fix: detect mapping in data reader after advancing time keeper

* Minor fix

* More fixes

* More fixes

* Fixes for universe files

* More fixes for daily resolution data

* Separate DateChangeTimeKeeper to its own file

* Add DateChangeTimeKeeper unit tests

* Minor fix

* Add more DateChangeTimeKeeper unit tests

* Address peer review

* Address peer review

* Address peer review

* Detect mappings using the config NewSymbol event

* DateChangeTimeKeeper performance improvement for time zone conversions

* Clean up date change time keeper

* Cleanup

* Minor regression algo update

* Cleanup

* Cleanup

* Fix perform universe selection on sundays for continuous futures with extended market hours

* Cleanup

* Address peer review

* More cleanup

* More cleanup
2024-10-21 09:38:00 -03:00
Jhonathan Abreu
159fa5a182 Fix Python Consolidate API to respect strict daily times for Daily resolution (#8373)
* Fix ConsolidateRegressionAlgorithm

- Fix Bitcoin custom data time range. Historical data goes from April 2014
- Fix expected consolidated bar counts
- Fix python Consolidate implementations to respect daily strict times for Daily resolution

* Housekeeping
2024-10-16 17:35:10 -03:00
Ricardo Andrés Marino Rojas
8ef0a4977b Fix bug in QuantBook.UniverseHistory() when using Monthly date rule (#8368)
* Fix bug in Universe history with montly selection

* Reduce duplication

* Fix missing overload method

* Address requests

* Nit change

* Improve implementation

* Improve implementation

* Fix bug and add more unit tests

* Nit change

* Address requested changes

* Address requested changes

* Nit change
2024-10-16 17:34:26 -03:00
Martin-Molinero
ffdb615a4d Add research node packet (#8360) 2024-10-15 13:38:39 -03:00
Martin-Molinero
8f57a8c8ff Update readme.md 2024-10-14 18:56:42 -03:00
Roman Yavnikov
a831adc9c8 Fix: Broken Regression Algorithms (#8366)
* fix: CustomData/RegisterIndicator-RegressionAlgorithm

* fix: CustomDataPropertiesRegressionAlgorithm

* fix: CustomDataRegressionAlgorithm py

* fix: CustomDataPropertiesRegressionAlgorithm py

* fix: RegisterIndicatorRegressionAlgorithm py

* refactror: use nasdaq instead of quandl in proxy url
2024-10-10 11:36:18 -03:00
Roman Yavnikov
6b22254924 Feature: new sorting property in SubscriptionDataSource and SortEnumerator (#8352)
* feat: sort property in SubscriptionDataSource

* refactor: read lines (with sort opportunity) in TextSubscriptionDataSourceReader

* refactor: xml description of Sort property in SubscriptionDataSource

* revet: TextSubscriptionDataSourceReader changes

* feat: develop UnsortedTextSubscriptionDataSourceReader

* remove: UnsortedTextSubscriptionDataSourceReader

* feat: develop SortEnumerator
feat: use SortEnumerator in SubscriptionDataReader

* revert: TextSubscriptionDataSourceReader changes

* feat: use sort Enumerator in LiveCustomDataSubscriptionEnumeratorFactory

* test:feat: Unsorted Live Data Feed with using Object Store

* test:feat: history CustomData request with unsorted data

* refactor: develop TryWrapper on SortEnumerator

* remove: extra spacing

* refactor: Sort in SubscriptionDataSource

* feat: add RegressionAlgorithms when source return data in Descending format

* refactor: xml description of prop Sort in  SubscriptionDataSource

* refactor: SortEnumerator

* test:refactor access modifier in ExampleCustomDataWithSort

* test:refactor: increase performance LiveDataFeedSourcesDataFromObjectStore

* feat: add xml comment of regression algorithm

* test:revert: access modifier to public in internal test class

* test:refactor: use while instead of timer

* Revert "test:refactor: use while instead of timer"

This reverts commit 4fe43da809.
2024-10-07 18:16:33 -03:00
Ricardo Andrés Marino Rojas
0e61415ce2 Fix bug ImmediateExecutionModel when using Crypto (#8355)
* First draft of the solution

* Add missing algorithm

* Improve regression tests

* Nit change

* Address requests

* Nit change

* Address minor requests

* Nit changes

* Nit suggestion
2024-10-07 16:46:37 -03:00
Martin-Molinero
16c893deb6 Fix history manager configuration assertion (#8361) 2024-10-07 10:40:28 -03:00
Ricardo Andrés Marino Rojas
33048149af Add custom ToString() method in API classes (#8357)
* Potential solution

* Improve solution

* Nit change

* Nit change
2024-10-07 10:37:11 -03:00
Martin-Molinero
0a2c05ab1e Improve performance of OptionChain (#8359)
- Improve performance of OptionChain by creating a single pandas df
2024-10-04 20:03:53 -03:00
Martin-Molinero
e16b27f089 Update readme.md 2024-10-04 13:33:59 -03:00
Jhonathan Abreu
0a9dc2c71c QCAlgorithm's OptionChain() api refactor (#8334)
* Fix pandas converter to handle list of data with different symbols

* Properly convert list of data into dataframe

Take into consideration data for multiple symbols in the same list

* Cleanup

* Index dataframes by symbol object instead of SID string

* Add symbol equality operator to compare against object

* Exclude "ID" from option chain dataframe

* Minor fix

* Add greeks columns directly in option chain dataframe.

Also add pass-through properties for greek values in OptionUniverse

* Some cleanup

* Minor fix

* Add new QCAlgorithm.OptionChains() method

- Use OptionChains as output
- Add DataFrame to OptionChain and OptionChains
- Rename Greeks classes
- Add ISymbolProvider for classes that have a symbol (IBaseData, OptionContract)

* Unify QCAlgorithmOptionChain API

Also refactor OptionContract to handle: (1) Actual market data and option price model data, and (2) OptionUniverse data

* Pass symbol properties to OptionUniverse option chain from algorithm

* Format OptionContract for dataframe

* Minor fix

* Add multiple option chains api regression algorithms and other minor changes

* Address peer review

Add NullGreeks class: keep ModeledGreeks as internal as possible

* Minor fix and add PandasConverter unit tests

* Peer review: Non-thread-safe Lazy for Python

* Handle Greeks unwrapping by PandasData

* PandasData cleanup

* Add data and other minor changes

* Unit test fix

* Update Pythonnet to 2.0.39

* Cleanup

* PandasData handling children class members

Address peer review

* Fix: indexing symbol conversion in pandas mapper

* Fix pandas mapper to convert string keys to symbol only when necessary

* Cleanup

* Cleanup

* Add PandasColumn python class to handle proper indexing

This allows propery hash and equality between Symbols, C# strings and Python strings

* Minor fixes

* Symbol cache improvements

* Minor fix for cache miss

* Revert PandasMapper reserved names and improvements

* Minor fix

* Revert reserved names

* Minor fix for Symbol equality operators

---------

Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
2024-10-04 12:26:15 -04:00
Martin-Molinero
7c9aa858c2 Improve python command serialization (#8351)
- Fix bug in python command serialization, expanding existing tests
2024-10-02 09:19:04 -03:00
Martin-Molinero
8fb70b20d0 Enhance command support (#8348)
* Enhance command support

- Enhance command support, adding link helper methods. Adding and
  expanding new tests
- Minor improvement for command str representation

* Minor test fix
2024-09-30 16:01:08 -03:00
Louis Szeto
809faa24de Add Backspread Option Strategies (#8312)
* Call and put backspread definitions

* Margin model

* regression tests

* strategy unit test

* refactor

* Use option strategies to order
2024-09-26 16:57:20 -03:00
Jhonathan Abreu
ad5aa263c0 Infer data type from configs in bar count history requests (#8344)
* Infer data type from configs in bar count history requests

* Infer data type from configs in bar count history requests

* Minor changes

* Minor fix

* Cleanup
2024-09-26 16:51:19 -03:00
Roman Yavnikov
a1bb907e03 Feature:Alpaca: support MarketOnOpen and MarketOnClose (#8341)
* feat: missed Alpaca config in Launcher

* feature: support of new OrderTypes for Equtity in AlpacaBrokerage model
2024-09-25 14:30:27 -03:00
Roman Yavnikov
71540f5015 Feature: support MarketOnOpen and MarketOnClose (#8340)
* remove: not used proxy config TradeStation

* feat: missed config of TradeStation in Launcher

* feat: support new OrderTypes in TradeStationBrokerageModel
2024-09-24 15:11:36 -03:00
Kevin Wheeler
a0055a3695 Improve data not found error messages. (#8295)
* Improve data not found error messages.

* Minor tweaks

---------

Co-authored-by: Kevin Wheeler <spreadlove5683@gmail.com>
Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
2024-09-20 16:56:58 -03:00
Martin-Molinero
0b285df496 Minor fix for option contract universe (#8337) 2024-09-20 13:16:20 -03:00
Martin Molinero
4d37096b3f Reduce realtime shutdown timeout 2024-09-20 10:04:58 -03:00
Martin Molinero
7c42ea795f Minor improvement for live trading shutdown 2024-09-19 20:09:21 -03:00
Martin-Molinero
f2f1d06237 Improve shutdown (#8335) 2024-09-19 19:32:29 -03:00
Martin-Molinero
86fd80a31a Generic live command support (#8330)
* Generic command support

- Adding generic algorithm command support. Adding regression algorithms
- Allow PythonWrapper to validate classes too

* Minor improvements
2024-09-19 16:02:42 -03:00
Roman Yavnikov
c556d16775 Feature: new Tick constructor for TickType.OpenInterest (#8323)
* feat: create OpenInterest constrcutor of Tick

* feat: GetSubscribedSymbols by TickType

* test:feat: GetSubscribeSymbolsBySpecificTickType

* refactor: equal channel name with InvariantCultureIgnoreCase
2024-09-17 12:52:24 -03:00
Martin-Molinero
6351773a01 Option universe resolution improvements (#8324)
* Option universe improvements

- Improvement for resolution handling of option universes, affecting
  performance in live mode. Adding regression algorithm

* Minor fix for research test
2024-09-16 10:22:58 -03:00
Jhonathan Abreu
bf4b08e202 Fix: adjust option expiry reference date (#8322)
* Fix: adjust option expiry reference date

* Add universe files

* Update data and other minor changes

* Minor changes

* Add regression algorithm summary
2024-09-13 18:22:26 -04:00
Jhonathan Abreu
fa9ff399cc Euro Stoxx 50 Index and Index Futures support (#8278)
* EUREX data

EUREX data model and sample data

* Add EUREX futures expiry function and sample algorithms

* Add EuroStoxx50 futures map and factor files

* Reduce eurex data for repo

* Map eurex market to primary exchange

* Update Euro Stoxx 50 (FESX) map and factol files

* Update Euro Stoxx 50 (FESX) minute data

* Added EURSD data

* Added 2 basic FESX futures algorithms in CSharp and Python (#2)

* Add regression algorithms

* Update regression algorithms and data

* Minor change

* Cleanup

---------

Co-authored-by: paulius-an <118921953+paulius-an@users.noreply.github.com>
2024-09-12 10:00:16 -04:00
Jhonathan Abreu
16c4259342 Add QCAlgorithm.OptionChain() method to fetch option chains (#8316)
* Add new QCAlgorithm.OptionChain method to get full data option chain

* Add extension method to get canonical symbol

* Support future options in new OptionChain method

* Replace option chain provider with OptionChain method in some regression algorithms

* Add new regression algorithms for OptionChain method

* Replace option chain provider with OptionChain method in some regression algorithms

* Minor

* Cleanup

* Minor changes in regression algorithms

* Minor adjustments
2024-09-11 15:15:51 -04:00
Ricardo Andrés Marino Rojas
724d0b06a5 Add extra argument in QuantBook.UniverseHistory() for using an IDateRule (#8301)
* First draft of the solution

* Handle end date better

* Improve unit tests

* Add extra argument in missing method

* Nit change

* Nit change

* Nit change

* Undo changes to C# generic UniverseHistory()

* Address suggestions

* Improve unit test

* Add null checks

* Minor adjustment

---------

Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
2024-09-11 13:41:57 -03:00
Ricardo Andrés Marino Rojas
ba7fe05574 Add BeforeMarketOpen() and AfterMarketClose() date rules (#8311)
* First draft of the solution

* Add unit tests

* Improve unit tests

* Nit changes
2024-09-10 15:56:31 -03:00
Ricardo Andrés Marino Rojas
50437946e2 Add missing end_date in python regression algorithm (#8315) 2024-09-10 14:33:44 -03:00
Ricardo Andrés Marino Rojas
418970bb48 Add TravisExclude category to failing CI unit test (#8313) 2024-09-10 13:25:41 -03:00
Roman Yavnikov
bef045a360 Fix: Get GroupOrders ByBrokerageId (#8310)
* fix: Get GroupOrders ByBrokerageId

* test:feat: return all combo orders with the same brokerageId
2024-09-10 13:25:22 -03:00
Jhonathan Abreu
49bf436aa2 Remove Lean path info from runtime exceptions (#8309)
* Strip lean path info from runtime exceptions

* Minor fix
2024-09-09 17:54:29 -04:00
Jhonathan Abreu
e29bb2c5e0 File-based options universe (#8212)
* Initial options universe with greeks implementation

* Options universe improvements

* Address peer review

* File based options universe fixes and improvements.

- Adjust OptionUniverse start-end times and period.
- Adapt unit tests and some algorithms to pass with new options universe selection.

* Updated options regression algorithms stats for new universe data

* Updated options regression algorithms stats for new universe data

* Updated options regression algorithms stats for new universe data

* Updated options regression algorithms stats for new universe data

* Updated options regression algorithms stats for new universe data

* Option chain provider with new options universe

* Allow canonical option history requests

* Address peer review

* Address peer review

* Fix symbols parsing in OptionUniverse

* Fix universe selection subscriptions start time to not include extended market hours

* Minor changes

* Minor changes

* Peer recommended changes and fixes

* Update regression algorithm stats

* Update regression algorithms stats and minor fixes

* Fix option chain provider history request

* Round option indicators values

* Added option universe csv header property

* Update regression algorithms stats

* Update regression algorithms stats

* Data fixes and regression algos stats update

* Unit test fixes

* Minor changes

* Option chain handling in live trading data feed

* Minor changes

* Added processed data provider

* Fix thread-safety violation in Slice class

* Minor change

* Update options filter universe API to use OptionUniverse data

Add new filter methods for greeks, IV and open interest

* Option filter universe api updates

* Add OptionUniverse history regression algorithms

* Add regression algorithms for new options filter universe api methods

* Added options greeks data and updated regression algorithms

* Address peer review

* Address peer review

* Add more assertions to new options filter api regression algorithms

* Minor performance improvement.

Reduce greeks binomial model steps to 140

* Minor tests updates

* Greeks numerical models performance improvements

* Greeks numerical models performance improvements

* Revert array pool change for option pricing numerical models

* Update default dividend yield provider depending on option type

* [TEST]

* Add helper method con calculate time till expiration

* Use double in price option numerical models

* Implied volatility calculation improvements

- Adjust root finding method accuracy as a factor of the option price
- Use BSM to get a first guess

* Cleanup

* Some regression algorithms and unit tests cleanup

* Regression tests updates after rebasing from master

* Add universe files

* Self review and cleanup

* Minor regression tests updates after rebase

* Fix: set data time zone to same as exchange tz for options universes

* Minor change

* Minor change

* Fix for live trading options universe selection

* Keep underlying when aggregating collections in BaseDataCollectionAggregatorEnumerator

* Update index options regression algorithms stats

* Minor change

* Address peer review

* Memory usage improvements

* Minor build fix

* Minor changes and test fixes

* Cache symbols in OptionUniverse

* Cleanup

* Fix index option creation in OptionUniverse

* Use cached underlying SID when parsing from string

* Abstract symbols cache to BaseDataCollection

* Return actual underlying symbol when mapping decomposing ICO ticker

* Address peer review

* Minor performance improvements reduce garbage

* Limit Symbols and SIDs cache size to help with memory usage

* Minor fix in symbols and sid cache cleanup

* Build fix

* Lazily parse greeks on individual access

* Cleanup and tests

* Address peer review

* Minor greeks fix

---------

Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
2024-09-09 12:39:31 -03:00
Dennis Yemelyanov
8fcc9f7d4e fix some comments for option security types (#8304) 2024-09-09 11:37:26 -03:00
Andy Geach
5209332074 Update readme.md to remove references to Visual Studio for Mac, which has been discontinued (#8298) 2024-09-06 11:59:28 -03:00
Roman Yavnikov
adfad475cc Feature:TradeStationBrokerage: support ComboMarket && ComboLimit (#8290)
* refactor: adding OrderId in GroupOrderManger

* feat: new support of OrderTypes in TradeStationBrokerageModel
feat: unSupported OrderTypes in CanUpdateOrder's TradeStationBrokerageModel

* feat: AllOrNone property in TradeStationOrderProperties

* feat: unsupported SubmitCrossZero of Combo Order in TSBrokerageModel

* test:feat: submit / update CrossZero Combo Orders

* feat: new Message Brokerage error message
refactor: use new Message in TradeStationBrokerageModel

* feat: setter of Id in GroupOrderManager

* feat: new constructor of GroupOrderManager

* feat: develop GroupOrderCacheManager service

* fix: groupOrderManger.Id in OrderProvider

* fix: incrementOrderGroupOrderManagerID in BrokerageTransactionHandler
feat: add _groupOrderManagerId in OrderProvider

* remove: extra semicolon

* refactor: prevent increment GroupOrderID

* feat: add new Exchanges

* feat: Try Get Group Combo Orders extension

* refactor: ComboORderType in TSBrokerageModel

* remove: implementing of prop ID in GroupOrderManager

* refactor: UnsupportedCrossZeroByOrderType message

* fix: warning of UnsupportedCrossZeroByOrderType

* fix: several exchanges code based on tradier docs
https://documentation.tradier.com/brokerage-api/reference/exchanges

* feat: add missed Exchange in Global class

* refactor: possible update LimitPrice in TSBrokerageModel
test:feat: validate upddate LimitPrice of ComboLimit Order

* refactor: GroupOrderCacheManager
remove: TryGetGroupCachedOrders from extension

* refactor: exchange SPHR to MIAX_SAPPHIRE

* remove: Exchange BYX cuz It is BATS_Y

* refactor: change position of Exchange C2

* refactor: change constructor's access modifier in class Exchange
2024-09-06 10:31:14 -03:00
Martin-Molinero
21fcadf0f8 Ignore failing live future option unit test (#8300) 2024-09-05 16:42:42 -03:00
Ricardo Andrés Marino Rojas
e893e67e9b Throw exception when base currency not found (#8289)
* First draft of the solution

* The same check for crytpo is done before

* Fix failing unit tests

* Remove non perpetual crypto futures from SPDB

* Address requests

* Fix failing unit tests
2024-09-04 12:14:53 -03:00
Alexandre Catarino
3b588d04fb Adds Overload to AddIndexOption (#8291)
* Adds Overload to AddIndexOption

Simplify usage. We don't need to create/add the underlying explicitly, see AddIndexOption(string, Resolution, string, bool) overload.

* Addresses Peer-Review

- Default market is `null` instead of `Market.USA` allowing for `BrokerageModel` setup.
- `AddIndexOption` and `AddIndexOptionContract` methods now return `indexOption` objects.

* Fixes Logic Bug
2024-09-04 10:30:05 -03:00
Ricardo Andrés Marino Rojas
e81bcbb987 Improve PythonIndicator.IsReady implementation (#8287)
* First draft of the solution

* nit change

* Add improvements

* Fix failing unit tests

* Add improvements
2024-09-04 10:07:13 -03:00
Roman Yavnikov
96e91b446d Fix: #8226, update spdb binance/binanceus (#8293)
* feature: update binance spdb data

* feature: update binanceus spdb data

* test:fix: EURUSDC stable coins conversation
2024-09-04 10:05:07 -03:00
Ricardo Andrés Marino Rojas
403f0348bd Update Bybit SPDB (#8294)
* Update Bybit SPDB

* Remove trailing comma
2024-09-03 17:55:12 -03:00
Ricardo Andrés Marino Rojas
eeeb310438 Update minimum price variation of some entries of CME futures in SPDB (#8288)
* Update some entries of CME futures in SPDB

* Adjust 6B minimum price variation
2024-08-28 19:59:40 -03:00
oussamanahdi
271f0bb08e Update readme.md (#8286) 2024-08-26 19:11:04 -03:00
Ricardo Andrés Marino Rojas
3a09c70851 Fix warm up indicator bugs (#8279)
* Potential solution

* Try a different approach

* Improve unit tests

* Nit change

* Improve implementation

* Fix another bug and improve unit tests
2024-08-26 10:20:40 -03:00
Roman Yavnikov
f31251732e Fix: Coinbase MinimumOrderSize tests based on new SPDB data (#8276)
* test:fix: minimValue based on new SPDB data

* fix: Estimated Strategy Capacity in FractionalQuantityRegressionAlgorithm
2024-08-23 11:47:45 -03:00
Roman Yavnikov
9baacdbdd6 feat: Coinbase SPDB update (#8273) 2024-08-22 17:42:58 -03:00
Martin-Molinero
363d469d6a Minor indicator history fix (#8270)
* Minor indicator history fix

- Take into account warmup period when used, the last bar of the warmup
  period is counted as a data point.
- Fix bug where in some cases the last data point could of been missed
  and the indicator not updated with it

* Minor tweak
2024-08-22 16:48:26 -03:00
Ricardo Andrés Marino Rojas
c186addf94 Add missing price magnifier in SPDB (#8271) 2024-08-22 16:44:26 -03:00
Ricardo Andrés Marino Rojas
17049dcd56 Fix null exception thrown in SubscriptionManager.ScanPastConsolidators (#8267)
* Initial draft of the solution

* Improve implemetation

* Nit change

* Address requests

* Switch from LinkedList ot List

* Fix bug
2024-08-22 09:55:41 -03:00
Jhonathan Abreu
d88387ac67 Extend Python wrappers error messages (#8257)
* Implement runtime checks for python wrappers

* Implement runtime checks for python wrappers

* Add more python wrappers runtime checks

* Add dictionary conversion unit tests

* Add python wrappers runtime checks for properties

* CLeanup base python wrapper messages
2024-08-19 14:27:32 -04:00
Ricardo Andrés Marino Rojas
74c3501ed3 Fix bug for history requests with custom symbols (#8262)
* Potential solution to the bug

* Add test file

* Fix bugs

* Address requested changes
2024-08-19 15:26:42 -03:00
Ricardo Andrés Marino Rojas
a543af71dc Solve bug (#8256) 2024-08-19 11:57:21 -03:00
Jhonathan Abreu
9b332c2149 Dividend yield calculation fix (#8264)
* Fix dividend yield calculation

* Get security price as input for dividend yield provider

* Account for splits in dividend yield provider

* Fix split adjustment for dividend yield calculation

* Use right dividend yield in options indicators
2024-08-19 09:30:05 -04:00
keshavdalmia10
1e620e54fe Feature 8132 implement vortex indicator (#8242)
* Implemented the vortex indicator.

* changed the vortex.cs calculations

* chore: Refactor VortexTests.cs and QCAlgorithm.Indicators.cs

* Refactor VortexTests.cs

* made changes according to the comments

* used indicator exxtension methods

* made changes in the naming convention and added condition for division by zero.

* Using composite indicators to clean up

---------

Co-authored-by: Jhonathan Abreu <jdabreu25@gmail.com>
2024-08-14 15:43:21 -03:00
Martin-Molinero
7879795207 Enable daily precise end time by default (#8254)
* Default daily precise end times

- Enable by default daily precise end times. Updating stats
- Minor fix for algorithm manager consolidator updates, adding new regression test
  asserting behavior and updating others
- Minor fix for SubscriptionData creator avoid round down on warmup if
  not appropiate
- Adjust consolidators to emit on daily strict end times if requested
  daily resolution and setting enabled
- Updating regression algorithms

* Skip daily data on extended market hours

* Some cleanup and self review

* Revert unrequired change
2024-08-14 12:49:56 -03:00
Noah Misch
d2d366e3f9 Fix sign of order quantity in example algorithm OnMarginCall(). (#8251)
Despite the comments about avoiding margin calls and about padding, this
turned a proposed sale of 100 shares into a *buy* of 110 shares.
2024-08-12 17:40:51 -03:00
Ricardo Andrés Marino Rojas
5226b7a468 Add more options to Field class (#8228)
* First draft of the solution

* Reduce duplication and add more properties

* Add regression tests

* Add xml docs

* Add unit tests

* Improve regression and unit tests

* Address requested changes

* Address request and improve unit tests

* Add unit test and fix bug

* Improve unit tests and implementation

* Nit change

* Address reviews

* Improve regression tests

* Address requests

* Fix bug

* Address requests
2024-08-07 19:08:34 -03:00
FemtoTrader
1947a58541 Implements new indicator - CKS - ChandeKrollStop (#8198)
* Implements ChandeKrollStop

* readonly

* Move IsReady/WarmUpPeriod above the constructors

* remove private _period

* minor

* rename Stops to Short/Long

* using Maximum/Minimum

* fix tests

* rename some variables and use movingAverageType for ATR

* movingAverageType
2024-08-07 14:51:39 -03:00
Roman Yavnikov
1bca3f6081 feat: missed reference on DownloaderDataProvider in Lean.Launcher (#8247) 2024-08-07 14:51:05 -03:00
Noah Misch
2b1136e446 Fix algorithms using OnData(TradeBars) w/o using arg or other OnData(). (#8245)
Commit d24f665ee4 removed the
Engine/AlgorithmManager.cs support for OnData(TradeBars), making these
methods dead code.  Hence, some of these algorithms no longer placed
orders.  Fix by changing OnData(TradeBars) to OnData(Slice).  Files that
use the TradeBars argument or use OnData(Dividends) have the same
trouble; leave them for future work.
2024-08-06 10:15:56 -03:00
886 changed files with 91438 additions and 6766 deletions

View File

@@ -128,7 +128,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "9"},
{"Average Win", "0.86%"},
{"Average Loss", "-0.27%"},
{"Compounding Annual Return", "184.364%"},
{"Compounding Annual Return", "206.404%"},
{"Drawdown", "1.700%"},
{"Expectancy", "1.781"},
{"Start Equity", "100000"},
@@ -148,10 +148,10 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0.532"},
{"Treynor Ratio", "-1.174"},
{"Total Fees", "$14.78"},
{"Estimated Strategy Capacity", "$47000000.00"},
{"Estimated Strategy Capacity", "$120000000.00"},
{"Lowest Capacity Asset", "IBM R735QTJ8XC9X"},
{"Portfolio Turnover", "41.18%"},
{"OrderListHash", "d929e7959f079ad4fed42e8f3b35e39e"}
{"OrderListHash", "713c956deb193bed2290e9f379c0f9f9"}
};
}
}

View File

@@ -40,8 +40,8 @@ namespace QuantConnect.Algorithm.CSharp
var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
_contract = OptionChainProvider.GetOptionContractList(aapl, Time)
.OrderBy(symbol => symbol.ID.Symbol)
_contract = OptionChain(aapl)
.OrderBy(x => x.ID.Symbol)
.FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
&& optionContract.ID.OptionStyle == OptionStyle.American);
AddOptionContract(_contract);
@@ -90,7 +90,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
public int AlgorithmHistoryDataPoints => 1;
/// <summary>
/// Final status of the algorithm

View File

@@ -39,8 +39,8 @@ namespace QuantConnect.Algorithm.CSharp
var aapl = AddEquity("AAPL").Symbol;
_contract = OptionChainProvider.GetOptionContractList(aapl, Time)
.OrderBy(symbol => symbol.ID.Symbol)
_contract = OptionChain(aapl)
.OrderBy(x => x.ID.Symbol)
.FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
&& optionContract.ID.OptionStyle == OptionStyle.American);
}
@@ -87,7 +87,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
public int AlgorithmHistoryDataPoints => 1;
/// <summary>
/// Final status of the algorithm

View File

@@ -115,7 +115,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 73;
public long DataPoints => 76;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -164,7 +164,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 311879;
public long DataPoints => 311881;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -49,7 +49,7 @@ namespace QuantConnect.Algorithm.CSharp
{
foreach (var contract in futuresContracts)
{
var option_contract_symbols = OptionChainProvider.GetOptionContractList(contract.Symbol, Time).ToList();
var option_contract_symbols = OptionChain(contract.Symbol).ToList();
if(option_contract_symbols.Count == 0)
{
continue;
@@ -93,7 +93,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 12169;
public long DataPoints => 12172;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -55,10 +55,10 @@ namespace QuantConnect.Algorithm.CSharp
{
_optionFilterRan = true;
var expiry = new HashSet<DateTime>(optionContracts.Select(x => x.Underlying.ID.Date)).SingleOrDefault();
// Cast to IEnumerable<Symbol> because OptionFilterContract overrides some LINQ operators like `Select` and `Where`
var expiry = new HashSet<DateTime>(optionContracts.Select(x => x.Symbol.Underlying.ID.Date)).SingleOrDefault();
// Cast to List<Symbol> because OptionFilterContract overrides some LINQ operators like `Select` and `Where`
// and cause it to mutate the underlying Symbol collection when using those operators.
var symbol = new HashSet<Symbol>(((IEnumerable<Symbol>)optionContracts).Select(x => x.Underlying)).SingleOrDefault();
var symbol = new HashSet<Symbol>(((List<Symbol>)optionContracts).Select(x => x.Underlying)).SingleOrDefault();
if (expiry == null || symbol == null)
{
@@ -220,7 +220,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 608377;
public long DataPoints => 608380;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -46,8 +46,8 @@ namespace QuantConnect.Algorithm.CSharp
{
if (_option == null)
{
var option = OptionChainProvider.GetOptionContractList(_twx, Time)
.OrderBy(symbol => symbol.ID.Symbol)
var option = OptionChain(_twx)
.OrderBy(x => x.ID.Symbol)
.FirstOrDefault(optionContract => optionContract.ID.Date == _expiration
&& optionContract.ID.OptionRight == OptionRight.Call
&& optionContract.ID.OptionStyle == OptionStyle.American);
@@ -122,7 +122,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
public int AlgorithmHistoryDataPoints => 1;
/// <summary>
/// Final status of the algorithm

View File

@@ -13,12 +13,12 @@
* limitations under the License.
*/
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Algorithm.CSharp
{
@@ -110,14 +110,14 @@ namespace QuantConnect.Algorithm.CSharp
foreach (var addedSecurity in changes.AddedSecurities)
{
var option = OptionChainProvider.GetOptionContractList(addedSecurity.Symbol, Time)
.OrderBy(symbol => symbol.ID.Symbol)
var option = OptionChain(addedSecurity.Symbol)
.OrderBy(contractData => contractData.ID.Symbol)
.First(optionContract => optionContract.ID.Date == _expiration
&& optionContract.ID.OptionRight == OptionRight.Call
&& optionContract.ID.OptionStyle == OptionStyle.American);
AddOptionContract(option);
foreach (var symbol in new[] { option, option.Underlying })
foreach (var symbol in new[] { option.Symbol, option.UnderlyingSymbol })
{
var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol).ToList();
@@ -174,7 +174,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
public int AlgorithmHistoryDataPoints => 2;
/// <summary>
/// Final status of the algorithm

View File

@@ -39,12 +39,12 @@ namespace QuantConnect.Algorithm.CSharp
UniverseSettings.MinimumTimeInUniverse = TimeSpan.Zero;
UniverseSettings.FillForward = false;
AddEquity("SPY", Resolution.Daily);
AddEquity("SPY", Resolution.Hour);
var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
_contract = OptionChainProvider.GetOptionContractList(aapl, Time)
.OrderBy(symbol => symbol.ID.StrikePrice)
_contract = OptionChain(aapl)
.OrderBy(x => x.ID.StrikePrice)
.FirstOrDefault(optionContract => optionContract.ID.OptionRight == OptionRight.Call
&& optionContract.ID.OptionStyle == OptionStyle.American);
AddOptionContract(_contract);
@@ -116,12 +116,12 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 3930;
public long DataPoints => 3814;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
public int AlgorithmHistoryDataPoints => 1;
/// <summary>
/// Final status of the algorithm
@@ -135,13 +135,13 @@ namespace QuantConnect.Algorithm.CSharp
{
{"Total Orders", "2"},
{"Average Win", "0%"},
{"Average Loss", "-0.70%"},
{"Compounding Annual Return", "-47.178%"},
{"Average Loss", "-0.50%"},
{"Compounding Annual Return", "-39.406%"},
{"Drawdown", "0.700%"},
{"Expectancy", "-1"},
{"Start Equity", "100000"},
{"End Equity", "99303"},
{"Net Profit", "-0.697%"},
{"End Equity", "99498"},
{"Net Profit", "-0.502%"},
{"Sharpe Ratio", "0"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
@@ -156,10 +156,10 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0.008"},
{"Treynor Ratio", "0"},
{"Total Fees", "$2.00"},
{"Estimated Strategy Capacity", "$6400000.00"},
{"Estimated Strategy Capacity", "$5000000.00"},
{"Lowest Capacity Asset", "AAPL VXBK4R62CXGM|AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "22.80%"},
{"OrderListHash", "c2878a81bbb4e52c4fcd6a4f259abc3d"}
{"Portfolio Turnover", "22.70%"},
{"OrderListHash", "29fd1b75f6db05dd823a6db7e8bd90a9"}
};
}
}

View File

@@ -13,7 +13,6 @@
* limitations under the License.
*/
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data.UniverseSelection;
@@ -59,19 +58,9 @@ namespace QuantConnect.Algorithm.CSharp
var changeOptions = changes.AddedSecurities.Concat(changes.RemovedSecurities)
.Where(s => s.Type == SecurityType.Option);
// Susbtract one minute to get the actual market open. If market open is at 9:30am, this will be invoked at 9:31am
var expectedTime = Time.TimeOfDay - TimeSpan.FromMinutes(1);
var allOptionsWereChangedOnMarketOpen = changeOptions.All(s =>
if (Time != Time.Date)
{
var firstMarketSegment = s.Exchange.Hours.MarketHours[Time.DayOfWeek].Segments
.First(segment => segment.State == MarketHoursState.Market);
return firstMarketSegment.Start == expectedTime;
});
if (!allOptionsWereChangedOnMarketOpen)
{
throw new RegressionTestException("Expected options filter to be run only on market open");
throw new RegressionTestException($"Expected options filter to be run only at midnight. Actual was {Time}");
}
}
@@ -88,7 +77,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all time slices of algorithm
/// </summary>
public long DataPoints => 5952220;
public long DataPoints => 470217;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -35,14 +35,15 @@ namespace QuantConnect.Algorithm.CSharp
private readonly HashSet<Symbol> _expectedData = new HashSet<Symbol>();
private readonly HashSet<Symbol> _expectedUniverses = new HashSet<Symbol>();
private bool _expectUniverseSubscription;
private DateTime _universeSubscriptionTime;
// order of expected contract additions as price moves
private int _expectedContractIndex;
private readonly List<Symbol> _expectedContracts = new List<Symbol>
{
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00747500"),
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00750000"),
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00752500")
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00752500"),
SymbolRepresentation.ParseOptionTickerOSI("GOOG 151224P00755000")
};
public override void Initialize()
@@ -68,7 +69,7 @@ namespace QuantConnect.Algorithm.CSharp
Log($"SubscriptionManager.Subscriptions: {string.Join(" -- ", SubscriptionManager.Subscriptions)}");
throw new RegressionTestException($"Unexpected {OptionChainSymbol} subscription presence");
}
if (!slice.ContainsKey(Underlying))
if (Time != _universeSubscriptionTime && !slice.ContainsKey(Underlying))
{
// TODO : In fact, we're unable to properly detect whether or not we auto-added or it was manually added
// this is because when we auto-add the underlying we don't mark it as an internal security like we do with other auto adds
@@ -91,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
var actual = string.Join(Environment.NewLine, UniverseManager.Keys.OrderBy(s => s.ToString()));
throw new RegressionTestException($"{Time}:: Detected differences in expected and actual universes{Environment.NewLine}Expected:{Environment.NewLine}{expected}{Environment.NewLine}Actual:{Environment.NewLine}{actual}");
}
if (_expectedData.AreDifferent(slice.Keys.ToHashSet()))
if (Time != _universeSubscriptionTime && _expectedData.AreDifferent(slice.Keys.ToHashSet()))
{
var expected = string.Join(Environment.NewLine, _expectedData.OrderBy(s => s.ToString()));
var actual = string.Join(Environment.NewLine, slice.Keys.OrderBy(s => s.ToString()));
@@ -99,7 +100,7 @@ namespace QuantConnect.Algorithm.CSharp
}
// 10AM add GOOG option chain
if (Time.TimeOfDay.Hours == 10 && Time.TimeOfDay.Minutes == 0)
if (Time.TimeOfDay.Hours == 10 && Time.TimeOfDay.Minutes == 0 && !_expectUniverseSubscription)
{
if (Securities.ContainsKey(OptionChainSymbol))
{
@@ -110,9 +111,9 @@ namespace QuantConnect.Algorithm.CSharp
googOptionChain.SetFilter(u =>
{
// we added the universe at 10, the universe selection data should not be from before
if (u.Underlying.EndTime.Hour < 10)
if (u.LocalTime.Hour < 10)
{
throw new RegressionTestException($"Unexpected underlying data point {u.Underlying.EndTime} {u.Underlying}");
throw new RegressionTestException($"Unexpected selection time {u.LocalTime}");
}
// find first put above market price
return u.IncludeWeeklys()
@@ -124,6 +125,7 @@ namespace QuantConnect.Algorithm.CSharp
_expectedSecurities.Add(OptionChainSymbol);
_expectedUniverses.Add(OptionChainSymbol);
_expectUniverseSubscription = true;
_universeSubscriptionTime = Time;
}
// 11:30AM remove GOOG option chain
@@ -151,7 +153,7 @@ namespace QuantConnect.Algorithm.CSharp
var expectedContract = _expectedContracts[_expectedContractIndex];
if (added.Symbol != expectedContract)
{
throw new RegressionTestException($"Expected option contract {expectedContract} to be added but received {added.Symbol}");
throw new RegressionTestException($"Expected option contract {expectedContract.Value} to be added but received {added.Symbol}");
}
_expectedContractIndex++;
@@ -186,7 +188,7 @@ namespace QuantConnect.Algorithm.CSharp
if (Securities.ContainsKey(Underlying))
{
Console.WriteLine($"{Time:o}:: PRICE:: {Securities[Underlying].Price} CHANGES:: {changes}");
Log($"{Time:o}:: PRICE:: {Securities[Underlying].Price} CHANGES:: {changes}");
}
}
@@ -203,7 +205,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 200807;
public long DataPoints => 3502;
/// <summary>
/// Data Points count of the algorithm history
@@ -227,7 +229,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "99079"},
{"End Equity", "98784"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Sortino Ratio", "0"},
@@ -243,10 +245,10 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$6.00"},
{"Estimated Strategy Capacity", "$3000.00"},
{"Lowest Capacity Asset", "GOOCV 305RBR0BSWIX2|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "1.49%"},
{"OrderListHash", "bd115ec8bb7734b1561d6a6cc6c00039"}
{"Estimated Strategy Capacity", "$4000.00"},
{"Lowest Capacity Asset", "GOOCV 305RBQ2BZBZT2|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "2.58%"},
{"OrderListHash", "09f766c470a8bcf4bb6862da52bf25a7"}
};
}
}

View File

@@ -41,8 +41,8 @@ namespace QuantConnect.Algorithm.CSharp
var aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
var contracts = OptionChainProvider.GetOptionContractList(aapl, Time)
.OrderBy(symbol => symbol.ID.StrikePrice)
var contracts = OptionChain(aapl)
.OrderBy(x => x.ID.StrikePrice)
.Where(optionContract => optionContract.ID.OptionRight == OptionRight.Call
&& optionContract.ID.OptionStyle == OptionStyle.American)
.Take(2)
@@ -106,7 +106,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
public int AlgorithmHistoryDataPoints => 1;
/// <summary>
/// Final status of the algorithm

View File

@@ -81,7 +81,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 53;
public long DataPoints => 50;
/// <summary>
/// Data Points count of the algorithm history
@@ -98,33 +98,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "10"},
{"Average Win", "0%"},
{"Average Loss", "-0.01%"},
{"Compounding Annual Return", "-14.233%"},
{"Drawdown", "3.300%"},
{"Expectancy", "-1"},
{"Total Orders", "6"},
{"Average Win", "0.01%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "1296.838%"},
{"Drawdown", "0.400%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "99831.88"},
{"Net Profit", "-0.168%"},
{"Sharpe Ratio", "62.464"},
{"End Equity", "102684.23"},
{"Net Profit", "2.684%"},
{"Sharpe Ratio", "34.319"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "1.117"},
{"Beta", "1.19"},
{"Annual Standard Deviation", "0.213"},
{"Annual Variance", "0.046"},
{"Information Ratio", "70.778"},
{"Tracking Error", "0.043"},
{"Treynor Ratio", "11.2"},
{"Total Fees", "$22.21"},
{"Estimated Strategy Capacity", "$340000000.00"},
{"Alpha", "-5.738"},
{"Beta", "1.381"},
{"Annual Standard Deviation", "0.246"},
{"Annual Variance", "0.06"},
{"Information Ratio", "-26.937"},
{"Tracking Error", "0.068"},
{"Treynor Ratio", "6.106"},
{"Total Fees", "$18.61"},
{"Estimated Strategy Capacity", "$980000000.00"},
{"Lowest Capacity Asset", "FB V6OIPNZEM8V9"},
{"Portfolio Turnover", "26.92%"},
{"OrderListHash", "3832790c7dd9d50805b6206129b01110"}
{"Portfolio Turnover", "25.56%"},
{"OrderListHash", "5ee20c8556d706ab0a63ae41b6579c62"}
};
}
}

View File

@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 234018;
public long DataPoints => 234015;
/// <summary>
/// Data Points count of the algorithm history
@@ -109,33 +109,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "23"},
{"Average Win", "0.00%"},
{"Total Orders", "21"},
{"Average Win", "0.01%"},
{"Average Loss", "-0.01%"},
{"Compounding Annual Return", "-75.275%"},
{"Drawdown", "5.800%"},
{"Expectancy", "-0.609"},
{"Compounding Annual Return", "-77.566%"},
{"Drawdown", "6.000%"},
{"Expectancy", "-0.811"},
{"Start Equity", "100000"},
{"End Equity", "94419.21"},
{"Net Profit", "-5.581%"},
{"Sharpe Ratio", "-3.288"},
{"Sortino Ratio", "-3.828"},
{"Probabilistic Sharpe Ratio", "5.546%"},
{"Loss Rate", "73%"},
{"Win Rate", "27%"},
{"Profit-Loss Ratio", "0.43"},
{"Alpha", "-0.495"},
{"Beta", "1.484"},
{"Annual Standard Deviation", "0.196"},
{"Annual Variance", "0.039"},
{"Information Ratio", "-3.843"},
{"Tracking Error", "0.141"},
{"Treynor Ratio", "-0.435"},
{"Total Fees", "$31.25"},
{"Estimated Strategy Capacity", "$550000000.00"},
{"End Equity", "94042.73"},
{"Net Profit", "-5.957%"},
{"Sharpe Ratio", "-3.345"},
{"Sortino Ratio", "-3.766"},
{"Probabilistic Sharpe Ratio", "4.557%"},
{"Loss Rate", "89%"},
{"Win Rate", "11%"},
{"Profit-Loss Ratio", "0.70"},
{"Alpha", "-0.519"},
{"Beta", "1.491"},
{"Annual Standard Deviation", "0.2"},
{"Annual Variance", "0.04"},
{"Information Ratio", "-3.878"},
{"Tracking Error", "0.147"},
{"Treynor Ratio", "-0.449"},
{"Total Fees", "$29.11"},
{"Estimated Strategy Capacity", "$680000000.00"},
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "7.33%"},
{"OrderListHash", "2add92a1f922c6730d8c20ff65934a46"}
{"Portfolio Turnover", "7.48%"},
{"OrderListHash", "2c814c55e7d7c56482411c065b861b33"}
};
}
}

View File

@@ -238,7 +238,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 37748;
public long DataPoints => 36573;
/// <summary>
/// Data Points count of the algorithm history
@@ -255,33 +255,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "5"},
{"Total Orders", "8"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "19.147%"},
{"Drawdown", "0%"},
{"Compounding Annual Return", "11.027%"},
{"Drawdown", "0.000%"},
{"Expectancy", "0"},
{"Start Equity", "10000000"},
{"End Equity", "10019217.27"},
{"Net Profit", "0.192%"},
{"Sharpe Ratio", "15.743"},
{"End Equity", "10011469.88"},
{"Net Profit", "0.115%"},
{"Sharpe Ratio", "11.963"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.17"},
{"Beta", "0.037"},
{"Annual Standard Deviation", "0.01"},
{"Alpha", "0.07"},
{"Beta", "-0.077"},
{"Annual Standard Deviation", "0.008"},
{"Annual Variance", "0"},
{"Information Ratio", "5"},
{"Tracking Error", "0.094"},
{"Treynor Ratio", "4.278"},
{"Total Fees", "$307.50"},
{"Estimated Strategy Capacity", "$2600000.00"},
{"Lowest Capacity Asset", "GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "10.61%"},
{"OrderListHash", "854d4ba6a4ae39f9be2f9a10c8544fe5"}
{"Information Ratio", "3.876"},
{"Tracking Error", "0.105"},
{"Treynor Ratio", "-1.215"},
{"Total Fees", "$282.50"},
{"Estimated Strategy Capacity", "$61000000000.00"},
{"Lowest Capacity Asset", "NB R735QTJ8XC9X"},
{"Portfolio Turnover", "3.62%"},
{"OrderListHash", "0ea806c53bfa2bdca2504ba7155ef130"}
};
}
}

View File

@@ -93,33 +93,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "52"},
{"Total Orders", "53"},
{"Average Win", "0.00%"},
{"Average Loss", "0.00%"},
{"Compounding Annual Return", "0.096%"},
{"Compounding Annual Return", "0.076%"},
{"Drawdown", "0.100%"},
{"Expectancy", "3.321"},
{"Expectancy", "2.933"},
{"Start Equity", "100000"},
{"End Equity", "100089.09"},
{"Net Profit", "0.089%"},
{"Sharpe Ratio", "-8.214"},
{"Sortino Ratio", "-9.025"},
{"Probabilistic Sharpe Ratio", "40.893%"},
{"Loss Rate", "24%"},
{"Win Rate", "76%"},
{"Profit-Loss Ratio", "4.67"},
{"End Equity", "100070.90"},
{"Net Profit", "0.071%"},
{"Sharpe Ratio", "-9.164"},
{"Sortino Ratio", "-9.852"},
{"Probabilistic Sharpe Ratio", "36.417%"},
{"Loss Rate", "27%"},
{"Win Rate", "73%"},
{"Profit-Loss Ratio", "4.41"},
{"Alpha", "-0.008"},
{"Beta", "0.008"},
{"Annual Standard Deviation", "0.001"},
{"Annual Variance", "0"},
{"Information Ratio", "-1.961"},
{"Tracking Error", "0.092"},
{"Treynor Ratio", "-0.826"},
{"Total Fees", "$52.00"},
{"Estimated Strategy Capacity", "$32000000000.00"},
{"Treynor Ratio", "-0.911"},
{"Total Fees", "$53.00"},
{"Estimated Strategy Capacity", "$16000000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "0.02%"},
{"OrderListHash", "fab920b5fc92a6e14d8128564249fbfa"}
{"OrderListHash", "685c37df6e4c49b75792c133be189094"}
};
}
}

View File

@@ -296,7 +296,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 1267414;
public long DataPoints => 27071;
/// <summary>
/// Data Points count of the algorithm history
@@ -316,7 +316,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "3"},
{"Average Win", "0%"},
{"Average Loss", "-0.40%"},
{"Compounding Annual Return", "-22.717%"},
{"Compounding Annual Return", "-21.378%"},
{"Drawdown", "0.400%"},
{"Expectancy", "-1"},
{"Start Equity", "100000"},

View File

@@ -118,7 +118,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 713369;
public long DataPoints => 713375;
/// <summary>
/// Data Points count of the algorithm history
@@ -136,32 +136,32 @@ namespace QuantConnect.Algorithm.CSharp
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "5"},
{"Average Win", "2.90%"},
{"Average Win", "2.48%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "13.087%"},
{"Drawdown", "1.100%"},
{"Compounding Annual Return", "11.325%"},
{"Drawdown", "1.500%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "106387.1"},
{"Net Profit", "6.387%"},
{"Sharpe Ratio", "1.532"},
{"Sortino Ratio", "871.704"},
{"Probabilistic Sharpe Ratio", "90.613%"},
{"End Equity", "105549.6"},
{"Net Profit", "5.550%"},
{"Sharpe Ratio", "1.332"},
{"Sortino Ratio", "879.904"},
{"Probabilistic Sharpe Ratio", "79.894%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.088"},
{"Beta", "-0.022"},
{"Annual Standard Deviation", "0.054"},
{"Alpha", "0.075"},
{"Beta", "-0.017"},
{"Annual Standard Deviation", "0.053"},
{"Annual Variance", "0.003"},
{"Information Ratio", "-1.35"},
{"Tracking Error", "0.1"},
{"Treynor Ratio", "-3.781"},
{"Information Ratio", "-1.48"},
{"Tracking Error", "0.099"},
{"Treynor Ratio", "-4.187"},
{"Total Fees", "$10.75"},
{"Estimated Strategy Capacity", "$1100000000.00"},
{"Estimated Strategy Capacity", "$7100000.00"},
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
{"Portfolio Turnover", "2.32%"},
{"OrderListHash", "2f6afca6b20a56eea9dd327dcb401682"}
{"Portfolio Turnover", "2.33%"},
{"OrderListHash", "9c524830ffc7354327638142ae62acd2"}
};
}
}

View File

@@ -123,7 +123,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 2217299;
public long DataPoints => 2217328;
/// <summary>
/// Data Points count of the algorithm history
@@ -141,32 +141,32 @@ namespace QuantConnect.Algorithm.CSharp
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "5"},
{"Average Win", "4.45%"},
{"Average Loss", "-0.26%"},
{"Compounding Annual Return", "8.423%"},
{"Drawdown", "0.800%"},
{"Expectancy", "8.202"},
{"Average Win", "2.86%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "12.959%"},
{"Drawdown", "1.100%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "104162.1"},
{"Net Profit", "4.162%"},
{"Sharpe Ratio", "0.951"},
{"Sortino Ratio", "2.8"},
{"Probabilistic Sharpe Ratio", "53.568%"},
{"Loss Rate", "50%"},
{"Win Rate", "50%"},
{"Profit-Loss Ratio", "17.40"},
{"Alpha", "0.053"},
{"Beta", "-0.005"},
{"Annual Standard Deviation", "0.054"},
{"End Equity", "106337.1"},
{"Net Profit", "6.337%"},
{"Sharpe Ratio", "1.41"},
{"Sortino Ratio", "1.242"},
{"Probabilistic Sharpe Ratio", "77.992%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.071"},
{"Beta", "0.054"},
{"Annual Standard Deviation", "0.059"},
{"Annual Variance", "0.003"},
{"Information Ratio", "-1.681"},
{"Tracking Error", "0.099"},
{"Treynor Ratio", "-10.255"},
{"Information Ratio", "-1.392"},
{"Tracking Error", "0.097"},
{"Treynor Ratio", "1.518"},
{"Total Fees", "$10.75"},
{"Estimated Strategy Capacity", "$190000000.00"},
{"Estimated Strategy Capacity", "$890000000.00"},
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
{"Portfolio Turnover", "2.34%"},
{"OrderListHash", "f34d9277d1d81a8125879f5ff8202626"}
{"Portfolio Turnover", "2.32%"},
{"OrderListHash", "f60fc7dcba2c1ff077afeb191aee5008"}
};
}
}

View File

@@ -66,7 +66,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 73;
public long DataPoints => 72;
/// <summary>
/// Data Points count of the algorithm history
@@ -86,30 +86,30 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "246.546%"},
{"Drawdown", "1.200%"},
{"Compounding Annual Return", "424.375%"},
{"Drawdown", "0.800%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "103463.69"},
{"Net Profit", "3.464%"},
{"Sharpe Ratio", "19.094"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "97.754%"},
{"End Equity", "104486.22"},
{"Net Profit", "4.486%"},
{"Sharpe Ratio", "17.304"},
{"Sortino Ratio", "35.217"},
{"Probabilistic Sharpe Ratio", "96.835%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.005"},
{"Beta", "0.998"},
{"Annual Standard Deviation", "0.138"},
{"Annual Variance", "0.019"},
{"Information Ratio", "-34.028"},
{"Tracking Error", "0"},
{"Treynor Ratio", "2.644"},
{"Total Fees", "$3.45"},
{"Estimated Strategy Capacity", "$970000000.00"},
{"Alpha", "-0.249"},
{"Beta", "1.015"},
{"Annual Standard Deviation", "0.141"},
{"Annual Variance", "0.02"},
{"Information Ratio", "-19"},
{"Tracking Error", "0.011"},
{"Treynor Ratio", "2.403"},
{"Total Fees", "$3.49"},
{"Estimated Strategy Capacity", "$1200000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "10.09%"},
{"OrderListHash", "39a84b9f15bb4e8ead0f0ecb59f28562"}
{"Portfolio Turnover", "10.01%"},
{"OrderListHash", "70f21e930175a2ec9d465b21edc1b6d9"}
};
}
}

View File

@@ -0,0 +1,239 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using System;
using System.Collections.Generic;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
using QuantConnect.Orders;
using QuantConnect.Securities;
using QuantConnect.Securities.Future;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This algorithm tests and demonstrates EUREX futures subscription and trading:
/// - It tests contracts rollover by adding a continuous future and asserting that mapping happens at some point.
/// - It tests basic trading by buying a contract and holding it until expiration.
/// - It tests delisting and asserts the holdings are liquidated after that.
/// </summary>
public class BasicTemplateEurexFuturesAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Future _continuousContract;
private Symbol _mappedSymbol;
private Symbol _contractToTrade;
private int _mappingsCount;
private decimal _boughtQuantity;
private decimal _liquidatedQuantity;
private bool _delisted;
public override void Initialize()
{
SetStartDate(2024, 5, 30);
SetEndDate(2024, 6, 23);
SetAccountCurrency(Currencies.EUR);
SetCash(1000000);
_continuousContract = AddFuture(Futures.Indices.EuroStoxx50, Resolution.Minute,
dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
dataMappingMode: DataMappingMode.FirstDayMonth,
contractDepthOffset: 0);
_continuousContract.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(180));
_mappedSymbol = _continuousContract.Mapped;
var benchmark = AddIndex("SX5E", market: Market.EUREX);
SetBenchmark(benchmark.Symbol);
var seeder = new FuncSecuritySeeder(GetLastKnownPrices);
SetSecurityInitializer(security => seeder.SeedSecurity(security));
}
public override void OnData(Slice slice)
{
foreach (var changedEvent in slice.SymbolChangedEvents.Values)
{
if (++_mappingsCount > 1)
{
throw new RegressionTestException($"{Time} - Unexpected number of symbol changed events (mappings): {_mappingsCount}. " +
$"Expected only 1.");
}
Debug($"{Time} - SymbolChanged event: {changedEvent}");
if (changedEvent.OldSymbol != _mappedSymbol.ID.ToString())
{
throw new RegressionTestException($"{Time} - Unexpected symbol changed event old symbol: {changedEvent}");
}
if (changedEvent.NewSymbol != _continuousContract.Mapped.ID.ToString())
{
throw new RegressionTestException($"{Time} - Unexpected symbol changed event new symbol: {changedEvent}");
}
// Let's trade the previous mapped contract, so we can hold it until expiration for testing
// (will be sooner than the new mapped contract)
_contractToTrade = _mappedSymbol;
_mappedSymbol = _continuousContract.Mapped;
}
// Let's trade after the mapping is done
if (_contractToTrade != null && _boughtQuantity == 0 && Securities[_contractToTrade].Exchange.ExchangeOpen)
{
Buy(_contractToTrade, 1);
}
if (_contractToTrade != null && slice.Delistings.TryGetValue(_contractToTrade, out var delisting))
{
if (delisting.Type == DelistingType.Delisted)
{
_delisted = true;
if (Portfolio.Invested)
{
throw new RegressionTestException($"{Time} - Portfolio should not be invested after the traded contract is delisted.");
}
}
}
}
public override void OnOrderEvent(OrderEvent orderEvent)
{
if (orderEvent.Symbol != _contractToTrade)
{
throw new RegressionTestException($"{Time} - Unexpected order event symbol: {orderEvent.Symbol}. Expected {_contractToTrade}");
}
if (orderEvent.Direction == OrderDirection.Buy)
{
if (orderEvent.Status == OrderStatus.Filled)
{
if (_boughtQuantity != 0 && _liquidatedQuantity != 0)
{
throw new RegressionTestException($"{Time} - Unexpected buy order event status: {orderEvent.Status}");
}
_boughtQuantity = orderEvent.Quantity;
}
}
else if (orderEvent.Direction == OrderDirection.Sell)
{
if (orderEvent.Status == OrderStatus.Filled)
{
if (_boughtQuantity <= 0 && _liquidatedQuantity != 0)
{
throw new RegressionTestException($"{Time} - Unexpected sell order event status: {orderEvent.Status}");
}
_liquidatedQuantity = orderEvent.Quantity;
if (_liquidatedQuantity != -_boughtQuantity)
{
throw new RegressionTestException($"{Time} - Unexpected liquidated quantity: {_liquidatedQuantity}. Expected: {-_boughtQuantity}");
}
}
}
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
foreach (var addedSecurity in changes.AddedSecurities)
{
if (addedSecurity.Symbol.SecurityType == SecurityType.Future && addedSecurity.Symbol.IsCanonical())
{
_mappedSymbol = _continuousContract.Mapped;
}
}
}
public override void OnEndOfAlgorithm()
{
if (_mappingsCount == 0)
{
throw new RegressionTestException($"Unexpected number of symbol changed events (mappings): {_mappingsCount}. Expected 1.");
}
if (!_delisted)
{
throw new RegressionTestException("Contract was not delisted");
}
// Make sure we traded and that the position was liquidated on delisting
if (_boughtQuantity <= 0 || _liquidatedQuantity >= 0)
{
throw new RegressionTestException($"Unexpected sold quantity: {_boughtQuantity} and liquidated quantity: {_liquidatedQuantity}");
}
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; } = true;
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 133947;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 26;
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "2"},
{"Average Win", "0%"},
{"Average Loss", "-0.11%"},
{"Compounding Annual Return", "-1.667%"},
{"Drawdown", "0.100%"},
{"Expectancy", "-1"},
{"Start Equity", "1000000"},
{"End Equity", "998849.48"},
{"Net Profit", "-0.115%"},
{"Sharpe Ratio", "-34.455"},
{"Sortino Ratio", "-57.336"},
{"Probabilistic Sharpe Ratio", "0.002%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0.002"},
{"Annual Variance", "0"},
{"Information Ratio", "-6.176"},
{"Tracking Error", "0.002"},
{"Treynor Ratio", "0"},
{"Total Fees", "€1.02"},
{"Estimated Strategy Capacity", "€2300000000.00"},
{"Lowest Capacity Asset", "FESX YJHOAMPYKRS5"},
{"Portfolio Turnover", "0.40%"},
{"OrderListHash", "54040d29a467becaedcf59d79323321b"}
};
}
}

View File

@@ -13,6 +13,7 @@
* limitations under the License.
*/
using QuantConnect.Data;
using QuantConnect.Data.Market;
namespace QuantConnect.Algorithm.CSharp
@@ -41,8 +42,8 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
/// </summary>
/// <param name="data">TradeBars IDictionary object with your stock data</param>
public void OnData(TradeBars data)
/// <param name="slice">Slice object keyed by symbol containing the stock data</param>
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{

View File

@@ -176,12 +176,12 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 1325;
public long DataPoints => 1199;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 4;
public int AlgorithmHistoryDataPoints => 2;
/// <summary>
/// Final status of the algorithm
@@ -193,33 +193,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "2"},
{"Average Win", "0.53%"},
{"Total Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "3.011%"},
{"Compounding Annual Return", "-0.010%"},
{"Drawdown", "0.000%"},
{"Expectancy", "0"},
{"Start Equity", "1000000"},
{"End Equity", "1005283.2"},
{"Net Profit", "0.528%"},
{"Sharpe Ratio", "1.285"},
{"End Equity", "999983.2"},
{"Net Profit", "-0.002%"},
{"Sharpe Ratio", "-225.214"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "83.704%"},
{"Probabilistic Sharpe Ratio", "0.135%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.015"},
{"Beta", "-0.004"},
{"Annual Standard Deviation", "0.011"},
{"Alpha", "-0.008"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "-4.774"},
{"Tracking Error", "0.084"},
{"Treynor Ratio", "-3.121"},
{"Total Fees", "$4.30"},
{"Estimated Strategy Capacity", "$5900000000.00"},
{"Information Ratio", "-5.146"},
{"Tracking Error", "0.083"},
{"Treynor Ratio", "-542.359"},
{"Total Fees", "$2.15"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
{"Portfolio Turnover", "0.27%"},
{"OrderListHash", "90f952729deb9cb20be75867576e5b87"}
{"Portfolio Turnover", "0.13%"},
{"OrderListHash", "273dd05b937c075b75baf8af46d3c7de"}
};
}
}

View File

@@ -83,7 +83,7 @@ namespace QuantConnect.Algorithm.CSharp
// if found, trade it.
// Also check if exchange is open for regular or extended hours. Since daily data comes at 8PM, this allows us prevent the
// algorithm from trading on friday when there is not after-market.
if (contract != null && Securities[contract.Symbol].Exchange.Hours.IsOpen(Time, true))
if (contract != null)
{
MarketOrder(contract.Symbol, 1);
}
@@ -117,7 +117,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public virtual long DataPoints => 13934;
public virtual long DataPoints => 12455;
/// <summary>
/// Data Points count of the algorithm history
@@ -134,33 +134,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "128"},
{"Average Win", "0.26%"},
{"Average Loss", "-0.01%"},
{"Compounding Annual Return", "-0.071%"},
{"Drawdown", "0.400%"},
{"Expectancy", "-0.116"},
{"Total Orders", "34"},
{"Average Win", "0.33%"},
{"Average Loss", "-0.04%"},
{"Compounding Annual Return", "0.106%"},
{"Drawdown", "0.300%"},
{"Expectancy", "0.178"},
{"Start Equity", "1000000"},
{"End Equity", "999287.06"},
{"Net Profit", "-0.071%"},
{"Sharpe Ratio", "-1.999"},
{"Sortino Ratio", "-1.806"},
{"Probabilistic Sharpe Ratio", "10.091%"},
{"Loss Rate", "97%"},
{"Win Rate", "3%"},
{"Profit-Loss Ratio", "27.29"},
{"Alpha", "-0.008"},
{"Beta", "0.001"},
{"End Equity", "1001066.2"},
{"Net Profit", "0.107%"},
{"Sharpe Ratio", "-1.695"},
{"Sortino Ratio", "-0.804"},
{"Probabilistic Sharpe Ratio", "14.797%"},
{"Loss Rate", "88%"},
{"Win Rate", "12%"},
{"Profit-Loss Ratio", "9.01"},
{"Alpha", "-0.007"},
{"Beta", "0.002"},
{"Annual Standard Deviation", "0.004"},
{"Annual Variance", "0"},
{"Information Ratio", "-1.367"},
{"Information Ratio", "-1.353"},
{"Tracking Error", "0.089"},
{"Treynor Ratio", "-5.445"},
{"Total Fees", "$285.44"},
{"Estimated Strategy Capacity", "$1000.00"},
{"Treynor Ratio", "-4.112"},
{"Total Fees", "$76.30"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", "ES VRJST036ZY0X"},
{"Portfolio Turnover", "3.41%"},
{"OrderListHash", "394c47e4e0f54c5981d7c8aa99e9bc83"}
{"Portfolio Turnover", "0.92%"},
{"OrderListHash", "7afa589d648c3f24253cd59156a2014e"}
};
}
}

View File

@@ -41,7 +41,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 163415;
public override long DataPoints => 163416;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

View File

@@ -41,40 +41,40 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 87289;
public override long DataPoints => 87292;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "638"},
{"Average Win", "0.02%"},
{"Total Orders", "716"},
{"Average Win", "0.03%"},
{"Average Loss", "-0.01%"},
{"Compounding Annual Return", "-1.610%"},
{"Drawdown", "1.600%"},
{"Expectancy", "-0.841"},
{"Compounding Annual Return", "-1.716%"},
{"Drawdown", "1.700%"},
{"Expectancy", "-0.770"},
{"Start Equity", "1000000"},
{"End Equity", "983783.82"},
{"Net Profit", "-1.622%"},
{"Sharpe Ratio", "-8.787"},
{"Sortino Ratio", "-5.428"},
{"End Equity", "982718.38"},
{"Net Profit", "-1.728%"},
{"Sharpe Ratio", "-8.845"},
{"Sortino Ratio", "-5.449"},
{"Probabilistic Sharpe Ratio", "0.000%"},
{"Loss Rate", "96%"},
{"Win Rate", "4%"},
{"Profit-Loss Ratio", "3.21"},
{"Profit-Loss Ratio", "4.89"},
{"Alpha", "-0.018"},
{"Beta", "-0.003"},
{"Beta", "-0.002"},
{"Annual Standard Deviation", "0.002"},
{"Annual Variance", "0"},
{"Information Ratio", "-1.473"},
{"Information Ratio", "-1.483"},
{"Tracking Error", "0.089"},
{"Treynor Ratio", "5.593"},
{"Total Fees", "$1456.18"},
{"Estimated Strategy Capacity", "$9000.00"},
{"Treynor Ratio", "9.102"},
{"Total Fees", "$1634.12"},
{"Estimated Strategy Capacity", "$8000.00"},
{"Lowest Capacity Asset", "ES VP274HSU1AF5"},
{"Portfolio Turnover", "17.91%"},
{"OrderListHash", "b5214a0fcd0694093aa2a478a983de1a"}
{"Portfolio Turnover", "20.10%"},
{"OrderListHash", "aa7e574f86b70428ca0afae381be80ba"}
};
}
}

View File

@@ -14,14 +14,7 @@
*
*/
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Orders;
using QuantConnect.Securities;
using QuantConnect.Securities.Future;
namespace QuantConnect.Algorithm.CSharp
{
@@ -43,40 +36,40 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 16161;
public override long DataPoints => 14884;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "156"},
{"Average Win", "0.31%"},
{"Average Loss", "-0.01%"},
{"Compounding Annual Return", "-0.024%"},
{"Drawdown", "0.400%"},
{"Expectancy", "-0.035"},
{"Total Orders", "32"},
{"Average Win", "0.33%"},
{"Average Loss", "-0.04%"},
{"Compounding Annual Return", "0.110%"},
{"Drawdown", "0.300%"},
{"Expectancy", "0.184"},
{"Start Equity", "1000000"},
{"End Equity", "999754.94"},
{"Net Profit", "-0.025%"},
{"Sharpe Ratio", "-1.602"},
{"Sortino Ratio", "-1.913"},
{"Probabilistic Sharpe Ratio", "11.172%"},
{"Loss Rate", "97%"},
{"Win Rate", "3%"},
{"Profit-Loss Ratio", "36.65"},
{"End Equity", "1001108"},
{"Net Profit", "0.111%"},
{"Sharpe Ratio", "-1.688"},
{"Sortino Ratio", "-0.772"},
{"Probabilistic Sharpe Ratio", "14.944%"},
{"Loss Rate", "88%"},
{"Win Rate", "12%"},
{"Profit-Loss Ratio", "8.47"},
{"Alpha", "-0.007"},
{"Beta", "-0.001"},
{"Annual Standard Deviation", "0.005"},
{"Beta", "0.002"},
{"Annual Standard Deviation", "0.004"},
{"Annual Variance", "0"},
{"Information Ratio", "-1.359"},
{"Information Ratio", "-1.353"},
{"Tracking Error", "0.089"},
{"Treynor Ratio", "8.008"},
{"Total Fees", "$347.56"},
{"Estimated Strategy Capacity", "$1000.00"},
{"Treynor Ratio", "-4.099"},
{"Total Fees", "$72.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", "ES VRJST036ZY0X"},
{"Portfolio Turnover", "4.16%"},
{"OrderListHash", "52580f1e94ab1875301d3bbd157f4580"}
{"Portfolio Turnover", "0.87%"},
{"OrderListHash", "ef59fd5e4a7ae483a60d25736cf5d2d8"}
};
}
}

View File

@@ -41,24 +41,24 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 228834;
public override long DataPoints => 228935;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "1990"},
{"Total Orders", "1992"},
{"Average Win", "0.01%"},
{"Average Loss", "-0.01%"},
{"Compounding Annual Return", "-4.683%"},
{"Compounding Annual Return", "-4.687%"},
{"Drawdown", "4.700%"},
{"Expectancy", "-0.911"},
{"Start Equity", "1000000"},
{"End Equity", "952831.02"},
{"Net Profit", "-4.717%"},
{"Sharpe Ratio", "-7.178"},
{"Sortino Ratio", "-5.126"},
{"End Equity", "952789.22"},
{"Net Profit", "-4.721%"},
{"Sharpe Ratio", "-7.183"},
{"Sortino Ratio", "-5.14"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "97%"},
{"Win Rate", "3%"},
@@ -69,12 +69,12 @@ namespace QuantConnect.Algorithm.CSharp
{"Annual Variance", "0"},
{"Information Ratio", "-1.702"},
{"Tracking Error", "0.09"},
{"Treynor Ratio", "5.049"},
{"Total Fees", "$4538.98"},
{"Treynor Ratio", "5.054"},
{"Total Fees", "$4543.28"},
{"Estimated Strategy Capacity", "$3000.00"},
{"Lowest Capacity Asset", "ES VP274HSU1AF5"},
{"Portfolio Turnover", "56.68%"},
{"OrderListHash", "60f85901ecc345e597c0153506792285"}
{"Portfolio Turnover", "56.73%"},
{"OrderListHash", "424536177e9be5895bab50638ef43a9d"}
};
}
}

View File

@@ -61,8 +61,8 @@ namespace QuantConnect.Algorithm.CSharp
AddIndexOptionContract(SpxOption, Resolution);
_emaSlow = EMA(Spx, 80);
_emaFast = EMA(Spx, 200);
_emaSlow = EMA(Spx, Resolution > Resolution.Minute ? 6 : 80);
_emaFast = EMA(Spx, Resolution > Resolution.Minute ? 2 : 200);
Settings.DailyPreciseEndTime = true;
}
@@ -93,12 +93,25 @@ namespace QuantConnect.Algorithm.CSharp
}
}
/// <summary>
/// Asserts indicators are ready
/// </summary>
/// <exception cref="RegressionTestException"></exception>
protected void AssertIndicators()
{
if (!_emaSlow.IsReady || !_emaFast.IsReady)
{
throw new RegressionTestException("Indicators are not ready!");
}
}
public override void OnEndOfAlgorithm()
{
if (Portfolio[Spx].TotalSaleVolume > 0)
{
throw new RegressionTestException("Index is not tradable.");
}
AssertIndicators();
}
/// <summary>

View File

@@ -62,6 +62,7 @@ namespace QuantConnect.Algorithm.CSharp
{
throw new ArgumentException($"Bar Count {BarCounter} is not expected count of {ExpectedBarCount}");
}
AssertIndicators();
if (Resolution != Resolution.Daily)
{

View File

@@ -14,7 +14,6 @@
*
*/
using System;
using QuantConnect.Data;
using System.Collections.Generic;
using QuantConnect.Indicators;
@@ -48,8 +47,8 @@ namespace QuantConnect.Algorithm.CSharp
var spxOptions = AddIndexOption(_spx, Resolution);
spxOptions.SetFilter(filterFunc => filterFunc.CallsOnly());
_emaSlow = EMA(_spx, 80);
_emaFast = EMA(_spx, 200);
_emaSlow = EMA(_spx, Resolution > Resolution.Minute ? 6 : 80);
_emaFast = EMA(_spx, Resolution > Resolution.Minute ? 2 : 200);
Settings.DailyPreciseEndTime = true;
}
@@ -110,6 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
{
throw new RegressionTestException("Trade volume should be greater than zero by the end of this algorithm");
}
AssertIndicators();
}
public Symbol InvertOption(Symbol symbol)
@@ -123,6 +123,18 @@ namespace QuantConnect.Algorithm.CSharp
symbol.ID.Date);
}
/// <summary>
/// Asserts indicators are ready
/// </summary>
/// <exception cref="RegressionTestException"></exception>
protected void AssertIndicators()
{
if (!_emaSlow.IsReady || !_emaFast.IsReady)
{
throw new RegressionTestException("Indicators are not ready!");
}
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>

View File

@@ -67,7 +67,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 378;
public override long DataPoints => 356;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -38,7 +38,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 2163;
public override long DataPoints => 1269;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -102,7 +102,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 471135;
public long DataPoints => 15023;
/// <summary>
/// Data Points count of the algorithm history
@@ -142,7 +142,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$26.00"},
{"Estimated Strategy Capacity", "$70000.00"},
{"Estimated Strategy Capacity", "$69000.00"},
{"Lowest Capacity Asset", "GOOCV W78ZERHAOVVQ|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "61.31%"},
{"OrderListHash", "35d406df401e5b27244e20f5ec57346e"}

View File

@@ -112,7 +112,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 471124;
public long DataPoints => 15130;
/// <summary>
/// Data Points count of the algorithm history
@@ -152,7 +152,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$543.40"},
{"Estimated Strategy Capacity", "$3000.00"},
{"Estimated Strategy Capacity", "$4000.00"},
{"Lowest Capacity Asset", "GOOCV W78ZFMEBBB2E|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "338.60%"},
{"OrderListHash", "301c15063f6e269023d144ca69a765da"}

View File

@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 471124;
public long DataPoints => 15012;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -34,21 +34,21 @@ namespace QuantConnect.Algorithm.CSharp
/// <meta name="tag" content="filter selection" />
public class BasicTemplateOptionsDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private const string UnderlyingTicker = "GOOG";
private const string UnderlyingTicker = "AAPL";
private Symbol _optionSymbol;
private bool _optionExpired;
public override void Initialize()
{
SetStartDate(2015, 12, 23);
SetEndDate(2016, 1, 20);
SetStartDate(2015, 12, 15);
SetEndDate(2016, 2, 1);
SetCash(100000);
var equity = AddEquity(UnderlyingTicker, Resolution.Daily);
var option = AddOption(UnderlyingTicker, Resolution.Daily);
_optionSymbol = option.Symbol;
option.SetFilter(x => x.CallsOnly().Strikes(0, 1).Expiration(0, 30));
option.SetFilter(x => x.CallsOnly().Expiration(0, 60));
// use the underlying equity as the benchmark
SetBenchmark(equity.Symbol);
@@ -122,7 +122,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 36834;
public long DataPoints => 308;
/// <summary>
/// Data Points count of the algorithm history
@@ -141,31 +141,31 @@ namespace QuantConnect.Algorithm.CSharp
{
{"Total Orders", "2"},
{"Average Win", "0%"},
{"Average Loss", "-1.31%"},
{"Compounding Annual Return", "-15.304%"},
{"Drawdown", "1.300%"},
{"Average Loss", "-1.16%"},
{"Compounding Annual Return", "-8.351%"},
{"Drawdown", "1.200%"},
{"Expectancy", "-1"},
{"Start Equity", "100000"},
{"End Equity", "98689"},
{"Net Profit", "-1.311%"},
{"Sharpe Ratio", "-3.607"},
{"Sortino Ratio", "-1.188"},
{"Probabilistic Sharpe Ratio", "0.035%"},
{"End Equity", "98844"},
{"Net Profit", "-1.156%"},
{"Sharpe Ratio", "-4.04"},
{"Sortino Ratio", "-2.422"},
{"Probabilistic Sharpe Ratio", "0.099%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0.034"},
{"Annual Variance", "0.001"},
{"Information Ratio", "-3.31"},
{"Tracking Error", "0.034"},
{"Treynor Ratio", "0"},
{"Alpha", "-0.058"},
{"Beta", "0.021"},
{"Annual Standard Deviation", "0.017"},
{"Annual Variance", "0"},
{"Information Ratio", "1.49"},
{"Tracking Error", "0.289"},
{"Treynor Ratio", "-3.212"},
{"Total Fees", "$1.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", "GOOCV W78ZFMML01JA|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "0.05%"},
{"OrderListHash", "e188868e048fab6b6a0481b4479e97f9"}
{"Estimated Strategy Capacity", "$72000.00"},
{"Lowest Capacity Asset", "AAPL W78ZEO2985GM|AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "0.02%"},
{"OrderListHash", "b3125e0af79da0f5eea4cfda09806324"}
};
}
}

View File

@@ -14,7 +14,6 @@
*
*/
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
@@ -100,7 +99,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 1252633;
public long DataPoints => 12290;
/// <summary>
/// Data Points count of the algorithm history
@@ -120,7 +119,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "2"},
{"Average Win", "0%"},
{"Average Loss", "-0.40%"},
{"Compounding Annual Return", "-21.622%"},
{"Compounding Annual Return", "-20.338%"},
{"Drawdown", "0.300%"},
{"Expectancy", "-1"},
{"Start Equity", "100000"},

View File

@@ -139,7 +139,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 1847643;
public long DataPoints => 17486;
/// <summary>
/// Data Points count of the algorithm history
@@ -157,32 +157,32 @@ namespace QuantConnect.Algorithm.CSharp
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "5"},
{"Average Win", "0.14%"},
{"Average Loss", "-0.28%"},
{"Compounding Annual Return", "-47.543%"},
{"Average Win", "0.13%"},
{"Average Loss", "-0.30%"},
{"Compounding Annual Return", "-46.395%"},
{"Drawdown", "1.600%"},
{"Expectancy", "0.502"},
{"Expectancy", "0.429"},
{"Start Equity", "100000"},
{"End Equity", "99178.50"},
{"Net Profit", "-0.821%"},
{"Sharpe Ratio", "-4.136"},
{"End Equity", "99149.50"},
{"Net Profit", "-0.850%"},
{"Sharpe Ratio", "-4.298"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "17.155%"},
{"Probabilistic Sharpe Ratio", "15.319%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0.50"},
{"Alpha", "-0.855"},
{"Beta", "1.047"},
{"Annual Standard Deviation", "0.099"},
{"Profit-Loss Ratio", "0.43"},
{"Alpha", "-0.84"},
{"Beta", "0.986"},
{"Annual Standard Deviation", "0.098"},
{"Annual Variance", "0.01"},
{"Information Ratio", "-9.141"},
{"Information Ratio", "-9.299"},
{"Tracking Error", "0.091"},
{"Treynor Ratio", "-0.392"},
{"Treynor Ratio", "-0.428"},
{"Total Fees", "$4.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "13.49%"},
{"OrderListHash", "2722fee93126736e03d66d7ab880b537"}
{"Portfolio Turnover", "13.50%"},
{"OrderListHash", "cf14a7ce9c86e6844051820fd4c9394c"}
};
}
}

View File

@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 32351;
public long DataPoints => 9504;
/// <summary>
/// Data Points count of the algorithm history
@@ -129,7 +129,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "5"},
{"Average Win", "0%"},
{"Average Loss", "-0.07%"},
{"Compounding Annual Return", "-12.496%"},
{"Compounding Annual Return", "-11.517%"},
{"Drawdown", "0.200%"},
{"Expectancy", "-1"},
{"Start Equity", "100000"},

View File

@@ -43,14 +43,12 @@ namespace QuantConnect.Algorithm.CSharp
SetEndDate(2021, 1, 10);
SetCash(1000000);
var spx = AddIndex("SPX").Symbol;
// regular option SPX contracts
var spxOptions = AddIndexOption(spx);
var spxOptions = AddIndexOption("SPX");
spxOptions.SetFilter(u => u.Strikes(0, 1).Expiration(0, 30));
// weekly option SPX contracts
var spxw = AddIndexOption(spx, "SPXW");
var spxw = AddIndexOption("SPX", "SPXW");
spxw.SetFilter(u => u.Strikes(0, 1)
// single week ahead since there are many SPXW contracts and we want to preserve performance
.Expiration(0, 7)
@@ -105,7 +103,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public virtual long DataPoints => 57869;
public virtual long DataPoints => 21467;
/// <summary>
/// Data Points count of the algorithm history
@@ -125,29 +123,29 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "5"},
{"Average Win", "0%"},
{"Average Loss", "-0.69%"},
{"Compounding Annual Return", "59.804%"},
{"Compounding Annual Return", "54.478%"},
{"Drawdown", "0.400%"},
{"Expectancy", "-0.5"},
{"Start Equity", "1000000"},
{"End Equity", "1006025"},
{"Net Profit", "0.602%"},
{"Sharpe Ratio", "3.01"},
{"Sharpe Ratio", "2.62"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "62.865%"},
{"Probabilistic Sharpe Ratio", "63.221%"},
{"Loss Rate", "50%"},
{"Win Rate", "50%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.249"},
{"Beta", "-0.033"},
{"Alpha", "0.067"},
{"Beta", "-0.013"},
{"Annual Standard Deviation", "0.004"},
{"Annual Variance", "0"},
{"Information Ratio", "-99.414"},
{"Tracking Error", "0.072"},
{"Treynor Ratio", "-0.382"},
{"Information Ratio", "-50.808"},
{"Tracking Error", "0.086"},
{"Treynor Ratio", "-0.725"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$580000.00"},
{"Lowest Capacity Asset", "SPXW 31K54PVWHUJHQ|SPX 31"},
{"Portfolio Turnover", "0.48%"},
{"Portfolio Turnover", "0.40%"},
{"OrderListHash", "07a085baedb37bb7c8d460558ea77e88"}
};
}

View File

@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public virtual long DataPoints => 40968;
public virtual long DataPoints => 16680;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -15,6 +15,7 @@
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.Fundamental;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
@@ -68,8 +69,8 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
return topFine.Select(x => x.Symbol);
}
//Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol.
public void OnData(TradeBars data)
//Data Event Handler: New data arrives here.
public override void OnData(Slice slice)
{
// if we have no changes, do nothing
if (_changes == SecurityChanges.None) return;

View File

@@ -16,6 +16,7 @@
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Indicators;
@@ -58,7 +59,7 @@ namespace QuantConnect.Algorithm.CSharp.Benchmarks
}).ToArray();
}
public void OnData(TradeBars data)
public override void OnData(Slice slice)
{
// wait for our entire ribbon to be ready
if (!_ribbon.All(x => x.IsReady)) return;

View File

@@ -93,33 +93,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "14"},
{"Average Win", "0%"},
{"Average Loss", "-0.23%"},
{"Compounding Annual Return", "63.336%"},
{"Total Orders", "22"},
{"Average Win", "0.00%"},
{"Average Loss", "-0.14%"},
{"Compounding Annual Return", "71.152%"},
{"Drawdown", "1.100%"},
{"Expectancy", "-1"},
{"Expectancy", "-0.797"},
{"Start Equity", "100000"},
{"End Equity", "100674.37"},
{"Net Profit", "0.674%"},
{"Sharpe Ratio", "3.986"},
{"End Equity", "100738.86"},
{"Net Profit", "0.739%"},
{"Sharpe Ratio", "4.46"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "58.892%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.595"},
{"Beta", "0.57"},
{"Probabilistic Sharpe Ratio", "60.106%"},
{"Loss Rate", "80%"},
{"Win Rate", "20%"},
{"Profit-Loss Ratio", "0.02"},
{"Alpha", "-0.552"},
{"Beta", "0.579"},
{"Annual Standard Deviation", "0.133"},
{"Annual Variance", "0.018"},
{"Information Ratio", "-13.918"},
{"Tracking Error", "0.104"},
{"Treynor Ratio", "0.93"},
{"Total Fees", "$40.20"},
{"Estimated Strategy Capacity", "$4400000.00"},
{"Information Ratio", "-13.953"},
{"Tracking Error", "0.099"},
{"Treynor Ratio", "1.024"},
{"Total Fees", "$46.24"},
{"Estimated Strategy Capacity", "$2600000.00"},
{"Lowest Capacity Asset", "AIG R735QTJ8XC9X"},
{"Portfolio Turnover", "64.47%"},
{"OrderListHash", "fa0af3b345296ccc41e25c0b6c30fc96"}
{"Portfolio Turnover", "69.06%"},
{"OrderListHash", "44a85134cd1c91c9720549bc0e007f80"}
};
}
}

View File

@@ -14,6 +14,7 @@
*/
using QuantConnect.Brokerages;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Orders;
using QuantConnect.Securities;
@@ -58,8 +59,8 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
/// </summary>
/// <param name="data">TradeBars IDictionary object with your stock data</param>
public void OnData(TradeBars data)
/// <param name="slice">Slice object keyed by symbol containing the stock data</param>
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{

View File

@@ -116,9 +116,9 @@ namespace QuantConnect.Algorithm.CSharp
}
/// <summary>
/// New TradeBar data for our assets.
/// New data for our assets.
/// </summary>
public void OnData(TradeBars data)
public override void OnData(Slice slice)
{
try
{

View File

@@ -0,0 +1,159 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
using System;
using QuantConnect.Commands;
using QuantConnect.Interfaces;
using System.Collections.Generic;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm asserting the behavior of different callback commands call
/// </summary>
public class CallbackCommandRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
/// <summary>
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
/// </summary>
public override void Initialize()
{
SetStartDate(2013, 10, 07);
SetEndDate(2013, 10, 11);
AddEquity("SPY");
AddEquity("BAC");
AddEquity("IBM");
AddCommand<BoolCommand>();
AddCommand<VoidCommand>();
var potentialCommand = new VoidCommand
{
Target = new[] { "BAC" },
Quantity = 10,
Parameters = new() { { "tag", "Signal X" } }
};
var commandLink = Link(potentialCommand);
Notify.Email("email@address", "Trade Command Event", $"Signal X trade\nFollow link to trigger: {commandLink}");
var commandLink2 = Link(new { Symbol = "SPY", Parameters = new Dictionary<string, int>() { { "Quantity", 10 } } });
Notify.Email("email@address", "Untyped Command Event", $"Signal Y trade\nFollow link to trigger: {commandLink2}");
}
/// <summary>
/// Handle generic command callback
/// </summary>
public override bool? OnCommand(dynamic data)
{
Buy(data.Symbol, data.parameters["quantity"]);
return true;
}
private class VoidCommand : Command
{
public DateTime TargetTime { get; set; }
public string[] Target { get; set; }
public decimal Quantity { get; set; }
public Dictionary<string, string> Parameters { get; set; }
public override bool? Run(IAlgorithm algorithm)
{
if (TargetTime != algorithm.Time)
{
return null;
}
((QCAlgorithm)algorithm).Order(Target[0], Quantity, tag: Parameters["tag"]);
return null;
}
}
private class BoolCommand : Command
{
public bool? Result { get; set; }
public override bool? Run(IAlgorithm algorithm)
{
var shouldTrade = MyCustomMethod();
if (shouldTrade.HasValue && shouldTrade.Value)
{
((QCAlgorithm)algorithm).Buy("IBM", 1);
}
return shouldTrade;
}
private bool? MyCustomMethod()
{
return Result;
}
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; }
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 3943;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "271.453%"},
{"Drawdown", "2.200%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "101691.92"},
{"Net Profit", "1.692%"},
{"Sharpe Ratio", "8.854"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "67.609%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.005"},
{"Beta", "0.996"},
{"Annual Standard Deviation", "0.222"},
{"Annual Variance", "0.049"},
{"Information Ratio", "-14.565"},
{"Tracking Error", "0.001"},
{"Treynor Ratio", "1.97"},
{"Total Fees", "$3.44"},
{"Estimated Strategy Capacity", "$56000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "19.93%"},
{"OrderListHash", "3da9fa60bf95b9ed148b95e02e0cfc9e"}
};
}
}

View File

@@ -15,6 +15,7 @@
using QuantConnect.Interfaces;
using System.Collections.Generic;
using QuantConnect.Data;
using QuantConnect.Data.Consolidators;
using QuantConnect.Data.Market;
@@ -71,7 +72,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// We're doing our analysis in the OnRenkoBar method, but the framework verifies that this method exists, so we define it.
/// </summary>
public void OnData(TradeBars data)
public override void OnData(Slice slice)
{
}
@@ -134,7 +135,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "29"},
{"Average Win", "1.85%"},
{"Average Loss", "-1.49%"},
{"Compounding Annual Return", "7.817%"},
{"Compounding Annual Return", "7.824%"},
{"Drawdown", "6.800%"},
{"Expectancy", "0.281"},
{"Start Equity", "100000"},
@@ -154,10 +155,10 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0.083"},
{"Treynor Ratio", "0.118"},
{"Total Fees", "$129.34"},
{"Estimated Strategy Capacity", "$1000000000.00"},
{"Estimated Strategy Capacity", "$2500000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "7.91%"},
{"OrderListHash", "cb118f22e33089e9ab4af8514e4f2b5f"}
{"OrderListHash", "2668157409450ab9949a71716a5dbc2e"}
};
}
}

View File

@@ -15,6 +15,7 @@
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.Fundamental;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
@@ -80,8 +81,8 @@ namespace QuantConnect.Algorithm.CSharp
return topFine.Select(x => x.Symbol);
}
//Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol.
public void OnData(TradeBars data)
//Data Event Handler: New data arrives here.
public override void OnData(Slice slice)
{
// if we have no changes, do nothing
if (_changes == SecurityChanges.None) return;

View File

@@ -177,32 +177,32 @@ namespace QuantConnect.Algorithm.CSharp
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "2"},
{"Average Win", "1.16%"},
{"Average Win", "1.39%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "32.505%"},
{"Compounding Annual Return", "40.025%"},
{"Drawdown", "1.400%"},
{"Expectancy", "0"},
{"Start Equity", "50000"},
{"End Equity", "50581.67"},
{"Net Profit", "1.163%"},
{"Sharpe Ratio", "2.666"},
{"Sortino Ratio", "19.179"},
{"Probabilistic Sharpe Ratio", "64.748%"},
{"End Equity", "50696.56"},
{"Net Profit", "1.393%"},
{"Sharpe Ratio", "3.192"},
{"Sortino Ratio", "4.952"},
{"Probabilistic Sharpe Ratio", "68.664%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.272"},
{"Beta", "0.436"},
{"Annual Standard Deviation", "0.086"},
{"Annual Variance", "0.007"},
{"Information Ratio", "3.572"},
{"Tracking Error", "0.092"},
{"Treynor Ratio", "0.523"},
{"Alpha", "0.328"},
{"Beta", "0.474"},
{"Annual Standard Deviation", "0.088"},
{"Annual Variance", "0.008"},
{"Information Ratio", "4.219"},
{"Tracking Error", "0.09"},
{"Treynor Ratio", "0.59"},
{"Total Fees", "$2.00"},
{"Estimated Strategy Capacity", "$49000000.00"},
{"Estimated Strategy Capacity", "$81000000.00"},
{"Lowest Capacity Asset", "IBM R735QTJ8XC9X"},
{"Portfolio Turnover", "6.64%"},
{"OrderListHash", "69614ad86028ebc190bff5fb42795a3f"}
{"Portfolio Turnover", "6.65%"},
{"OrderListHash", "4eaacdd341a5be0d04cb32647d931471"}
};
}
}

View File

@@ -48,7 +48,12 @@ namespace QuantConnect.Algorithm.CSharp
UniverseSettings.Resolution = Resolution.Minute;
SetStartDate(2014, 06, 04);
SetEndDate(2014, 06, 06);
// TWX is selected the 4th and 5th and aapl after that.
// If the algo ends on the 6th, TWX subscriptions will not be removed before OnEndOfAlgorithm is called:
// - 6th: AAPL is selected, TWX is removed but subscriptions are not removed because the securities are invested.
// - TWX and its options are liquidated.
// - 7th: Since options universe selection is daily now, TWX subscriptions are removed the next day (7th)
SetEndDate(2014, 06, 07);
var selectionUniverse = AddUniverse(enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl },
enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl });
@@ -157,7 +162,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 998464;
public long DataPoints => 18993;
/// <summary>
/// Data Points count of the algorithm history
@@ -197,8 +202,8 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0.048"},
{"Treynor Ratio", "0.172"},
{"Total Fees", "$16.10"},
{"Estimated Strategy Capacity", "$3100000.00"},
{"Lowest Capacity Asset", "AOL VRKS95ENLBYE|AOL R735QTJ8XC9X"},
{"Estimated Strategy Capacity", "$5000000.00"},
{"Lowest Capacity Asset", "AOL R735QTJ8XC9X"},
{"Portfolio Turnover", "17.64%"},
{"OrderListHash", "a8605c1f5a9c67f60f1ddc963ec45542"}
};

View File

@@ -111,7 +111,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 35405;
public long DataPoints => 35402;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -118,7 +118,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 78091;
public long DataPoints => 78088;
/// <summary>
/// Data Points count of the algorithm history
@@ -136,32 +136,32 @@ namespace QuantConnect.Algorithm.CSharp
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "12"},
{"Average Win", "0.55%"},
{"Average Loss", "-0.26%"},
{"Compounding Annual Return", "16.717%"},
{"Drawdown", "1.700%"},
{"Expectancy", "0.850"},
{"Average Win", "0.63%"},
{"Average Loss", "-0.49%"},
{"Compounding Annual Return", "-35.851%"},
{"Drawdown", "2.700%"},
{"Expectancy", "-0.542"},
{"Start Equity", "50000"},
{"End Equity", "50318.65"},
{"Net Profit", "0.637%"},
{"Sharpe Ratio", "1.024"},
{"Sortino Ratio", "2.169"},
{"Probabilistic Sharpe Ratio", "50.223%"},
{"Loss Rate", "40%"},
{"Win Rate", "60%"},
{"Profit-Loss Ratio", "2.08"},
{"Alpha", "0.196"},
{"Beta", "0.741"},
{"Annual Standard Deviation", "0.118"},
{"Annual Variance", "0.014"},
{"Information Ratio", "2.294"},
{"Tracking Error", "0.097"},
{"Treynor Ratio", "0.163"},
{"Total Fees", "$27.94"},
{"Estimated Strategy Capacity", "$200000000.00"},
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "26.69%"},
{"OrderListHash", "82ca991c660ecefbcbdf0b4cc90ddd67"}
{"End Equity", "49096.01"},
{"Net Profit", "-1.808%"},
{"Sharpe Ratio", "-1.989"},
{"Sortino Ratio", "-3.359"},
{"Probabilistic Sharpe Ratio", "23.898%"},
{"Loss Rate", "80%"},
{"Win Rate", "20%"},
{"Profit-Loss Ratio", "1.29"},
{"Alpha", "-0.172"},
{"Beta", "1.068"},
{"Annual Standard Deviation", "0.141"},
{"Annual Variance", "0.02"},
{"Information Ratio", "-1.865"},
{"Tracking Error", "0.096"},
{"Treynor Ratio", "-0.263"},
{"Total Fees", "$26.72"},
{"Estimated Strategy Capacity", "$630000000.00"},
{"Lowest Capacity Asset", "FB V6OIPNZEM8V9"},
{"Portfolio Turnover", "24.59%"},
{"OrderListHash", "90b57d40d047eedbff7111d2a73a1290"}
};
}
}

View File

@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 70952;
public long DataPoints => 70951;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -13,12 +13,11 @@
* limitations under the License.
*/
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
using System.Collections.Generic;
using QuantConnect.Data.UniverseSelection;
namespace QuantConnect.Algorithm.CSharp
{
@@ -30,7 +29,7 @@ namespace QuantConnect.Algorithm.CSharp
public class CoarseSelectionTimeRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _spy;
private decimal _historyCoarseSpyPrice;
private decimal _spyPrice;
/// <summary>
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
@@ -53,7 +52,12 @@ namespace QuantConnect.Algorithm.CSharp
.Where(fundamental => fundamental.Symbol != _spy) // ignore spy
.Take(1);
_historyCoarseSpyPrice = History(_spy, 1).First().Close;
var historyCoarseSpyPrice = History(_spy, 1).First().Close;
if (_spyPrice != 0 && (historyCoarseSpyPrice == 0 || historyCoarseSpyPrice != _spyPrice))
{
throw new RegressionTestException($"Unexpected SPY price: {historyCoarseSpyPrice}");
}
_spyPrice = 0;
return top.Select(x => x.Symbol);
}
@@ -72,12 +76,9 @@ namespace QuantConnect.Algorithm.CSharp
{
throw new RegressionTestException($"Unexpected ActiveSecurities count: {ActiveSecurities.Count}");
}
// the price obtained by the previous coarse selection should be the same as the current price
if (_historyCoarseSpyPrice != 0 && _historyCoarseSpyPrice != Securities[_spy].Price)
{
throw new RegressionTestException($"Unexpected SPY price: {_historyCoarseSpyPrice}");
}
_historyCoarseSpyPrice = 0;
// we get the data at 4PM, selection happening at midnight
_spyPrice = Securities[_spy].Price;
if (!Portfolio.Invested)
{
SetHoldings(_spy, 1);
@@ -98,7 +99,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 49662;
public long DataPoints => 49660;
/// <summary>
/// Data Points count of the algorithm history
@@ -118,30 +119,30 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "57.657%"},
{"Drawdown", "1.000%"},
{"Compounding Annual Return", "36.033%"},
{"Drawdown", "1.300%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "101002.81"},
{"Net Profit", "1.003%"},
{"Sharpe Ratio", "5.273"},
{"Sortino Ratio", "7.973"},
{"Probabilistic Sharpe Ratio", "69.521%"},
{"End Equity", "100676.75"},
{"Net Profit", "0.677%"},
{"Sharpe Ratio", "2.646"},
{"Sortino Ratio", "2.77"},
{"Probabilistic Sharpe Ratio", "58.013%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "1.003"},
{"Annual Standard Deviation", "0.087"},
{"Annual Variance", "0.007"},
{"Information Ratio", "6.477"},
{"Tracking Error", "0"},
{"Treynor Ratio", "0.455"},
{"Total Fees", "$3.08"},
{"Estimated Strategy Capacity", "$720000000.00"},
{"Alpha", "-0.264"},
{"Beta", "1.183"},
{"Annual Standard Deviation", "0.103"},
{"Annual Variance", "0.011"},
{"Information Ratio", "-8.158"},
{"Tracking Error", "0.022"},
{"Treynor Ratio", "0.231"},
{"Total Fees", "$3.07"},
{"Estimated Strategy Capacity", "$930000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "12.54%"},
{"OrderListHash", "472e90ba189aaf55e0edab9087c3d8e7"}
{"Portfolio Turnover", "12.65%"},
{"OrderListHash", "87438e51988f37757a2d7f97389483ea"}
};
}
}

View File

@@ -70,7 +70,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 471135;
public override long DataPoints => 15023;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -136,7 +136,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 471135;
public override long DataPoints => 15023;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -52,7 +52,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 471135;
public override long DataPoints => 15023;
/// <summary>
/// Data Points count of the algorithm history
@@ -92,7 +92,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$26.00"},
{"Estimated Strategy Capacity", "$70000.00"},
{"Estimated Strategy Capacity", "$69000.00"},
{"Lowest Capacity Asset", "GOOCV W78ZERHAOVVQ|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "30.35%"},
{"OrderListHash", "615c795b0c450cb8e4c3cba803ebb180"}

View File

@@ -331,7 +331,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 471135;
public long DataPoints => 15023;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -86,33 +86,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "14"},
{"Average Win", "0.00%"},
{"Average Loss", "-0.23%"},
{"Compounding Annual Return", "-36.885%"},
{"Drawdown", "1.800%"},
{"Expectancy", "-0.549"},
{"Total Orders", "16"},
{"Average Win", "0.01%"},
{"Average Loss", "-0.18%"},
{"Compounding Annual Return", "-35.728%"},
{"Drawdown", "1.700%"},
{"Expectancy", "-0.690"},
{"Start Equity", "100000"},
{"End Equity", "99413.33"},
{"Net Profit", "-0.587%"},
{"Sharpe Ratio", "-2.494"},
{"Sortino Ratio", "-3.393"},
{"Probabilistic Sharpe Ratio", "34.321%"},
{"Loss Rate", "56%"},
{"Win Rate", "44%"},
{"Profit-Loss Ratio", "0.01"},
{"Alpha", "-0.888"},
{"Beta", "0.349"},
{"Annual Standard Deviation", "0.08"},
{"Annual Variance", "0.006"},
{"Information Ratio", "-14.897"},
{"Tracking Error", "0.146"},
{"Treynor Ratio", "-0.568"},
{"Total Fees", "$37.79"},
{"End Equity", "99436.42"},
{"Net Profit", "-0.564%"},
{"Sharpe Ratio", "-2.767"},
{"Sortino Ratio", "-3.388"},
{"Probabilistic Sharpe Ratio", "32.568%"},
{"Loss Rate", "70%"},
{"Win Rate", "30%"},
{"Profit-Loss Ratio", "0.03"},
{"Alpha", "-0.771"},
{"Beta", "0.296"},
{"Annual Standard Deviation", "0.068"},
{"Annual Variance", "0.005"},
{"Information Ratio", "-13.734"},
{"Tracking Error", "0.157"},
{"Treynor Ratio", "-0.632"},
{"Total Fees", "$39.85"},
{"Estimated Strategy Capacity", "$4700000.00"},
{"Lowest Capacity Asset", "AIG R735QTJ8XC9X"},
{"Portfolio Turnover", "60.65%"},
{"OrderListHash", "d84db24a398d074200c5ed979c4410f3"}
{"Portfolio Turnover", "60.79%"},
{"OrderListHash", "7a65de0f613e5c6161e410d499f45445"}
};
}
}

View File

@@ -22,6 +22,7 @@ using QuantConnect.Data.Market;
using QuantConnect.Indicators;
using QuantConnect.Interfaces;
using QuantConnect.Securities;
using QuantConnect.Securities.Future;
namespace QuantConnect.Algorithm.CSharp
{
@@ -31,69 +32,83 @@ namespace QuantConnect.Algorithm.CSharp
public class ConsolidateRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private List<int> _consolidationCounts;
private List<int> _expectedConsolidationCounts;
private List<SimpleMovingAverage> _smas;
private List<DateTime> _lastSmaUpdates;
private int _expectedConsolidations;
private int _customDataConsolidator;
private Symbol _symbol;
private int _customDataConsolidatorCount;
private Future _future;
/// <summary>
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
/// </summary>
public override void Initialize()
{
SetStartDate(2013, 10, 08);
SetEndDate(2013, 10, 20);
SetStartDate(2020, 01, 05);
SetEndDate(2020, 01, 20);
var SP500 = QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME);
_symbol = FutureChainProvider.GetFutureContractList(SP500, StartDate).First();
var security = AddFutureContract(_symbol);
var symbol = FutureChainProvider.GetFutureContractList(SP500, StartDate).First();
_future = AddFutureContract(symbol);
_consolidationCounts = Enumerable.Repeat(0, 9).ToList();
var tradableDatesCount = QuantConnect.Time.EachTradeableDayInTimeZone(_future.Exchange.Hours,
StartDate,
EndDate,
_future.Exchange.TimeZone,
false).Count();
_expectedConsolidationCounts = new(10);
Consolidate<QuoteBar>(symbol, time => new CalendarInfo(time.RoundDown(TimeSpan.FromDays(1)), TimeSpan.FromDays(1)),
bar => UpdateQuoteBar(bar, 0));
// The consolidator will respect the full 1 day bar span and will not consolidate the last tradable date,
// since scan will not be called at 202/01/21 12am
_expectedConsolidationCounts.Add(tradableDatesCount - 1);
Consolidate<QuoteBar>(symbol, time => new CalendarInfo(time.RoundDown(TimeSpan.FromDays(1)), TimeSpan.FromDays(1)),
TickType.Quote, bar => UpdateQuoteBar(bar, 1));
_expectedConsolidationCounts.Add(tradableDatesCount - 1);
Consolidate<QuoteBar>(symbol, TimeSpan.FromDays(1), bar => UpdateQuoteBar(bar, 2));
_expectedConsolidationCounts.Add(tradableDatesCount - 1);
Consolidate(symbol, Resolution.Daily, TickType.Quote, (Action<QuoteBar>)(bar => UpdateQuoteBar(bar, 3)));
_expectedConsolidationCounts.Add(tradableDatesCount);
Consolidate(symbol, TimeSpan.FromDays(1), bar => UpdateTradeBar(bar, 4));
_expectedConsolidationCounts.Add(tradableDatesCount - 1);
Consolidate<TradeBar>(symbol, TimeSpan.FromDays(1), bar => UpdateTradeBar(bar, 5));
_expectedConsolidationCounts.Add(tradableDatesCount - 1);
// Test using abstract T types, through defining a 'BaseData' handler
Consolidate(symbol, Resolution.Daily, null, (Action<BaseData>)(bar => UpdateBar(bar, 6)));
_expectedConsolidationCounts.Add(tradableDatesCount);
Consolidate(symbol, TimeSpan.FromDays(1), null, (Action<BaseData>)(bar => UpdateBar(bar, 7)));
_expectedConsolidationCounts.Add(tradableDatesCount - 1);
Consolidate(symbol, TimeSpan.FromDays(1), (Action<BaseData>)(bar => UpdateBar(bar, 8)));
_expectedConsolidationCounts.Add(tradableDatesCount - 1);
_consolidationCounts = Enumerable.Repeat(0, _expectedConsolidationCounts.Count).ToList();
_smas = _consolidationCounts.Select(_ => new SimpleMovingAverage(10)).ToList();
_lastSmaUpdates = _consolidationCounts.Select(_ => DateTime.MinValue).ToList();
Consolidate<QuoteBar>(_symbol, time => new CalendarInfo(time.RoundDown(TimeSpan.FromDays(1)), TimeSpan.FromDays(1)),
bar => UpdateQuoteBar(bar, 0));
Consolidate<QuoteBar>(_symbol, time => new CalendarInfo(time.RoundDown(TimeSpan.FromDays(1)), TimeSpan.FromDays(1)),
TickType.Quote, bar => UpdateQuoteBar(bar, 1));
Consolidate<QuoteBar>(_symbol, TimeSpan.FromDays(1), bar => UpdateQuoteBar(bar, 2));
Consolidate(_symbol, Resolution.Daily, TickType.Quote, (Action<QuoteBar>)(bar => UpdateQuoteBar(bar, 3)));
Consolidate(_symbol, TimeSpan.FromDays(1), bar => UpdateTradeBar(bar, 4));
Consolidate<TradeBar>(_symbol, TimeSpan.FromDays(1), bar => UpdateTradeBar(bar, 5));
// custom data
var symbol = AddData<CustomDataRegressionAlgorithm.Bitcoin>("BTC", Resolution.Minute).Symbol;
Consolidate<TradeBar>(symbol, TimeSpan.FromDays(1), bar => _customDataConsolidator++);
var customSecurity = AddData<CustomDataRegressionAlgorithm.Bitcoin>("BTC", Resolution.Minute);
Consolidate<TradeBar>(customSecurity.Symbol, TimeSpan.FromDays(1), bar => _customDataConsolidatorCount++);
try
{
Consolidate<QuoteBar>(symbol, TimeSpan.FromDays(1), bar => { UpdateQuoteBar(bar, -1); });
Consolidate<QuoteBar>(customSecurity.Symbol, TimeSpan.FromDays(1), bar => { UpdateQuoteBar(bar, -1); });
throw new RegressionTestException($"Expected {nameof(ArgumentException)} to be thrown");
}
catch (ArgumentException)
{
// will try to use BaseDataConsolidator for which input is TradeBars not QuoteBars
}
// Test using abstract T types, through defining a 'BaseData' handler
Consolidate(_symbol, Resolution.Daily, null, (Action<BaseData>)(bar => UpdateBar(bar, 6)));
Consolidate(_symbol, TimeSpan.FromDays(1), null, (Action<BaseData>)(bar => UpdateBar(bar, 7)));
Consolidate(_symbol, TimeSpan.FromDays(1), (Action<BaseData>)(bar => UpdateBar(bar, 8)));
_expectedConsolidations = QuantConnect.Time.EachTradeableDayInTimeZone(security.Exchange.Hours,
StartDate,
EndDate,
security.Exchange.TimeZone,
false).Count();
}
private void UpdateBar(BaseData tradeBar, int position)
{
if (!(tradeBar is TradeBar))
@@ -119,16 +134,27 @@ namespace QuantConnect.Algorithm.CSharp
public override void OnEndOfAlgorithm()
{
if (_consolidationCounts.Any(i => i != _expectedConsolidations) || _customDataConsolidator == 0)
for (var i = 0; i < _consolidationCounts.Count; i++)
{
throw new RegressionTestException("Unexpected consolidation count");
var consolidationCount = _consolidationCounts[i];
var expectedConsolidationCount = _expectedConsolidationCounts[i];
if (consolidationCount != expectedConsolidationCount)
{
throw new RegressionTestException($"Expected {expectedConsolidationCount} consolidations for consolidator {i} but received {consolidationCount}");
}
}
if (_customDataConsolidatorCount == 0)
{
throw new RegressionTestException($"Unexpected custom data consolidation count: {_customDataConsolidatorCount}");
}
for (var i = 0; i < _smas.Count; i++)
{
if (_smas[i].Samples != _expectedConsolidations)
if (_smas[i].Samples != _expectedConsolidationCounts[i])
{
throw new RegressionTestException($"Expected {_expectedConsolidations} samples in each SMA but found {_smas[i].Samples} in SMA in index {i}");
throw new RegressionTestException($"Expected {_expectedConsolidationCounts} samples in each SMA but found {_smas[i].Samples} in SMA in index {i}");
}
if (_smas[i].Current.Time != _lastSmaUpdates[i])
@@ -144,9 +170,9 @@ namespace QuantConnect.Algorithm.CSharp
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
if (!Portfolio.Invested && _future.HasData)
{
SetHoldings(_symbol, 0.5);
SetHoldings(_future.Symbol, 0.5);
}
}
@@ -163,7 +189,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 12244;
public long DataPoints => 14228;
/// <summary>
/// Data Points count of the algorithm history
@@ -183,30 +209,30 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "6636.699%"},
{"Drawdown", "15.900%"},
{"Compounding Annual Return", "665.524%"},
{"Drawdown", "1.500%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "116177.7"},
{"Net Profit", "16.178%"},
{"Sharpe Ratio", "640.313"},
{"End Equity", "109332.4"},
{"Net Profit", "9.332%"},
{"Sharpe Ratio", "9.805"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "99.824%"},
{"Probabilistic Sharpe Ratio", "93.474%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "636.164"},
{"Beta", "5.924"},
{"Annual Standard Deviation", "1.012"},
{"Annual Variance", "1.024"},
{"Information Ratio", "696.123"},
{"Tracking Error", "0.928"},
{"Treynor Ratio", "109.404"},
{"Total Fees", "$23.65"},
{"Estimated Strategy Capacity", "$210000000.00"},
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
{"Portfolio Turnover", "81.19%"},
{"OrderListHash", "dfd9a280d3c6470b305c03e0b72c234e"}
{"Alpha", "3.164"},
{"Beta", "0.957"},
{"Annual Standard Deviation", "0.383"},
{"Annual Variance", "0.146"},
{"Information Ratio", "8.29"},
{"Tracking Error", "0.379"},
{"Treynor Ratio", "3.917"},
{"Total Fees", "$15.05"},
{"Estimated Strategy Capacity", "$2100000000.00"},
{"Lowest Capacity Asset", "ES XCZJLC9NOB29"},
{"Portfolio Turnover", "64.34%"},
{"OrderListHash", "d814db6d5a9c97ee6de477ea06cd3834"}
};
}
}

View File

@@ -52,9 +52,10 @@ namespace QuantConnect.Algorithm.CSharp
SetHoldings("SPY", 1);
}
});
_consolidationDaily.Enqueue(new DateTime(2013, 10, 8, 0, 0, 0));
_consolidationDaily.Enqueue(new DateTime(2013, 10, 9, 0, 0, 0));
_consolidationDaily.Enqueue(new DateTime(2013, 10, 10, 0, 0, 0));
_consolidationDaily.Enqueue(new DateTime(2013, 10, 7, 16, 0, 0));
_consolidationDaily.Enqueue(new DateTime(2013, 10, 8, 16, 0, 0));
_consolidationDaily.Enqueue(new DateTime(2013, 10, 9, 16, 0, 0));
_consolidationDaily.Enqueue(new DateTime(2013, 10, 10, 16, 0, 0));
Consolidate("SPY", TimeSpan.FromHours(3), (TradeBar bar) =>
{
@@ -153,7 +154,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Estimated Strategy Capacity", "$130000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "25.24%"},
{"OrderListHash", "faeb006f6e2015131523994ae78d4eb7"}
{"OrderListHash", "bbda6d0a04ae0b87b2fa10e036296cbb"}
};
}
}

View File

@@ -29,10 +29,11 @@ namespace QuantConnect.Algorithm.CSharp
public class ConsolidatorAnIdentityIndicatorRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private readonly Dictionary<DateTime, decimal> _expectedValues = new Dictionary<DateTime, decimal> {
{ new DateTime(2013, 10, 8), 144.75578537200m },
{ new DateTime(2013, 10, 9), 143.07840976800m },
{ new DateTime(2013, 10, 10), 143.15622616200m },
{ new DateTime(2013, 10, 11), 146.32940578400m }
{ new DateTime(2013, 10, 7, 16, 0, 0), 144.75578537200m },
{ new DateTime(2013, 10, 8, 16, 0, 0), 143.07840976800m },
{ new DateTime(2013, 10, 9, 16, 0, 0), 143.15622616200m },
{ new DateTime(2013, 10, 10, 16, 0, 0), 146.32940578400m },
{ new DateTime(2013, 10, 11, 16, 0, 0), 147.24590998000m }
};
private Identity _identity;
private int _assertCount;
@@ -80,9 +81,9 @@ namespace QuantConnect.Algorithm.CSharp
public override void OnEndOfAlgorithm()
{
if (_assertCount != 12)
if (_assertCount != 15)
{
throw new RegressionTestException($"IUnexpected assertiong count: {_assertCount}");
throw new RegressionTestException($"Unexpected asserting count: {_assertCount}");
}
}

View File

@@ -113,23 +113,12 @@ namespace QuantConnect.Algorithm.CSharp
throw new RegressionTestException($"Unexpected data count, step: {_step}");
}
}
else if (_step == 5)
{
if (!slice.ContainsKey(_fb)
|| !slice.ContainsKey(_spy))
{
throw new RegressionTestException($"Unexpected symbols found, step: {_step}");
}
if (slice.Count != 2)
{
throw new RegressionTestException($"Unexpected data count, step: {_step}");
}
}
}
public override void OnEndOfAlgorithm()
{
if (_step != 5)
// First selection is on the midnight of the 8th, start getting data from the 8th to the 11th
if (_step != 4)
{
throw new RegressionTestException($"Unexpected step count: {_step}");
}
@@ -139,12 +128,12 @@ namespace QuantConnect.Algorithm.CSharp
{
foreach (var added in changes.AddedSecurities)
{
Log($"AddedSecurities {added}");
Log($"{Time} AddedSecurities {added}");
}
foreach (var removed in changes.RemovedSecurities)
{
Log($"RemovedSecurities {removed} {_step}");
Log($"{Time} RemovedSecurities {removed} {_step}");
// we are currently notifying the removal of AAPl twice,
// when deselected and when finally removed (since it stayed pending)
if (removed.Symbol == _appl && _step != 1 && _step != 2
@@ -168,7 +157,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 52;
public long DataPoints => 50;
/// <summary>
/// Data Points count of the algorithm history
@@ -186,32 +175,32 @@ namespace QuantConnect.Algorithm.CSharp
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "2"},
{"Average Win", "0%"},
{"Average Loss", "-0.54%"},
{"Compounding Annual Return", "-32.671%"},
{"Drawdown", "0.900%"},
{"Expectancy", "-1"},
{"Average Win", "0.68%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "70.501%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "99459.59"},
{"Net Profit", "-0.540%"},
{"Sharpe Ratio", "-3.436"},
{"End Equity", "100684.53"},
{"Net Profit", "0.685%"},
{"Sharpe Ratio", "13.41"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "25.715%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Probabilistic Sharpe Ratio", "99.997%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.73"},
{"Beta", "0.22"},
{"Annual Standard Deviation", "0.086"},
{"Annual Variance", "0.007"},
{"Information Ratio", "-12.125"},
{"Tracking Error", "0.187"},
{"Treynor Ratio", "-1.338"},
{"Total Fees", "$32.32"},
{"Estimated Strategy Capacity", "$95000000.00"},
{"Alpha", "0.235"},
{"Beta", "0.15"},
{"Annual Standard Deviation", "0.04"},
{"Annual Variance", "0.002"},
{"Information Ratio", "-7.587"},
{"Tracking Error", "0.19"},
{"Treynor Ratio", "3.546"},
{"Total Fees", "$32.77"},
{"Estimated Strategy Capacity", "$230000000.00"},
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "20.06%"},
{"OrderListHash", "2271d307c23224ed7abc7fc852a51f24"}
{"Portfolio Turnover", "20.15%"},
{"OrderListHash", "d269ebced0796dde34f9eb775772e027"}
};
}
}

View File

@@ -139,7 +139,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 713369;
public long DataPoints => 713371;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -155,7 +155,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 723496;
public long DataPoints => 723498;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -120,7 +120,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public virtual long DataPoints => 9956;
public virtual long DataPoints => 9951;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -34,6 +34,6 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 15820;
public override long DataPoints => 15813;
}
}

View File

@@ -184,7 +184,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 596356;
public long DataPoints => 596358;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -78,7 +78,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 19886;
public long DataPoints => 19888;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -0,0 +1,237 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
using QuantConnect.Orders;
using QuantConnect.Securities;
using QuantConnect.Securities.Future;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm reproducing GH issue #8386 and other related bugs.
/// It asserts that open positions are liquidated when a contract is delisted, even if the contract was added as an internal subscription.
/// It also asserts that the contract is not tradable after being delisted.
/// </summary>
public class ContinuousFutureOpenPositionsLiquidationOnDelistingRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Future _continuousContract;
private Symbol _prevContractSymbol;
private bool _traded;
private bool _mapped;
private bool _delistedContractChecked;
private DateTime _firstMappedContractRemovalTime;
private int _removalCount;
public override void Initialize()
{
SetStartDate(2013, 10, 08);
SetEndDate(2013, 12, 30);
_continuousContract = AddFuture(Futures.Indices.SP500EMini,
dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
dataMappingMode: DataMappingMode.OpenInterest,
contractDepthOffset: 0
);
}
public override void OnData(Slice slice)
{
if (!_traded && _continuousContract.HasData)
{
var ticket = MarketOrder(_continuousContract.Mapped, 1);
if (ticket.Status == OrderStatus.Invalid)
{
throw new RegressionTestException($"Order should be valid: {ticket}");
}
_traded = true;
}
if (slice.SymbolChangedEvents.Count > 0)
{
foreach (var change in slice.SymbolChangedEvents.Values)
{
Debug($"[{Time}] :: Mapping: {change}");
_prevContractSymbol = Symbol(change.OldSymbol);
_mapped = true;
}
}
if (!_delistedContractChecked &&
_prevContractSymbol != null &&
Time.Date > _prevContractSymbol.ID.Date &&
IsMarketOpen(_prevContractSymbol))
{
_delistedContractChecked = true;
var delistedContract = Securities.Total.Single(sec => sec.Symbol == _prevContractSymbol);
if (delistedContract.Invested)
{
throw new RegressionTestException($"Position should be closed when {_prevContractSymbol} got delisted {_prevContractSymbol.ID.Date}");
}
if (!delistedContract.IsDelisted)
{
throw new RegressionTestException($"Contract should be delisted: {delistedContract.Symbol}");
}
if (delistedContract.IsTradable)
{
throw new RegressionTestException($"Contract should not be tradable: {delistedContract.Symbol}");
}
var ticket = MarketOrder(_prevContractSymbol, 1);
if (ticket.Status != OrderStatus.Invalid)
{
throw new RegressionTestException($"Delisted contract order should be invalid: {ticket}");
}
}
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
if (_prevContractSymbol != null)
{
if (changes.RemovedSecurities.Any(x => x.Symbol == _prevContractSymbol))
{
throw new RegressionTestException($"Previous contract symbol {_prevContractSymbol} should not be removed as a non-internal security");
}
changes.FilterInternalSecurities = false;
if (!changes.RemovedSecurities.Any(x => x.Symbol == _prevContractSymbol))
{
throw new RegressionTestException($"Previous contract symbol {_prevContractSymbol} should be removed as an internal security");
}
_firstMappedContractRemovalTime = Time;
_removalCount++;
}
changes.FilterInternalSecurities = false;
Debug($"[{Time}] :: {changes}");
}
public override void OnOrderEvent(OrderEvent orderEvent)
{
Debug($"[{Time}] :: Order event: {orderEvent}");
}
public override void OnEndOfAlgorithm()
{
if (!_traded)
{
throw new RegressionTestException("No trades have been made");
}
if (!_mapped)
{
throw new RegressionTestException("No mapping events have been fired");
}
if (!_delistedContractChecked)
{
throw new RegressionTestException("No delisted contract has been checked");
}
if (_prevContractSymbol == null)
{
throw new RegressionTestException("No previous contract symbol has been set");
}
var tradedContract = Securities.Total.Single(sec => sec.Symbol == _prevContractSymbol);
if (tradedContract.Invested)
{
throw new RegressionTestException($"Position should be closed when {_prevContractSymbol} got delisted on {_prevContractSymbol.ID.Date}");
}
if (_firstMappedContractRemovalTime == default || _firstMappedContractRemovalTime >= _prevContractSymbol.ID.Date)
{
throw new RegressionTestException($"First mapped contract should have been removed before it's expiry date");
}
if (_removalCount != 1)
{
throw new RegressionTestException($"The mapped contract should have been removed once only");
}
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; } = true;
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public List<Language> Languages { get; } = new() { Language.CSharp };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public virtual long DataPoints => 396945;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "2"},
{"Average Win", "7.02%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "34.386%"},
{"Drawdown", "1.500%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "107016.6"},
{"Net Profit", "7.017%"},
{"Sharpe Ratio", "3.217"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "99.828%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.227"},
{"Beta", "0.109"},
{"Annual Standard Deviation", "0.084"},
{"Annual Variance", "0.007"},
{"Information Ratio", "-1.122"},
{"Tracking Error", "0.112"},
{"Treynor Ratio", "2.49"},
{"Total Fees", "$2.15"},
{"Estimated Strategy Capacity", "$1700000000.00"},
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
{"Portfolio Turnover", "2.01%"},
{"OrderListHash", "838e662caaa5a385c43ef27df1efbaf4"}
};
}
}

View File

@@ -19,7 +19,6 @@ using QuantConnect.Data;
using QuantConnect.Orders;
using QuantConnect.Interfaces;
using QuantConnect.Securities;
using QuantConnect.Data.Market;
using System.Collections.Generic;
using QuantConnect.Securities.Future;
using QuantConnect.Data.UniverseSelection;
@@ -31,7 +30,7 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public class ContinuousFutureRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private List<SymbolChangedEvent> _mappings = new();
private List<Symbol> _previousMappedContractSymbols = new();
private Symbol _currentMappedSymbol;
private Future _continuousContract;
private DateTime _lastMonth;
@@ -77,7 +76,7 @@ namespace QuantConnect.Algorithm.CSharp
{
if (changedEvent.Symbol == _continuousContract.Symbol)
{
_mappings.Add(changedEvent);
_previousMappedContractSymbols.Add(Symbol(changedEvent.OldSymbol));
Log($"{Time} - SymbolChanged event: {changedEvent}");
if (_currentMappedSymbol == _continuousContract.Mapped)
@@ -144,15 +143,20 @@ namespace QuantConnect.Algorithm.CSharp
public override void OnEndOfAlgorithm()
{
var expectedMappingCounts = 2;
if (_mappings.Count != expectedMappingCounts)
if (_previousMappedContractSymbols.Count != expectedMappingCounts)
{
throw new RegressionTestException($"Unexpected symbol changed events: {_mappings.Count}, was expecting {expectedMappingCounts}");
throw new RegressionTestException($"Unexpected symbol changed events: {_previousMappedContractSymbols.Count}, was expecting {expectedMappingCounts}");
}
var securities = Securities.Total.Where(sec => !sec.IsTradable && !sec.Symbol.IsCanonical() && sec.Symbol.SecurityType == SecurityType.Future).ToList();
if (securities.Count != 1)
var delistedSecurities = _previousMappedContractSymbols
.Select(x => Securities.Total.Single(sec => sec.Symbol == x))
.Where(x => x.Symbol.ID.Date < Time)
.ToList();
var markedDelistedSecurities = delistedSecurities.Where(x => x.IsDelisted && !x.IsTradable).ToList();
if (markedDelistedSecurities.Count != delistedSecurities.Count)
{
throw new RegressionTestException($"We should have a single non tradable future contract security! found: {securities.Count}");
throw new RegressionTestException($"Not all delisted contracts are properly market as delisted and non-tradable: " +
$"only {markedDelistedSecurities.Count} are marked, was expecting {delistedSecurities.Count}");
}
}
@@ -169,7 +173,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 713369;
public long DataPoints => 713375;
/// <summary>
/// Data Points count of the algorithm history
@@ -186,18 +190,18 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "3"},
{"Average Win", "1.50%"},
{"Total Orders", "4"},
{"Average Win", "0.84%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "3.337%"},
{"Compounding Annual Return", "3.380%"},
{"Drawdown", "1.600%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "101666.4"},
{"Net Profit", "1.666%"},
{"Sharpe Ratio", "0.594"},
{"Sortino Ratio", "0.198"},
{"Probabilistic Sharpe Ratio", "44.801%"},
{"End Equity", "101687.3"},
{"Net Profit", "1.687%"},
{"Sharpe Ratio", "0.605"},
{"Sortino Ratio", "0.202"},
{"Probabilistic Sharpe Ratio", "45.198%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
@@ -205,14 +209,14 @@ namespace QuantConnect.Algorithm.CSharp
{"Beta", "0.134"},
{"Annual Standard Deviation", "0.027"},
{"Annual Variance", "0.001"},
{"Information Ratio", "-2.69"},
{"Information Ratio", "-2.687"},
{"Tracking Error", "0.075"},
{"Treynor Ratio", "0.119"},
{"Treynor Ratio", "0.121"},
{"Total Fees", "$6.45"},
{"Estimated Strategy Capacity", "$8000000000.00"},
{"Estimated Strategy Capacity", "$2600000000.00"},
{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
{"Portfolio Turnover", "1.39%"},
{"OrderListHash", "40c1137e0bc83b2bc920495af119c8fc"}
{"Portfolio Turnover", "1.88%"},
{"OrderListHash", "1287c3b983c5bac6491bb5ac296c4b55"}
};
}
}

View File

@@ -0,0 +1,262 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using QuantConnect.Data;
using QuantConnect.Securities;
using QuantConnect.Securities.Future;
using System;
using QuantConnect.Util;
using System.Linq;
using NodaTime;
using QuantConnect.Interfaces;
using System.Collections.Generic;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data, regardless of the
/// offset between the exchange time zone and the data time zone.
/// </summary>
public abstract class ContinuousFutureRolloverBaseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
const string Ticker = Futures.Indices.SP500EMini;
private Future _continuousContract;
private DateTime _rolloverTime;
private MarketHoursDatabase.Entry _originalMhdbEntry;
protected abstract Resolution Resolution { get; }
protected abstract Offset ExchangeToDataTimeZoneOffset { get; }
private DateTimeZone DataTimeZone => TimeZones.Utc;
private DateTimeZone ExchangeTimeZone => DateTimeZone.ForOffset(ExchangeToDataTimeZoneOffset);
private bool RolloverHappened => _rolloverTime != DateTime.MinValue;
public override void Initialize()
{
SetStartDate(2013, 10, 8);
SetEndDate(2013, 12, 20);
_originalMhdbEntry = MarketHoursDatabase.GetEntry(Market.CME, Ticker, SecurityType.Future);
var exchangeHours = new SecurityExchangeHours(ExchangeTimeZone,
_originalMhdbEntry.ExchangeHours.Holidays,
_originalMhdbEntry.ExchangeHours.MarketHours.ToDictionary(),
_originalMhdbEntry.ExchangeHours.EarlyCloses,
_originalMhdbEntry.ExchangeHours.LateOpens);
MarketHoursDatabase.SetEntry(Market.CME, Ticker, SecurityType.Future, exchangeHours, DataTimeZone);
SetTimeZone(ExchangeTimeZone);
_continuousContract = AddFuture(Ticker,
Resolution,
extendedMarketHours: true,
dataNormalizationMode: DataNormalizationMode.Raw,
dataMappingMode: DataMappingMode.OpenInterest,
contractDepthOffset: 0
);
SetBenchmark(x => 0);
}
public override void OnData(Slice slice)
{
try
{
var receivedRollover = false;
foreach (var (symbol, symbolChangedEvent) in slice.SymbolChangedEvents)
{
if (RolloverHappened)
{
throw new RegressionTestException($"[{Time}] -- Unexpected symbol changed event for {symbol}. Expected only one mapping.");
}
receivedRollover = true;
_rolloverTime = symbolChangedEvent.EndTime;
var oldSymbol = symbolChangedEvent.OldSymbol;
var newSymbol = symbolChangedEvent.NewSymbol;
Debug($"[{Time}] -- Rollover: {oldSymbol} -> {newSymbol}");
if (symbol != _continuousContract.Symbol)
{
throw new RegressionTestException($"[{Time}] -- Unexpected symbol changed event for {symbol}");
}
var expectedMappingDate = new DateTime(2013, 12, 18);
if (_rolloverTime != expectedMappingDate)
{
throw new RegressionTestException($"[{Time}] -- Unexpected date {_rolloverTime}. Expected {expectedMappingDate}");
}
var expectedMappingOldSymbol = "ES VMKLFZIH2MTD";
var expectedMappingNewSymbol = "ES VP274HSU1AF5";
if (symbolChangedEvent.OldSymbol != expectedMappingOldSymbol || symbolChangedEvent.NewSymbol != expectedMappingNewSymbol)
{
throw new RegressionTestException($"[{Time}] -- Unexpected mapping. " +
$"Expected {expectedMappingOldSymbol} -> {expectedMappingNewSymbol} " +
$"but was {symbolChangedEvent.OldSymbol} -> {symbolChangedEvent.NewSymbol}");
}
}
var mappedFuture = Securities[_continuousContract.Mapped];
var mappedFuturePrice = mappedFuture.Price;
var otherFuture = Securities.Values.SingleOrDefault(x => !x.Symbol.IsCanonical() && x.Symbol != _continuousContract.Mapped);
var otherFuturePrice = otherFuture?.Price;
var continuousContractPrice = _continuousContract.Price;
Debug($"[{Time}] Contracts prices:\n" +
$" -- Mapped future: {mappedFuture.Symbol} :: {mappedFuture.Price} :: {mappedFuture.GetLastData()}\n" +
$" -- Other future: {otherFuture?.Symbol} :: {otherFuture?.Price} :: {otherFuture?.GetLastData()}\n" +
$" -- Mapped future from continuous contract: {_continuousContract.Symbol} :: {_continuousContract.Mapped} :: " +
$"{_continuousContract.Price} :: {_continuousContract.GetLastData()}\n");
if (receivedRollover)
{
if (continuousContractPrice != otherFuturePrice)
{
var continuousContractLastData = _continuousContract.GetLastData();
throw new RegressionTestException($"[{Time}] -- Prices do not match. " +
$"At the time of the rollover, expected continuous future price to be the same as " +
$"the previously mapped contract since no data for the new mapped contract has been received:\n" +
$" Continuous contract ({_continuousContract.Symbol}) price: " +
$"{continuousContractPrice} :: {continuousContractLastData.Symbol.Underlying} :: " +
$"{continuousContractLastData.Time} - {continuousContractLastData.EndTime} :: {continuousContractLastData}. \n" +
$" Mapped contract ({mappedFuture.Symbol}) price: {mappedFuturePrice} :: {mappedFuture.GetLastData()}. \n" +
$" Other contract ({otherFuture?.Symbol}) price: {otherFuturePrice} :: {otherFuture?.GetLastData()}\n");
}
}
else if (mappedFuturePrice != 0 || !RolloverHappened)
{
if (continuousContractPrice != mappedFuturePrice)
{
var continuousContractLastData = _continuousContract.GetLastData();
throw new RegressionTestException($"[{Time}] -- Prices do not match. " +
$"Expected continuous future price to be the same as the mapped contract:\n" +
$" Continuous contract ({_continuousContract.Symbol}) price: {continuousContractPrice} :: " +
$"{continuousContractLastData.Symbol.Underlying} :: {continuousContractLastData}. \n" +
$" Mapped contract ({mappedFuture.Symbol}) price: {mappedFuturePrice} :: {mappedFuture.GetLastData()}. \n" +
$" Other contract ({otherFuture?.Symbol}) price: {otherFuturePrice} :: {otherFuture?.GetLastData()}\n");
}
}
// No data for the mapped future yet after rollover
else
{
if (otherFuture == null)
{
throw new RegressionTestException($"[{Time}] --" +
$" Mapped future price is 0 (no data has arrived) so the previous mapped contract is expected to be there");
}
var continuousContractLastData = _continuousContract.GetLastData();
if (continuousContractLastData.EndTime > _rolloverTime)
{
throw new RegressionTestException($"[{Time}] -- Expected continuous future contract last data to be from the previously " +
$"mapped contract until the new mapped contract gets data:\n" +
$" Rollover time: {_rolloverTime}\n" +
$" Continuous contract ({_continuousContract.Symbol}) last data: " +
$"{continuousContractLastData.Symbol.Underlying} :: " +
$"{continuousContractLastData.Time} - {continuousContractLastData.EndTime} :: {continuousContractLastData}.");
}
}
}
catch (Exception ex)
{
ResetMarketHoursDatabase();
throw;
}
}
public override void OnEndOfAlgorithm()
{
ResetMarketHoursDatabase();
if (!RolloverHappened)
{
throw new RegressionTestException($"[{Time}] -- Rollover did not happen.");
}
}
private void ResetMarketHoursDatabase()
{
MarketHoursDatabase.SetEntry(Market.CME, Ticker, SecurityType.Future, _originalMhdbEntry.ExchangeHours, _originalMhdbEntry.DataTimeZone);
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; } = true;
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public List<Language> Languages { get; } = new() { Language.CSharp };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public virtual long DataPoints => 0;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "0"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "100000"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "0"},
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Portfolio Turnover", "0%"},
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
};
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the exchange time zone is ahead of the data time zone.
/// </summary>
public class ContinuousFutureRolloverDailyExchangeTimeZoneAheadOfDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Daily;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(2);
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 1022;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the exchange time zone is behind of the data time zone.
/// </summary>
public class ContinuousFutureRolloverDailyExchangeTimeZoneBehindOfDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Daily;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(-2);
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 1017;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the data time zone is the same as the exchange time zone.
/// </summary>
public class ContinuousFutureRolloverDailyExchangeTimeZoneSameAsDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Daily;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.Zero;
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 1015;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the exchange time zone is ahead of the data time zone.
/// </summary>
public class ContinuousFutureRolloverHourExchangeTimeZoneAheadOfDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Hour;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(2);
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 18850;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the exchange time zone is behind of the data time zone.
/// </summary>
public class ContinuousFutureRolloverHourExchangeTimeZoneBehindOfDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Hour;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(-2);
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 18844;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the data time zone is the same as the exchange time zone.
/// </summary>
public class ContinuousFutureRolloverHourExchangeTimeZoneSameAsDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Hour;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.Zero;
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 18846;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the exchange time zone is ahead of the data time zone.
/// </summary>
public class ContinuousFutureRolloverMinuteExchangeTimeZoneAheadOfDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Minute;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(2);
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 1127376;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the exchange time zone is behind of the data time zone.
/// </summary>
public class ContinuousFutureRolloverMinuteExchangeTimeZoneBehindOfDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Minute;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.FromHours(-2);
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 1127374;
}
}

View File

@@ -0,0 +1,38 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*/
using NodaTime;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Base class for regression algorithms testing that when a continuous future rollover happens,
/// the continuous contract is updated correctly with the new contract data.
/// The algorithms asserts the behavior for the case when the data time zone is the same as the exchange time zone.
/// </summary>
public class ContinuousFutureRolloverMinuteExchangeTimeZoneSameAsDataRegressionAlgorithm
: ContinuousFutureRolloverBaseRegressionAlgorithm
{
protected override Resolution Resolution => Resolution.Minute;
protected override Offset ExchangeToDataTimeZoneOffset => Offset.Zero;
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 1127488;
}
}

View File

@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 1361;
public long DataPoints => 1268;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -128,7 +128,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 22137;
public long DataPoints => 22136;
/// <summary>
/// Data Points count of the algorithm history
@@ -168,10 +168,10 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0.23"},
{"Treynor Ratio", "0.351"},
{"Total Fees", "$797.27"},
{"Estimated Strategy Capacity", "$1200000000.00"},
{"Estimated Strategy Capacity", "$1400000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "4.23%"},
{"OrderListHash", "1291b6615d6301b487f409a5e0ea475d"}
{"OrderListHash", "0422632afa17df1379757085f951de7b"}
};
}
}

View File

@@ -0,0 +1,134 @@
/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
using System.Collections.Generic;
using QuantConnect.Data;
using QuantConnect.Indicators;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Compares two correlation types and asserts they are not equal during the algorithm's execution.
/// </summary>
public class CorrelationTypeComparisonRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Correlation _correlationPearson;
private Correlation _correlationSpearman;
/// <summary>
/// Initialise the data and resolution required, as well as the start-end dates for your algorithm. All algorithms must initialized.
/// </summary>
public override void Initialize()
{
SetStartDate(2013, 10, 08); //Set Start Date
SetEndDate(2013, 10, 17); //Set End Date
var symbol = AddEquity("AAPL", Resolution.Daily).Symbol;
var spy = AddEquity("SPY", Resolution.Daily).Symbol;
_correlationPearson = C(symbol, spy, 5, CorrelationType.Pearson);
_correlationSpearman = C(symbol, spy, 5, CorrelationType.Spearman);
}
/// <summary>
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
/// </summary>
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
public override void OnData(Slice slice)
{
if (_correlationPearson.IsReady && _correlationSpearman.IsReady)
{
var pearsonValue = _correlationPearson.Current.Value;
var spearmanValue = _correlationSpearman.Current.Value;
// Check that the correlation values are not the same
if (pearsonValue == spearmanValue)
{
// Throw an exception if the correlation values are equal
throw new RegressionTestException($"Error: Pearson and Spearman correlation values are the same: Pearson = {pearsonValue}, Spearman = {spearmanValue}. This should not happen.");
}
}
}
/// <summary>
/// End of algorithm run event handler. This method is called at the end of a backtest or live trading operation. Intended for closing out logs.
/// </summary>
public override void OnEndOfAlgorithm()
{
if (!_correlationPearson.IsReady || !_correlationSpearman.IsReady)
{
throw new RegressionTestException("Error: Both correlation values should be ready at the end of the algorithm.");
}
}
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally => true;
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public List<Language> Languages { get; } = new() { Language.CSharp };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 80;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "0"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "100000"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "-19.184"},
{"Tracking Error", "0.138"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Portfolio Turnover", "0%"},
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
};
}
}

View File

@@ -97,7 +97,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 4490;
public override long DataPoints => 2298;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -97,7 +97,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 4490;
public override long DataPoints => 2298;
/// <summary>
/// Data Points count of the algorithm history

View File

@@ -106,7 +106,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 463141;
public long DataPoints => 7029;
/// </summary>
/// Data Points count of the algorithm history

View File

@@ -15,6 +15,7 @@
using System;
using QuantConnect.Brokerages;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Interfaces;
@@ -39,7 +40,7 @@ namespace QuantConnect.Algorithm.CSharp
SetBrokerageMessageHandler(new CustomBrokerageMessageHandler(this));
}
public void OnData(TradeBars data)
public override void OnData(Slice slice)
{
if (Portfolio.HoldStock) return;
Order("SPY", 100);

View File

@@ -153,7 +153,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "2"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "19.594%"},
{"Compounding Annual Return", "21.133%"},
{"Drawdown", "0.200%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
@@ -173,10 +173,10 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0.19"},
{"Treynor Ratio", "1.104"},
{"Total Fees", "$1.00"},
{"Estimated Strategy Capacity", "$4100000000.00"},
{"Estimated Strategy Capacity", "$5300000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "2.90%"},
{"OrderListHash", "2fceb6050a91cafd083d19579e482b82"}
{"OrderListHash", "4e8e27d7546eced2ef3512fcc840a634"}
};
}
}

View File

@@ -108,7 +108,7 @@ namespace QuantConnect.Algorithm.CSharp
public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
{
var source = Path.Combine(Globals.DataFolder, "equity", "usa", config.Resolution.ToString().ToLower(), LeanData.GenerateZipFileName(config.Symbol, date, config.Resolution, config.TickType));
return new SubscriptionDataSource(source, SubscriptionTransportMedium.LocalFile, FileFormat.Csv);
return new SubscriptionDataSource(source);
}
public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, bool isLiveMode)

View File

@@ -40,8 +40,8 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public override void Initialize()
{
SetStartDate(2011, 9, 13);
SetEndDate(2015, 12, 01);
SetStartDate(2020, 01, 05);
SetEndDate(2020, 01, 10);
//Set the cash for the strategy:
SetCash(100000);
@@ -109,7 +109,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 10491;
public long DataPoints => 57;
/// <summary>
/// Data Points count of the algorithm history
@@ -129,30 +129,30 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "155.211%"},
{"Drawdown", "84.800%"},
{"Compounding Annual Return", "34781.071%"},
{"Drawdown", "4.300%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "5223241.65"},
{"Net Profit", "5123.242%"},
{"Sharpe Ratio", "2.058"},
{"Sortino Ratio", "2.492"},
{"Probabilistic Sharpe Ratio", "68.833%"},
{"End Equity", "110102.2"},
{"Net Profit", "10.102%"},
{"Sharpe Ratio", "283.719"},
{"Sortino Ratio", "1123.876"},
{"Probabilistic Sharpe Ratio", "81.716%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "1.724"},
{"Beta", "0.043"},
{"Annual Standard Deviation", "0.841"},
{"Annual Variance", "0.707"},
{"Information Ratio", "1.902"},
{"Tracking Error", "0.848"},
{"Treynor Ratio", "40.293"},
{"Alpha", "184.11"},
{"Beta", "-6.241"},
{"Annual Standard Deviation", "0.635"},
{"Annual Variance", "0.403"},
{"Information Ratio", "260.511"},
{"Tracking Error", "0.689"},
{"Treynor Ratio", "-28.849"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", "BTC.Bitcoin 2S"},
{"Portfolio Turnover", "0.06%"},
{"OrderListHash", "999305e00ec9861f5ff261794e81213d"}
{"Portfolio Turnover", "16.73%"},
{"OrderListHash", "b890a8e73bf118e943ad2f2e712f12d0"}
};
/// <summary>
@@ -168,6 +168,7 @@ namespace QuantConnect.Algorithm.CSharp
public decimal High { get; set; }
[JsonProperty("low")]
public decimal Low { get; set; }
public decimal Mid { get; set; }
[JsonProperty("last")]
public decimal Close { get; set; }
[JsonProperty("bid")]
@@ -217,7 +218,10 @@ namespace QuantConnect.Algorithm.CSharp
//return "http://my-ftp-server.com/futures-data-" + date.ToString("Ymd") + ".zip";
// OR simply return a fixed small data file. Large files will slow down your backtest
return new SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", SubscriptionTransportMedium.RemoteFile);
return new SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/nasdaq/api/v3/datatables/QDL/BITFINEX.csv?code=BTCUSD&api_key=WyAazVXnq7ATy_fefTqm")
{
Sort = true
};
}
/// <summary>
@@ -248,20 +252,20 @@ namespace QuantConnect.Algorithm.CSharp
}
//Example Line Format:
//Date Open High Low Close Volume (BTC) Volume (Currency) Weighted Price
//2011-09-13 5.8 6.0 5.65 5.97 58.37138238, 346.0973893944 5.929230648356
// code date high low mid last bid ask volume
// BTCUSD 2024-10-08 63248.0 61940.0 62246.5 62245.0 62246.0 62247.0 5.929230648356
try
{
string[] data = line.Split(',');
coin.Time = DateTime.Parse(data[0], CultureInfo.InvariantCulture);
coin.Time = DateTime.Parse(data[1], CultureInfo.InvariantCulture);
coin.EndTime = coin.Time.AddDays(1);
coin.Open = Convert.ToDecimal(data[1], CultureInfo.InvariantCulture);
coin.High = Convert.ToDecimal(data[2], CultureInfo.InvariantCulture);
coin.Low = Convert.ToDecimal(data[3], CultureInfo.InvariantCulture);
coin.Close = Convert.ToDecimal(data[4], CultureInfo.InvariantCulture);
coin.VolumeBTC = Convert.ToDecimal(data[5], CultureInfo.InvariantCulture);
coin.VolumeUSD = Convert.ToDecimal(data[6], CultureInfo.InvariantCulture);
coin.WeightedPrice = Convert.ToDecimal(data[7], CultureInfo.InvariantCulture);
coin.Mid = Convert.ToDecimal(data[4], CultureInfo.InvariantCulture);
coin.Close = Convert.ToDecimal(data[5], CultureInfo.InvariantCulture);
coin.Bid = Convert.ToDecimal(data[6], CultureInfo.InvariantCulture);
coin.Ask = Convert.ToDecimal(data[7], CultureInfo.InvariantCulture);
coin.VolumeBTC = Convert.ToDecimal(data[8], CultureInfo.InvariantCulture);
coin.Value = coin.Close;
}
catch { /* Do nothing, skip first title row */ }

View File

@@ -33,15 +33,15 @@ namespace QuantConnect.Algorithm.CSharp
/// <meta name="tag" content="regression test" />
public class CustomDataRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private bool _warmedUpChecked = false;
private bool _warmedUpChecked;
/// <summary>
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
/// </summary>
public override void Initialize()
{
SetStartDate(2011, 9, 14);
SetEndDate(2015, 12, 01);
SetStartDate(2020, 01, 05);
SetEndDate(2020, 01, 10);
//Set the cash for the strategy:
SetCash(100000);
@@ -110,7 +110,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 8943;
public long DataPoints => 50;
/// <summary>
/// Data Points count of the algorithm history
@@ -130,30 +130,30 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "155.365%"},
{"Drawdown", "84.800%"},
{"Compounding Annual Return", "27587.925%"},
{"Drawdown", "4.200%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "5223170.23"},
{"Net Profit", "5123.170%"},
{"Sharpe Ratio", "2.094"},
{"Sortino Ratio", "2.535"},
{"Probabilistic Sharpe Ratio", "69.967%"},
{"End Equity", "109685"},
{"Net Profit", "9.685%"},
{"Sharpe Ratio", "238.834"},
{"Sortino Ratio", "945.079"},
{"Probabilistic Sharpe Ratio", "81.660%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "1.753"},
{"Beta", "0.055"},
{"Annual Standard Deviation", "0.84"},
{"Annual Variance", "0.706"},
{"Information Ratio", "1.942"},
{"Tracking Error", "0.848"},
{"Treynor Ratio", "32.18"},
{"Alpha", "149.482"},
{"Beta", "-6.002"},
{"Annual Standard Deviation", "0.61"},
{"Annual Variance", "0.371"},
{"Information Ratio", "218.36"},
{"Tracking Error", "0.664"},
{"Treynor Ratio", "-24.253"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", "BTC.Bitcoin 2S"},
{"Portfolio Turnover", "0.06%"},
{"OrderListHash", "e69e78cd6fe7bc4627da2f51e25539d0"}
{"Portfolio Turnover", "16.03%"},
{"OrderListHash", "dde8821614d33c89e6e75c536447b7da"}
};
/// <summary>
@@ -169,6 +169,8 @@ namespace QuantConnect.Algorithm.CSharp
public decimal High { get; set; }
[JsonProperty("low")]
public decimal Low { get; set; }
public decimal Mid { get; set; }
[JsonProperty("last")]
public decimal Close { get; set; }
[JsonProperty("bid")]
@@ -179,7 +181,6 @@ namespace QuantConnect.Algorithm.CSharp
public decimal WeightedPrice { get; set; }
[JsonProperty("volume")]
public decimal VolumeBTC { get; set; }
public decimal VolumeUSD { get; set; }
/// <summary>
/// The end time of this data. Some data covers spans (trade bars)
@@ -218,7 +219,10 @@ namespace QuantConnect.Algorithm.CSharp
//return "http://my-ftp-server.com/futures-data-" + date.ToString("Ymd") + ".zip";
// OR simply return a fixed small data file. Large files will slow down your backtest
return new SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/quandl/api/v3/datasets/BCHARTS/BITSTAMPUSD.csv?order=asc&api_key=WyAazVXnq7ATy_fefTqm", SubscriptionTransportMedium.RemoteFile);
return new SubscriptionDataSource("https://www.quantconnect.com/api/v2/proxy/nasdaq/api/v3/datatables/QDL/BITFINEX.csv?code=BTCUSD&api_key=qAWKpUfmSVFnU3bRQwKy")
{
Sort = true
};
}
/// <summary>
@@ -249,20 +253,20 @@ namespace QuantConnect.Algorithm.CSharp
}
//Example Line Format:
//Date Open High Low Close Volume (BTC) Volume (Currency) Weighted Price
//2011-09-13 5.8 6.0 5.65 5.97 58.37138238, 346.0973893944 5.929230648356
// code date high low mid last bid ask volume
// BTCUSD 2024-10-08 63248.0 61940.0 62246.5 62245.0 62246.0 62247.0 477.91102114
try
{
string[] data = line.Split(',');
coin.Time = DateTime.Parse(data[0], CultureInfo.InvariantCulture);
coin.Time = DateTime.Parse(data[1], CultureInfo.InvariantCulture);
coin.EndTime = coin.Time.AddDays(1);
coin.Open = Convert.ToDecimal(data[1], CultureInfo.InvariantCulture);
coin.High = Convert.ToDecimal(data[2], CultureInfo.InvariantCulture);
coin.Low = Convert.ToDecimal(data[3], CultureInfo.InvariantCulture);
coin.Close = Convert.ToDecimal(data[4], CultureInfo.InvariantCulture);
coin.VolumeBTC = Convert.ToDecimal(data[5], CultureInfo.InvariantCulture);
coin.VolumeUSD = Convert.ToDecimal(data[6], CultureInfo.InvariantCulture);
coin.WeightedPrice = Convert.ToDecimal(data[7], CultureInfo.InvariantCulture);
coin.Mid = Convert.ToDecimal(data[4], CultureInfo.InvariantCulture);
coin.Close = Convert.ToDecimal(data[5], CultureInfo.InvariantCulture);
coin.Bid = Convert.ToDecimal(data[6], CultureInfo.InvariantCulture);
coin.Ask = Convert.ToDecimal(data[7], CultureInfo.InvariantCulture);
coin.VolumeBTC = Convert.ToDecimal(data[8], CultureInfo.InvariantCulture);
coin.Value = coin.Close;
}
catch { /* Do nothing, skip first title row */ }

View File

@@ -27,6 +27,7 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public class CustomDataUniverseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private HashSet<Symbol> _currentUnderlyingSymbols = new();
private readonly Queue<DateTime> _selectionTime = new (new[] {
new DateTime(2014, 03, 24, 0, 0, 0),
new DateTime(2014, 03, 25, 0, 0, 0),
@@ -71,14 +72,20 @@ namespace QuantConnect.Algorithm.CSharp
if (!Portfolio.Invested)
{
var customData = slice.Get<CustomData>();
var symbols = slice.Keys.Where(symbol => symbol.SecurityType != SecurityType.Base).ToList();
foreach (var symbol in symbols)
if (customData.Count > 0)
{
SetHoldings(symbol, 1m / symbols.Count);
if (!customData.Any(custom => custom.Key.Underlying == symbol))
foreach (var symbol in _currentUnderlyingSymbols.OrderBy(x => x.ID.Symbol))
{
throw new RegressionTestException($"Custom data was not found for underlying symbol {symbol}");
if (!Securities[symbol].HasData)
{
continue;
}
SetHoldings(symbol, 1m / _currentUnderlyingSymbols.Count);
if (!customData.Any(custom => custom.Key.Underlying == symbol))
{
throw new RegressionTestException($"Custom data was not found for underlying symbol {symbol}");
}
}
}
}
@@ -92,6 +99,18 @@ namespace QuantConnect.Algorithm.CSharp
}
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
foreach(var security in changes.AddedSecurities.Where(sec => sec.Symbol.SecurityType != SecurityType.Base))
{
_currentUnderlyingSymbols.Add(security.Symbol);
}
foreach (var security in changes.RemovedSecurities.Where(sec => sec.Symbol.SecurityType != SecurityType.Base))
{
_currentUnderlyingSymbols.Remove(security.Symbol);
}
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
@@ -105,7 +124,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 42633;
public long DataPoints => 42622;
/// <summary>
/// Data Points count of the algorithm history
@@ -122,33 +141,33 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "7"},
{"Total Orders", "6"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "-65.130%"},
{"Drawdown", "2.900%"},
{"Compounding Annual Return", "-50.796%"},
{"Drawdown", "1.900%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "97717.31"},
{"Net Profit", "-2.283%"},
{"Sharpe Ratio", "-4.298"},
{"Sortino Ratio", "-4.067"},
{"Probabilistic Sharpe Ratio", "5.388%"},
{"End Equity", "98457.63"},
{"Net Profit", "-1.542%"},
{"Sharpe Ratio", "-4.343"},
{"Sortino Ratio", "-3.19"},
{"Probabilistic Sharpe Ratio", "4.159%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-1.062"},
{"Beta", "1.336"},
{"Annual Standard Deviation", "0.132"},
{"Annual Variance", "0.018"},
{"Information Ratio", "-12.03"},
{"Tracking Error", "0.078"},
{"Treynor Ratio", "-0.426"},
{"Total Fees", "$13.87"},
{"Estimated Strategy Capacity", "$430000000.00"},
{"Lowest Capacity Asset", "NB R735QTJ8XC9X"},
{"Portfolio Turnover", "12.54%"},
{"OrderListHash", "fae1a7c34d640dfa020330f24378bcf7"}
{"Alpha", "-0.804"},
{"Beta", "1.002"},
{"Annual Standard Deviation", "0.1"},
{"Annual Variance", "0.01"},
{"Information Ratio", "-14.419"},
{"Tracking Error", "0.056"},
{"Treynor Ratio", "-0.433"},
{"Total Fees", "$7.86"},
{"Estimated Strategy Capacity", "$1200000000.00"},
{"Lowest Capacity Asset", "GOOG T1AZ164W5VTX"},
{"Portfolio Turnover", "7.58%"},
{"OrderListHash", "fd3e6e9f401bc140d6b7cc8f1df8e46a"}
};
}
}

View File

@@ -27,6 +27,7 @@ namespace QuantConnect.Algorithm.CSharp
/// </summary>
public class CustomDataUniverseScheduledRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private List<Symbol> _currentUnderlyingSymbols = new();
private readonly Queue<DateTime> _selectionTime = new(new[] {
new DateTime(2014, 03, 25, 0, 0, 0),
new DateTime(2014, 03, 27, 0, 0, 0),
@@ -72,17 +73,21 @@ namespace QuantConnect.Algorithm.CSharp
if (!Portfolio.Invested)
{
var customData = slice.Get<CustomData>();
var symbols = slice.Keys.Where(symbol => symbol.SecurityType != SecurityType.Base).ToList();
foreach (var symbol in symbols)
if (customData.Count > 0)
{
SetHoldings(symbol, 1m / symbols.Count);
if (!customData.Any(custom => custom.Key.Underlying == symbol))
foreach (var symbol in _currentUnderlyingSymbols)
{
throw new RegressionTestException($"Custom data was not found for underlying symbol {symbol}");
SetHoldings(symbol, 1m / _currentUnderlyingSymbols.Count);
if (!customData.Any(custom => custom.Key.Underlying == symbol))
{
throw new RegressionTestException($"Custom data was not found for underlying symbol {symbol}");
}
}
}
}
// equity daily data arrives at 16 pm but custom data is set to arrive at midnight
_currentUnderlyingSymbols = slice.Keys.Where(symbol => symbol.SecurityType != SecurityType.Base).ToList();
}
public override void OnEndOfAlgorithm()
@@ -106,7 +111,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 21382;
public long DataPoints => 21374;
/// <summary>
/// Data Points count of the algorithm history
@@ -126,30 +131,30 @@ namespace QuantConnect.Algorithm.CSharp
{"Total Orders", "7"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "-65.130%"},
{"Drawdown", "2.900%"},
{"Compounding Annual Return", "-65.964%"},
{"Drawdown", "3.000%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "97717.31"},
{"Net Profit", "-2.283%"},
{"Sharpe Ratio", "-4.298"},
{"Sortino Ratio", "-4.067"},
{"Probabilistic Sharpe Ratio", "5.388%"},
{"End Equity", "97665.47"},
{"Net Profit", "-2.335%"},
{"Sharpe Ratio", "-3.693"},
{"Sortino Ratio", "-2.881"},
{"Probabilistic Sharpe Ratio", "6.625%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-1.062"},
{"Beta", "1.336"},
{"Annual Standard Deviation", "0.132"},
{"Annual Variance", "0.018"},
{"Information Ratio", "-12.03"},
{"Tracking Error", "0.078"},
{"Treynor Ratio", "-0.426"},
{"Total Fees", "$13.87"},
{"Estimated Strategy Capacity", "$430000000.00"},
{"Alpha", "-1.175"},
{"Beta", "1.621"},
{"Annual Standard Deviation", "0.156"},
{"Annual Variance", "0.024"},
{"Information Ratio", "-9.977"},
{"Tracking Error", "0.095"},
{"Treynor Ratio", "-0.355"},
{"Total Fees", "$13.86"},
{"Estimated Strategy Capacity", "$510000000.00"},
{"Lowest Capacity Asset", "NB R735QTJ8XC9X"},
{"Portfolio Turnover", "12.54%"},
{"OrderListHash", "fae1a7c34d640dfa020330f24378bcf7"}
{"Portfolio Turnover", "12.76%"},
{"OrderListHash", "4668d7bd05e2db15ff41d4e1aac621ab"}
};
}
}

View File

@@ -45,7 +45,7 @@ namespace QuantConnect.Algorithm.CSharp
AddSecurity(SecurityType.Equity, "SPY", Resolution.Hour);
}
public void OnData(TradeBars data)
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{

View File

@@ -82,7 +82,7 @@ namespace QuantConnect.Algorithm.CSharp
public long? ShortableQuantity(Symbol symbol, DateTime localTime)
{
if (localTime < new DateTime(2013, 10, 5))
if (localTime < new DateTime(2013, 10, 4, 16, 0, 0))
{
return 10;
}
@@ -106,7 +106,7 @@ namespace QuantConnect.Algorithm.CSharp
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 17;
public long DataPoints => 16;
/// <summary>
/// Data Points count of the algorithm history
@@ -149,7 +149,7 @@ namespace QuantConnect.Algorithm.CSharp
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Portfolio Turnover", "0%"},
{"OrderListHash", "65ce55aaad2f4a722858d84995fb7030"}
{"OrderListHash", "22bda6f4ef08246dbab1a43f97de6b68"}
};
}
}

View File

@@ -121,10 +121,10 @@ namespace QuantConnect.Algorithm.CSharp
{"Tracking Error", "0.087"},
{"Treynor Ratio", "-0.653"},
{"Total Fees", "$2.89"},
{"Estimated Strategy Capacity", "$1600000000.00"},
{"Estimated Strategy Capacity", "$2000000000.00"},
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "0.67%"},
{"OrderListHash", "d0880701c833c9b8521d634b7e1edf4d"}
{"OrderListHash", "6198706fef1ce2a60e8f16e7ab1485c1"}
};
}
}

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