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* Adding new algorithm data handling options
- Adding new QCAlgorithm data handling method options to override.
Adding Py/C# regression tests
- Removing old OnData Type specific invoker methods
* Address reviews. Remove old OnData C# only methods
* First draft of the solution
* Add missing changes
* Remove the new KPI's from report
* Fix bugs
* nit change
* Add improvements
* Fix regression tests
* Solve bugs in the regression algos
* Fix regression tests bugs
* Expand unit tests and add minor changes
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* Add Sortino ratio to statistics and report
* Adds Sortino Ratio to Report Key Statistics
* Addresses Peer-Review
Reuse `SharpeRatioReportElement` and change the template.
* Reuse Calculations Across Statistics and PortfolioStatistics
* Adds Sortino Ratio to Regression Algorithms
* Removes Sortino Ratio from Optimization Result Table
---------
Co-authored-by: Alexandre Catarino <AlexCatarino@users.noreply.github.com>
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* Add new Order.PriceAdjustmentMode property
* Minor fix and unit test
* Minor fix and regression algorithms' stats update
* Unit test fixes
* Minor fix
* Set order price adjustment mode to raw always for live trading
* Adds `SimpleCustomFillModel` to `CustomModelsAlgorithm`
The simple fill model shows how to implement a simpler version of the most popular order fills: Market, Stop Market and Limit.
This model was tested on QuantConnect Cloud, and will serve as additonal example, since we don't have an example that does not reuse the method of the base class.
* Handles Tick Resolution Case
Tick-resolution data doesn't have TradeBar. We can use the security price, since it represents a trade (`TickTrade`).
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* Refactor alpha statistics
- Refactor alpha statistics, cleaning up and simplifying no longer required calculations and scoring
- Adding new InsightEvaluator abstraction, adding C# & PY regression
algorithms
* Optimization backtest result json converter update
* Address reviews
- Remove IAlphaHandler, move insight storage responsability to IResultHandler
and centralizing insight collection on the QCAlgorithm.Insights to be
reused by the framework models
- Fix portfolio turnover single day backtests and duplicate time
sampling handling. Updating regression algorithms
* Add InsightCollection tests and minor fixes
* Adding more & improved tests
* add data count properties
* 'add history count property
* assert data counts
* update missing override
* consider override/virtual cases
* implement data count
* add message handler for regression tests
* use regression test message handler
* set algorithm manager for regression test message handler
* update data count
* check if stats are present, check if algo manager is not null
* update
* add c# algo
* make same as c# algo
* use new line
* logic shifted to RegressionTestMessageHandler
* cleanup
* auto cleanup
* skip non deterministic data count
* change data count
* use inheritance
* improve stats
* update couht
* add sma indicator to c# and customSMA to python
* call base method before executing further
* skip test
* revert to original
* add duplicate sma
* skip regression test
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* Implement scheduled event sampling solution
* Use UTC time, only update daily portfolio value once a day
* For daily resolutions sample chart always
* Cleanup
* Drop resample daily all together
* Force final sample
* Regression updates
* FIx LiveResultHandler to update portfolio and benchmark values outside of sampling event
* Name the daily sampling event
* Address review pt 1
* Drop force and use reference wrapper
* Adjust tests
* Fix warning for Benchmark Timezone Misalignment and also add test
* Fix for daily resolution orders and test adjustments
* Also warn on universe settings with daily resolution
* Update missed regression
* Fix reference wrapper use
* Update regression after rebase
* Add values back in for Daylight Algo
* Have statistics builder skip day 1 performance
* Regression adjustments
* Test adjustments
* Update regression unit test
* Adjust some regressions starts to show performance values
* Add hourly algorithm for beta comparison
* Address missing Python regression changes
* Remove null comment
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* Add property for capacity. Remove unused variable
* Move SymbolCapacity and CapacityEstimate to common, passed through Symbol to runtime statistics
* Add null checks
* Remove uninvested and untradable assets from capacty calculations
* Add SymbolCapacity influential period
* Updates Regression Tests
- DelistingEventsAlgorithm
- Allows additional contributions from delisted AAA.1
- DelistingFutureOptionRegressionAlgorithm
- Removes DC01H12 contributions one month later
- FutureOptionBuySellCallIntradayRegressionAlgorithm
- Allows additional contributions from future after expiry replacing the contribution of the next contract option
- DelistedFutureLiquidateRegressionAlgorithm
- FutureOptionCallITMExpiryRegressionAlgorithm
- FutureOptionCallITMGreeksExpiryRegressionAlgorithm
- FutureOptionPutITMExpiryRegressionAlgorithm
- FutureOptionShortCallITMExpiryRegressionAlgorithm
- FutureOptionShortPutITMExpiryRegressionAlgorithm
- FuturesAndFuturesOptionsExpiryTimeAndLiquidationRegressionAlgorithm
- Allows additional contributions from future after expiry
- FutureOptionCallOTMExpiryRegressionAlgorithm
- FutureOptionPutOTMExpiryRegressionAlgorithm
- FutureOptionShortPutOTMExpiryRegressionAlgorithm
- IndexOptionCallITMGreeksExpiryRegressionAlgorithm
- IndexOptionCallOTMExpiryRegressionAlgorithm
- IndexOptionShortCallOTMExpiryRegressionAlgorithm
- Allows additional contributions from option after expiry
- MACDTrendAlgorithm
- Removes contribution when SPY is not invested for over one month
- UniverseSelectionRegressionAlgorithm
- Allows additional contributions from delisted GOOAV replacing GOOG (new symbols)
* Adds Lowest Capacity Asset to Regression Tests
* Normalize expected value -0, because -0 is also written to file if updated
* Write Symbol.Value for lowestCapacitySymbol or empty string for empty Symbol
* Update Regressions
* Update 'Lowest Capacity Asset' to Symbol.ID
Co-authored-by: Jared Broad <jaredbroad@gmail.com>
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
Co-authored-by: Colton Sellers <Colton.R.Sellers@gmail.com>
* Fixes Double to Decimal Cast in GetAnnualPerformance
`GetAnnualPerformance` raises an exception if the `AnnualPerformance` calculation returns a double that cannot be cast to decimal (smaller than `decimal.MinValue` or bigger than `decimal.MaxValue`).
See `ProbabilisticSharpeRatio` where the same solution was applied.
* Updates SPY Market Data
SPY is a key asset since it is the default benchmark, and any change can lead to different `Alpha` and `Beta`
* Updates Unit Tests to Reflect Data Update
* Updates Regression Tests to Reflect Data Update I
Most of the regression tests change because of updated data (market and factors) of SPY (default benchmark) while the total trade remain the same.
* Updates Regression Tests to Reflect Data Update II
The following regression tests were changed to adapt to adjusted prices and keep the total trades:
- `BacktestingBrokerageRegressionAlgorithm`
- `LimitIfTouchedRegressionAlgorithm`
- `PortfolioRebalanceOnCustomFuncRegressionAlgorithm`
- `SetAccountCurrencySecurityMarginModelRegressionAlgorithm`
- `StopLossOnOrderEventRegressionAlgorithm`
- `TimeInForceAlgorithm`
The following regression tests have more trades since adjusted prices allowed more 1-2 shares trades that were rounded down to zero before:
- `FreePortfolioValueRegressionAlgorithm` 2 -> 3
- `PortfolioRebalanceOnDateRulesRegressionAlgorithm` 291 -> 298
- `TrailingStopRiskFrameworkAlgorithm` 5 -> 7
Especial cases:
- `AutoRegressiveIntegratedMovingAverageRegressionAlgorithm` 65 -> 52
- ARIMA model sensibility
- `BlackLittermanPortfolioOptimizationFrameworkAlgorithm` 18 -> 19
- BLM model sensibility
- `ExtendedMarketHoursHistoryRegressionAlgorithm` 20 -> 18
- Less minute bars before market opens
* Addresses Peer-Review
Fix `BacktestingBrokerageRegressionAlgorithm` to use `CalculateOrderQuantity` and round down `quantity` to an even number to pass a value assertion and update the expected value from 50 to 52.
The quantity calculated by `CalculateOrderQuantity` has changed from 50 to 53 because of factor file update.
* Adds CapacityEstimate and SymbolCapacity
The capacity estimation has been moved from
the report generator and wired directly into
Lean via the ResultHandler. In addition,
the capacity estimation strategy has changed
to account for errors in the previous iteration
of the capacity estimation.
Many many thanks to Jared for being much of the
mastermind behind this project. It would have
been harder to complete without him to bounce ideas
off of.
* Moves old tests to regression algorithms
* Adds Estimated Capacity statistic
* Removes old capacity estimation tests
Final report capacity estimation. Pushing to save state
* Fixes bugs, cleans up code and adds comments
* Adds forced sampling to Capacity Estimation
* Misc. bug fixes for daily data
* Updates capacity test cases' Estimated Strategy Capacity statistic
* Adds Capacity Estimate to all regression algorithms
* Removes Report's StrategyCapacity class and fixes bug in tests
* Adds null check in BacktestingResultHandler to fix
BacktestingTransactionHandler failing tests
* Deletes old capacity estimation classes
* Retrieve capacity estimates from backtest statistics results
instead of calculating at runtime
* Make $0.00 capacity return as "-" and Result = 0 in report
* Adds capacity to runtime statistics
* Converts capacity to number denoted by financial figures in RuntimeStats
* Addresses review: code cleanup for Capacity and adds comments to regression tests
* Update OrderListHash to use MD5 as hash instead of hash code
* Update regression algorithm OrderListHash statistic
* Use full MD5 hash as OrderListHash, update regression statistic
* Fixes failing regression tests
* Adds CustomBuyingPowerModelAlgorithm
This algorithms is an example on how to implement a custom buying power model.
In this particular case, it shows how to override `HasSufficientBuyingPowerForOrder` in order to place orders without sufficient buying power according to the default model.
* Upgrades CustomModelsAlgorithm to Include CustomBuyingPowerModel
The custom buying power model overrides `HasSufficientBuyingPowerForOrderResult` but it doesn't change the trades and, consequently, the regression statistics.
- `CashBook[NullCurrency] { get; }` will throw an exception
- Revert `Currencies.USD` changes in user facing algorithms
- Improve some documentation
- Revert some format changes
- Adding more asserts for regression test
- Adding new regression tests using a custom fee model which returns
`OrderFee.Zero`
- Adding a non-usd account currency test to the cash book tests
- Adding some unit tests for `NullCurrency` and `OrderFee.Zero`
- Removing `AccountCurrency` from `Cash` and `Brokerage` classes.
`ICurrencyConverter` will now provide the `AccountCurrency`
- Adding new static `OrderFee.Zero` which will return a 0 order fee in
`NullCurrency`
- Adding static `Currencies.USD` value, replacing all "USD".
- Addin new static `Currencies.NullCurrency`
- Updating Bitfinex `FeeModel` so it return fees in quote currency.
Adding unit tests
- Refactoring `IFeeModel`. *This is a breaking change* for implementations
inheriting directly from the interface. Deleting old and adding a new method
`OrderFee GetOrderFee(OrderFeeParameters parameters)` that will use a parameter
and a result object.
- Refactoring `CashAmount` so it does not embed a `ICurrencyConverter`
instance.
- Updating unit tests
- The `Security.QuoteCurrency`, a `Cash` instance, will provide access
to the `AccountCurrency` as a property.
- Will maintain backwards compatibility with old python custom
FeeModels, Adding unit test.
> Note that for now, consumers will ignore the currency, as before, and
directly consume the amount
- Modifying `IFillModel` interface removing old methods and adding new
method `Fill Fill(FillModelParameters)`. This is a breaking change.
- Adding new `PythonWrapper` property for the `FillModel` base class.
This is required due to a limitation in PythonNet:
- Given C# class T has `virtual` methods A and B. Where method A
calls method B. And given custom python class L inherits class T.
And overrides method B. When class L calls
base method A (of class T). And when method A internally calls method B.
It will call C# implementation, not the python override. This issue
is solved going back to the `PythonWrapper`. Adding unit tests.
- Adding new `Parameters` property for the `FillModel` base class that will
be set by the call to `Fill()`. The `Parameters` property will be used by
the modified `XxxxFill()` implementations
- Adding new `Fill` result object for the `Fill(FillModelParameters)`
method
- Adding new check before removing a `SubscriptionDataConfig` due to the FillModels consuming the configuration collection when determining which Price to use. WIll now only remove the `SDC` if the symbol was removed from the selecting `universe`, this will avoid the case where the symbol is never deselected and the subscription ends, which happens at the end of all executions.
- Adding unit tests showcasing retro compatibility.
- Enabling C# `CustomModelsAlgorithm` as a regression test. Python
version returns a different result due to random number generation.
Adds support for fee, fill and slippage custom modelling.
Adds CustomModelsAlgorithm to showcase the new feature
Modifies C# version of CustomModelsAlgorithm to match existing data in github
Ricardo Andrés Marino Rojas