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* Python research import improvements
- Improve start.py for research env
- Remove unrequired imports
* Centralize algorithm imports
* Add regression test GH action
* Unit test python import clean up
* Join research and main imports
* More python import clean up
* Fix failing skipped regression algorithm
* 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.
We didn't experience the expected performance improvements. Locally under
unit test there was aboout an order of magnitude throughput increase, but
when run against the history benchmark, this new approach was 60% slower.
We're reverting this for now to perform further analysis and better
understand the performance profiling of the python history stack.
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
Martin-Molinero