Martin Molinero
46baedf858
- 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.
110 lines
4.8 KiB
Python
110 lines
4.8 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from clr import AddReference
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AddReference("System")
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AddReference("QuantConnect.Algorithm")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Algorithm import *
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from QuantConnect.Orders import OrderStatus
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from QuantConnect.Orders.Fills import ImmediateFillModel
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import numpy as np
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import decimal as d
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import random
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### <summary>
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### Demonstration of using custom fee, slippage and fill models for modelling transactions in backtesting.
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### QuantConnect allows you to model all orders as deeply and accurately as you need.
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### </summary>
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### <meta name="tag" content="trading and orders" />
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### <meta name="tag" content="transaction fees and slippage" />
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### <meta name="tag" content="custom transaction models" />
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### <meta name="tag" content="custom slippage models" />
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### <meta name="tag" content="custom fee models" />
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class CustomModelsAlgorithm(QCAlgorithm):
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'''Demonstration of using custom fee, slippage and fill models for modelling transactions in backtesting.
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QuantConnect allows you to model all orders as deeply and accurately as you need.'''
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def Initialize(self):
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self.SetStartDate(2013,10,1) # Set Start Date
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self.SetEndDate(2013,10,31) # Set End Date
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self.security = self.AddEquity("SPY", Resolution.Hour)
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self.spy = self.security.Symbol
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# set our models
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self.security.SetFeeModel(CustomFeeModel(self))
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self.security.SetFillModel(CustomFillModel(self))
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self.security.SetSlippageModel(CustomSlippageModel(self))
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def OnData(self, data):
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open_orders = self.Transactions.GetOpenOrders(self.spy)
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if len(open_orders) != 0: return
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if self.Time.day > 10 and self.security.Holdings.Quantity <= 0:
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quantity = self.CalculateOrderQuantity(self.spy, .5)
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self.Log("MarketOrder: " + str(quantity))
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self.MarketOrder(self.spy, quantity, True) # async needed for partial fill market orders
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elif self.Time.day > 20 and self.security.Holdings.Quantity >= 0:
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quantity = self.CalculateOrderQuantity(self.spy, -.5)
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self.Log("MarketOrder: " + str(quantity))
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self.MarketOrder(self.spy, quantity, True) # async needed for partial fill market orders
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# If we want to use methods from other models, you need to inherit from one of them
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class CustomFillModel(ImmediateFillModel):
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def __init__(self, algorithm):
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self.algorithm = algorithm
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self.absoluteRemainingByOrderId = {}
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random.seed(100)
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def MarketFill(self, asset, order):
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#if not _absoluteRemainingByOrderId.TryGetValue(order.Id, absoluteRemaining):
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absoluteRemaining = order.AbsoluteQuantity
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self.absoluteRemainingByOrderId[order.Id] = order.AbsoluteQuantity
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fill = super().MarketFill(asset, order)
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absoluteFillQuantity = int(min(absoluteRemaining, random.randint(0, 2*int(order.AbsoluteQuantity))))
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fill.FillQuantity = np.sign(order.Quantity) * absoluteFillQuantity
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if absoluteRemaining == absoluteFillQuantity:
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fill.Status = OrderStatus.Filled
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if self.absoluteRemainingByOrderId.get(order.Id):
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self.absoluteRemainingByOrderId.pop(order.Id)
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else:
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absoluteRemaining = absoluteRemaining - absoluteFillQuantity
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self.absoluteRemainingByOrderId[order.Id] = absoluteRemaining
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fill.Status = OrderStatus.PartiallyFilled
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self.algorithm.Log("CustomFillModel: " + str(fill))
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return fill
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class CustomFeeModel:
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def __init__(self, algorithm):
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self.algorithm = algorithm
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def GetOrderFee(self, security, order):
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# custom fee math
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fee = max(1, security.Price * order.AbsoluteQuantity * d.Decimal(0.00001))
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self.algorithm.Log("CustomFeeModel: " + str(fee))
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return fee
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class CustomSlippageModel:
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def __init__(self, algorithm):
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self.algorithm = algorithm
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def GetSlippageApproximation(self, asset, order):
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# custom slippage math
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slippage = asset.Price * d.Decimal(0.0001 * np.log10(2*float(order.AbsoluteQuantity)))
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self.algorithm.Log("CustomSlippageModel: " + str(slippage))
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return slippage |