Jhonathan Abreu
956428b7bf
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* Dynamic security properties for quick objects storage * Documentation and other minor changes * Add Security indexer to access custom properties * Address peer review * Minor changes * Improve regression algorithms * Bumped pythonnet to version 2.0.19 * Bumped pythonnet to version 2.0.20 * Address peer review
91 lines
4.0 KiB
Python
91 lines
4.0 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 cmath import isclose
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from AlgorithmImports import *
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### <summary>
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### Demonstration of how to use custom security properties.
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### In this algorithm we trade a security based on the values of a slow and fast EMAs which are stored in the security itself.
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### </summary>
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class SecurityCustomPropertiesAlgorithm(QCAlgorithm):
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'''Demonstration of how to use custom security properties.
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In this algorithm we trade a security based on the values of a slow and fast EMAs which are stored in the security itself.'''
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def Initialize(self):
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self.SetStartDate(2013,10, 7)
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self.SetEndDate(2013,10,11)
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self.SetCash(100000)
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self.spy = self.AddEquity("SPY", Resolution.Minute)
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# Using the dynamic interface to store our indicator as a custom property.
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self.spy.SlowEma = self.EMA(self.spy.Symbol, 30, Resolution.Minute)
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# Using the generic interface to store our indicator as a custom property.
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self.spy.Add("FastEma", self.EMA(self.spy.Symbol, 60, Resolution.Minute))
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# Using the indexer to store our indicator as a custom property
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self.spy["BB"] = self.BB(self.spy.Symbol, 20, 1, MovingAverageType.Simple, Resolution.Minute);
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# Fee factor to be used by the custom fee model
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self.spy.FeeFactor = 0.00002
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self.spy.SetFeeModel(CustomFeeModel())
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# This property will be used to store the prices used to calculate the fees in order to assert the correct fee factor is used.
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self.spy.OrdersFeesPrices = {}
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def OnData(self, data):
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if not self.spy.FastEma.IsReady:
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return
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if not self.Portfolio.Invested:
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# Using the property and the generic interface to access our indicator
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if self.spy.SlowEma > self.spy.FastEma:
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self.SetHoldings(self.spy.Symbol, 1)
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else:
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if self.spy.Get[ExponentialMovingAverage]("SlowEma") < self.spy.Get[ExponentialMovingAverage]("FastEma"):
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self.Liquidate(self.spy.Symbol)
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# Using the indexer to access our indicator
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bb: BollingerBands = self.spy["BB"]
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self.Plot("BB", bb.UpperBand, bb.MiddleBand, bb.LowerBand)
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def OnOrderEvent(self, orderEvent):
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if orderEvent.Status == OrderStatus.Filled:
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fee = orderEvent.OrderFee
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expectedFee = self.spy.OrdersFeesPrices[orderEvent.OrderId] * orderEvent.AbsoluteFillQuantity * self.spy.FeeFactor
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if not isclose(fee.Value.Amount, expectedFee, rel_tol=1e-15):
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raise Exception(f"Custom fee model failed to set the correct fee. Expected: {expectedFee}. Actual: {fee.Value.Amount}")
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def OnEndOfAlgorithm(self):
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if self.Transactions.OrdersCount == 0:
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raise Exception("No orders executed")
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class CustomFeeModel(FeeModel):
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'''This custom fee is implemented for demonstration purposes only.'''
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def GetOrderFee(self, parameters):
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security = parameters.Security
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# custom fee math using the fee factor stored in security instance
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feeFactor = security.FeeFactor
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if feeFactor is None:
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feeFactor = 0.00001
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# Store the price used to calculate the fee for this order
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security["OrdersFeesPrices"][parameters.Order.Id] = security.Price
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fee = max(1.0, security.Price * parameters.Order.AbsoluteQuantity * feeFactor)
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return OrderFee(CashAmount(fee, "USD"))
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