Files
quantconnect--lean/Algorithm.Python/ZeroedBenchmarkRegressionAlgorithm.py
T
Colton Sellers 94d766ff89 Refactor Default Benchmark (#5158)
* Have BrokerageModel determine default benchmark

* Add DefaultBenchmark to Python wrapper

* Handle Null benchmark case

* Add NullBenchmarkRegressionAlgorithm

* Refactor solution to have BrokerageModel return IBenchmark; also refactor QCAlgorithm benchmark handling

* Always create a new security for benchmark

* Drop security overload, Always create a new security for benchmark

* Check our securities for a symbol matching the ticker before creating a new one

* No Python version of this regression

* Address review

* Create shared SecurityBenchmark creator function

* Add Python regression and needed FuncBenchmark constructor
2021-01-19 08:40:41 -03:00

59 lines
2.1 KiB
Python

# 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.
from clr import AddReference
AddReference("System.Core")
AddReference("QuantConnect.Common")
AddReference("QuantConnect.Algorithm")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import QCAlgorithm
from QuantConnect.Brokerages import *
from QuantConnect.Benchmarks import *
from QuantConnect.Data import *
from QuantConnect.Securities import *
### <summary>
### Regression algorithm to test zeroed benchmark through BrokerageModel override
### </summary>
### <meta name="tag" content="regression test" />
class ZeroedBenchmarkRegressionAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetCash(100000)
self.SetStartDate(2013,10,7)
self.SetEndDate(2013,10,8)
# Add Equity
self.AddEquity("SPY", Resolution.Hour)
# Use our Test Brokerage Model with zerod default benchmark
self.SetBrokerageModel(TestBrokerageModel())
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
Arguments:
data: Slice object keyed by symbol containing the stock data
'''
if not self.Portfolio.Invested:
self.SetHoldings("SPY", 1)
class TestBrokerageModel(DefaultBrokerageModel):
def GetBenchmark(self, securities):
return FuncBenchmark(self.func)
def func(self, datetime):
return 0;