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FilteredIdentityAlgorithm.py
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FilteredIdentityAlgorithm.py
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# 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 AlgorithmImports import *
### <summary>
### Example algorithm of the Identity indicator with the filtering enhancement. Filtering is used to check
### the output of the indicator before returning it.
### </summary>
### <meta name="tag" content="indicators" />
### <meta name="tag" content="indicator classes" />
class FilteredIdentityAlgorithm(QCAlgorithm):
''' Example algorithm of the Identity indicator with the filtering enhancement '''
def Initialize(self):
self.SetStartDate(2014,5,2) # Set Start Date
self.SetEndDate(self.StartDate) # Set End Date
self.SetCash(100000) # Set Stratgy Cash
# Find more symbols here: http://quantconnect.com/data
security = self.AddForex("EURUSD", Resolution.Tick)
self.symbol = security.Symbol
self.identity = self.FilteredIdentity(self.symbol, None, self.Filter)
def Filter(self, data):
'''Filter function: True if data is not an instance of Tick. If it is, true if TickType is Trade
data -- Data for applying the filter'''
if isinstance(data, Tick):
return data.TickType == TickType.Trade
return True
def OnData(self, data):
# Since we are only accepting TickType.Trade,
# this indicator will never be ready
if not self.identity.IsReady: return
if not self.Portfolio.Invested:
self.SetHoldings(self.symbol, 1)
self.Debug("Purchased Stock")