# 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 *
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### Basic template algorithm simply initializes the date range and cash
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class LimitFillRegressionAlgorithm(QCAlgorithm):
def initialize(self):
'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
self.set_start_date(2013,10,7) #Set Start Date
self.set_end_date(2013,10,11) #Set End Date
self.set_cash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.add_equity("SPY", Resolution.SECOND)
def on_data(self, data):
'''on_data event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
if data.contains_key("SPY"):
if self.is_round_hour(self.time):
negative = 1 if self.time < (self.start_date + timedelta(days=2)) else -1
self.limit_order("SPY", negative*10, data["SPY"].price)
def is_round_hour(self, date_time):
'''Verify whether datetime is round hour'''
return date_time.minute == 0 and date_time.second == 0
def on_order_event(self, order_event):
self.debug(str(order_event))