# 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 * ### ### Basic template algorithm simply initializes the date range and cash ### ### ### ### ### ### 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))