# 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>

### Demonstration of requesting daily resolution data for US Equities.

### This is a simple regression test algorithm using a skeleton algorithm and requesting daily data.

### </summary>

### <meta name="tag" content="using data" />

class BasicTemplateDailyAlgorithm(QCAlgorithm):

'''Basic template algorithm simply initializes the date range and cash'''

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(2013,10,8) #Set Start Date

self.set_end_date(2013,10,17) #Set End Date

self.set_cash(100000) #Set Strategy Cash

# Find more symbols here: http://quantconnect.com/data

self.add_equity("SPY", Resolution.DAILY)

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.

Arguments:

data: Slice object keyed by symbol containing the stock data

'''

if not self.portfolio.invested:

self.set_holdings("SPY", 1)

self.debug("Purchased Stock")