# 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>

### Basic template framework algorithm uses framework components to define the algorithm.

### </summary>

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

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

### <meta name="tag" content="trading and orders" />

class BasicTemplateIndiaAlgorithm(QCAlgorithm):

'''Basic template framework algorithm uses framework components to define the algorithm.'''

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_account_currency("INR") #Set Account Currency

self.set_start_date(2019, 1, 23) #Set Start Date

self.set_end_date(2019, 10, 31) #Set End Date

self.set_cash(100000) #Set Strategy Cash

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

self.add_equity("YESBANK", Resolution.MINUTE, Market.INDIA)

self.debug("numpy test >>> print numpy.pi: " + str(np.pi))

# Set Order Properties as per the requirements for order placement

self.default_order_properties = IndiaOrderProperties(Exchange.NSE)

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.market_order("YESBANK", 1)

def on_order_event(self, order_event):

if order_event.status == OrderStatus.FILLED:

self.debug("Purchased Stock: {0}".format(order_event.symbol))