# 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 India Index 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 BasicTemplateIndiaIndexAlgorithm(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.SetAccountCurrency("INR") #Set Account Currency

self.SetStartDate(2019, 1, 1) #Set Start Date

self.SetEndDate(2019, 1, 5) #Set End Date

self.SetCash(1000000) #Set Strategy Cash

# Use indicator for signal; but it cannot be traded

self.Nifty = self.AddIndex("NIFTY50", Resolution.Minute, Market.India).Symbol

# Trade Index based ETF

self.NiftyETF = self.AddEquity("JUNIORBEES", Resolution.Minute, Market.India).Symbol

# Set Order Properties as per the requirements for order placement

self.DefaultOrderProperties = IndiaOrderProperties(Exchange.NSE)

# Define indicator

self._emaSlow = self.EMA(self.Nifty, 80)

self._emaFast = self.EMA(self.Nifty, 200)

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

def OnData(self, data):

'''OnData 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 data.Bars.ContainsKey(self.Nifty) or not data.Bars.ContainsKey(self.NiftyETF):

return

if not self._emaSlow.IsReady:

return

if self._emaFast > self._emaSlow:

if not self.Portfolio.Invested:

self.marketTicket = self.MarketOrder(self.NiftyETF, 1)

else:

self.Liquidate()

def OnEndOfAlgorithm(self):

if self.Portfolio[self.Nifty].TotalSaleVolume > 0:

raise Exception("Index is not tradable.")