Louis Szeto
cece811cce
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Co-authored-by: LouisSzeto <hke0073@hotmail.com>
72 lines
2.9 KiB
Python
72 lines
2.9 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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### <summary>
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### Basic Template India Index Algorithm uses framework components to define the algorithm.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="using quantconnect" />
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### <meta name="tag" content="trading and orders" />
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class BasicTemplateIndiaIndexAlgorithm(QCAlgorithm):
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'''Basic template framework algorithm uses framework components to define the algorithm.'''
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def Initialize(self):
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'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
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self.SetAccountCurrency("INR") #Set Account Currency
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self.SetStartDate(2019, 1, 1) #Set Start Date
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self.SetEndDate(2019, 1, 5) #Set End Date
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self.SetCash(1000000) #Set Strategy Cash
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# Use indicator for signal; but it cannot be traded
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self.Nifty = self.AddIndex("NIFTY50", Resolution.Minute, Market.India).Symbol
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# Trade Index based ETF
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self.NiftyETF = self.AddEquity("JUNIORBEES", Resolution.Minute, Market.India).Symbol
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# Set Order Prperties as per the requirements for order placement
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self.DefaultOrderProperties = IndiaOrderProperties(Exchange.NSE)
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# Define indicator
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self._emaSlow = self.EMA(self.Nifty, 80)
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self._emaFast = self.EMA(self.Nifty, 200)
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self.Debug("numpy test >>> print numpy.pi: " + str(np.pi))
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def OnData(self, data):
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'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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Arguments:
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data: Slice object keyed by symbol containing the stock data
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'''
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if not data.Bars.ContainsKey(self.Nifty) or not data.Bars.ContainsKey(self.NiftyETF):
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return
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if not self._emaSlow.IsReady:
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return
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if self._emaFast > self._emaSlow:
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if not self.Portfolio.Invested:
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self.marketTicket = self.MarketOrder(self.NiftyETF, 1)
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else:
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self.Liquidate()
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def OnEndOfAlgorithm(self):
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if self.Portfolio[self.Nifty].TotalSaleVolume > 0:
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raise Exception("Index is not tradable.")
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