# 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 clr import AddReference

AddReference("System")

AddReference("QuantConnect.Algorithm")

AddReference("QuantConnect.Common")

from System import *

from QuantConnect import *

from QuantConnect.Algorithm import *

from QuantConnect.Data import SubscriptionDataSource

from QuantConnect.Python import PythonData

from datetime import date, timedelta, datetime

import decimal

import numpy as np

import math

import json

class CustomDataNIFTYAlgorithm(QCAlgorithm):

'''3.0 CUSTOM DATA SOURCE: USE YOUR OWN MARKET DATA (OPTIONS, FOREX, FUTURES, DERIVATIVES etc).

The new QuantConnect Lean Backtesting Engine is incredibly flexible and allows you to define your own data source.

This includes any data source which has a TIME and VALUE. These are the *only* requirements.

To demonstrate this we're loading in "Nifty" data. This by itself isn't special, the cool part is next:

We load the "Nifty" data as a tradable security we're calling "NIFTY".'''

def Initialize(self):

self.SetStartDate(2008, 1, 8)

self.SetEndDate(2014, 7, 25)

self.SetCash(100000)

# Define the symbol and "type" of our generic data:

self.AddData(DollarRupee, "USDINR")

self.AddData(Nifty, "NIFTY")

self.minimumCorrelationHistory = 50

self.today = CorrelationPair()

self.prices = []

def OnData(self, data):

if "USDINR" in data:

self.today = CorrelationPair(self.Time)

self.today.CurrencyPrice = data["USDINR"].Close

if "NIFTY" not in data: return

self.today.NiftyPrice = data["NIFTY"].Close

if self.today.date() == data["NIFTY"].Time.date():

self.prices.append(self.today)

if len(self.prices) > self.minimumCorrelationHistory:

self.prices.pop(0)

# Strategy

if self.Time.weekday() != 2: return

cur_qnty = self.Portfolio["NIFTY"].Quantity

quantity = decimal.Decimal(math.floor(self.Portfolio.MarginRemaining * decimal.Decimal(0.9) / data["NIFTY"].Close))

hi_nifty = max(price.NiftyPrice for price in self.prices)

lo_nifty = min(price.NiftyPrice for price in self.prices)

if data["NIFTY"].Open >= hi_nifty:

code = self.Order("NIFTY", quantity - cur_qnty)

self.Debug("LONG {0} Time: {1} Quantity: {2} Portfolio: {3} Nifty: {4} Buying Power: {5}".format(code, self.Time, quantity, self.Portfolio["NIFTY"].Quantity, data["NIFTY"].Close, self.Portfolio.TotalPortfolioValue))

elif data["NIFTY"].Open <= lo_nifty:

code = self.Order("NIFTY", -quantity - cur_qnty)

self.Debug("SHORT {0} Time: {1} Quantity: {2} Portfolio: {3} Nifty: {4} Buying Power: {5}".format(code, self.Time, quantity, self.Portfolio["NIFTY"].Quantity, data["NIFTY"].Close, self.Portfolio.TotalPortfolioValue))

class Nifty(PythonData):

'''NIFTY Custom Data Class'''

def GetSource(self, config, date, isLiveMode):

return SubscriptionDataSource("https://www.dropbox.com/s/rsmg44jr6wexn2h/CNXNIFTY.csv?dl=1", SubscriptionTransportMedium.RemoteFile);

def Reader(self, config, line, date, isLiveMode):

if not (line.strip() and line[0].isdigit()): return None

# New Nifty object

index = Nifty();

index.Symbol = config.Symbol

try:

# Example File Format:

# Date, Open High Low Close Volume Turnover

# 2011-09-13 7792.9 7799.9 7722.65 7748.7 116534670 6107.78

data = line.split(',')

index.Time = datetime.strptime(data[0], "%Y-%m-%d")

index.Value = decimal.Decimal(data[4])

index["Open"] = float(data[1])

index["High"] = float(data[2])

index["Low"] = float(data[3])

index["Close"] = float(data[4])

except ValueError:

# Do nothing

return None

return index

class DollarRupee(PythonData):

'''Dollar Rupe is a custom data type we create for this algorithm'''

def GetSource(self, config, date, isLiveMode):

return SubscriptionDataSource("https://www.dropbox.com/s/m6ecmkg9aijwzy2/USDINR.csv?dl=1", SubscriptionTransportMedium.RemoteFile)

def Reader(self, config, line, date, isLiveMode):

if not (line.strip() and line[0].isdigit()): return None

# New USDINR object

currency = DollarRupee();

currency.Symbol = config.Symbol

try:

data = line.split(',')

currency.Time = datetime.strptime(data[0], "%Y-%m-%d")

currency.Value = decimal.Decimal(data[1])

currency["Close"] = float(data[1])

except ValueError:

# Do nothing

return None

return currency;

class CorrelationPair:

'''Correlation Pair is a helper class to combine two data points which we'll use to perform the correlation.'''

def __init__(self, *args):

self.NiftyPrice = 0 # Nifty price for this correlation pair

self.CurrencyPrice = 0 # Currency price for this correlation pair

self._date = datetime.min # Date of the correlation pair

if len(args) > 0: self._date = args[0]

def date(self):

return self._date.date()