Overall Statistics Total Trades 3 Average Win 9.48% Average Loss 0% Compounding Annual Return 16.045% Drawdown 12.100% Expectancy 0 Net Profit 8.450% Sharpe Ratio 0.603 Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha 0 Beta 8.976 Annual Standard Deviation 0.204 Annual Variance 0.042 Information Ratio 0.535 Tracking Error 0.204 Treynor Ratio 0.014 Total Fees \$0.00
```from clr import AddReference

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

### <summary>
### This demonstration imports indian NSE index "NIFTY" as a tradable security in addition to the USDINR currency pair. We move into the
### NSE market when the economy is performing well.
### </summary>
### <meta name="tag" content="strategy example" />
### <meta name="tag" content="using data" />
### <meta name="tag" content="custom data" />
class CustomDataNIFTYAlgorithm(QCAlgorithm):

def Initialize(self):
self.SetStartDate(2008, 1, 8)
self.SetEndDate(2008, 7, 25)
self.SetCash(100000)

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

self.minimumCorrelationHistory = 50
self.today = CorrelationPair()
self.prices = []
self.increment = 0

consolidator = self.ResolveConsolidator("NIFTY", timedelta(30))
consolidator.DataConsolidated += self.OnDataConsolidated

def OnDataConsolidated(self, sender, bar):
self.Debug(self.increment)

def OnData(self, data):
self.increment = self.increment+1
if data.ContainsKey("USDINR"):
self.today = CorrelationPair(self.Time)
self.today.CurrencyPrice = data["USDINR"].Close

if not data.ContainsKey("NIFTY"): 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()```