| Overall Statistics |
|
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 Total Fees $0.00 |
# 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.Indicators")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
from datetime import datetime
### <summary>
### Simple indicator demonstration algorithm of MACD
### </summary>
### <meta name="tag" content="indicators" />
### <meta name="tag" content="indicator classes" />
### <meta name="tag" content="plotting indicators" />
class ForexScalping(QCAlgorithm):
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.SetStartDate(2015, 1, 1) #Set Start Date
self.SetEndDate(2015, 1, 5) #Set End Date
self.SetCash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.eurUsd = SymbolData(self,self.AddForex("EURUSD", Resolution.Minute).Symbol)
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
if not self.Portfolio.Invested \
and self.eurUsd.macd.Current.Value>0 \
and self.eurUsd.macd.Current.Value > self.eurUsd.macd.Signal.Current.Value \
and self.eurUsd.bb.UpperBand.Current.Value>self.eurUsd.bbUpperPrevious \
and self.eurUsd.rsi.Current.Value>0.7:
self.Debug("Place Order!")
stopLoss = self.eurUsd.atr.Current.Value * 0.1
profitTarget = self.eurUsd.atr.Current.Value * 0.15
currentPrice = data[self.eurUsd.symbol].Price
stopLossPrice = currentPrice - stopLoss
profitTargetPrice = currentPrice + profitTarget
limitPrice = self.eurUsd.bb.UpperBand.Current.Value
#Place an order with the following features:
# - enter 100% long position once price of currency pair is above limitPrice
# - close long position once the price of the currency pair is below stopLossPrice or above profitTargetPrice
else:
#cancel all open orders
self.Debug("Cancel orders!")
openOrders = self.Transactions.GetOpenOrders()
if len(openOrders)> 0:
for x in openOrders:
self.Transactions.CancelOrder(x.Id)
self.eurUsd.bbUpperPrevious = self.eurUsd.bb.UpperBand.Current.Value
class SymbolData:
def __init__(self,qcContext, symbol):
self.qcContext = qcContext
self.symbol = symbol
self.macd = qcContext.MACD(self.symbol, 12, 26, 9, MovingAverageType.Exponential, Resolution.Minute)
self.qcContext.RegisterIndicator(self.symbol, self.macd, Resolution.Minute)
self.bb = qcContext.BB(self.symbol, 12, 2, Resolution.Minute)
self.qcContext.RegisterIndicator(self.symbol, self.bb, Resolution.Minute)
self.rsi = qcContext.RSI(self.symbol, 7, Resolution.Minute)
self.qcContext.RegisterIndicator(self.symbol, self.rsi, Resolution.Minute)
self.bbUpperPrevious = self.bb.UpperBand.Current.Value
self.atr = qcContext.ATR(self.symbol, 7, Resolution.Daily)
self.qcContext.RegisterIndicator(self.symbol, self.atr, Resolution.Daily)
#self.qcContext.PlotIndicator("MACD_"+self.symbol, True, self.macd, self.macd.Signal)