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)