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 |
import numpy as np class BasicTemplateAlgorithm(QCAlgorithm): def Initialize(self): self.instrument_id = "USDJPY" self.N1,self.N2= 150, 20 self.SetStartDate(2016,1,1) #Set Start Date self.SetEndDate(2016,1,10) #Set End Date self.SetCash(10000) #Set Strategy Cash self.SetBrokerageModel(BrokerageName.OandaBrokerage, AccountType.Margin) self.AddForex(self.instrument_id, Resolution.Tick) self.SetBenchmark(self.instrument_id) self.Securities[self.instrument_id].SetLeverage(50) ## Need to declare consolidator as Tick QuoteBar Consolidator so it can handle Tick objects, rather thank QuoteBar which would ## be the appropriate type for anything with a coarser resolution than tick ## Note that if your tick data was for a security supporting TradeBars, then the proper consolidator would be TickConsolidator consolidator = TickQuoteBarConsolidator(TimeSpan.FromMinutes(30)) ## force consolidator to produce 30 minute bars consolidator.DataConsolidated += self.OnCandle self.SubscriptionManager.AddConsolidator(self.instrument_id, consolidator) def OnData(self, data): ## Any trading code in here will be at the tick level pass def OnCandle(self, sender, bar): ## Any trading code in here will be at the minute level self.Log('New 30M bar >> Bid Close price: ' + str(bar.Bid.Close))