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 Probabilistic 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 2.042 Tracking Error 0.399 Treynor Ratio 0 Total Fees $0.00 |
from clr import AddReference AddReference("System") AddReference("QuantConnect.Algorithm") AddReference("QuantConnect.Indicators") AddReference("QuantConnect.Common") from System import * from QuantConnect import * from QuantConnect.Data import * from QuantConnect.Data.Market import * from QuantConnect.Data.Consolidators import * from QuantConnect.Algorithm import * from QuantConnect.Indicators import * from QuantConnect.Securities import * from QuantConnect.Orders import * from datetime import datetime from System.Drawing import Color import decimal as d import numpy as np class Demo(QCAlgorithm): def Initialize(self): # configuration parameters (configurable inputs into the algorithm) MINUTES_AFTER_OPEN = 0 MINUTES_BEFORE_CLOSE = 1 SYMBOL = 'SPY' BBLENGTH = 20 BBDEV = 2 self.ORDER_MAP = ["Market", "Limit", "StopMarket", "StopLimit", "MarketOnOpen", "MarketOnClose", "OptionExercise"] # initialization self.SetStartDate(2020, 9, 1) self.SetEndDate(2020, 9, 3) self.SetCash(100000) self.stock = self.AddEquity(SYMBOL, Resolution.Minute) self.SetTimeZone("America/Chicago") self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin) self.Schedule.On(self.DateRules.EveryDay(self.stock.Symbol), self.TimeRules.AfterMarketOpen(self.stock.Symbol, MINUTES_AFTER_OPEN), self.OnMarketOpen) self.Schedule.On(self.DateRules.EveryDay(self.stock.Symbol), self.TimeRules.BeforeMarketClose(self.stock.Symbol, MINUTES_BEFORE_CLOSE), self.OnMarketClose) # set the trade flag to False. we'll only start trading when the flag flips to True (after the market open event) self.tradeFlag = False #self.bb = self.BB(SYMBOL, BBLENGTH, 2, MovingAverageType.Exponential, Resolution.Minute) self.bb = BollingerBands(BBLENGTH, 2, MovingAverageType.Exponential) self.lastPrice = 0.0 self.pl = 0.0 self._lo = None self.SetWarmUp(BBLENGTH * 5, Resolution.Minute) ## Change set warm up self.Consolidate(SYMBOL, timedelta(minutes=5), self.OnStockBarConsolidated) def OnMarketOpen(self): self.tradeFlag = True def OnMarketClose(self): # liquidate all holdings if self.stock.Invested: self.Liquidate(self.stock.Symbol, "EOD Liquidate") else: self.Transactions.CancelOpenOrders() # reset trade flag for following day self.tradeFlag = False def OnStockBarConsolidated(self, consolidated): #if self.IsWarmingUp or not self.tradeFlag or not self.bb.IsReady: ######### Need to remove # return self.bb.Update(consolidated.EndTime, consolidated.Close) if not self.bb.IsReady: return self.Plot("BB", "Upper", self.bb.UpperBand.Current.Value) self.Plot("BB", "Price", consolidated.Close) self.Plot("BB", "Lower", self.bb.LowerBand.Current.Value)