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 -1.138 Tracking Error 0.161 Treynor Ratio 0 Total Fees $0.00 |
from datetime import datetime,timedelta class ParticleNadionChamber(QCAlgorithm): def Initialize(self): self.SetStartDate(2015, 1, 13) # Set Start Date self.SetEndDate(datetime.now()-timedelta(days = 1)) self.SetCash(1000000) # Set Strategy Cash #Adding the symbols for the portfolio self.symbolList = ["AAPL"] #self.symbolList = ["GOOG", "GOOGL"] #GOOG is an issue self.allocation = round(1/len(self.symbolList),2) self.daily = {} # list of symbol objects self.SecuritySymbols = [] for name in self.symbolList: # get symbol object symbol = self.AddEquity(name, Resolution.Hour, Market.USA).Symbol # append to list self.SecuritySymbols.append(symbol) self.daily[symbol] = RollingWindow[float](2) self.SetWarmup(200) def OnData(self, data): '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. Arguments: data: Slice object keyed by symbol containing the stock data ''' for symbol in self.SecuritySymbols: if data.ContainsKey(symbol): #data.ContainsKey("EURUSD") #self.Debug("{}".format(symbol)) # get OHLC values to use later # o = data.Bars[symbol].Open # h = data.Bars[symbol].High # l = data.Bars[symbol].Low c = data.Bars[symbol].Close # update our rolling window self.daily[symbol].Add(c) # check if rolling window is full if not (self.daily[symbol].IsReady): return prev_hour_price = self.daily[symbol][1] current_bar_close = self.daily[symbol][0] else: pass