from datetime import timedelta
import decimal as d

class ETFEmaCross(QCAlgorithm):
    
    def Initialize(self):
        self.SetStartDate(2017,1,1)  
        self.SetEndDate(2017,12,29)    
        self.SetCash(25000)
        
        # Tolerance to avoid bouncing
        self.LongTolerance = .0020
        self.ShortTolerance = .00015
        
        self.etfs = [
            self.AddEquity("SPY", Resolution.Minute).Symbol,
            self.AddEquity("VXX", Resolution.Minute).Symbol,
            self.AddEquity("VONE", Resolution.Minute).Symbol,
            self.AddEquity("ILTB", Resolution.Minute).Symbol,
            self.AddEquity("FNCL", Resolution.Minute).Symbol,
            self.AddEquity("HYD", Resolution.Minute).Symbol,
            self.AddEquity("IXUS", Resolution.Minute).Symbol,
            self.AddEquity("ICVT", Resolution.Minute).Symbol,
            self.AddEquity("QAI", Resolution.Minute).Symbol,
            self.AddEquity("PICK", Resolution.Minute).Symbol,
            self.AddEquity("QQQ", Resolution.Minute).Symbol
        ]
          
        # add indicator dicts(to store an indicator per asset)
        self.ema13 = {}
        self.ema49 = {}
        for symbol in self.etfs:
            self.ema13[symbol] = self.EMA(symbol, 13, Resolution.Daily)
            self.ema49[symbol] = self.EMA(symbol, 49, Resolution.Daily)
            
        # Fire rebalance on open each day
        self.AddEquity("SPY", Resolution.Minute)
        self.Schedule.On(self.DateRules.EveryDay("SPY"),
                self.TimeRules.AfterMarketOpen("SPY", 30),
                Action(self.Rebalance))
                
        # Charting is cool for debugging, but careful not to overdo it and run out of quota
        self.charting_mode = False
        
        if self.charting_mode:
            stockPlot = Chart('Indicators')
            # On the Trade Plotter Chart we want 3 series: trades and price:
            for i, symbol in enumerate(self.etfs):
                stockPlot.AddSeries(Series('%s'%str(symbol), SeriesType.Line, i)) #y axis label only
                stockPlot.AddSeries(Series('%s_Price'%str(symbol), SeriesType.Line, i))
                stockPlot.AddSeries(Series('%s_13'%str(symbol), SeriesType.Line, i))
                stockPlot.AddSeries(Series('%s_49'%str(symbol), SeriesType.Line, i))
            self.AddChart(stockPlot)
           
        # warmup to prepare the indicators so they work on day 1(which are in daily mode, but algo steps in minute mode)
        self.SetWarmUp(int(6.5*60*49))
            
    def OnData(self, data):
        # fires every minute
        
        if self.IsWarmingUp: return
        
        pass
        
    def Rebalance(self):
        self.winnerLength = []
        # loop through universe
        for symbol in self.etfs:
            # Ensure the Indicators are ready and not returning 0.0
            if self.ema13[symbol].IsReady and self.ema49[symbol].IsReady:
                #self.winnerLength.append(1)
                #Long
                if self.ema13[symbol].Current.Value > self.ema49[symbol].Current.Value*d.Decimal(1+self.LongTolerance):
                    self.winnerLength.append(1)
                    if self.Portfolio[symbol].Quantity <= 0:
                        self.SetHoldings(symbol, 1./float(len(self.winnerLength)), tag="Long")
                # Liquidate
                elif self.ema13[symbol].Current.Value < self.ema49[symbol].Current.Value*d.Decimal(1+self.ShortTolerance):
                    if self.Portfolio[symbol].Quantity >= 0:
                        self.SetHoldings(symbol, 0/float(len(self.etfs)), tag="Short")
                
                if self.charting_mode:
                    self.Plot('Indicators', '%s_Price'%str(symbol), self.Securities[symbol].Price)
                    self.Plot('Indicators', '%s_13'%str(symbol), self.ema13[symbol].Current.Value)
                    self.Plot('Indicators', '%s_49'%str(symbol), self.ema49[symbol].Current.Value)