Overall Statistics
from QuantConnect.Data.Market import TradeBar
from datetime import timedelta
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
import decimal as d

class MyAlgorithm(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2013, 05, 1)  # Set Start Date
        self.SetEndDate(2013, 06, 01)
        self.SetCash(100000)  # Set Strategy Cash
        self.symbolData = dict()
        for ticker in ["SPY", "FB", "TWTR"]:
			symbol = self.AddEquity(ticker, Resolution.Second).Symbol

			consolidator_daily = TradeBarConsolidator(timedelta(1))
			consolidator_daily.DataConsolidated += self.OnDailyData
			self.SubscriptionManager.AddConsolidator(symbol, consolidator_daily)

			consolidator_minute = TradeBarConsolidator(60)
			consolidator_minute.DataConsolidated += self.OnMinuteData
			self.SubscriptionManager.AddConsolidator(symbol, consolidator_minute)
			self.symbolData[symbol] = SymbolData()

                         self.TimeRules.AfterMarketOpen('SPY', 2),
                         self.TimeRules.BeforeMarketClose('SPY', 1),

    # Add daily bar to daily rolling window
    def OnDailyData(self, sender, bar):

    def OnMinuteData(self, sender, bar):

    def one_minute_after_open_market(self):
        At 9:31 check if there has been a gap at the market open from the previous day.
        If so and the stock is gapping up and the first minute bar is negative, create a short selling signal.
        If the stock is gapping down and the first minute bar is positive, create a buying signal.

        for symbol in self.Securities.Keys:
            window = self.symbolData[symbol].window
            daily = self.symbolData[symbol].daily_rw
            minute = self.symbolData[symbol].minute_rw
            if not (window.IsReady and daily.IsReady and minute.IsReady): continue
            last_close = window[0].Close
            yesterday_daily_close = daily[1].Close
            first_minute_close = minute[1].Close
            first_minute_open = minute[1].Open
            gap = last_close - yesterday_daily_close
            first_minute_bar = first_minute_close - first_minute_open

            if not self.Portfolio[symbol].Invested:
                # If the stock is gapping down and the first minute bar is positive, create a buying signal.
                if gap < 0 and first_minute_bar > 0:
                    self.SetHoldings(symbol, 1.0/3.0)
                    self.Log('GOING LONG')
                # If the stock is gapping up and the first minute bar is negative, create a short selling signal
                elif gap > 0 and first_minute_bar < 0:
                    self.SetHoldings(symbol, -1.0/3.0)
                    self.Log('GOING SHORT')

    def before_close_market(self):
    	At the end of the day, if there is a short position, close it.
        self.Log('LIQUIDATE SHORT End of Day')

    def OnData(self, data):
    	for symbol in data.Keys:
    		if data[symbol] is None: continue
    	    # Create local variable to readability
    		window = self.symbolData[symbol].window
    		# Update the window. If not ready, continue
        	if not window.IsReady: continue	
        	if self.Portfolio[symbol].Invested:
        	    # Every second, check the price and if it's higher than the price the stock was bought for times 1.01, close the position.
        	    if self.Portfolio[symbol].AveragePrice * d.Decimal(1.01) < window[0].Close:
            		self.Log('LIQUIDATE AT THRESHOLD REACHED.')
    def OnEndOfDay(self):
    	self.Plot("Portfolio", "MarginRemaining", self.Portfolio.MarginRemaining)
    def OnEndOfAlgorithm(self):
    	self.Log('LIQUIDATE AT End Of Algorithm.')
class SymbolData(object):
    def __init__(self):
		self.daily_rw = RollingWindow[TradeBar](2)
		self.minute_rw = RollingWindow[TradeBar](2)
		self.window = RollingWindow[TradeBar](2)