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
#
#   QuantConnect Basic Template:
#	Fundamentals to using a QuantConnect algorithm.
#
#	You can view the QCAlgorithm base class on Github: 
#	https://github.com/QuantConnect/Lean/tree/master/Algorithm
#

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(2017, 8, 21)  # Set Start Date
        self.SetEndDate(2017, 9, 13)
        self.SetCash(10000)  # Set Strategy Cash
        self.symbol = self.AddEquity("AAPL", Resolution.Second).Symbol

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

        consolidator_minute = TradeBarConsolidator(60)
        consolidator_minute.DataConsolidated += self.OnMinuteData
        self.SubscriptionManager.AddConsolidator(self.symbol, consolidator_minute)

        self.daily_rw = RollingWindow[TradeBar](2)
        self.minute_rw = RollingWindow[TradeBar](2)
        self.window = RollingWindow[TradeBar](2)

        self.Schedule.On(self.DateRules.EveryDay(),
                         self.TimeRules.AfterMarketOpen(self.symbol, 5),
                         Action(self.five_minutes_after_open_market))

        self.Schedule.On(self.DateRules.EveryDay(),
                         self.TimeRules.BeforeMarketClose(self.symbol, 1),
                         Action(self.before_close_market))

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

    def OnMinuteData(self, sender, bar):
        self.minute_rw.Add(bar)

    def five_minutes_after_open_market(self):
        
        if not (self.window.IsReady and self.daily_rw.IsReady and self.minute_rw.IsReady): return
        last_close = self.window[0].Close
        #self.Log(last_close)
        yesterday_daily_close = self.daily_rw[0].Close
        last_minute_close = self.minute_rw[0].Close
        last_minute_open = self.minute_rw[0].Open
        curr_price = self.Securities[self.symbol].Price
        
        gap = (last_close - yesterday_daily_close)/yesterday_daily_close*100
        last_minute_bar = last_minute_close - last_minute_open
        stop_price06 = yesterday_daily_close*d.Decimal(0.6)
        stop_price12 = yesterday_daily_close*d.Decimal(1.2)
        stop_price18 = yesterday_daily_close*d.Decimal(1.8)
        stop_price24 = yesterday_daily_close*d.Decimal(2.4)
        stop_price30 = yesterday_daily_close*d.Decimal(3.0)
        stop_price36 = yesterday_daily_close*d.Decimal(3.6)
        stop_price42 = yesterday_daily_close*d.Decimal(4.2)
        stop_price48 = yesterday_daily_close*d.Decimal(4.8)
       

        if not self.Portfolio[self.symbol].Invested:
           
            if last_close < stop_price06 and last_minute_bar > 0:
                self.StopMarketOrder(self.symbol, 60, stop_price06)
                self.Log('GOING LONG @ 0.6')
                self.Log('Last bar close: {0}'.format(last_close))
                self.Log('Pr day close: {0}'.format(yesterday_daily_close))
                self.Log('Last min close: {0}'.format(last_minute_close))
                self.Log('Last min open: {0}'.format(last_minute_open))
           
            elif last_close < stop_price12 and last_minute_bar > 0:
            	self.StopMarketOrder(self.symbol, 60, stop_price12)
                self.Log('GOING LONG @ 1.2')
                #self.SetHoldings(self.symbol, -1)
                #self.Log('GOING SHORT')
            elif last_close < stop_price18 and last_minute_bar > 0:
            	self.StopMarketOrder(self.symbol, 60, stop_price18)
                self.Log('GOING LONG @ 1.8')

    def before_close_market(self):
    	"""
    	At the end of the day, if there is a short position, close it.
    	"""
        if self.Portfolio[self.symbol].IsShort:
            self.Liquidate(self.symbol)
            self.Log('LIQUIDATE SHORT End of Day')

    # Add second bar to window rolling window
    def OnData(self, data):
        if data[self.symbol] is None:
            return
        self.window.Add(data[self.symbol])
        if not (self.window.IsReady and self.minute_rw.IsReady and self.daily_rw.IsReady):
            return
        # self.Log("haha")
        factor = d.Decimal(1.006)

        currBar = self.window[0].High
        curr_price = data[self.symbol]
        last_minute_close = self.minute_rw[0].Close
        last_minute_open = self.minute_rw[0].Open
        yesterday_daily_close = self.daily_rw[0].Close
        last_minute_bar = last_minute_close - last_minute_open
        stop_price06 = yesterday_daily_close*d.Decimal(0.6)
        stop_price12 = yesterday_daily_close*d.Decimal(1.2)
        stop_price18 = yesterday_daily_close*d.Decimal(1.8)
        stop_price24 = yesterday_daily_close*d.Decimal(2.4)
        stop_price30 = yesterday_daily_close*d.Decimal(3.0)
        stop_price36 = yesterday_daily_close*d.Decimal(3.6)
        stop_price42 = yesterday_daily_close*d.Decimal(4.2)
        stop_price48 = yesterday_daily_close*d.Decimal(4.8)
       
        if not self.Portfolio[self.symbol].Invested:
        	if curr_price == stop_price06 and last_minute_bar > 0:
            		self.SetHoldings(self.symbol, 1)
                	self.Log('GOING LONG @ 0.6')
            	elif curr_price == stop_price12 and last_minute_bar > 0:
            		self.SetHoldings(self.symbol, 1)
                	self.Log('GOING LONG @ 1.2')
            	elif curr_price == stop_price18 and last_minute_bar > 0:
            		self.SetHoldings(self.symbol, 1)
                	self.Log('GOING LONG @ 1.8')    
        
        # Every second, check the price and if it's higher than the price the stock was bought for times 1.006, close the position.
        if self.Portfolio[self.symbol].Invested and self.Portfolio[self.symbol].AveragePrice * factor <= curr_price:
            self.Liquidate(self.symbol)
            self.Log('LIQUIDATE AT THRESHOLD REACHED.')