import numpy as np
import pandas as pd
from datetime import datetime, timedelta
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Data.Market import TradeBar

class BasicTemplateAlgorithm(QCAlgorithm):
    '''High beta strategy'''

    def Initialize(self):
  
        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialize.'''
        
        #Initial investment and backtest period
        self.SetStartDate(2019,2,25)    #Set Start Date
        self.SetEndDate(2019,2,27)       #Set End Date
        self.SetCash(10000)          #Set Strategy Cash
        
        #Capture initial investment for risk off purposes
        self.ClosingPortValue = self.Portfolio.TotalPortfolioValue
        self.CurrentPortValue = self.Portfolio.TotalPortfolioValue
        self.CurrentHoldValue = self.Portfolio.TotalHoldingsValue
        
        #Universe
        self.AddEquity("SPY",  Resolution.Daily)
        
        '''Schedule Function Here'''        
        self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.Every(TimeSpan.FromMinutes(6)), self.UpdatePortValues)        
        self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.Every(TimeSpan.FromMinutes(7)), self.CheckDailyLosses)        
        
        '''Set Warmup Here'''
        
        self.SetWarmup(TimeSpan.FromDays(30))

#OnData        
    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'''
        
        #Verify all indicators have warmed up before anything happens   
        if self.IsWarmingUp: return
    
        self.SetHoldings("SPY", 0.10)    
    
#Update Portfolio Values    
    def UpdatePortValues(self):
        
        self.marginRemaining = self.Portfolio.MarginRemaining
        self.CurrentPortValue = self.Portfolio.TotalPortfolioValue
        self.CurrentHoldValue = self.Portfolio.TotalHoldingsValue

        self.Log("Portfolio Values Have Been Updated")            
            
#CheckLosses            
    #Check intraday losses and run defensive function if a 5.6% drop is recognized        
    def CheckDailyLosses(self):
        
        
        self.CurrentPerformance = round( ((float(self.CurrentPortValue)/float(self.ClosingPortValue))-1)*100,2)
        
        if (self.CurrentPortValue <= self.ClosingPortValue*0.944):
            if(self.IsMarketOpen("SPY")):
                self.HighLosses()
            
        else: self.Log("Current Performance: {0}%".format(self.CurrentPerformance))
        
        return