Overall Statistics
Total Trades
20
Average Win
0%
Average Loss
0.00%
Compounding Annual Return
-0.981%
Drawdown
0.000%
Expectancy
-1
Net Profit
-0.013%
Sharpe Ratio
-68.807
Probabilistic Sharpe Ratio
0%
Loss Rate
100%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
-0.005
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
-6.694
Tracking Error
0.14
Treynor Ratio
18.653
Total Fees
$0.00
from Execution.ImmediateExecutionModel import ImmediateExecutionModel
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Data import *
from datetime import timedelta
import pandas as pd
from io import StringIO

 
class main(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020,7,27)  # Set Start Date
        self.SetEndDate(2020,12,31)# Set End Date
        self.SetCash(100000)  # Set Strategy Cash
        
        # If using dropbox remember to add the &dl=1 to trigger a download
        csv = self.Download("https://www.dropbox.com/s/2hlxb85lo7y10i3/test.csv?dl=1")

        # read file (which needs to be a csv) to a pandas DataFrame. include following imports above
    
        self.df = pd.read_csv(StringIO(csv))
        
        self.SetExecution(ImmediateExecutionModel())
        self.AveragePrice = None
        self.security= None
        self.quantity= None
        
        
        for i in range(len(self.df)) :
            self.security=str(self.df.iloc[i,0]).replace(" ", "")
            self.quantity=self.df.iloc[i,1]
            self.AddEquity(self.security,Resolution.Minute).SetDataNormalizationMode(DataNormalizationMode.Raw)
            self.Debug(i)

            # DAY'S START BUY ACTION
            ################################################################################################################################  
            self.Schedule.On(self.DateRules.EveryDay(self.security), self.TimeRules.At(self.df.iloc[i,4], self.df.iloc[i,5]),Action(self.EveryDayAfterMarketOpen))

        
        #DAY'S END LIQUIDATE SELL ACTION
      ##################################################################################################################################   
            self.Schedule.On(self.DateRules.EveryDay(self.security), self.TimeRules.At(self.df.iloc[i,6], self.df.iloc[i,7]),Action(self.SpecificTime))

        
        ############## SLIPPAGE & FEE MODEL####################################################################
            self.Securities[self.security].FeeModel = ConstantFeeModel(0)
            self.Securities[self.security].SlippageModel = ConstantSlippageModel(0)
        
        

    def SpecificTime(self):
        self.Liquidate(self.security)

        
    def EveryDayAfterMarketOpen(self):
        self.MarketOrder(self.security, self.quantity)
        self.AveragePrice = self.Portfolio[self.security].AveragePrice
            
    
        ## CODE TO TRIGGER STOP LOSSES AND TAKE PROFITS    
    def OnData(self, slice):
            if not slice.Bars.ContainsKey(self.security): return
        
            if self.AveragePrice != None :
                    if (slice[self.security].Price > self.AveragePrice * self.df.iloc[0,2]):
                        self.Liquidate(self.security," TAKE PROFIT @ " + str(slice[self.security].Price) +" AverageFillPrice " +str(self.AveragePrice))
                    if (slice[self.security].Price < self.AveragePrice * self.df.iloc[0,3]):
                        self.Liquidate(self.security," STOP LOSS @ " + str(slice[self.security].Price) +" AverageFillPrice " +str(self.AveragePrice))