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
Probabilistic 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
2.008
Tracking Error
0.168
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
# region imports
from AlgorithmImports import *
import pandas as pd
import numpy as np
from datetime import time, datetime, timedelta
# endregion

class CombinedAlgorithm(QCAlgorithm):
	
    def Initialize(self):

        # INITIALIZE
        self.SetStartDate(2022, 1, 1)  # Set Start Date
        self.SetEndDate(2022, 3, 1)
        self.SetCash(10000)  # Set Strategy Cash
        self.spy = self.AddEquity('SPY', Resolution.Minute)
        self.spy.SetDataNormalizationMode(DataNormalizationMode.Raw)

        self.trigger_week_high = 0
        self.trigger_week_low = 0



        weeklyConsolidator = TradeBarConsolidator(Calendar.Weekly)
        weeklyConsolidator.DataConsolidated += self.OnTwoWeekBar
        self.SubscriptionManager.AddConsolidator("SPY", weeklyConsolidator)
        
        self.weekBarWindow = RollingWindow[TradeBar](1) # 2

    
      



    def OnData(self, data):
        # VARIABLES
        pass
            #self.Log(f'{self.trigger_week_high} previous weeks high ORDER')

    def OnTwoWeekBar(self, sender, bar):
        self.Log("OnDataConsolidated called on " + str(self.Time))
        self.Log(str(bar.High))
        self.weekBarWindow.Add(bar)

        if not self.weekBarWindow.IsReady:
            return         
        
        trigger_week = self.weekBarWindow[0]
        
       
        self.trigger_week_high = trigger_week.High
        self.trigger_week_low = trigger_week.Low
        #self.Log(f'{self.trigger_week_high} previous weeks high')