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
-33.971
Tracking Error
0.399
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
from System import *
from QuantConnect import *
from QuantConnect.Indicators import *
from QuantConnect.Data import *
from QuantConnect.Data.Market import *
from QuantConnect.Data.Custom import *
from QuantConnect.Algorithm import *
from QuantConnect.Python import *
from QuantConnect import Market
import pandas as pd
import numpy as np
import talib
from collections import deque

class EMACrossover(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2020, 4, 1)  # Set Start Date
        self.SetEndDate(2020, 4, 20)
        self.SetCash(10000)  # Set Strategy Cash
        self.SetWarmUp(150)
        self.AddEquity("AMD", Resolution.Minute, Market.USA, True, 1, False)
        self.sym ="AMD"
        self.consolidatedwindow = RollingWindow[TradeBar](10)
        
        self.consolidator = TradeBarConsolidator(timedelta(1))
        self.consolidator.DataConsolidated += self.consolidation_handler
        self.SubscriptionManager.AddConsolidator("AMD", self.consolidator)
        
    def consolidation_handler(self, sender, bar):
        self.consolidatedwindow.Add(bar)
        
    def OnData(self, data):
        if not all([data.Bars.ContainsKey("AMD")]):
            return
        if not (self.consolidatedwindow.IsReady):
            return
        
        yesterday_close = self.consolidatedwindow[0].Close
        today_open = self.consolidator.WorkingBar.Open
        
        self.Debug(f"at {data.Time}, yest close: {yesterday_close}; today open: {today_open}")