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
0
Tracking Error
0
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
# region imports
from AlgorithmImports import *
# endregion

class FormalAsparagusBadger(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2022, 10, 3)  
        self.SetEndDate(2022, 10, 4) 
        self.SetCash(100000)  # Set Strategy Cash
        self.symbol = self.AddEquity("SPY", Resolution.Minute).Symbol

        self.Schedule.On(self.DateRules.EveryDay(), self.TimeRules.AfterMarketOpen('SPY', 1), self._PrintPrice)

        self.opening_prices = pd.Series()
        self.lookback = 5
        self.day = -1
        #self.SetWarmup(self.lookback, Resolution.Daily)        
    
    def _PrintPrice(self):
        self.Log(str(self.Time) +' '+'print price')
        self.Log(str(self.Time) +' '+'spy open is : '+str(self.Securities['SPY'].Open))

    def OnData(self, data: Slice):
        if self.day != data.Time.day and self.symbol in data.Bars:
            self.day = data.Time.day
            
            # Save opening price
            self.opening_prices.loc[data.Time.date()] = data[self.symbol].Open
            self.opening_prices = self.opening_prices[-self.lookback:]