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
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
 
class AdjustmentTest(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2012, 1, 1)
        self.SetEndDate(2012, 1, 8)
        self.SetCash(15000)

        # Constant definitions
        self.ASSET_UNDERLYING = 'SPY'
        self.ASSET_TRADE_LONG = 'AAPL'

        # Initialization process
        self._asset_underlying = self.AddEquity(self.ASSET_UNDERLYING, Resolution.Minute)
        # self._asset_trade_long = self.AddEquity(self.ASSET_TRADE_LONG, Resolution.Minute)
        
        self._asset_underlying.SetDataNormalizationMode(DataNormalizationMode.Raw)
        # self._asset_trade_long.SetDataNormalizationMode(DataNormalizationMode.Raw)
        
        self.Schedule.On(
            self.DateRules.EveryDay(self.ASSET_UNDERLYING),
            self.TimeRules.BeforeMarketClose(self.ASSET_UNDERLYING, 1),
            Action(self._print)
        )
        
        stockPlot = Chart('Price Plot')
        stockPlot.AddSeries(Series(self.ASSET_UNDERLYING, SeriesType.Line, 0))
        # stockPlot.AddSeries(Series(self.ASSET_TRADE_LONG, SeriesType.Line, 0))
        self.AddChart(stockPlot)

    def _print(self):
        # Get all historic quotes
        underlying_price = float(self.Securities[self.ASSET_UNDERLYING].Close)
        # long_price = float(self.Securities[self.ASSET_TRADE_LONG].Close)
        
        self.Plot('Price Plot', self.ASSET_UNDERLYING, underlying_price)
        # self.Plot('Price Plot', self.ASSET_TRADE_LONG, long_price)