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
Sortino 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
-0.538
Tracking Error
0.147
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
Portfolio Turnover
0%
 
# region imports
from AlgorithmImports import *
import matplotlib as plt
from collections import deque
# endregion

class MuscularFluorescentOrangeGoat(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2021, 1, 1)
        self.SetCash(100000)
        self.ticker = self.AddEquity("SPY", Resolution.Daily)
        
        self.window = 10
        self.prices = deque(maxlen=self.window)
        self.dates = deque(maxlen=self.window)

        self.stockPlot = Chart('Stock Plot')
        self.stockPlot.AddSeries(Series('Price', SeriesType.Line))
        self.stockPlot.AddSeries(Series('High', SeriesType.Scatter))
        self.stockPlot.AddSeries(Series('Low', SeriesType.Scatter))
        self.AddChart(self.stockPlot)

    def OnData(self, data: Slice):
        self.Plot('Stock Plot', 'Price', data[self.ticker.Symbol].Close)
        self.prices.appendleft(data[self.ticker.Symbol].Close)
        self.dates.appendleft(data.Time)

        if len(self.prices) == self.window:
            lag_high = max(self.prices)
            self.Plot('Stock Plot', 'High', lag_high)
            
            lag_low = min(self.prices)
            self.Plot('Stock Plot', 'Low', lag_low)
            
            self.prices = deque(maxlen=self.window)