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
-0.593
Tracking Error
0.227
Treynor Ratio
0
Total Fees
$0.00
class ResistanceMultidimensionalCompensator(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020, 8, 25)  # Set Start Date
        self.SetEndDate(2020, 9, 3)
        
        self.SetCash(100000)  # Set Strategy Cash
        
        
        self.symbol = Symbol.Create("AAPL", SecurityType.Equity, Market.USA)
        
        self.SetAlpha(MyAlpha(self.symbol))
        
        self.SetExecution(ImmediateExecutionModel())

        self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())

        self.SetUniverseSelection(CoarseFundamentalUniverseSelectionModel(self.CoarseSelectionFunction))
        self.UniverseSettings.Resolution = Resolution.Daily

    def CoarseSelectionFunction(self, coarse):
        c = [c for c in coarse if c.Symbol == self.symbol]
        
        self.Plot("Price", "Raw", c[0].Price)
        
        return [self.symbol]
    
class MyAlpha(AlphaModel):
    
    symbol = None
    
    def __init__(self, symbol):
        self.symbol = symbol
    
    def Update(self, algorithm, data):
        
        if self.symbol is None or not data.ContainsKey(self.symbol) or data[self.symbol] is None:
            return []
        
        algorithm.Plot("Price", "Adjusted", data[self.symbol].Close)
        
        return []
        
    def OnSecuritiesChanged(self, algorithm, changes):
        pass