Overall Statistics
Total Trades
1
Average Win
0%
Average Loss
0%
Compounding Annual Return
-98.323%
Drawdown
100.000%
Expectancy
0
Net Profit
-5.093%
Sharpe Ratio
-18.845
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
-1.754
Beta
-2.541
Annual Standard Deviation
0.052
Annual Variance
0.003
Information Ratio
-9.285
Tracking Error
0.072
Treynor Ratio
0.384
Total Fees
$33.97
class FormalYellowGreenDogfish(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2007, 4, 20)  # Set Start Date
        self.SetEndDate(2007, 4, 24)
        self.SetCash(100000)  # Set Strategy Cash

        symbols = [Symbol.Create(ticker, SecurityType.Equity, Market.USA) for ticker in ["EWA", "EPP"]]
        self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
        
        self.AddAlpha(MyAlpha())
        self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel(lambda x: None))
        self.SetExecution(ImmediateExecutionModel())


class MyAlpha(AlphaModel):
    symbols = []
    called = False
    
    def Update(self, algorithm, data):
        
        algorithm.Plot("Equity", "Value", algorithm.Portfolio.TotalPortfolioValue)
        for symbol in self.symbols:
            if data.ContainsKey(symbol) and data[symbol] is not None:
                algorithm.Plot("Price", symbol, data[symbol].Price)
        
        if not self.called:
            self.called = True
            insights = []
            for symbol in self.symbols:
                if symbol.Value == 'EWA':
                    algorithm.Debug(f"Up for {symbol}")
                    insights.append(Insight.Price(symbol, timedelta(days=30), InsightDirection.Up))
            return insights
        return []
    
    def OnSecuritiesChanged(self, algorithm, changes):
        for security in changes.AddedSecurities:
            self.symbols.append(security.Symbol)