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
1.824
Tracking Error
0.161
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
class FocusedGreenDonkey(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020, 1, 1)
        self.SetEndDate(2020, 2, 28)
        self.SetCash(100000) 
        
        self.AddUniverse(self.MyCoarseFilterFunction)
        self.symbolDataBySymbol = {}
        
    def MyCoarseFilterFunction(self,coarse):
        StocksUnder10 = [c.Symbol for c in coarse if c.Price < 10]
        
        return StocksUnder10
    
    def OnSecuritiesChanged(self, changes):
        
        for security in changes.AddedSecurities:
            symbol = security.Symbol
            if symbol not in self.symbolDataBySymbol:
                self.symbolDataBySymbol[symbol] = SymbolData(self, symbol)
                
            if self.symbolDataBySymbol[symbol].HasNewMax:
                self.MarketOrder(symbol, 100)
            
        for security in changes.RemovedSecurities:
            symbol = security.Symbol
            self.Liquidate(symbol)
            self.symbolDataBySymbol.pop(symbol)
            
            
class SymbolData:
    def __init__(self, algorithm, symbol):
        self.symbol = symbol
        
        self.max = algorithm.MAX(symbol, 252, Resolution.Daily, Field.High)
        self.maxWindow = RollingWindow[IndicatorDataPoint](2)
        
        # Warm up
        history = algorithm.History(symbol, 253, Resolution.Daily)
        for bar in history.itertuples():
            self.max.Update(bar.Index[1], bar.high)
        
        self.max.Updated += lambda sender, bar: self.maxWindow.Add(bar)
        
    @property
    def HasNewMax(self):
        if self.maxWindow.IsReady:
            return self.maxWindow[0] > self.maxWindow[1]
        else:
            return False