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
-2.906
Tracking Error
0.55
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
class SquareFluorescentPinkRat(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2021, 7, 1) #Startdatum
        self.SetEndDate(2021, 8, 1) #Enddatum
        self.SetCash(10000) #PortfolioBalance
        self.SetBrokerageModel(BrokerageName.Bitfinex, AccountType.Cash) #Broker Modell
        
        # Manual Universe Selection Model
        self.UniverseSettings.Resolution = Resolution.Daily
        symbols = ["LTCUSD", "ETHUSD", "BTCUSD", "XRPUSD"]
        self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
        
    def OnData(self, data):
        pass
        
    def CoarseSelectionFunction(self, coarse):    

        for cf in coarse:
            if cf.Symbol.SecurityType == SecurityType.Crypto:
                #self.Debug(type(cf))
                #self.Debug(type(cf.Symbol))
                self.Debug(cf.Symbol.SecurityType)
                self.Debug("SecurityType.Crypto={}".format(SecurityType.Crypto))
                self.stateData[cf.Symbol] = SelectionData(cf.Symbol, 200)
        pass
        

    def FineSelectionFunction(self, fine):
        pass
    
class SelectionData():
    def __init__(self):
        self.macd = MovingAverageConvergenceDivergence(12, 26, 9)
    
    def is_ready(self):
        return self.macd.IsReady
    
    #4. Use the "indicator.Update" method to update the time and price of both indicators
    def update(self, time, price):
        self.macd.Update(time, price)