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
-4.459
Tracking Error
0.636
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
class MuscularGreenAlbatross(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020, 1, 1)  # Set Start Date
        self.SetEndDate(2021, 3, 1) #Set End Date
        self.SetCash(100000)  # Set Strategy Cash
        self.SetBrokerageModel(BrokerageName.Bitfinex, AccountType.Cash) #Broker Modell
        self.Settings.FreePortfolioValuePercentage = 0.05
        self.positionSizeUSD = 5000
        self.btc = self.AddCrypto("BTCUSD", Resolution.Daily).Symbol
        #self.SetBenchmark("BTCUSD")
        
        #NMA Indikator
        length1 = 120
        length2 = 12
        self.SetWarmUp(length1 + length2, Resolution.Daily)
        
        alpha = float(length1 / length2)
        beta = (alpha * float(length1 - 1)) / float(length1 - alpha)
        gamma = float(beta) + 1
        
        #self.Debug(alpha)
        #self.Debug(beta)
        #self.Debug(gamma)
        
        #NMA with SMA
        #self.sma1 = self.SMA(self.btc, length1, Resolution.Daily)
        #self.sma_sma = IndicatorExtensions.Of(SimpleMovingAverage(length2), self.sma1)
        
        #NMA with EMA
        self.ema1 = self.EMA(self.btc, length1)
        self.ema_ema = IndicatorExtensions.Of(SimpleMovingAverage(length2), self.ema1)
        self.nma_a = IndicatorExtensions.Times(self.ema1, float(gamma))
        self.nma_b = IndicatorExtensions.Times(self.ema_ema, float(beta))
        self.nma = IndicatorExtensions.Minus(self.nma_a, self.nma_b)
        self.nma2 = IndicatorExtensions.Minus(IndicatorExtensions.Times(self.ema1, float(gamma)),IndicatorExtensions.Times(self.ema_ema, float(beta)))
        
    def OnData(self, data):
        if self.IsWarmingUp: 
            return
        if not self.ema1.IsReady or not self.ema_ema.IsReady: 
            return
        
        #self.Plot("Benchmark", "SMA1", self.sma1.Current.Value)
        #self.Plot("Benchmark", "SMA2 of SMA1", self.sma_sma.Current.Value)
        
        #self.Plot("Benchmark", "EMA1", self.ema1.Current.Value)
        #self.Plot("Benchmark", "EMA2 of EMA1", self.ema_ema.Current.Value)
        #self.Plot("Benchmark", "NMA", self.nma.Current.Value)       
        self.Plot("Benchmark", "NMA_A", self.nma_a.Current.Value)    
        self.Plot("Benchmark", "NMA_B", self.nma_b.Current.Value)    
        self.Plot("Benchmark", "NMA_2", self.nma2.Current.Value)