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
-3.428
Tracking Error
0.655
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
# NMA indicator
  
# --------------------------------------------------------------------------------
MA_1 = 120; MA_2 = 12; ALPFA = float(MA_1/ MA_2); 
BETA = (ALPFA * float(MA_1 - 1)) / float(MA_1 - ALPFA); GAMMA = float(BETA) + 1.0; 
# -------------------------------------------------------------------------------- 

class MuscularGreenAlbatross(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020, 9, 1) 
        self.SetEndDate(2021, 10, 7) 
        self.SetBrokerageModel(BrokerageName.Bitfinex, AccountType.Cash) 
        self.btc = self.AddCrypto("BTCUSD", Resolution.Daily).Symbol
        self.SetBenchmark("BTCUSD")
        self.SetWarmUp((MA_1 + MA_2), Resolution.Daily)
        self.ma1 = self.SMA(self.btc, MA_1, Resolution.Daily)
        self.ma2_ma1 = IndicatorExtensions.Of(SimpleMovingAverage(MA_2), self.ma1)

        
    def OnData(self, data):
        if self.IsWarmingUp: return
        if not self.ma1.IsReady or not self.ma2_ma1.IsReady: return
    
        ma1 = self.ma1.Current.Value
        ma2_ma1 = self.ma2_ma1.Current.Value
        
        nma = ma1 * GAMMA - ma2_ma1 * BETA

        self.Plot("Benchmark", "nma", nma)
        
        self.Plot("Calc", "step 1", ma1 * GAMMA )
        self.Plot("Calc", "step 2", ma2_ma1 * BETA)
        self.Plot("Calc", "step 3", nma)