Indicators

class LiquidUniverseSelection(QCAlgorithm):
    
    filteredByPrice = None
    changes = None
    def __init__(self):
        self.mom = []
      
    
    def Initialize(self):
        self.SetStartDate(2018, 1, 2)  
        self.SetEndDate(2019, 1, 9) 
        self.SetCash(100000)  
        self.AddUniverse(self.CoarseSelectionFilter)
        self.SetAlpha(MOMAlphaModel())
        
    def CoarseSelectionFilter(self, coarse):
        EquityCountCoarseSelectionFilter = 0
        self.Debug(f"EquityStartCountCoarseSelectionFilter = {EquityCountCoarseSelectionFilter}")
        for cf in coarse:
            symbol = cf.Symbol
            EquityCountCoarseSelectionFilter = EquityCountCoarseSelectionFilter + 1
        self.Debug(f"EquityEndCountCoarseSelectionFilter = {EquityCountCoarseSelectionFilter}")
        
       
        
        #1. Sort descending by daily dollar volume
        self.sortedByDollarVolume = sorted(coarse, key=lambda c: c.DollarVolume, reverse=True)
        
        #2. Select only Symbols with a price of more than $10 per share
        self.symbols_by_price = [c.Symbol for c in self.sortedByDollarVolume]# if c.Price > 10]
        
        #3. Return the 8 most liquid Symbols from the filteredByPrice list
        self.Top100 = self.symbols_by_price[:100]
        
        
        self.Debug(f"NumberOfEquitiesInTop100 = {len(self.Top100)}")
        self.Debug(f"TopOneInTop100 = {self.Top100[0]}")
        self.Debug(f"TopOneInTop100 = {self.Top100[0]}")
        self.Debug(f"BottemOneInTop100 = {self.Top100[-1]}")
        #self.Debug(f"OnUpdate({self.Time}:: ","ordered (sorted_mom=)",ordered)
        return self.Top100
    

    
class MOMAlphaModel(AlphaModel): 
    def __init__(self):
        self.mom = {}
        #self.DailyMovingAverage
    def OnSecuritiesChanged(self, algorithm, changes):
        
        # 1. Initialize a 14-day momentum indicator for each symbol
        
        
        for security in changes.AddedSecurities:
            symbol = security.Symbol
            algorithm.Debug(f"added security={symbol} ")
            x=algorithm.MOM(symbol, 2, Resolution.Daily)
            algorithm.Debug(f"indicator={x}")
            symbol_string = "{}".format(symbol)
            algorithm.Debug(f"added security={symbol}")
            #algorithm.Debug(f"dictionary={self.mom}")
        pass

Hi Andre,

The algorithm above logs 0 for the indicator values because the indicators are never warmed up.

In addition, when we have a dynamic universe of securities, we should use the full indicator name (Momentum) instead of the short-cut method (algorithm.MOM). Refer to this related thread for an example.

Best,
Derek Melchin

Hi Derek,

Thank you . I managed to warm up the indicator with a history call. 

You leave me with a cliffhanger though, as the link to the related thread leads to an error 404...

Thanks again for your time :)

Regards,

Andre