I am trying to adapt the EmaCrossAlphaModel to a large universe of futures, using the Algorithm Framework.

the algorithm is initialized by 

class MovingAverageCrossTrendFollowing(QCAlgorithm):

def Initialize(self):
self.SetStartDate(2019, 1, 1) # Set Start Date
self.SetStartDate(2019, 3,30) # Set End Date
self.SetCash(100000) # Set Strategy Cash
self.UniverseSettings.Resolution = Resolution.Daily
self.AddAlpha(MovingAverageCrossAlphaModel(50, 200, Resolution.Minute))




def SelectFuturesSymbols(self, utcTime):
tickers = [Futures.Indices.SP500EMini,
#Many more futures
return [ Symbol.Create(ticker, SecurityType.Future, Market.USA) for ticker in tickers]



just filters the futures by expiration date:

class FuturesUniverseSelectionModel(FutureUniverseSelectionModel):

def __init__(self, select_future_chain_symbols):
super().__init__(timedelta(1), select_future_chain_symbols)

def Filter(self, filter):
return (filter.Expiration(timedelta(0), timedelta(90))

The Update method in MovingAverageCrossAlphaMode starts with a selection of the contract with the highest open interest per chain:

def Update(self, algorithm, data):
for chain in data.FutureChains:

#1. Filter to choose popular contracts with OpenInterest > 1000
popularContracts = [contract for contract in chain.Value if contract.OpenInterest>1000]

#2. If the length of contracts in this chain is zero, continue to the next chain
if len(popularContracts) is 0:

#3. Sort our contracts by open interest in descending order and save to sortedByOIContracts
sortedByOIContracts = sorted(popularContracts, key=lambda k : k.OpenInterest, reverse=True)

#4. Save the contract with the highest open interest to self.liquidContract
liquidContract = sortedByOIContracts[0]

#5. Generate insights based on EMA crossings

return insights

As the attached backtest shows, however, the Update method is never called, despite the initialization

self.UniverseSettings.Resolution = Resolution.Daily

What is the problem, here?