HI all ,

I have applied a sector weighted portfolio as was provided within the tutorials help , but expanded the backtest duration to 4 years from 2017 to 2021 then , add more sectors while number of chosen sectors have been extended to include the top 50 dollar volume wise in each sector , yet when I clicked the backtest button , it started well then stopped at 2017 and did not continue without providing any error message of what so ever , so I wonder if some body can help on this and feed me back here 

from datetime import timedelta from QuantConnect.Data.UniverseSelection import * from Selection.FundamentalUniverseSelectionModel import FundamentalUniverseSelectionModel class SectorBalancedPortfolioConstruction(QCAlgorithm): def Initialize(self): self.SetStartDate(2017, 3, 28) self.SetEndDate(2021, 3, 1) self.SetCash(10000000) self.UniverseSettings.Resolution = Resolution.Hour self.SetUniverseSelection(MyUniverseSelectionModel()) self.SetAlpha(ConstantAlphaModel(InsightType.Price, InsightDirection.Up, timedelta(1), 0.025, None)) self.SetPortfolioConstruction(MySectorWeightingPortfolioConstructionModel()) self.SetExecution(ImmediateExecutionModel()) class MyUniverseSelectionModel(FundamentalUniverseSelectionModel): def __init__(self): super().__init__(True, None, None) def SelectCoarse(self, algorithm, coarse): filtered = [x for x in coarse if x.HasFundamentalData and x.Price > 10] sortedByDollarVolume = sorted(filtered, key=lambda x: x.DollarVolume, reverse=True) return [x.Symbol for x in sortedByDollarVolume][:1000] def SelectFine(self, algorithm, fine): filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Technology] self.technology = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.FinancialServices] self.financialServices = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.ConsumerDefensive] self.consumerDefensive = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] return [x.Symbol for x in self.technology + self.financialServices + self.consumerDefensive] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Industrials] self.industrial = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Energy] self.energy = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.BasicMaterials] self.basicmaterial = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.CommunicationServices] self.communication = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Utilities] self.utility = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Healthcare] self.health = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.ConsumerCyclical] self.consumerCyclical = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.RealEstate] self.realestate = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:50] class MySectorWeightingPortfolioConstructionModel(EqualWeightingPortfolioConstructionModel): def __init__(self, rebalance = Resolution.Daily): super().__init__() self.symbolBySectorCode = dict() self.result = dict() def DetermineTargetPercent(self, activeInsights): #1. Set the self.sectorBuyingPower before by dividing one by the length of self.symbolBySectorCode self.sectorBuyingPower = 1/len(self.symbolBySectorCode) for sector, symbols in self.symbolBySectorCode.items(): #2. Search for the active insights in this sector. Save the variable self.insightsInSector self.insightsInSector = [insight for insight in activeInsights if insight.Symbol in symbols] #3. Divide the self.sectorBuyingPower by the length of self.insightsInSector to calculate the variable percent # The percent is the weight we'll assign the direction of the insight self.percent = self.sectorBuyingPower / len(self.insightsInSector) #4. For each insight in self.insightsInSector, assign each insight an allocation. # The allocation is calculated by multiplying the insight direction by the self.percent for insight in self.insightsInSector: self.result[insight] = insight.Direction * self.percent return self.result def OnSecuritiesChanged(self, algorithm, changes): for security in changes.AddedSecurities: sectorCode = security.Fundamentals.AssetClassification.MorningstarSectorCode if sectorCode not in self.symbolBySectorCode: self.symbolBySectorCode[sectorCode] = list() self.symbolBySectorCode[sectorCode].append(security.Symbol) for security in changes.RemovedSecurities: sectorCode = security.Fundamentals.AssetClassification.MorningstarSectorCode if sectorCode in self.symbolBySectorCode: symbol = security.Symbol if symbol in self.symbolBySectorCode[sectorCode]: self.symbolBySectorCode[sectorCode].remove(symbol) super().OnSecuritiesChanged(algorithm, changes)

bets regards