Share New Research 
Hello !
Does someone knows why this algorithm is stuck and can help to fix it.
Thank you
from datetime import timedelta, datetime
from Selection.FundamentalUniverseSelectionModel import FundamentalUniverseSelectionModel
from QuantConnect.Data.UniverseSelection import *
class HorizontalQuantumCompensator(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2019, 8, 10) # Set Start Date
self.SetCash(100000)
self.AddUniverseSelection
self.UniverseSettings.Resolution = Resolution.Daily
self.UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw
self.SetAlpha(MOMAlphaModel())
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
self.SetExecution(ImmediateExecutionModel())
self.AddUniverseSelection(LiquidValueUniverseSelectionModel())
class LiquidValueUniverseSelectionModel(FundamentalUniverseSelectionModel):
def __init__(self):
super().__init__(True, None, None)
def SelectCoarse(self, algorithm, coarse):
sortedByDollarVolume = sorted([x for x in coarse if x.HasFundamentalData],key=lambda x: x.DollarVolume, reverse=True)
return [x.Symbol for x in sortedByDollarVolume[:200]]
class MOMAlphaModel(AlphaModel):
def __init__(self):
self.SMAS = []
self.SMAL = []
self.RSI = []
def OnSecuritiesChanged(self, algorithm, changes):
for security in changes.AddedSecurities:
symbol = security.Symbol
self.SMAS.append({"symbol":symbol, "indicator":algorithm.SMA(symbol, 20, Resolution.Daily)})
self.SMAL.append({"symbol":symbol, "indicator":algorithm.SMA(symbol, 50, Resolution.Daily)})
self.RSI.append({"symbol":symbol, "indicator":algorithm.RSI(symbol, 14, Resolution.Daily)})
def Update(self, algorithm, data):
for s in symbol:
SMA20 = self.SMAS.Current.Value
SMA50 = self.SMAS.Current.Value
RSI = self.RSI.Current.Value
if SMA20>SMA50 and RSI < 30 :
return Insight.Group(
[Insights.Price(self.SMA20.Symbol,timedelta(1),InsightDirection.Up)])
if SMA20<SMA50 and RSI > 70 :
return Insight.Group(
[Insights.Price(self.SMA20.Symbol,timedelta(1),InsightDirection.Down)])
Rahul Chowdhury
Hi Wawes,
You can create a SymbolData class to hold all the indicators for each symbol. Then you can create a dictionary keyed by symbol which holds our SymbolData objects. Organizing our indicators this way makes our code simpler.
In the Update method, cycle through the symbols in the dictionary and create insights for the symbols which meet the entry signals. Append those insights to our list of insights and finally return that list at the end of Update.
Wawes23
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