Hi,

I am trying to backtest this strategy,m but I get several errors. Why?

Runtime Error: ArgumentNullException : Value cannot be null.
Parameter name: key
at System.Collections.Concurrent.ConcurrentDictionary`2[TKey,TValue].ThrowKeyNullException () [0x00000] in <b0e1ad7573a24fd5a9f2af9595e677e7>:0
at System.Collections.Concurrent.ConcurrentDictionary`2[TKey,TValue].ContainsKey (TKey key) [0x00008] in <b0e1ad7573a24fd5a9f2af9595e677e7>:0
at QuantConnect.Securities.UniverseManager.get_Item (QuantConnect.Symbol symbol) [0x00000] in <e2116c6c2b30479ab313dc7ef47ce6f3>:0
at (wrapper managed-to-native) System.Reflection.MonoMethod.InternalInvoke(System.Reflection.MonoMethod,object,object[],System.Exception&)
at System.Reflection.MonoMethod.Invoke (System.Object obj, System.Reflection.BindingFlags invokeAttr, System.Reflection.Binder binder, System.Object[] parameters, System.Globalization.CultureInfo culture) [0x00032] in <b0e1ad7573a24fd5a9f2af9595e677e7>:0
at OnData in main.py:line 44
:: for i in self.UniverseManager[self.uni_symbol].Members:
ArgumentNullException : Value cannot be null.
Parameter name: key
at System.Collections.Concurrent.ConcurrentDictionary`2[TKey,TValue].ThrowKeyNullException () [0x00000] in <b0e1ad7573a24fd5a9f2af9595e677e7>:0
at System.Collections.Concurrent.ConcurrentDictionary`2[TKey,TValue].ContainsKey (TKey key) [0x00008] in <b0e1ad7573a24fd5a9f2af9595e677e7>:0
at QuantConnect.Securities.UniverseManager.get_Item (QuantConnect.Symbol symbol) [0x00000] in <e2116c6c2b30479ab313dc7ef47ce6f3>:0
at (wrapper managed-to-native) System.Reflection.MonoMethod.InternalInvoke(System.Reflection.MonoMethod,object,object[],System.Exception&)
at System.Reflection.MonoMethod.Invoke (System.Object obj, System.Reflection.BindingFlags invokeAttr, System.Reflection.Binder binder, System.Object[] parameters, System.Globalization.CultureInfo culture) [0x00032] in <b0e1ad7573a24fd5a9f2af9595e677e7>:0 (Open Stacktrace)11 | 10:38:59: Algorithm Id:(a29db63a8d6f8aaca4c44cd521845a2a) completed in 15.46 seconds at 0k data points per second. Processing total of 6,864 data points.

from clr import AddReference
AddReference("System.Core")
AddReference("System.Collections")
AddReference("QuantConnect.Common")
AddReference("QuantConnect.Algorithm")
import statistics
from datetime import datetime
from System.Collections.Generic import List

class ShortTimeReversal(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2005, 1, 1)
        self.SetEndDate(2017, 5, 10)
        self.SetCash(1000000)
        
        self.UniverseSettings.Resolution = Resolution.Daily
        self.AddUniverse(self.CoarseSelectionFunction)
        self._numberOfSymbols = 100
        self._numberOfTradings = int(0.1 * self._numberOfSymbols)
        
        self._numOfWeeks = 0
        self._LastDay = -1
        self._ifWarmUp = False
        
        self._stocks = []
        self._values = {}

    def CoarseSelectionFunction(self, coarse):
        sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True)
        top100 = sortedByDollarVolume[:self._numberOfSymbols]
        return [i.Symbol for i in top100]

    def OnData(self, data):
        
        if not self._ifWarmUp:
            if self._LastDay == -1:
                self._LastDay = self.Time.date()
                self._stocks = []
                self.uni_symbol = None
                symbols = self.UniverseManager.Keys
                for i in symbols:
                    if str(i.Value) == "QC-UNIVERSE-COARSE-USA":
                        self.uni_symbol = i
                for i in self.UniverseManager[self.uni_symbol].Members:
                    self._stocks.append(i.Value.Symbol)
                    self._values[i.Value.Symbol] = [self.Securities[i.Value.Symbol].Price]
            else:
                delta = self.Time.date() - self._LastDay
                if delta.days >= 7:
                    self._LastDay = self.Time.date()
                    for stock in self._stocks:
                        self._values[stock].append(self.Securities[stock].Price)
            self._numOfWeeks += 1
            if self._numOfWeeks == 3:
                self._ifWarmUp = True
        else:
            delta = self.Time.date() - self._LastDay
            if delta.days >= 7:
                self._LastDay = self.Time.date()
                
                returns = {}
                for stock in self._stocks:
                    newPrice = self.Securities[stock].Price
                    oldPrice = self._values[stock].pop(0)
                    self._values[stock].append(newPrice)
                    try:
                        returns[stock] = newPrice/oldPrice
                    except:
                        returns[stock] = 0

                newArr = [(v,k) for k,v in returns.items()]
                newArr.sort()
                for ret, stock in newArr[self._numberOfTradings:-self._numberOfTradings]:
                    if self.Portfolio[stock].Invested:
                        self.Liquidate(stock)
                for ret, stock in newArr[0:self._numberOfTradings]:
                    self.SetHoldings(stock, 0.5/self._numberOfTradings)
                for ret, stock in newArr[-self._numberOfTradings:]:
                    self.SetHoldings(stock, -0.5/self._numberOfTradings)
                self._LastDay = self.Time.date()