Hi everyone, 

I am aiming for a 60/30/10 portfolio allocation to momentum stocks, bond etfs, and market neutral etf respectively with annual rebalancement (using rebalancement flags for triggers). I also conduct universe selection monthly and update my momentum stocks on a monthly basis. 

When i first run my algo, i expect to be holding 60/30/10 60/30/10 portfolio allocation to momentum stocks, bond etfs (IEI, TLT) and market neutral ETF (BTAL). However, when i look through the orders for the backtest, my algo did not execute long positions in the bond etfs nor the market neutral etf at the start but it did execute the positions in the momentum stocks. 

Can someone please help me out on this issue? Much appreciated!!

import pandas as pd import numpy as np from datetime import datetime, timedelta from QuantConnect.Data.UniverseSelection import * from scipy.stats import linregress class Momentum(QCAlgorithm): def __init__(self): self.reb1 = 1 # set the flag for rebalance self.reb2 = 12 # set the flag for rebalance self.num_coarse = 500 # Number of stocks to pass CoarseSelection process self.num_fine = 20 # Number of stocks to long self.symbols = None def Initialize(self): self.SetStartDate(2012, 1, 1) # Set Start Date self.SetEndDate(2013,6, 1) # Set End Date self.SetCash(150000) # Set Strategy Cash self.btal = self.AddEquity("BTAL", Resolution.Minute).Symbol # BTAL hedge self.iei = self.AddEquity("IEI", Resolution.Minute).Symbol # bond hedge self.tlt = self.AddEquity("TLT", Resolution.Minute).Symbol # bond hedge self.list = [self.btal, self.iei, self.tlt] self.reb1 = 1 # set the flag for momentum stock rebalancement self.reb2 = 1 # set the flag for rebalance self.AddUniverse(self.CoarseSelectionFunction,self.FineSelectionFunction) self.spy = self.AddEquity("SPY", Resolution.Daily).Symbol self.Schedule.On(self.DateRules.MonthStart(self.spy), self.TimeRules.AfterMarketOpen(self.spy,5), Action(self.rebalance)) self.SetSecurityInitializer(self.CustomSecurityInitializer) self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Cash) def CustomSecurityInitializer(self, security): security.SetDataNormalizationMode(DataNormalizationMode.SplitAdjusted) def CoarseSelectionFunction(self, coarse): # if the rebalance flag is not 1, return null list to save time. if self.reb1 != 1: return self.long # make universe selection once a month sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True) filtered = [x.Symbol for x in sortedByDollarVolume if x.HasFundamentalData] # filtered down to the 500 most liquid stocks return filtered[:self.num_coarse] def FineSelectionFunction(self, fine): # return null list if it's not time to rebalance if self.reb1 != 1: return self.long # drop counter (will update back to 1 after rebalancement has occurred) self.reb1 = 0 #will not include this portion of code - essentially filters for top momentum stocks self.long = sorted_symbolLong[:self.num_fine] return self.long def OnData(self, data): pass def rebalance(self): long_list = self.long # to update the momentum stocks only monthly for i in self.Portfolio.Values: if i.Invested and i.Symbol not in long_list and i.Symbol not in self.list: self.Liquidate(i.Symbol) # annual portfolio rebalancement if self.reb2 % 12 == 0: self.SetHoldings(self.iei, 0.15) self.SetHoldings(self.tlt, 0.15) self.SetHoldings(self.btal, 0.10) for i in long_list: self.SetHoldings(i, 0.6/self.num_fine) else: # monthly rebalancement of momentum stocks only, leaving bonds and market neutral etfs untouched for i in long_list: if not self.Securities[i].Invested: self.SetHoldings(i, 0.6/self.num_fine) self.reb1 = 1 self.reb2 += 1