import numpy as np
import pandas as pd
from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Data import *
from datetime import timedelta
from System.Collections.Generic import List
from QuantConnect.Data.UniverseSelection import *
class QualityMomentumModel(QCAlgorithm):
def __init__(self):
# Set target number of securities to hold
self.TARGET_SECURITIES = 5
#trend following filter
self.TF_LOOKBACK = 200
self.TF_CURRENT_LOOKBACK = 20
self.TF_up = 0
#determining momentum
self.MOMENTUM_LOOKBACK_DAYS = 126 #how many days to lookback
self.MOMENTUM_SKIP_DAYS = 10 #how many days to skip
overall_lookback = (self.MOMENTUM_LOOKBACK_DAYS + self.MOMENTUM_SKIP_DAYS)
def Initialize(self):
self.SetStartDate(2010, 1, 1) # Set Start Date
self.SetEndDate(2012, 1, 1)
self.SetCash(1000) # Set Strategy Cash
self.spy = self.AddEquity("SPY", Resolution.Minute) #add SPY to use for trends
self.UniverseSettings.Resolution = Resolution.Minute #update the universe every minute
#adding a universe of stocks
#schedule function for selecting stocks and weights
self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.AfterMarketOpen("SPY", 30), Action(self.select_stocks_set_weights))
self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose("SPY", 30), Action(self.select_stocks_set_weights))
#schedule function for making trades
self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.AfterMarketOpen("SPY", 30), Action(self.trade))
self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose("SPY", 30), Action(self.trade))
#50 Day moving average of SPY
self.spy_ma_fast = self.SMA("SPY", 50)
#200 Day moving average of SPY
self.spy_ma_slow = self.SMA("SPY", 200)
self.trend_up = self.spy_ma_fast >= self.spy_ma_slow
if self.spy_ma_fast >= self.spy_ma_slow:
self.TF_up = 1
self.UniverseSettings.Resolution = Resolution.Daily
self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)
def CoarseSelectionFunction(self, coarse):
'''Drop securities which have no fundamental data or have too low prices.
Select those with highest by dollar volume'''
selected = [x for x in coarse if (x.HasFundamentalData)
and (float(x.Price) > 20)]
filtered = sorted(selected, key=lambda x: x.DollarVolume, reverse=True)
return [x.Symbol for x in filtered[:2000]]
def FineSelectionFunction(self, fine):
if self.TF_up == 1:
filtered_fine = [x for x in fine if x.ValuationRatios.FCFYield
and x.ValuationRatios.CashReturn
and x.OperationRatios.ROIC
and x.OperationRatios.LongTermDebtEquityRatio.NineMonths]
value = [x for x in filtered_fine if x.ValuationRatios.CashReturn
and x.ValuationRatios.FCFYield]
quality = [x for x in value if x.OperationRatios.ROIC
and x.OperationRatios.LongTermDebtEquityRatio]
self.returns_overall = sorted(quality,
key = lambda f: f.OperationRatios.RevenueGrowth.overall_lookback)
self.returns_recent = sorted(quality,
key = lambda f: f.OperationRatios.RevenueGrowth.MOMENTUM_SKIP_DAYS)
self.momentum = sorted(quality,
key = lambda f: self.returns_overall -
self.returns_recent)
self.top_quality = sorted(quality,
key = lambda f: f.OperationRatios.ROE.OneMonth)
TQ2 = [x[0] for x in self.top_quality]
self.stocks_to_hold = [x.symbol for x in TQ2[:self.TARGET_SECURITIES]]
return self.stocks_to_hold
print(self.stocks_to_hold)
def OnData(self, data):
pass
def select_stocks_set_weights(self):
# Set desired stock weights
# Equally weight
self.stock_weight = 1.0 / self.TARGET_SECURITIES
self.stock_weights = pd.Series(index=self.stocks_to_hold, data=self.stock_weight)
def trade(self):
for i in self.Portfolio.Values:
if (i.Invested) and (i not in self.stocks_to_hold):
self.Liquidate(i.Symbol)
for i in self.stocks_to_hold:
self.SetHoldings(i, self.stock_weight)
Here I've tried to create a filter for ROE ROIC FCF and whatnot for when SPY is bullish, However, when I try to backtest it, nothing gets traded the list of stocks don't get printed. I don't know where my error is but any help would be appreciated, thanks.
Derek Melchin
Hi Jimothy,
The problem is that the filtration process in the FineSelectionFunction from line 90-99 is so strict that no securities pass all the requirements. See the attached backtest and plot for reference. However, note the attached backtest requires further work before it'll trade with the securities that pass the filter.
Nothing was being printed because the `print` command is below a `return` command.
Best,
Derek Melchin
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Jimothy
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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