Examples and references, meant for copying and pasting as needed. https://quantconnect.com
One of the challenges I had is how to control frequency of Universe selection. This forum post list 3 alternatives to address that, using ScheduledUniverseSelection, data consolidator and flags. Using flags allows using Course and Fine filters easily, as per code below.
Usually Course and Fine will run every day by default. This code ensure it runs only once a month
def Initialize(self):
self.SetStartDate(2019, 1, 1) # Set Start Date
self.SetEndDate(2019, 12, 31)
self.SetCash(10000)
self.month = -1
self.AddUniverse(self.CourseSelectionFilter)
def CourseSelectionFilter(self, course):
if (self.month == self.Time.month):
return Universe.Unchanged
#1. Sort descending by daily dollar volume
sortedByDollarVolume = sorted(course, key=lambda c: c.DollarVolume, reverse = True)
#2. Select only Symbols with a price of more than $10 per share
symbols_by_price = [c.Symbol for c in sortedByDollarVolume if c.Price > 10]
self.filteredByPrice = symbols_by_price[:8]
#self.Debug(self.filteredByPrice)
self.Debug(self.Time)
self.month = self.Time.month
return self.filteredByPrice
def Initialize(self):
self.SetStartDate(2019, 1, 1) # Set Start Date
self.SetEndDate(2019, 12, 31)
self.SetCash(10000)
self.AddUniverse(self.CourseSelectionFilter)
self.update = False
def CourseSelectionFilter(self, course):
if not self.Time.month%3 == 0:
self.update = True
if not (self.update and self.Time.month%3==0): return []
self.update = False
#1. Sort descending by daily dollar volume
sortedByDollarVolume = sorted(course, key=lambda c: c.DollarVolume, reverse = True)
#2. Select only Symbols with a price of more than $10 per share
symbols_by_price = [c.Symbol for c in sortedByDollarVolume if c.Price > 10]
self.filteredByPrice = symbols_by_price[:8]
self.Debug("quarter! " + str(self.Time))
return self.filteredByPrice
def Initialize(self):
self.SetStartDate(2019, 1, 1)
self.SetEndDate(2019, 12, 31)
self.SetCash(100000)
self.UniverseSettings.Resolution = Resolution.Hour
self.SetUniverseSelection(MyUniverseSelectionModel())
class MyUniverseSelectionModel(FundamentalUniverseSelectionModel):
def __init__(self):
super().__init__(True, None)
def SelectCoarse(self, algorithm, coarse):
filtered = [x for x in coarse if x.HasFundamentalData and x.Price > 0]
sortedByDollarVolume = sorted(filtered, key=lambda x: x.DollarVolume, reverse=True)
return [x.Symbol for x in sortedByDollarVolume][:100]def Initialize(self):
self.SetStartDate(2019, 1, 1)
self.SetEndDate(2019, 12, 31)
self.SetCash(100000)
self.UniverseSettings.Resolution = Resolution.Hour
self.SetUniverseSelection(MyUniverseSelectionModel())
class MyUniverseSelectionModel(FundamentalUniverseSelectionModel):
def __init__(self):
super().__init__(True, None)
def SelectCoarse(self, algorithm, coarse):
filtered = [x for x in coarse if x.HasFundamentalData and x.Price > 0]
sortedByDollarVolume = sorted(filtered, key=lambda x: x.DollarVolume, reverse=True)
return [x.Symbol for x in sortedByDollarVolume][:100]
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)[:3]
filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.FinancialServices]
self.financialServices = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:2]
filtered = [f for f in fine if f.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.ConsumerDefensive]
self.consumerDefensive = sorted(filtered, key=lambda f: f.MarketCap, reverse=True)[:1]
return [x.Symbol for x in self.technology + self.financialServices + self.consumerDefensive]