Morningstar

Morningstar was founded by Joe Mansueto in 1984 with the goal of empowering investors by connecting people to the investing information and tools they need. Morningstar provides access extensive line of products and services for individual investors, financial advisors, asset managers, and retirement plan providers. Morningstar provides data on approximately 525,000 investment offerings including stocks, mutual funds, and similar vehicles, along with real-time global market data on nearly 18 million equities, indexes, futures, options, commodities, and precious metals, in addition to foreign exchange and Treasury markets. Morningstar also offers investment management services through its investment advisory subsidiaries, with $244 billion in assets under advisement or management as of 2021.

The following snippet demonstrates how to request data from the US Fundamental dataset:

from QuantConnect.DataSource import *

self.AddUniverse(self.SelectCoarse, self.SelectFine)

using QuantConnect.DataSource;

AddUniverse(SelectCoarse, SelectFine);

The following table describes the dataset properties:

To view the supported assets in the US Fundamental dataset, see the Data Explorer.

The US Fundamentals dataset provides FineFundamental objects. To filter FineFundamental objects, you can use the MorningstarSectorCode, MorningstarIndustryGroupCode, and MorningstarIndustryCode enumeration values.

FineFundamental Attributes

FineFundamental objects have the following attributes:

MorningstarSectorCode Enumeration

Sectors are large super categories of data. To access the sector of an Equity, use the MorningstarSectorCode property.

filteredFine = fine.Where(x => x.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Technology);

filtered_fine = [x for x in fine if x.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Technology]

The MorningstarSectorCode enumeration has the following members:

MorningstarIndustryGroupCode Enumeration

Industry groups are clusters of related industries which tie together. To access the industry group of an Equity, use the MorningstarIndustryGroupCode property.

filteredFine = fine.Where(x => x.AssetClassification.MorningstarIndustryGroupCode == MorningstarIndustryGroupCode.ApplicationSoftware);

filtered_fine = [x for x in fine if x.AssetClassification.MorningstarIndustryGroupCode == MorningstarIndustryGroupCode.ApplicationSoftware]

The MorningstarIndustryGroupCode enumeration has the following members:

MorningstarIndustryCode Enumeration

Industries are the finest level of classification available and are the individual industries according to the Morningstar classification system. To access the industry group of an Equity, use the MorningstarIndustryCode property.

filteredFine = fine.Where(x => x.AssetClassification.MorningstarIndustryCode == MorningstarIndustryCode.SoftwareApplication);

filtered_fine = [x for x in fine if x.AssetClassification.MorningstarIndustryCode == MorningstarIndustryCode.SoftwareApplication]

The MorningstarIndustryCode enumeration has the following members:

Exchange ID Values

The exchange ID represents the exchange that lists the Equity. To access the exchange ID of an Equity, use the PrimaryExchangeID property.

filteredFine = fine.Where(x => x.CompanyReference.PrimaryExchangeID == "NAS");

filtered_fine = [x for x in fine if x.CompanyReference.PrimaryExchangeID == "NAS"]

The exchanges are represented by the following string values:

To add US Fundamental data to your algorithm, pass a fine universe selection method to the AddUniverse or AddUniverseSelection method.

class MorningStarDataAlgorithm(QCAlgorithm):

    def Initialize(self) -> None:
        self.SetStartDate(2021, 1, 1)
        self.SetEndDate(2021, 7, 1)
        self.SetCash(100000) 
        
        self.AddUniverse(self.SelectCoarse, self.SelectFine)

namespace QuantConnect
{
    public class MorningStarDataAlgorithm : QCAlgorithm
    {    	
        public override void Initialize()
        {
            SetStartDate(2021, 1, 1);
            SetEndDate(2021, 7, 1);
            SetCash(100000);
            
            AddUniverse(SelectCoarse, SelectFine);
        }
    }
}

To access fundamental data, use the FineFundamental objects in your second selection function or use the Fundamental property of the Equity objects in your algorithm. The Symbol objects you return from the coarse selection function are the Symbol objects that comprise the FineFundamental objects in your fine fundamental selection function.

def SelectCoarse(self, coarse: List[CoarseFundamental]) -> List[Symbol]:
    selected = [c for c in coarse if c.HasFundamentalData]
    sorted_by_dollar_volume = sorted(selected, key=lambda c: c.DollarVolume, reverse=True)
    return [ c.Symbol for c in sorted_by_dollar_volume[:20] ]
    
def SelectFine(self, fine: List[FineFundamental]) -> List[Symbol]:
    sorted_by_pe_ratio = sorted(fine, key=lambda f: f.ValuationRatios.PERatio, reverse=True)
    return [ f.Symbol for f in sorted_by_pe_ratio[:5] ]

public IEnumerable<Symbol> SelectCoarse(IEnumerable<CoarseFundamental> coarse)
{
    return coarse.OrderByDescending(x => x.DollarVolume).Take(20).Select(x => x.Symbol);
}
        
public IEnumerable<Symbol> SelectFine(IEnumerable<FineFundamental> fine)
{
    return fine.OrderByDescending(x => x.ValuationRatios.PERatio).Take(5).Select(x => x.Symbol);
}

Many of the MorningStar values are MultiPeriodField objects. These objects represent a timespan of data, normally either OneMonth, ThreeMonths, SixMonths, or TwelveMonths. To view the objects, see the the auto-generated classes in the LEAN GitHub repository.

To access fundamental data outside of your fine fundamental selection function, use the Fundamental property of the Equity objects in your algorithm.

fundamentals = self.Securities[symbol].Fundamentals

var fundamentals = Securities[symbol].Fundamentals;

It's currently only possible to get historical fundamental data from the Research Environment. To get historical data, call the GetFundamental method with the Equity Symbol, a FineFundamental property, a start date, and an end date. If there is no data in the period you request, the history result is empty.

history = qb.GetFundamental(symbol, "ValuationRatios.PERatio", datetime(2021, 1, 1), datetime(2021, 7, 1))

var history = qb.GetFundamental(symbol, "ValuationRatios.PERatio", new DateTime(2021, 1, 1), new DateTime(2021, 7, 1));

For more information about historical US Equity fundamental data in the Research Environment, see Equity Fundamental Data.

To be notified when historical fundamental data is available in an algorithm, subscribe to GitHub Issue #4890.

The US Fundamentals dataset enables you to design strategies harnessing fundamental data points. Examples include the following strategies:

• Ranking a universe of securities by a value factor like the book-to-market ratio and buying a subset of the universe with the best factor ranking
• Using the Morningstar asset classification to target specific industries or to ensure your strategy is diversified across several sectors
• Trading securities that recently performed an IPO