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 snippets demonstrate how to request data from the US Fundamental dataset:

• Direct Access using the Security object

equity = self.add_equity("IBM")
ibm_fundamental = equity.fundamentals

var equity = AddEquity("IBM");
var ibmFundamental = equity.Fundamentals;

• Direct Access using the Symbol object

ibm = Symbol.create("IBM", SecurityType.EQUITY, Market.USA)
ibm_fundamental = self.fundamentals(ibm)

var ibm = QuantConnect.Symbol.Create("IBM", SecurityType.Equity, Market.USA);
var ibmFundamental = Fundamentals(ibm);

• Universe Selection

def initialize(self) -> None:
    self._universe = self.add_universe(self.fundamental_filter_function)

def fundamental_filter_function(self, fundamental: List[Fundamental]):
    filtered = [f for f in fundamental if f.has_fundamental_data and f.price > 10 and not np.isnan(f.valuation_ratios.pe_ratio)]
    sorted_by_pe_ratio = sorted(filtered, key=lambda f: f.valuation_ratios.pe_ratio)
    return [f.symbol for f in sorted_by_pe_ratio[:10]]

public override void Initialize()
{
    _universe = AddUniverseSelection(new FundamentalUniverseSelectionModel(FundamentalFilterFunction));
}

public override List<Symbol> FundamentalFilterFunction(List<Fundamental> fundamental)
{
    return (from f in fundamental
            where f.HasFundamentalData && f.Price > 10 && !Double.IsNaN(f.ValuationRatios.PERatio)
            orderby f.ValuationRatios.PERatio
            select f.Symbol).Take(10);
}

The following table describes the dataset properties:

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 Piotroski F-score 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

For more example algorithms, see Examples.

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

Fundamental Attributes

Fundamental 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.

filteredFundamentals = fundamental.Where(x =>
    x.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Technology);

filtered_fundamentals = [x for x in fundamental
    if x.asset_classification.morningstar_sector_code == MorningstarSectorCode.TECHNOLOGY]

The MorningstarSectorCode enumeration has the following members: