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Data is delivered as a daily updated zip archive of map and factor files. The data is designed to be used in the LEAN Engine and cannot be consumed another way. The following table shows the dataset properties:

You don't need any special code to utilize the US Equity Security Master. It automatically loads when you request US Equities data.

The US Security Master enables you to accurately design strategies harnessing any core corporate actions. Examples include the following strategies:

• Post-dividend announcement trading strategies.
• Trading on new Equities by monitoring for IPOs.
• Harnessing split announcements for reverse-split announcement momentum.

For more example algorithms, see Examples.

The US Equity Security Master dataset provides Split, Dividend, Delisting, and SymbolChangedEvent objects.

Split Attributes

When a split or merger occurs, we pass the previous Symbol data into your algorithm. Split objects have the following attributes:

Dividend Attributes

Dividend events are triggered on the payment date. Dividend objects have the following attributes:

Delisting Attributes

When a security is delisted, we notify your algorithm. Delisting objects have the following attributes:

SymbolChangedEvent Attributes

When a security changes their ticker, we notify your algorithm. SymbolChangedEvent objects have the following attributes:

To view the supported assets in the US Equity Security Master dataset, see the Data Explorer. This dataset doesn't include Over-the-Counter (OTC) stocks.

To get the current split data, index the Splitssplits property of the current Slice with the Equity Symbol. Slice objects deliver unique events to your algorithm as they happen, but the Slice may not contain data for your security at every time step. To avoid issues, check if the Slice contains the data you want before you index it.

def on_data(self, slice: Slice) -> None:
    # Check if any splits for the symbol
    if slice.splits.contains_key(self._symbol):
        # If so, get the mapped split object
        split = slice.splits[self._symbol]
        split_type = {0: "Warning", 1: "SplitOccurred"}.get(split.type)
        self.log(f"Split: {split.symbol}\t{split.split_factor}\t{split.reference_price}\t{split_type}")

public override void OnData(Slice slice)
{
    // Check if any splits for the symbol
    if (slice.Splits.ContainsKey(_symbol))
    {
        // If so, get the mapped split object
        var split = slice.Splits[_symbol];
        Log($"Split: {split.Symbol}\t{split.SplitFactor}\t{split.ReferencePrice}\t{split.Type}");
    }
}

For more information about accessing splits, see Splits.

To get the current dividend data, index the Dividendsdividends property of the current Slice with the Equity Symbol. Slice objects deliver unique events to your algorithm as they happen, but the Slice may not contain data for your security at every time step. To avoid issues, check if the Slice contains the data you want before you index it.

def on_data(self, slice: Slice) -> None:
    # Check if any dividend for the symbol
    if slice.dividends.contains_key(self._symbol):
        # If so, get the mapped dividend object
        dividend = slice.dividends[self._symbol]
        self.log(f'Dividend: {dividend.symbol}\t{dividend.distribution}\t{dividend.reference_price}')