In This Page

Introduction

About the Provider

Getting Started

Data Summary

Example Applications

Data Point Attributes

Requesting Data

Accessing Data

Historical Data

Remove Subscriptions

Example Applications

Securities and Exchange Commission

US SEC Filings

Introduction

The US SEC Filings dataset provides the quarterly financial earning reports that the United States Securities and Exchange Commission (SEC) requires from publicly traded companies in the US. The data covers 15,000 US Equities, starts in January 1998, and is delivered on a daily frequency. The data is sourced from the SEC's Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system. QuantConnect downloads and formats the Quarterly Financial Reports (10-Q) and Annual Financial Report (8-K) filings of companies into a format for easy consumption by LEAN.

For more information about the US SEC Filings dataset, including CLI commands and pricing, see the dataset listing.

About the Provider

The mission of the U.S. Securities and Exchange Commission is to protect investors, maintain fair, orderly, and efficient markets, and facilitate capital formation. The SEC oversees the key participants in the securities world, including securities exchanges, securities brokers and dealers, investment advisors, and mutual funds. The SEC is concerned primarily with promoting the disclosure of important market-related information, maintaining fair dealing, and protecting against fraud.

Getting Started

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

Select Language:

from QuantConnect.DataSource import *

self.aapl = self.add_equity("AAPL", Resolution.MINUTE).symbol
self.report_8k_symbol = self.add_data(SECReport8K, self.aapl).symbol
self.report_10k_symbol = self.add_data(SECReport10K, self.aapl).symbol
self.report_10q_symbol = self.add_data(SECReport10Q, self.aapl).symbol

using QuantConnect.DataSource;

_symbol = AddEquity("AAPL", Resolution.Daily).Symbol;
_report8KSymbol = AddData<SECReport8K>(_symbol, Resolution.Daily).Symbol;
_report10KSymbol = AddData<SECReport10K>(_symbol, Resolution.Daily).Symbol;
_report10QSymbol = AddData<SECReport10Q>(_symbol, Resolution.Daily).Symbol;

Data Summary

The following table describes the dataset properties:

Property	Value
Start Date	January 1998
Asset Coverage	15,000 US Equities
Data Density	Sparse
Resolution	Daily
Timezone	UTC

Example Applications

The US SEC Filings dataset enables you to create strategies using information from SEC reports. Examples include the following strategies:

Extracting information about corporate earnings from the documents for further analysis
Applying sentiment analysis to the text content of the documents (for example, keyword scoring and ranking)

For more example algorithms, see Examples.

Data Point Attributes

The US SEC Filings dataset provides SECReport8K, SECReport10K, and SECReport10Q objects.

Report 8K Attributes

SECReport8K objects have the following attributes:

SECReport8K Select Language:

Contents of the actual SEC report

report: SECReportSubmission

Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.

data_type: MarketDataType

True if this is a fill forward piece of data

is_fill_forward: bool

Current time marker of this data packet.

time: DateTime

The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered

end_time: DateTime

Symbol representation for underlying Security

symbol: Symbol

Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.

value: decimal

As this is a backtesting platform we'll provide an alias of value as price.

price: decimal

Report 10K Attributes

SECReport10K objects have the following attributes:

SECReport10K Select Language:

Contents of the actual SEC report

report: SECReportSubmission

Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.

data_type: MarketDataType

True if this is a fill forward piece of data

is_fill_forward: bool

Current time marker of this data packet.

time: DateTime

The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered

end_time: DateTime

Symbol representation for underlying Security

symbol: Symbol

Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.

value: decimal

As this is a backtesting platform we'll provide an alias of value as price.

price: decimal

Report 10Q Attributes

SECReport10Q objects have the following attributes:

SECReport10Q Select Language:

Contents of the actual SEC report

report: SECReportSubmission

Market Data Type of this data - does it come in individual price packets or is it grouped into OHLC.

data_type: MarketDataType

True if this is a fill forward piece of data

is_fill_forward: bool

Current time marker of this data packet.

time: DateTime

The end time of this data. Some data covers spans (trade bars) and as such we want to know the entire time span covered

end_time: DateTime

Symbol representation for underlying Security

symbol: Symbol

Value representation of this data packet. All data requires a representative value for this moment in time. For streams of data this is the price now, for OHLC packets this is the closing price.

value: decimal

As this is a backtesting platform we'll provide an alias of value as price.

price: decimal

Requesting Data

To add US SEC Filings data to your algorithm, call the AddDataadd_data method. Save a reference to the dataset Symbol so you can access the data later in your algorithm.

Select Language:

class SECReportAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2019, 1, 1)
        self.set_end_date(2019, 8, 21)
        self.set_cash(100000)

        self.aapl = self.add_equity("AAPL", Resolution.MINUTE).symbol
        self.report_8k_symbol = self.add_data(SECReport8K, self.aapl).symbol
        self.report_10k_symbol = self.add_data(SECReport10K, self.aapl).symbol
        self.report_10q_symbol = self.add_data(SECReport10Q, self.aapl).symbol

namespace QuantConnect
{
    public class SECReportAlgorithm : QCAlgorithm
    {
        private Symbol _symbol, _report8KSymbol, _report10KSymbol, _report10QSymbol;

        public override void Initialize()
        {
            SetStartDate(2019, 1, 1);
            SetEndDate(2019, 8, 21);
            SetCash(100000);

            _symbol = AddEquity("AAPL", Resolution.Daily).Symbol;
            _report8KSymbol = AddData<SECReport8K>(_symbol, Resolution.Daily).Symbol;
            _report10KSymbol = AddData<SECReport10K>(_symbol, Resolution.Daily).Symbol;
            _report10QSymbol = AddData<SECReport10Q>(_symbol, Resolution.Daily).Symbol;
        }
    }
}

Accessing Data

To get the current US SEC Filings data, index the current Slice with the dataset Symbol. Slice objects deliver unique events to your algorithm as they happen, but the Slice may not contain data for your dataset at every time step. To avoid issues, check if the Slice contains the data you want before you index it.

Select Language:

def on_data(self, slice: Slice) -> None:
    if slice.contains_key(self.report_8k_symbol):
        data_point = slice[self.report_8k_symbol]
        self.log(f"{self.report_8k_symbol} report count at {slice.time}: {len(data_point.report.documents)}")

    if slice.contains_key(self.report_10k_symbol):
        data_point = slice[self.report_10k_symbol]
        self.log(f"{self.report_10k_symbol} report count at {slice.time}: {len(data_point.report.documents)}")

    if slice.ContainsKey(self.report_10q_symbol):
        data_point = slice[self.report_10q_symbol]
        self.log(f"{self.report_10q_symbol} report count at {slice.Time}: {len(data_point.report.documents)}")

public override void OnData(Slice slice)
{
    if (slice.ContainsKey(_report8KSymbol))
    {
        var dataPoint = slice[_report8KSymbol];
        Log($"{_report8KSymbol} report count at {slice.Time}: {data_point.Report.Documents.Count}");
    }

    if (slice.ContainsKey(_report10KSymbol))
    {
        var dataPoint = slice[_report10KSymbol];
        Log($"{_report10KSymbol} report count at {slice.Time}: {data_point.Report.Documents.Count}");
    }

    if (slice.ContainsKey(_report10QSymbol))
    {
        var dataPoint = slice[_report10QSymbol];
        Log($"{_report10QSymbol} report count at {slice.Time}: {data_point.Report.Documents.Count}");
    }
}

To iterate through all of the dataset objects in the current Slice, call the Getget method.

Select Language:

def on_data(self, slice: Slice) -> None:
    for dataset_symbol, data_point in slice.get(SECReport8K).items():
        self.log(f"{dataset_symbol} report count at {slice.time}: {len(data_point.report.documents)}")

    for dataset_symbol, data_point in slice.get(SECReport10K).items():
        self.log(f"{dataset_symbol} report count at {slice.time}: {len(data_point.report.documents)}")

    for dataset_symbol, data_point in slice.get(SECReport10Q).items():
        self.log(f"{dataset_symbol} report count at {slice.time}: {len(data_point.report.documents)}")

public override void OnData(Slice slice)
{
    foreach (var kvp in slice.Get<SECReport8K>())
    {
        var datasetSymbol = kvp.Key;
        var dataPoint = kvp.Value;
        Log($"{datasetSymbol} report count at {slice.Time}: {dataPoint.Report.Documents.Count}");
    }

    foreach (var kvp in slice.Get<SECReport10K>())
    {
        var datasetSymbol = kvp.Key;
        var dataPoint = kvp.Value;
        Log($"{datasetSymbol} report count at {slice.Time}: {dataPoint.Report.Documents.Count}");
    }

    foreach (var kvp in slice.Get<SECReport10Q>())
    {
        var datasetSymbol = kvp.Key;
        var dataPoint = kvp.Value;
        Log($"{datasetSymbol} report count at {slice.Time}: {dataPoint.Report.Documents.Count}");
    }
}

Historical Data

To get historical US SEC Filings data, call the Historyhistory method with the dataset Symbol. If there is no data in the period you request, the history result is empty.

Select Language:

# DataFrames
report_8k_history_df = self.history(self.report_8k_symbol, 100, Resolution.DAILY)
report_10k_history_df = self.history(self.report_10k_symbol, 100, Resolution.DAILY)
report_10q_history_df = self.history(self.report_10q_symbol, 100, Resolution.DAILY)
history_df = self.history([self.report_8k_symbol, 
                           self.report_10k_symbol,
                           self.report_10q_symbol], 100, Resolution.DAILY)

# Dataset objects
report_8k_history_bars = self.history[SECReport8K](self.report_8k_symbol, 100, Resolution.DAILY)
report_10k_history_bars = self.history[SECReport10K](self.report_10k_symbol, 100, Resolution.DAILY)
report_10q_history_bars = self.history[SECReport10Q](self.report_10q_symbol, 100, Resolution.DAILY)

// Dataset objects
var report8KHistory = History<SECReport8K>(_report8KSymbol, 100, Resolution.Daily);
var report10KHistory = History<SECReport10K>(_report10KSymbol, 100, Resolution.Daily);
var report10QHistory = History<SECReport10Q>(_report10QSymbol, 100, Resolution.Daily);

// Slice objects
var history = History(new[] {_report8KSymbol, _report10KSymbol, _report10QSymbol}, 100, Resolution.Daily);

For more information about historical data, see History Requests.

Remove Subscriptions

To remove a subscription, call the RemoveSecurityremove_security method.

Select Language:

self.remove_security(self.report_8k_symbol)
self.remove_security(self.report_10k_symbol)
self.remove_security(self.report_10q_symbol)

RemoveSecurity(_report8KSymbol);
RemoveSecurity(_report10KSymbol);
RemoveSecurity(_report10QSymbol);

If you subscribe to US SEC Filings data for assets in a dynamic universe, remove the dataset subscription when the asset leaves your universe. To view a common design pattern, see Track Security Changes.

Example Applications

The US SEC Filings dataset enables you to create strategies using information from SEC reports. Examples include the following strategies:

Extracting information about corporate earnings from the documents for further analysis
Applying sentiment analysis to the text content of the documents (for example, keyword scoring and ranking)

For more example algorithms, see Examples.

You can also see our Videos. You can also get in touch with us via Discord.

Did you find this page helpful?

Contribute to the documentation:

SIGN IN

Browse

Cloud Platform

Writing Algorithms

▶Key Concepts

Initialization

▶Securities

▶Portfolio

▶Universes

▶Datasets

▶Importing Data

▶Consolidating Data

▶Historical Data

▶Trading and Orders

▶Reality Modeling

Scheduled Events

▶Indicators

Object Store

▶Optimization

▶Machine Learning

▶Algorithm Framework

Charting

Logging

▶Statistics

▶Live Trading

Strategy Library

API Reference

▶Migrations

Research Environment

Local Platform

LEAN CLI

LEAN Engine

Hello

Securities and Exchange Commission

US SEC Filings

Introduction

About the Provider

Getting Started

Data Summary

Example Applications

Data Point Attributes

Report 8K Attributes

Report 10K Attributes

Report 10Q Attributes

Requesting Data

Accessing Data

Historical Data

Remove Subscriptions

Example Applications

▶
Key Concepts

▶
Securities

▶
Portfolio

▶
Universes

▶
Datasets

▶
Importing Data

▶
Consolidating Data

▶
Historical Data

▶
Trading and Orders

▶
Reality Modeling

▶
Indicators

▶
Optimization

▶
Machine Learning

▶
Algorithm Framework

▶
Statistics

▶
Live Trading

▶
Migrations