Resources & Tutorials

Articles and tutorials with ready-to-execute source code designed to assist you in navigating the world of SEC filings and datasets.

An Explanation for the Halloween Effect (Sell in May, and go away)

A first empirical explanation for the Halloween effect, linking seasonal SEC filing patterns to stock market performance.

Fama-French Factor Model in Python

Learn how to apply the Fama-French factor model to the monthly returns of the QQQ ETF from 2006 to 2023, and analyze the impact of the factors on the ETF's performance.

Testing Statistical Significance in Financial Data with Python

Learn how to calculate test statistics and p-values, what statistical tests to choose for what type of dataset, and how to perform hypothesis testing on financial data using Python.

13F Alpha Pursuit: Performance, Volatility & Survival of Funds

Explore fund performances through Python analysis of 13F filings: rank top funds, visualize alpha distributions, compare asset growth against benchmarks, and assess fund survival rates.

8-K Filings & Material Event Disclosure Activity

Analyze 8-K filings and material event disclosure activity with Python, and learn how to extract and visualize the most frequent 8-K event types and their trends over time.

Fed Funds Rate Projections in Python

Extract and analyze the federal funds rate predictions by FOMC meeting participants. From data retrieval and cleaning to visualizing multi-year forecasts in a heatmap.

EDGAR Filing Trends & Patterns (1994 - 2022)

Analyze EDGAR filing volume from 1994-2022 across dimensions like form types, sectors, and SEC offices, visualized with charts and insights on trends and anomalies.

EDGAR Filer Analysis (1994 - 2022)

Use Python to analyze SEC EDGAR filer trends across sectors, SIC codes, and SEC offices using visualization techniques like bar charts and heatmaps, while uncovering early warning signs of major market events such as the dot-com bubble, 2008/09 financial crisis, and the 2021 SPAC boom.

Download and Analyze SEC Comment Letters

Learn how to find, download and analyze SEC Comment letters from the EDGAR database with Python, BERTopic, pandas and various APIs.

Download SEC Filings from EDGAR

Download and save 10-K and 10-Q SEC filings to your local disk with Python, and learn how to convert any EDGAR filing to PDFs.

Download Financial Statements from EDGAR Filings as Excel File

Download financial reports as Excel files attached to 10-K and 10-Q filings with Python, and learn how to search and filter the EDGAR database.

Extract Google's Revenue Metrics from 10-K Filings with Python

Extract revenue by product categories and regions from 10-K filings and XBRL data, and visualize the data over time in bar charts with Python.

Extract Financial Statements from SEC Filings with Python

Extract income statements from 10-Ks, convert them into dataframes, and visualize revenue metrics by product categories and geographical regions.

Extract Textual Data from EDGAR 10-K Filings Using Python

Learn how to extract content from SEC EDGAR 10-K filings and use pandas to convert extracted financial statements from HTML tables into dataframes.

Download 10-K Filings of Russell 3000 Companies from SEC EDGAR

This Python tutorial demonstrates how to download all SEC 10-K filings of Russell 3000 companies from the EDGAR database.

Extract Counterparties of Swap Derivatives from N-PORT Filings

Learn how to extract counterparties of swap derivatives disclosed in SEC N-PORT filings using Python.

Download XML Files from SEC EDGAR Using Python

The tutorial explains how to find all URLs of XML files attached to SEC EDGAR filings to download the identified XML files with Python.

Lucene Query Syntax - Overview

An overview of commonly used Lucene query expressions with examples.