Learn the code that drives top-tier empirical research in accounting & finance.
More than a coding course. Learn the data techniques and research conventions behind empirical work, applied to the databases researchers actually use: WRDS, CRSP, Compustat, and EDGAR.
✓ Preview real lessons and code free before you pay. No credit card required.
Built and taught by BYU professors with 50+ publications in the top journals and 12,000+ combined Google Scholar citations.
It moves you closer to publication.
Coding is only the tool. What advances your research are the tried-and-true data techniques and common research conventions that empirical work is built on. Just as important, it teaches you to think like an empirical researcher.
Learn the conventions, not just the syntax.
Generic coding courses teach you a language. We teach the tried-and-true data techniques and research conventions that turn code into published accounting and finance research.
Built for research. Not generic coding.
Learn through the actual datasets, workflows, and problems used in empirical accounting and finance, not toy examples.
Learn the hard parts.
Master the parts of the pipeline that get people stuck:
Taught by published professors.
Learn from active researchers with publications in the field's top journals: The Accounting Review, Contemporary Accounting Research, Journal of Accounting and Economics, Journal of Accounting Research, Journal of Finance, Journal of Financial Economics, Management Science, and Review of Accounting Studies.
AI can write the code. It can't do the research for you.
Claude, Copilot, and ChatGPT will generate a WRDS query or a data merge in seconds. But empirical research runs on conventions, and AI doesn't always know which ones your reviewers expect. If you can't tell when an answer is wrong, it works against you.
AI on its own
- Generates plausible-looking code
- Doesn't know your field's methods
- Can be wrong in ways you won't catch
AI + the conventions we teach
- You know the standard method before you prompt
- You spot the mistakes before a referee does
- You direct AI like a skilled research assistant
- The speed of AI, with the judgment to check it
We teach the research conventions behind the code: how to pull and merge CRSP and Compustat, winsorize, build abnormal returns, and measure disclosure tone the way published work does. That context is what lets you use AI well.
What you'll be able to do upon completing the camps
- ✓ Pull data directly from WRDS.
- ✓ Merge, clean, and prep a dataset that's ready for analysis.
- ✓ Scrape filings from EDGAR and prices from Yahoo! Finance.
- ✓ Compute common market and financial statement variables.
- ✓ Run textual analysis.
- ✓ Produce clean tables.
Everything in the research pipeline, one camp
Foundational programming in Python, SAS, and STATA, applied to the tasks empirical accounting and finance research requires.
Introduction to Programming
The foundations of Python, SAS, and STATA for empirical research.
Wharton Research Data Services
Access WRDS from Python and SAS. Pull Compustat and CRSP with SQL; build common financial-statement variables and abnormal returns.
Data Preparation & Analysis
Import, merge, clean, and explore, including winsorization, truncation, descriptive stats, and regression.
Web Scraping
HTML structure and browser interaction, applied to scraping EDGAR and Yahoo! Finance.
Textual Analysis
Regular expressions, tokenization, pre-processing, and word counts to compute disclosure tone and the Fog index.
Robotic Process Automation
Validate user input, automate the keyboard and mouse, and manage files in the OS.
Machine Learning
Random forests, neural networks, support vector machines, and latent Dirichlet allocation for financial data.
ChatGPT for Research Code
Write, optimize, and debug your code faster with AI assistance.
Integrated Development Environments
Get productive in the two most popular Python IDEs: VS Code and PyCharm.
Preview the entire camp for free.
You don't have to take our word for it. Get free access to preview the course: watch real lessons, read the actual code, and judge the teaching for yourself before you spend a dollar. No credit card required.
Start your free previewHundreds trained, and programs that keep coming back
Wherever you are in the research pipeline
PhD Students
Accelerate your dissertation. Run the data yourself (pull, merge, and clean it) and produce results without waiting on others.
Junior Faculty
Take control of your research pipeline and keep publishing without waiting on RAs or co-authors.
Research Assistants
Learn the actual workflows professors use to clean and merge datasets, so you can contribute on real empirical projects.
PhD Programs & Departments
A scalable research-methods supplement for your doctoral program, so cohorts arrive prepared instead of spending faculty time on basics. See department access →
Choose your access
Full access to every camp (introductory, intermediate, and advanced Python, plus SAS and STATA) for one year from enrollment. All programs, solutions, and replication code included to download.
Python Track
Get fluent in the language empirical research runs on.
- Introductory, Intermediate & Advanced Python
- WRDS, data prep, web scraping
- Textual analysis & machine learning
- One year of access
The Full Camp
Every language and workflow: the complete pipeline, end to end.
- Everything in the Python Track
- SAS + STATA camps
- The full empirical pipeline, end to end
- All solution & replication code
- One year of access
Institutional Access
Equip a whole cohort with the foundation faculty wish they already had.
- Full Camp access for every student
- 20% off for 3+ seats
- Protect faculty time; standardize skills
- A research-methods supplement for your program
Prefer a single camp or a custom combination? Individual camps start at $600.
Give your doctoral students the empirical coding foundation faculty wish they already had.
Cohorts that arrive unprepared spend expensive faculty time on basic data and code issues. A scalable, self-paced foundation gets every student productive and protects your faculty's research time.
Or email instructors@accountingcodingcamp.com
Taught by researchers who publish
The Accounting Coding Camp is taught by Mike Drake, Josh Lee, and Jake Thornock, professors of accounting at BYU's Marriott School of Business and active empirical researchers who use these techniques in their own published work.
Their work appears in The Accounting Review, Contemporary Accounting Research, Journal of Accounting and Economics, Journal of Accounting Research, Journal of Finance, Journal of Financial Economics, Management Science, and Review of Accounting Studies.
See for yourself on Google Scholar: Michael Drake · Joshua Lee · Jake Thornock
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More than just coding. It moves you closer to publication.