Skip to content

Python Tools & Books

Open-Source Tools by Jeroen Bouma (USE alumnus)

  • Finance Toolkit Python Global — An open-source Python toolkit for transparent financial analysis. Covers 150+ financial ratios, indicators, and performance measurements for equities, options, currencies, ETFs, indices, and more. Also includes economic indicators for 60+ countries. (GitHub)
pip install financetoolkit
  • Finance Database Python Global — A database of 300,000+ financial symbols (equities, ETFs, funds, indices, currencies, cryptocurrencies, money markets) categorized by country, sector, and industry. Useful for identifying which products exist in a given market or industry. (GitHub)
pip install financedatabase

Other Open-Source Tools

  • yfinance Python Global — Widely-used open-source Python library for downloading market data from Yahoo Finance. Covers historical prices, dividends, splits, fundamentals, options chains, and more for stocks, ETFs, mutual funds, currencies, and cryptocurrencies. (GitHub)
pip install yfinance
  • Alpha Vantage API Python Global — Free API providing historical and real-time market data for equities, forex, and cryptocurrencies, plus 50+ technical indicators and U.S. economic indicators. Free tier available (25 API calls/day); premium plans for higher rate limits. Requires a free API key. Python access via alpha-vantage. (GitHub)
pip install alpha-vantage

Data Access

  • pandas-datareader Python Global — Standard library for downloading economic and financial data into pandas DataFrames. Connects to FRED, World Bank, OECD, Eurostat, Yahoo Finance, and more. (GitHub)
pip install pandas-datareader
  • fredapi Python US — Official Python wrapper for the FRED API, providing access to 800,000+ economic time series from the Federal Reserve Bank of St. Louis. Requires a free API key from FRED. (GitHub)
pip install fredapi
  • wrds Python Global — Official WRDS Python connector for direct database access to Compustat, CRSP, and all WRDS datasets via SQL queries. Requires a WRDS account (available to UU students and staff). See also the WRDS Python guide.
pip install wrds

Econometrics & Analysis

  • linearmodels Python — Panel data models (fixed effects, random effects, between estimator), instrumental variables (2SLS, LIML, GMM), and system estimation. Standard package for applied finance research with panel data. (GitHub)
pip install linearmodels
  • statsmodels Python — Time series analysis (ARIMA, VAR, VECM, GARCH via arch), hypothesis testing, OLS/WLS/GLS regression, and diagnostic tools. Foundation for econometric work in Python. (GitHub)
pip install statsmodels

Books

  • Tidy Finance with Python — Open-source textbook on empirical finance with Python, by Scheuch, Voigt, Weiss & Frey (Chapman & Hall/CRC). Covers tidy data principles, asset pricing (beta estimation, portfolio sorts, Fama-French factors), machine learning (ridge, lasso, random forests, neural networks), and portfolio optimization. Full book available free online. Also provides the tidyfinance Python package with helper functions for downloading and preparing financial datasets.

Note

Many examples in Tidy Finance use CRSP data, which Utrecht University does not have access to. The book's open-source data chapters and methodology sections remain fully usable.

See also: Economic Data (with APIs) — the Finance Toolkit also covers economic indicators for 60+ countries.