finm

A Python package for financial mathematics and quantitative finance education, created by students and educators at the University of Chicago Financial Mathematics program.

Installation

pip install finm

For all optional dependencies (CLI, data access):

pip install finm[all]

Data Access

Load financial data from multiple sources with a consistent interface. See the Data Module documentation for details.

import finm

# Fama-French factors (bundled data, no download needed)
factors = finm.load_fama_french_factors()
factors = finm.load_fama_french_factors(start="2020-01-01", end="2023-12-31")

# Pull fresh data from Ken French's Data Library
finm.pull_fama_french_factors(data_dir="./data", accept_license=True)

# Federal Reserve yield curve (GSW model)
finm.pull_fed_yield_curve(data_dir="./data", accept_license=True)
yields = finm.load_fed_yield_curve(data_dir="./data")

# He-Kelly-Manela intermediary capital factors
finm.pull_he_kelly_manela(data_dir="./data", accept_license=True)
hkm = finm.load_he_kelly_manela_factors_monthly(data_dir="./data")

# Open Source Bond Asset Pricing data
finm.pull_open_source_bond(data_dir="./data", accept_license=True)
treasury = finm.load_treasury_returns(data_dir="./data")
corporate = finm.load_corporate_bond_returns(data_dir="./data")

# WRDS data (requires authentication)
finm.pull_wrds_treasury(
    data_dir="./data",
    wrds_username="your_username",
    start_date="2020-01-01",
    end_date="2023-12-31"
)

Analytics

Calculate risk metrics and factor exposures.

import finm

# Load factors
factors = finm.load_fama_french_factors()

# Fama-French 3-factor exposures
exposures = finm.calculate_factor_exposures(stock_returns, factors)
print(f"Market Beta: {exposures['market_beta']:.3f}")
print(f"SMB Beta:    {exposures['smb_beta']:.3f}")
print(f"HML Beta:    {exposures['hml_beta']:.3f}")
print(f"Sharpe:      {exposures['sharpe_ratio']:.3f}")

# Individual metrics
beta = finm.calculate_beta(stock_returns, market_returns)
sharpe = finm.calculate_sharpe_ratio(returns, risk_free_rate=0.02)

Fixed Income

Bond pricing, duration, and yield curve modeling.

import finm

# Bond pricing
price = finm.bond_price(
    face_value=1000,
    coupon_rate=0.05,
    ytm=0.04,
    periods=10,
    frequency=2  # semiannual
)

# Duration and convexity
dur = finm.duration(1000, 0.05, 0.04, 10, frequency=2)
mod_dur = finm.modified_duration(1000, 0.05, 0.04, 10, frequency=2)
conv = finm.convexity(1000, 0.05, 0.04, 10, frequency=2)

# Yield to maturity
ytm = finm.yield_to_maturity(
    price=1050,
    face_value=1000,
    coupon_rate=0.05,
    periods=10,
    frequency=2
)

# Time value of money
pv = finm.present_value(future_value=1000, rate=0.05, periods=3)
fv = finm.future_value(present_value=1000, rate=0.05, periods=3)

The package also includes an implementation of the Gurkaynak-Sack-Wright (2006) yield curve model. See the API documentation for spot, discount, fit, and related functions.

Command Line Interface

Manage data downloads from the terminal. See the CLI documentation for details.

# List available datasets
finm list

# Get info about a dataset
finm info fama_french

# Pull data (--accept-license flag required)
finm pull fama_french --data-dir=./data --accept-license
finm pull fed_yield_curve --data-dir=./data --accept-license

# Pull WRDS data (requires credentials)
finm pull wrds_treasury --wrds-username=myuser --start-date=2020-01-01 --end-date=2023-12-31 --accept-license

Documentation

Full documentation is available at jeremybejarano.com/finm.

Data Licensing

Citation Requirements

When using data from these sources in academic work, please cite appropriately:

License Types

Fair Use

The data access functionality in this package is provided for:

• Educational purposes
• Academic research
• Personal, non-commercial analysis

For commercial use, please consult the original data provider's licensing terms.

License

Modified BSD License. See LICENSE for details.

Acknowledgments

Created and maintained by students and educators at the University of Chicago Financial Mathematics program.