Excess Bond Premium
Retrieves the credit spread of Gilchrist and Zakrajšek (2012) and its excess bond premium, monthly from 1973, as the Federal Reserve Board updates them. The GZ credit spread is the average spread of US corporate bonds over Treasuries with the same cash flows, built bond by bond from the secondary market. The excess bond premium is the part of that spread that expected defaults do not explain: a measure of investors’ appetite for credit risk, and one of the best predictors of economic activity in the literature. The Recession Probability column is the probability of a recession over the next twelve months the premium implies.
Gilchrist, S., & Zakrajšek, E. (2012). Credit Spreads and Business Cycle Fluctuations. American Economic Review, 102(4), 1692-1720. https://doi.org/10.1257/aer.102.4.1692
No API key is needed. The spread and premium are returned as decimal fractions (0.0084 for 0.84 percentage points) and the probability as a fraction (0.108 for 10.8%).
See definition: https://www.federalreserve.gov/econres/notes/feds-notes/updating-the-recession-risk-and-the-excess-bond-premium-20161006.html
Also known as: GZ spread, Gilchrist-Zakrajšek spread, EBP, credit market sentiment.
Excess Bond Premium in Python
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_excess_bond_premium as shown below.
from financetoolkit import FixedIncome
fixedincome = FixedIncome(start_date='2026-02-01', end_date='2026-07-31')
fixedincome.get_excess_bond_premium()
Which returns:
| date | GZ Credit Spread | Excess Bond Premium | Recession Probability |
|---|---|---|---|
| 2026-02 | 0.0097 | -0.0026 | 0.1222 |
| 2026-03 | 0.0103 | -0.0026 | 0.1208 |
| 2026-04 | 0.0092 | -0.002 | 0.1374 |
| 2026-05 | 0.0083 | -0.0037 | 0.0951 |
| 2026-06 | 0.0086 | -0.0028 | 0.1152 |
| 2026-07 | 0.0084 | -0.0031 | 0.1093 |
Parameters
The function accepts the following parameters:
- rounding (int | None, optional): The number of decimals to round the results to. Defaults to None.
- growth (bool, optional): Whether to return the growth data or the actual data. Defaults to False.
- lag (int, optional): The number of periods to lag the growth data by. Defaults to 1.
- standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.