This dataset is free to browse and gated for download. Approval is tied to a Papers With Backtest subscription, which also covers the other datasets in this organisation and the strategy catalogue at https://paperswithbacktest.com. Plans and what each one includes: https://paperswithbacktest.com/pricing

Bonds Daily Price

This dataset includes daily rate data for various bonds.

1,415,096 rows over 209 symbols, 7 columns, covering 1969-04-30 to 2026-07-31. Refreshed monthly.

Strategies Built on This Data

590 papers in the Papers With Backtest catalogue declare this dataset as an input. 560 of them have been coded and run over their own full history. The median replicated Sharpe ratio is +0.48, and 59% clear a t-statistic of 1.96 on their own sample, against 48% across all 4,837 replications in the library.

Some of the strongest results that lean on it:

Strategy	Sharpe	t-stat	Tested over
Forecasting Bond Risk Premia using Stationary Yield Factors	+1.06	6.4	36 years
Statistical and Economic Benefits of Whitening Residuals in Bond Yields	+0.90	4.9	29 years
Explaining low annuity demand: an optimal portfolio application to Japan	+1.60	9.6	36 years
Inflation and Stock Returns at B3	+1.49	8.8	35 years

A Sharpe ratio quoted without its t-statistic hides how much of the library cannot be distinguished from zero, which is why both are shown. The figures are in-sample over each strategy's own window and carry no transaction costs.

Why It Matters

This dataset powers fixed-income and cross-asset trading workflows by:

Rate momentum and carry: Daily history of global bond benchmarks supports duration timing and curve-trading signals.
Cross-asset hedging: Bond moves provide defensive context for equities, credit, FX, and commodities risk overlays.
Long history: 209 sovereign curves, the oldest starting in 1969, which is enough span to test a rate signal across several full cycles.

Load It

Installation/Upgrade:

pip install --upgrade pwb-toolbox

Load the Dataset: Optionally pass instrument tickers (e.g., US10Y).

from pwb_toolbox import datasets as pwb_ds

df = pwb_ds.load_dataset("Bonds-Daily-Price", symbols=["US10Y"])
print(df.iloc[0, :])

Example Output:

symbol         US10Y
date      1985-10-25
open          10.186
high          10.186
low           10.186
close         10.186
volume             0

Columns

Column Name	Description
symbol	Bond or rate instrument ticker.
date	Trading date (YYYY-MM-DD).
open	Opening rate level for the session.
high	Highest rate level reached during the session.
low	Lowest rate level reached during the session.
close	Closing rate level for the session.
volume	Always zero. Rate benchmarks are quotes rather than traded instruments, so nothing is reported here.

What This Data Does Not Cover

These are yields, not prices. The 209 series are sovereign benchmark rates in percent, so close for US10Y is a yield near 4, not a bond price near 100. A total-return series has to be built from the yield and the duration; a momentum signal computed straight off close has the sign of a rate move, which is the opposite of the bond return it is usually taken for.

Access

Browsing the card and the schema is open to anyone. Downloading the files needs an approved request, tied to a subscription: what each plan includes. The same subscription covers the other datasets in this organisation.

Elsewhere

Dataset page and coverage charts
The strategy catalogue, 3,806 papers and 4,837 replicated strategies
pwb-toolbox, the loader used in the snippet above
awesome-systematic-trading, the replicated strategies with their measured Sharpe
Every dataset in this organisation

Papers With Backtest publishes 32 datasets on the Hub and codes the papers that use them. Every strategy in the catalogue is run over its own full history before it is published, which is where the numbers above come from.

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