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

Indices Daily Price

This dataset includes daily price data for various indices.

815,441 rows over 113 symbols, 8 columns, covering 1927-12-30 to 2026-08-03. Refreshed monthly.

Strategies Built on This Data

1,324 papers in the Papers With Backtest catalogue declare this dataset as an input. 1,226 of them have been coded and run over their own full history. The median replicated Sharpe ratio is +0.49, and 62% 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
The Anomalous Behavior of the S&P Covered Call Closed End Fund	+1.36	8.2	36 years
Are Heuristics Better than Theory if Market Crashes Are	+1.10	6.5	35 years
A Risk Based Approach to Tactical Asset Allocation	+1.06	6.3	35 years
Predictors and Portfolios over the Life Cycle	+0.88	5.3	36 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 informs index-based strategies and macro overlays by:

Benchmarking and hedging: Index levels anchor portfolio beta management and overlay hedges.
Trend and breadth analysis: Daily OHLCV allows momentum screens and volatility-aware position sizing on broad markets.
Event studies: Use index moves around macro events to calibrate systematic responses across asset classes.

Load It

Installation/Upgrade:

pip install --upgrade pwb-toolbox

Load the Dataset:

from pwb_toolbox import datasets as pwb_ds

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

Example Output:

symbol           SPX
date      1927-12-30
volume             0
close          17.66
open           17.66
high           17.66
low            17.66

Columns

Column Name	Description
symbol	Equity index ticker.
date	Trading date (YYYY-MM-DD).
volume	Zero for 112 of the 113 symbols. Only `IDX:US`, which is a listed security rather than an index, carries any.
close	Closing index level for the session.
open	Opening index level for the session.
high	Highest index level observed during the session.
low	Lowest index level observed during the session.
adj_close	Adjusted closing level. It equals `close` for 112 of the 113 symbols, so the adjustment `load_dataset` applies is a no-op on all but one of them.

What This Data Does Not Cover

One symbol is not an index. IDX:US is a listed security rather than an index: it has volume, its adj_close differs from its close, and its history stops in 2022. It is the only one of the 113 symbols where the two closing columns diverge.

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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