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Stocks Quarterly WikipediaViews

Quarterly Wikipedia page view volumes for US-listed companies.

8,360,636 rows over 2,193 symbols, 11 columns, covering 2015-07-31 to 2026-01-07. The most recent observation is 2026-01-07.

Why It Matters

This dataset brings attention-based signals into equity models by:

  • Attention signals: Spikes in page views can precede volatility, news coverage, or retail trading activity.
  • Event detection: Quarterly aggregation smooths noise while highlighting sustained interest trends.
  • Alternative data overlay: Combine with price/volume to craft attention-adjusted signals and risk alerts.

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("Stocks-Quarterly-WikipediaViews", symbols=["AAPL"])
print(df.iloc[0, :])

Example Output:

symbol                             AAPL
datetime            2015-07-31 00:00:00
views                            9935.0
relative_views                 0.999732
alpha_short                    0.663812
beta_short                     0.675321
alpha_long                     0.554069
beta_long                      0.638651
long_short_alpha               0.474706
long_short_beta                 0.49371
search_pressure                0.541194

Columns

Column Name Description
symbol Stock ticker.
datetime Quarter-end timestamp.
views Total Wikipedia page views during the quarter.
relative_views Page views scaled relative to the broader universe.
alpha_short Short-term alpha estimate derived from view trends.
beta_short Short-term beta estimate derived from view trends.
alpha_long Long-term alpha estimate derived from view trends.
beta_long Long-term beta estimate derived from view trends.
long_short_alpha Combined long/short alpha estimate.
long_short_beta Combined long/short beta estimate.
search_pressure Normalized search pressure signal.

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

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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