| --- |
| pretty_name: Stocks Quarterly WikipediaViews |
| language: |
| - en |
| license: other |
| task_categories: |
| - time-series-forecasting |
| - tabular-regression |
| tags: |
| - finance |
| - quantitative-trading |
| - backtesting |
| - algorithmic-trading |
| - stocks |
| - equities |
| - quarterly |
| - fundamentals |
| size_categories: |
| - 1M<n<10M |
| extra_gated_prompt: "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" |
| dataset_info: |
| features: |
| - name: symbol |
| dtype: string |
| - name: datetime |
| dtype: string |
| - name: views |
| dtype: float64 |
| - name: relative_views |
| dtype: float64 |
| - name: alpha_short |
| dtype: float64 |
| - name: beta_short |
| dtype: float64 |
| - name: alpha_long |
| dtype: float64 |
| - name: beta_long |
| dtype: float64 |
| - name: long_short_alpha |
| dtype: float64 |
| - name: long_short_beta |
| dtype: float64 |
| - name: search_pressure |
| dtype: float64 |
| splits: |
| - name: train |
| num_examples: 8360636 |
| --- |
| |
| # 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:** |
|
|
| ```bash |
| pip install --upgrade pwb-toolbox |
| ``` |
|
|
| **Load the Dataset:** |
|
|
| ```python |
| 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](https://paperswithbacktest.com/pricing). The same subscription covers the other datasets in this organisation. |
|
|
| ## Elsewhere |
|
|
| - [Dataset page and coverage charts](https://paperswithbacktest.com/datasets/stocks-quarterly-wikipediaviews) |
| - [The strategy catalogue](https://paperswithbacktest.com/strategies), 3,806 papers and 4,837 replicated strategies |
| - [`pwb-toolbox`](https://github.com/paperswithbacktest/pwb-toolbox), the loader used in the snippet above |
| - [`awesome-systematic-trading`](https://github.com/paperswithbacktest/awesome-systematic-trading), the replicated strategies with their measured Sharpe |
| - [Every dataset in this organisation](https://huggingface.co/datasets/paperswithbacktest) |
|
|
| 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. |
|
|
