数据集:

edarchimbaud/short-interest-sp500

语言:

en

许可:

mit
中文

Dataset Card for "short-interest-sp500"

Dataset Summary

The short-interest-sp500 dataset provides short interest data for companies listed on the S&P 500 index. This includes the number of shares that have been sold short but have not yet been covered or closed out.

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

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Data Fields

  • symbol (string): A string representing the ticker symbol or abbreviation used to identify the company.
  • date (string): A string representing the date when the data was collected.
  • id (int64): A unique integer identifier for each data instance.
  • settlement_date (timestamp[ns]): The date by which a buyer must pay for the securities delivered by the seller.
  • interest (float64): A floating point number representing the short interest of the company on the specified date.
  • avg_daily_share_volume (float64): A floating point number representing the average daily trading volume of the company.
  • days_to_cover (float64): A floating point number representing the days to cover metric, which is the number of days volume worth of short interest.

Data Splits

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Dataset Creation

Curation Rationale

The short-interest-sp500 dataset was created to facilitate the study of market dynamics, particularly the role of short selling.

Source Data

Initial Data Collection and Normalization

The dataset was compiled from publicly available sources.

Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

The short-interest-sp500 dataset was collected by https://edarchimbaud.substack.com .

Licensing Information

The short-interest-sp500 dataset is licensed under the MIT License.

Citation Information

https://edarchimbaud.substack.com , short-interest-sp500 dataset, GitHub repository, https://github.com/edarchimbaud

Contributions

Thanks to @edarchimbaud for adding this dataset.