Project Layline is a research initiative that aims to leverage high performance and cloud computing to create publicly accessible datasets for research in financial economics. It lowers barriers to entry by democratizing access to data and also brings increased transparency to the field by facilitating replication studies.
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1 to 4 of 4 Results
Mar 28, 2024
Balogh, Attila, 2023, "Layline insider trading dataset", https://doi.org/10.7910/DVN/VH6GVH, Harvard Dataverse, V292
This dataset captures insider trading activity at publicly traded companies. The Securities and Exchange Commission has made these insider trading reports available on its web site in a structured format since mid-2003. However, most academic papers use proprietary commercial dat...
Mar 28, 2024
Balogh, Attila, 2023, "Layline corporate filings dataset", https://doi.org/10.7910/DVN/WACGV5, Harvard Dataverse, V268
Regulatory filing metadata obtained from the SEC's EDGAR system.
Mar 27, 2024
Balogh, Attila, 2023, "Layline shareholder activism dataset", https://doi.org/10.7910/DVN/SHB2EC, Harvard Dataverse, V267
A set of datasets that includes metadata for passive and active blockholders, corporate filings, institutional investor filings, and non-management proxy filings.
Mar 22, 2024
Balogh, Attila, 2023, "Layline institutional holding reports", https://doi.org/10.7910/DVN/TZM1QT, Harvard Dataverse, V219
This dataset captures the quarterly investment holdings of institutional investment managers and maps the ownership structure of public firms. These Schedule 13F reports are submitted to the Securities and Exchange Commission quarterly by all institutional investment managers wit...
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