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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31 to 38 of 38 Results
hr_panel_2019.zip
May 28, 2024 - Layline institutional holding reports
ZIP Archive - 150.5 MB - MD5: 99d622cb6ac04f0ee7211d218aaf22e1
Merged holding report panel - 2019
hr_panel_2020.zip
May 28, 2024 - Layline institutional holding reports
ZIP Archive - 155.6 MB - MD5: 593b6cfb0e8a383a2c0b7e95c4175da4
Merged holding report panel - 2020
hr_panel_2021.zip
May 28, 2024 - Layline institutional holding reports
ZIP Archive - 183.1 MB - MD5: fa09425883cc4c106a4d441716ce0dc6
Merged holding report panel - 2021
hr_panel_2022.zip
May 28, 2024 - Layline institutional holding reports
ZIP Archive - 195.7 MB - MD5: bc6f7f8ae40556f16f89b705a97f31a9
Merged holding report panel - 2022
hr_panel_2023.zip
May 28, 2024 - Layline institutional holding reports
ZIP Archive - 211.8 MB - MD5: bf2bb8a6ea1f290dcb7a03442e425800
Merged holding report panel - 2023
hr_panel_2024.zip
May 28, 2024 - Layline institutional holding reports
ZIP Archive - 52.5 MB - MD5: f3f57708769628ff20bba19c43449e5b
Merged holding report panel - 2024
panel_dataset.do
May 2, 2023 - Layline insider trading dataset
Stata Syntax - 8.9 KB - MD5: 9baa1616711d153c7abcaa9340afb1e7
Code
STATA code for creating panel dataset
panel_dataset.py
May 2, 2023 - Layline insider trading dataset
Python Source Code - 19.0 KB - MD5: 670819266575828376fc9c19ce123d0a
Code
Python code for creating panel dataset
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