How to build a better database: When python programming meets Bloomberg's Open API

Adriano Durante and Eahab Elsaid

Finance Research Letters, 2018, vol. 24, issue C, 64-72

Abstract: The need to hand collect data from SEC filings, among other sources, has long constituted a significant obstacle when conducting research in the area of finance (more specifically corporate finance) – and, indeed, business broadly defined. We propose a novel data collection alternative; using the Python programming language and Bloomberg's Open API we show how to automate the data collection process and generate databases of indefinite size. This is particularly useful when collecting data generally thought to be available only in proxy statements. Such variables include, but are not limited to: CEO age, CEO tenure, board size, number of independent and female directors on the board, and number of shares held by insiders. The approach described in our paper has significant implications for research, academia and in areas heretofore limited by the need to hand collect data.

Keywords: Bloomberg Open API; Python; Hand-collected data; SEC filings; Databases (search for similar items in EconPapers)
JEL-codes: G32 G34 M15 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612317302349
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:24:y:2018:i:c:p:64-72

DOI: 10.1016/j.frl.2017.07.006

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().