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

Author

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  • Durante, Adriano
  • Elsaid, Eahab

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.

Suggested Citation

  • Durante, Adriano & Elsaid, Eahab, 2018. "How to build a better database: When python programming meets Bloomberg's Open API," Finance Research Letters, Elsevier, vol. 24(C), pages 64-72.
    • Handle: RePEc:eee:finlet:v:24:y:2018:i:c:p:64-72
    DOI: 10.1016/j.frl.2017.07.006
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    More about this item

    Keywords

    Bloomberg Open API; Python; Hand-collected data; SEC filings; Databases;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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