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An approach to cleaning MiFID II corporate bond transaction reports

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  • Jurkatis, Simon

    (Bank of England)

Abstract

Since 2018, EU and UK financial markets regulators have been in receipt of data on transactions in debt instruments, such as corporate bonds, reported under the Markets in Financial Instrument Regulation. The data gives regulators a more detailed and broader view of trading in these instruments than previously. Reports submitted under this framework, however, come with a number of unique challenges that require careful consideration. Among those challenges are that reports are not submitted in a completely standardised way, that prices and quantities can be reported in different units, and that reports may be submitted by both counterparties of a transaction. This paper describes an approach for handling these issues for transaction reports on corporate bonds, with the aim of helping to enhance the data quality and supporting robust research into this market.

Suggested Citation

  • Jurkatis, Simon, 2024. "An approach to cleaning MiFID II corporate bond transaction reports," Bank of England working papers 1071, Bank of England.
    • Handle: RePEc:boe:boeewp:1071
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    File URL: https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2024/an-approach-to-cleaning-mifid-ii-corporate-bond-transaction-reports.pdf
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    More about this item

    Keywords

    Corporate bonds; data cleaning; deduplication; outlier detection.;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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