Get M&A deal data via Python API

r.j.galema

I am having a problem understanding how to query M&A deal data through the Eikon Python API. The only documentation I have found on this matter is this post on GitHub (https://github.com/Refinitiv-API-Samples/Example.EikonAPI.Python.DealsAnalysis/blob/master/Example.EikonData.Python.DealsAnalysis.ipynb) that provides a query example. From the example, however, it is not clear to me (1) how to use the filters; (2) how many filters are available; (3) how many deal-related variables are available for each deal. Does anyone know by any chance if a complete and clear guide is available?

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Accepted answers

nick.zincone

Hi @r.j.galema

The M&A notebook you referenced utilizes the Search service available within the platform. To better understand the basics and some advanced details related to the Search service, I would recommend the following articles:

Building Search into your Application Workflow
This article introduces the core concepts around Search, which includes filters, navigators and dozens of examples demonstrating the features of the service
Build queries easily using Refinitiv's Search API
This is a more advanced article for users that are comfortable with the Search service but want to simplify the ways to figure out how to filter and which properties to select.

Search is a very rich, but powerful service that is sensitive to filter expressions but does allow the ability to retrieve the desired content on a granular level.

Hope this helps.

All comments

nick.zincone

Hi @r.j.galema

Building Search into your Application Workflow
This article introduces the core concepts around Search, which includes filters, navigators and dozens of examples demonstrating the features of the service
Build queries easily using Refinitiv's Search API
This is a more advanced article for users that are comfortable with the Search service but want to simplify the ways to figure out how to filter and which properties to select.

Search is a very rich, but powerful service that is sensitive to filter expressions but does allow the ability to retrieve the desired content on a granular level.

Hope this helps.

aramyan.h

Hi @r.j.galema ,

In addition to @nick.zincone's comment I would like to share a code snipped which was build following the resources that Nick has shared. I have built that in this article for getting M&A data for predictive analysis. I am using RDP API there, however for your ease I posting the code build using our latest RD Libraries here as well.

MnA = rd.discovery.search(
    view = rd.discovery.Views.DEALS_MERGERS_AND_ACQUISITIONS,

    #specify filtering properties
    filter = "((AcquirerCompanyName ne 'Creditors' and AcquirerCompanyName ne 'Shareholder') and (TargetCountry eq 'US' or TargetCountry eq 'UK')"
    + "and TransactionValueIncludingNetDebtOfTarget ge 100 and TargetPublicStatus eq 'Public')"
    + "and (TransactionStatus eq 'Completed' or TransactionStatus eq 'Pending' or TransactionStatus eq 'Withdrawn')"
    + "and (FormOfTransactionName xeq 'Merger' or FormOfTransactionName xeq 'Acquisition') and (TransactionAnnouncementDate le 2022-04-14 and TransactionAnnouncementDate ge 2022-01-01)",

    #select only the required fields and order them based on announcement date
    #then specify number of items to be 10000, default value is 100
    select = 'TransactionAnnouncementDate, TargetCompanyName, TargetRIC',
    order_by = 'TransactionAnnouncementDate desc',
    top = 10000)

MnA.head()

Hope this also will be useful.

Best regards,

Haykaz

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