I am currently writing my Masters thesis and I would like to have access to this data to calculate the risk factors of the Fama-French 3 factor model. I know how to download them individually but I am trying to be time efficient here and downloaded them in one shot.
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How to download historical Price to Book Value ratio, Market Cap, Market Returns and ESG Score for each of the companies of the MSCI World Index between 2016 and 2021 ?
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Hi @trstudent13 ,
May I advise reading the article 'Gathering aggregated ESG data on companies', especially its code on GitHub. An example of code you could use from this 'ESG_Boolean_Data' Python Class is:
tes0 = ESG_Boolean_Data(Value = "True", Antivalue = "False") tes1 = tes0.get_data(Companies = ['0#.MIWO00000PUS'], # e.g.: SPX, MIWO00000PUS Fields = ['TR.AnalyticEnvControv','TR.EnvMaterialsSourcing','TR.EnvSupplyChainMgt','TR.PolicySustainablePackaging'], Static_fields = ['TR.HeadquartersCountry', 'TR.TRBCEconomicSector']) tes1.df
Which will provide MSCI World Index companies' ESG boolean data outlined.
Otherwise, I must say that simply just constructing a banal eikon api call is the most efficient way to go about your request, e.g.:
df, err = ek.get_data(instruments=['0#.MIWO00000PUS'], # This renders a list of all the companies in the MSCI world.
fields=All_fields,
parameters={'SDate' : '2020-01-01', 'EDate' : '2021-01-01', 'Frq' : 'FY'})
Note that - due to the naturally low frequency of ESG data publication - only annual ESG data points are considered reliable (and it most often is the highest frequency available for ESG data).
MSCI World is a large list of companies, you may thus hit eikon's data-request limit. I would advise using this technique to circumvent the issue - here it is used on Datastream calls, but it would work on eikon calls too.
