Choosing European Stock Return Data for Academic Research

Summary

The document asks which datasets are suitable for academic research on European stock returns and whether alternatives to FactSet are available. It offers only a brief response: researchers seeking clean return series may prefer commercial data, but the appropriate choice depends on how returns are defined. The examples named include price returns, total returns, cumulative returns, and log returns.

It also points out that academic studies may construct returns differently to fit their research aims. This means that a dataset comparison should consider not only coverage and data quality, but also the return definition and calculation conventions. The response does not identify specific vendors or dataset identifiers, compare costs or coverage, or provide evidence for the recommendation. It is therefore a limited research-design note rather than a guide to selecting a European equities database.

Key ideas

• Commercial data may be useful when clean stock return observations are a priority.
• The suitable return series depends on whether the analysis needs price, total, cumulative, or log returns.
• Academic studies can define and calculate returns differently to meet their research objectives.
• The response does not name or compare specific European stock datasets.

Tags

# what is the best academic dataset for returns of European stocks?


# what is the best academic dataset for returns of European stocks?












what is the best academic dataset for returns of European stocks? what are their identifiers? I know Factset. is there other datasets?

## Answer by user84893 (score 0)

https://quant.stackexchange.com/a/81407

My understanding if you want a very clean stock returns, it is better to calculate that from commercial data.

and this also depends on what return you want to calculate - such as price return, total return, cumulative return or log returns. Academic papers sometimes might have a different way to calculate returns to satisfy their own needs.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.