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Big Data in Economics and Finance

Special Issue Information

Dear Colleagues,

Big data is en vogue. What it actually is, however, appears to differ from field to field, and even from practitioners within fields. Ever increasing computer power and storage has enabled increasingly large datasets to be analysed. This has allowed some age old questions to be answered, but equally has made apparent the reality that standard issues of statistical inference remain writ large even with big data. It has also required the development of new methods to analyse sufficiently large datasets; indeed one definition of big data is that it must entail this.

This Special Issue focusses on big data in economics and finance. In particular, how big data applications have developed, the kinds of questions that have been better answered using big data, and the kinds of challenges that remain to be overcome. In economics, we think of large social media and public sector databases being made available, alongside the more proprietary datasets such as those collected by supermarkets on customers. In finance, big data seems to fit most naturally when dealing with trade and quotes data, which update on a millisecond basis and can be easily integrated with news and social media tweets.

Prof. Dr. Massimiliano Caporin
Dr. Juri Marcucci
Dr. J. James Reade
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Econometrics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Big data
  • econometrics
  • statistics
  • finance
  • inference

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Econometrics - ISSN 2225-1146