Special Issue "Big Data in Economics and Finance"
A special issue of Econometrics (ISSN 2225-1146).
Deadline for manuscript submissions: closed (31 May 2019).
Interests: financial time series analysis; risk management; market risk; systemic risk; univariate and multivariate volatility models; quantitative portfolio allocation strategies; managed portfolios performance measurement; high-frequency data analysis and trading strategies; dynamic models for energy and weather applications
Special Issues and Collections in MDPI journals
Interests: financial econometrics; forecasting; empirical finance and applied econometrics; bid data econometrics and high-dimensional econometrics
Interests: applied econometrics; empirical macroeconomics; big data; sport economics
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
Manuscript Submission Information
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- Big data