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Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections

Chia-Lin Chang (), Michael McAleer and Wing-Keung Wong ()

Journal of Risk and Financial Management, 2018, vol. 11, issue 1, 1-29

Abstract: The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses research issues that are related to the various disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models, as well as conduct simulation to examine whether the estimators in their theories on estimation and hypothesis testing have good size and high power. Thereafter, academics and practitioners could apply theory to analyse some interesting issues in the seven disciplines and cognate areas.

Keywords: big data; computational science; economics; finance; management; theoretical models; econometric and statistical models; applications (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2018
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Related works:
Working Paper: Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections (2018) Downloads
Working Paper: Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections (2018) Downloads
Working Paper: Big data, computational science, economics, finance, marketing, management, and psychology: connections (2018) Downloads
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