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Review

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

by
Chia-Lin Chang
1,
Michael McAleer
2,3,4,5,6,* and
Wing-Keung Wong
7,8,9,10
1
Department of Applied Economics and Department of Finance, National Chung Hsing University, Taichung 40227, Taiwan
2
Department of Finance, Asia University, Taichung 41354, Taiwan
3
Discipline of Business Analytics, University of Sydney Business School, Sydney, NSW 2006, Australia
4
Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, 3062 PA Rotterdam, The Netherlands
5
Department of Economic Analysis and ICAE, Complutense University of Madrid, 28223 Madrid, Spain
6
Institute of Advanced Sciences, Yokohama National University, Yokohama 240-8501, Japan
7
Department of Finance, Fintech Center, and Big Data Research Center, Asia University, Taichung 41354, Taiwan
8
Department of Medical Research, China Medical University Hospital, Taichung 40447, Taiwan
9
Department of Economics and Finance, Hang Seng Management College, Hong Kong, China
10
Department of Economics, Lingnan University, Hong Kong, China
*
Author to whom correspondence should be addressed.
J. Risk Financ. Manag. 2018, 11(1), 15; https://doi.org/10.3390/jrfm11010015
Submission received: 4 February 2018 / Revised: 7 March 2018 / Accepted: 13 March 2018 / Published: 20 March 2018
(This article belongs to the Special Issue Review Papers for Journal of Risk and Financial Management (JRFM))
Versions Notes

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 big data; computational science; economics; finance; management; theoretical models; econometric and statistical models; applications

Share and Cite

MDPI and ACS Style

Chang, C.-L.; McAleer, M.; Wong, W.-K. Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections. J. Risk Financ. Manag. 2018, 11, 15. https://doi.org/10.3390/jrfm11010015

AMA Style

Chang C-L, McAleer M, Wong W-K. Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections. Journal of Risk and Financial Management. 2018; 11(1):15. https://doi.org/10.3390/jrfm11010015

Chicago/Turabian Style

Chang, Chia-Lin, Michael McAleer, and Wing-Keung Wong. 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections" Journal of Risk and Financial Management 11, no. 1: 15. https://doi.org/10.3390/jrfm11010015

APA Style

Chang, C.-L., McAleer, M., & Wong, W.-K. (2018). Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections. Journal of Risk and Financial Management, 11(1), 15. https://doi.org/10.3390/jrfm11010015

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