2026-06-08T01:06:06Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/174122023-08-11T07:26:30Zcom_20.500.14352_14col_20.500.14352_17
Docta Complutense
author
Chang, Chia-Lin
author
McAleer, Michael
author
Wong, Wing-Keung
2023-06-17T17:53:26Z
2023-06-17T17:53:26Z
2018
2341-2356
https://hdl.handle.net/20.500.14352/17412
https://www.ucm.es/icae
The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses some research that is related to the seven 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.
eng
Atribución-NoComercial-CompartirIgual 3.0 España
Big data, computational science, economics, finance, marketing, management, and psychology: connections
technical report
URL
https://docta.ucm.es/bitstreams/bde92b66-1edb-4feb-a7e9-e253c798c870/download
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application/pdf
1805.pdf
URL
https://docta.ucm.es/bitstreams/12d2e303-5a36-4338-9013-50044fdb1684/download
File
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1805.pdf.txt