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

Chang, Chia‐Lin; McAleer, Michael; Wong, Wing‐Keung

doi:10.2139/ssrn.3117386

Cited by 15 publications

(6 citation statements)

References 165 publications

(123 reference statements)

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“…Although we have discussed many studies on market efficiency and anomalies, there are still many theoretical contributions in other areas that could also be useful to explain and interpret market efficiency and anomalies. Readers may refer to Chang et al (2016aChang et al ( , 2016bChang et al ( , 2016cChang et al ( , 2017Chang et al ( , 2018 for contributions in other cognate areas that might be useful in theory and practice that related to market efficiency and anomalies. Finally, we note that this review is useful to academics for their studies in EMH, anomalies, and Behavioral Finance; useful to investors for their decisions on their investment; and useful to policy makers in reviewing their policies in stock markets.…”

Section: Discussionmentioning

confidence: 99%

Efficiency and Anomalies in Stock Markets

2022

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Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. About the EditorProfessor Wing-Keung Wong obtained his Ph.D. from the University of Wisconsin-Madison, the USA with a major in Business Statistics (Statistics and Finance) and obtained his Bachelor degree from the

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Section: Discussionmentioning

confidence: 99%

Efficiency and Anomalies in Stock Markets

2022

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“…Finally, we note that, although all of the propositions and corollaries developed in our paper are relatively easy to derive, all the results developed in our paper are useful to both academics and practitioners because there is a wide range of applications with variables that have a negative range. Readers may refer to (Chang et al 2016(Chang et al , 2018a(Chang et al , 2018b(Chang et al , 2018cChang et al 2015;) for more information on the applications in different areas.…”

Section: Discussionmentioning

confidence: 99%

Mathematical Finance with Applications

Wong¹,

Guo²,

Lozza³

2020

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“…Chang, McAleer, and Wong (2017b) apply the theoretical models and econometric and statistical models to big data, computational science, economics, finance and management. Academics and practitioners could apply their theories to other financial economic problems.…”

Section: Applications In Economics and Financementioning

confidence: 99%

“…Interested readers may wish to refer to Chang, McAleer, and Wong (2017b) for a discussion as to why analysing big data is different from analyzing medium data or small data.…”

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confidence: 99%

Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections

2018

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This paper provides a review of some connecting literature in Decision Sciences, Economics, Finance, Business, Computing, and Big Data. We then discuss some research that is related to the six cognate disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models. Moreover, they could then conduct simulations to examine whether the estimators or statistics in the new theories on estimation and hypothesis have small size and high power. Thereafter, academics and practitioners could then apply their theories to analyze interesting problems and issues in the six disciplines and other cognate areas. KeywordsDecision sciences, economics, finance, business, computing, and big data, theoretical models, econometric and statistical models, applications. JEL Classification AbstractThis paper provides a review of some connecting literature in Decision Sciences, Economics, Finance, Business, Computing, and Big Data. We then discuss some research that is related to the six cognate disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models. Moreover, they could then conduct simulations to examine whether the estimators or statistics in the new theories on estimation and hypothesis have small size and high power. Thereafter, academics and practitioners could then apply their theories to analyze interesting problems and issues in the six disciplines and other cognate areas.

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

Abstract: trabajo-del-icaeWorking papers are in draft form and are distributed for discussion. It may not be reproduced without permission of the author/s.

Cited by 15 publications

References 165 publications

Efficiency and Anomalies in Stock Markets

Efficiency and Anomalies in Stock Markets

Mathematical Finance with Applications

Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections

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