Modeling Cascading Failures in Stock Markets by a Pretopological Framework

Publication:

Modeling Cascading Failures in Stock Markets by a Pretopological Framework

datacite.subject.fos	oecd::Social sciences::Economics and Business
dc.contributor.author	Ngoc Kim Khanh Nguyen
dc.contributor.author	Marc Bui
dc.date.accessioned	2022-11-02T02:46:54Z
dc.date.available	2022-11-02T02:46:54Z
dc.date.issued	2020
dc.description.abstract	We introduce a computational framework, namely, a pretopological construct, for mining stock prices’ time series in order to expand a set of stocks by adding other stocks whose average correlations with the set are above a threshold. We increase the threshold with the set’s size to verify group impact in financial crises. This approach is tested by a consecutive expansion process started from a stock of Merrill Lynch & Co., and a consecutive contraction process of the rest. The test’s results and the comparison to graph theory show that our model and pretopology theory are helpful to study stock markets.
dc.identifier.doi	10.1142/S2196888821500019
dc.identifier.uri	http://repository.vlu.edu.vn:443/handle/123456789/630
dc.language.iso	en_US
dc.relation.ispartof	Vietnam Journal of Computer Science
dc.relation.issn	2196-8888
dc.relation.issn	2196-8896
dc.subject	Pretopology theory
dc.subject	modeling stock market crash
dc.subject	computational intelligent
dc.title	Modeling Cascading Failures in Stock Markets by a Pretopological Framework
dc.type	journal-article
dspace.entity.type	Publication
oaire.citation.issue	01
oaire.citation.volume	08

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