Publication:
Mining Stock Market Time Series and Modeling Stock Price Crash Using a Pretopological Framework.

datacite.subject.fos oecd::Natural sciences::Mathematics
dc.contributor.author Nguyễn Ngọc Kim Khánh
dc.date.accessioned 2022-11-09T11:30:10Z
dc.date.available 2022-11-09T11:30:10Z
dc.date.issued 2019
dc.description.abstract We introduce a computational framework, namely a pretopological construct, for mining time series of stock prices in a financial market in order to expand a set of stocks by adding outside stocks whose average correlations with the inside are above a threshold. The threshold is considered as a function of the set’s size to verify the effect of group impact in a financial crisis. The efficiency of this approach is tested by a consecutive expansion process started from a single stock of Merrill Lynch & Co., which had a large influence in the United State market during the studying time. We found that the ability to imitate the real diffusion process can be classified into three cases according to the value of \( \theta \) - a scaling constant of the threshold function. Finally, the process using pretopological framework is compared to a classical one, the minimum spanning tree of the corresponding stock network, showing its pertinence.
dc.identifier.doi 10.1007/978-3-030-28377-3_53
dc.identifier.isbn 9783030283766
dc.identifier.isbn 9783030283773
dc.identifier.uri http://repository.vlu.edu.vn:443/handle/123456789/1149
dc.language.iso en_US
dc.relation.ispartof Computational Collective Intelligence
dc.relation.ispartof Lecture Notes in Computer Science
dc.relation.issn 0302-9743
dc.relation.issn 1611-3349
dc.subject Pretopology theory
dc.subject Modeling of a stock market crash
dc.subject Computational intelligence
dc.title Mining Stock Market Time Series and Modeling Stock Price Crash Using a Pretopological Framework.
dc.type Resource Types::text::journal::journal article
dspace.entity.type Publication
oairecerif.author.affiliation #PLACEHOLDER_PARENT_METADATA_VALUE#
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