Analysis of integration of financial series classification and constrained portfolio optimization

Diniz Campos Ferreira, FG; Gandomi, AH; Nogueira Cardoso, RT

Analysis of integration of financial series classification and constrained portfolio optimization

Diniz Campos Ferreira, FG Gandomi, AH Nogueira Cardoso, RT

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2022, 00
Issue Date:: 2022

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Field	Value	Language
dc.contributor.author	Diniz Campos Ferreira, FG
dc.contributor.author	Gandomi, AH
dc.contributor.author	Nogueira Cardoso, RT
dc.date	2021-12-05
dc.date.accessioned	2023-04-06T03:17:42Z
dc.date.available	2023-04-06T03:17:42Z
dc.date.issued	2022
dc.identifier.citation	2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2022, 00
dc.identifier.isbn	978-1-7281-9048-8
dc.identifier.uri	http://hdl.handle.net/10453/169291
dc.description.abstract	This paper proposes a new way of combining classification of financial asset price series and portfolio optimization, in which the optimization model has a constraint that ensures that the best rated assets in the classification process are present in the portfolio. This proposed combination is compared to each of the approaches applied separately. Trading simulation in the stock market using each of the strategies is carried out to evaluate the performance of each strategy, considering monthly performance metrics. Results show that portfolio optimization provides a lower risk, but classification shows great potential for a rapid increase in financial gain. The proposed combination manages to provide a greater gain than portfolio optimization, with a statistically equal risk, therefore, surpassing each of the individual approaches.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2021 IEEE Symposium Series on Computational Intelligence (SSCI)
dc.relation.ispartof	IEEE Symposium Series on Computational Intelligence
dc.relation.isbasedon	10.1109/ssci50451.2021.9660144
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Analysis of integration of financial series classification and constrained portfolio optimization
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Orlando, FL, USA
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2023-04-06T03:17:41Z
pubs.finish-date	2021-12-07
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2021-12-05
pubs.volume	00
dc.location	Piscataway, USA

Abstract:

This paper proposes a new way of combining classification of financial asset price series and portfolio optimization, in which the optimization model has a constraint that ensures that the best rated assets in the classification process are present in the portfolio. This proposed combination is compared to each of the approaches applied separately. Trading simulation in the stock market using each of the strategies is carried out to evaluate the performance of each strategy, considering monthly performance metrics. Results show that portfolio optimization provides a lower risk, but classification shows great potential for a rapid increase in financial gain. The proposed combination manages to provide a greater gain than portfolio optimization, with a statistically equal risk, therefore, surpassing each of the individual approaches.

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http://hdl.handle.net/10453/169291