Explainable artificial intelligence enhanced quantum-inspired spider monkey optimization for a constrained portfolio optimization proble

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10260212" target="_blank" >RIV/61989100:27240/25:10260212 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s42484-025-00338-5" target="_blank" >https://link.springer.com/article/10.1007/s42484-025-00338-5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s42484-025-00338-5" target="_blank" >10.1007/s42484-025-00338-5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Explainable artificial intelligence enhanced quantum-inspired spider monkey optimization for a constrained portfolio optimization proble

Popis výsledku v původním jazyce

Optimizing portfolios has consistently posed significant challenges while being an extensively researched subject in finance and accounting. This process requires selecting and distributing appropriate assets in alignment with a set of specified objectives. This nonlinear constraint issue is not effectively solvable using traditional methods. This paper investigates the use of spider monkey optimization, ageist spider monkey optimization, and a newly proposed enhanced spider monkey optimization technique for portfolio optimization problems. The explainability of the spider monkey optimization has been improved without compromising the optimization results. It has been observed that the proposed technique marginally enhances the results of spider monkey optimization and can improve trust and risk management in the portfolio optimization problem. Furthermore, a quantum-inspired version of the proposed method is also implemented, and the results are compared using three benchmarked datasets from Dow Jones, BSE, and NASDAQ. Experimental results obtained using these benchmark datasets demonstrate that the newly introduced technique within the quantum-inspired framework marginally outperforms all other methods in the classical and quantum-inspired domains. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

Název v anglickém jazyce

Explainable artificial intelligence enhanced quantum-inspired spider monkey optimization for a constrained portfolio optimization proble

Popis výsledku anglicky

Optimizing portfolios has consistently posed significant challenges while being an extensively researched subject in finance and accounting. This process requires selecting and distributing appropriate assets in alignment with a set of specified objectives. This nonlinear constraint issue is not effectively solvable using traditional methods. This paper investigates the use of spider monkey optimization, ageist spider monkey optimization, and a newly proposed enhanced spider monkey optimization technique for portfolio optimization problems. The explainability of the spider monkey optimization has been improved without compromising the optimization results. It has been observed that the proposed technique marginally enhances the results of spider monkey optimization and can improve trust and risk management in the portfolio optimization problem. Furthermore, a quantum-inspired version of the proposed method is also implemented, and the results are compared using three benchmarked datasets from Dow Jones, BSE, and NASDAQ. Experimental results obtained using these benchmark datasets demonstrate that the newly introduced technique within the quantum-inspired framework marginally outperforms all other methods in the classical and quantum-inspired domains. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Quantum Machine Intelligence

ISSN

2524-4906

e-ISSN

—

Svazek periodika

7

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

38

Strana od-do

nestránkováno

Kód UT WoS článku

001615775000002

EID výsledku v databázi Scopus

2-s2.0-105022056733