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Erschienen in:
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2022 | OriginalPaper | Buchkapitel

12. An Overview of New Generation Bio-Inspired Algorithms for Portfolio Optimization

verfasst von : Hilal Arslan, Onur Uğurlu, Deniz Türsel Eliiyi

Erschienen in: The Impact of Artificial Intelligence on Governance, Economics and Finance, Volume 2

Verlag: Springer Nature Singapore

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Abstract

Bio-inspired computing is one of the foremost subfields of artificial intelligence, which aims to tackle complex optimization problems. The main advantage of bio-inspired algorithms over traditional methods is their searching ability. Portfolio selection is a popular optimization problem in economics and finance. It aims to find an optimal allocation of capital among a set of assets by maximization of return with simultaneous minimization of risk. Since the portfolio optimization problem is NP-hard, a large number of researchers have resorted to bio-inspired algorithms to deal with the computational complexity. This study provides an overview of the new generation bio-inspired algorithms from the recently published literature for portfolio optimization. Besides, opportunities for future research within this area discussed.

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Vorheriges Kapitel The Role of Artificial Intelligence in Health Care
Nächstes Kapitel The Effects of Artificial Intelligence on the Insurance Sector: Emergence, Applications, Challenges, and Opportunities
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Metadaten
Titel
An Overview of New Generation Bio-Inspired Algorithms for Portfolio Optimization
verfasst von
Hilal Arslan
Onur Uğurlu
Deniz Türsel Eliiyi
Copyright-Jahr
2022
Verlag
Springer Nature Singapore
Buch
The Impact of Artificial Intelligence on Governance, Economics and Finance, Volume 2

Print ISBN: 978-981-16-8996-3

Electronic ISBN: 978-981-16-8997-0

Copyright-Jahr: 2022

DOI
https://doi.org/10.1007/978-981-16-8997-0_12

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