Financial Asset Management Using Artificial Neural Networks

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Author(s): Roohollah Younes Sinaki (Ohio University, USA), Azadeh Sadeghi (Ohio University, USA), Dustin S. Lynch (Ohio University, USA), William A. Young II (Ohio University, USA)and Gary R. Weckman (Ohio University, USA)
Copyright: 2022
Pages: 22
Source title: Research Anthology on Artificial Neural Network Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-2408-7.ch066

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science Reference / Neural Networks

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Abstract

Investors typically build portfolios for retirement. Investment portfolios are typically based on four asset classes that are commonly managed by large investment firms. The research presented in this article involves the development of an artificial neural network-based methodology that investors can use to support decisions related to determining how assets are allocated within an investment portfolio. The machine learning-based methodology was applied during a time period that included the stock market crash of 2008. Even though this time period was highly volatile, the methodology produced desirable results. Methodologies such as the one presented in this article should be considered by investors because they have produced promising results, especially within unstable markets.

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Financial Asset Management Using Artificial Neural Networks

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