Financial Asset Management Using Artificial Neural Networks

Roohollah Younes Sinaki, Azadeh Sadeghi, Dustin S. Lynch, William A. Young and Gary R. Weckman
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Roohollah Younes Sinaki: Ohio University, USA
Azadeh Sadeghi: Ohio University, USA
Dustin S. Lynch: Ohio University, USA
William A. Young: Ohio University, USA
Gary R. Weckman: Ohio University, USA

International Journal of Operations Research and Information Systems (IJORIS), 2020, vol. 11, issue 3, 66-86

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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:igg:joris0:v:11:y:2020:i:3:p:66-86

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