Financial Asset Management Using Artificial Neural Networks
| Autor: | Dustin Shane Lynch, Gary R. Weckman, Azadeh Sadeghi, William A. Young, Roohollah Younes Sinaki |
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| Rok vydání: | 2020 |
| Předmět: |
Finance
Information Systems and Management Artificial neural network Computer Networks and Communications Financial asset business.industry Asset allocation 02 engineering and technology Investment (macroeconomics) Computer Science Applications Management Information Systems Investment portfolio 020303 mechanical engineering & transports 0203 mechanical engineering Computational Theory and Mathematics Stock market crash 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Business Information Systems |
| Zdroj: | International Journal of Operations Research and Information Systems. 11:66-86 |
| ISSN: | 1947-9336 1947-9328 |
| DOI: | 10.4018/ijoris.2020070104 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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