Financial Asset Management Using Artificial Neural Networks
- Resource Type
- Authors
- Dustin Shane Lynch; Gary R. Weckman; Azadeh Sadeghi; William A. Young; Roohollah Younes Sinaki
- Source
- International Journal of Operations Research and Information Systems. 11:66-86
- Subject
- 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
- Language
- ISSN
- 1947-9336
1947-9328
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.