Neural Networks in Investments Essay -- Computers Technology Investing

skittish Networks in InvestmentsI. ABSTRACTInvestment managers often find themselves overwhelmed with the large amount of data obtained from the monetary markets. Most of the data available is numeric and noisy in nature, making the decision-making process harder. These decisions usually rely on the integration of statistical measures that attempt to iron much of the data and qualitative depictions such as graphs and bar charts with news events and other pertinent information. Investment decisions usually involve non-linear relationships among the various components of the data. Computers in general, argon very adept at dealing with large amounts of numeric information. However, some algorithms are crucial in analyzing and combining disparate information that can feign security prices. Artificial Intelligence based methods uses clever algorithms and rules of thumb (heuristics) in the decision-making process. neuronic Network and expert systems applications have been successfully deployed in the domain of Finance, and in the area of investment management.This paper discusses the basics and the theory behind neural networks and provides an introduction to an application area of neural networks in the domain of Finance. The application areas of queasy Networks discussed in the paper are corporate finance, financial institutions, and the professional investor. The purpose of the second paper will be to discuss the specifics of each of these applications.II. INTRODUCTIONNeural network computing is an information processing method that was developed from research to make computers that could imitate the way people learned. The field initially grew from 1930s ideas astir(predicate) how biological systems like the human brain works... ...in of finance is essential for further development.V. REFERENCES 1. Deboeck Guido J., Trading on the Edge Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets, John Wiley & Sons Inc., 1994. 2. Trippi Robert R., lee(prenominal) Jae K., State-of-the-Art Portfolio Selection Using Knowledge Based Systems to Enhance Investment Performance, Probus Publishing Company, 1992. 3. Refenes Paul, Neural Networks in the Capital Markets, John Wiley & Sons Inc., 1995. 4. Proceedings of the Second supranational Conference on Artificial Intelligence Applications on Wall Street, April 19-22 1993, New York City. 5. Neural Network Resources on the World Wide Web, http//www.med-web.com/nnres/ 6. Neural Network Toolbox, http//www.mathworks.com/products/neuralnet/ 7. Neural Network WWW References, http//ftp.funet.fi/pub/sci/neural/www/www-catalogue.html