SELECTION OF VARIABLES AND LEARNING PROCESS IN SECURITIES MARKET ANALYSIS WITH THE USE OF ARTIFICIAL NEURAL NETWORKS

• Authors: Kowerda G.
• Languages of publication: PL

Abstracts

EN

For the last ten (or so) years, Poland has seen the securities market grow steadily. Investment efficiency depends on many factors including the sort of information investors have. Choosing the adequate source of information is, for the most part, tantamount to success in investment. The most often used practical methods do not always provide the right responses as the results of analyses obtained by use of different methods do not often match the actual data. This has caused an increased interest in mathematical models, such as neural networks, as tools for analysis of financial time series. The use of artificial neural networks in capital market analyses may improve and accelerate the data processing which results in creation of additional information for investors and this becomes a key trump card in 'playing the market'. It is therefore reasonable to treat the neural networks as a complement of those methods.

Keywords

EN

NEURAL NETWORK IN CAPITAL MARKET; SECURITIES MARKET (POLAND)

Discipline

• ECONOMICS: ECONOMICS

• Journal: Optimum. Studia Ekonomiczne
• Year: 2008
• Issue: 2(38)
• Pages: 89-102
• Document type: ARTICLE

Contributors

author

Kowerda G.

• G. Kowerda, c/o Uniwersytet w Bialymstoku, Wydzial Ekonomii i Zarzadzania, ul. Warszawska 63, 15-062 Bialystok, Poland

Identifiers

CEJSH db identifier

08PLAAAA05039572