data mining on romanian stock market using neural networks for price prediction

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ID: 213697
2013
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Abstract
Predicting future prices by using time series forecasting models has become a relevant trading strategy for most stock market players. Intuition and speculation are no longer reliable as many new trading strategies based on artificial intelligence emerge. Data mining represents a good source of information, as it ensures data processing in a convenient manner. Neural networks are considered useful prediction models when designing forecasting strategies. In this paper we present a series of neural networks designed for stock exchange rates forecasting applied on three Romanian stocks traded on the Bucharest Stock Exchange (BSE). A multistep ahead strategy was used in order to predict short-time price fluctuations. Later, the findings of our study can be integrated with an intelligent multi-agent system model which uses data mining and data stream processing techniques for helping users in the decision making process of buying or selling stocks.
Reference Key
nemes2013informaticdata Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Magdalena Daniela NEMES;Alexandru BUTOI
Journal fuel
Year 2013
DOI
10.12948/issn14531305/17.3.2013.11
URL
http://revistaie.ase.ro/content/67/11%20-%20Nemes,%20Butoi.pdf
Keywords
Data mining neural networks multi-agent system mlp information resources library science

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