Data Mining on Romanian Stock Market Using Neural Networks for Price Prediction

Informatică economică

关键词: Data Mining;    Neural Networks;    MLP;    Multi-agent System;    Majority Voting;    Time series Forecasting;   

DOI  :  10.12948/issn14531305/17.3.2013.11

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown