Title of article :
Stock price forecast using Bayesian network
Author/Authors :
Zuo، نويسنده , , Yi and Kita، نويسنده , , Eisuke، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
Bayesian network is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph. This paper describes the price earnings ratio (P/E ratio) forecast by using Bayesian network. Firstly, the use of clustering algorithm transforms the continuous P/E ratio to the set of digitized values. The Bayesian network for the P/E ratio forecast is determined from the set of the digitized values. NIKKEI stock average (NIKKEI225) and Toyota motor corporation stock price are considered as numerical examples. The results show that the forecast accuracy of the present algorithm is better than that of the traditional time-series forecast algorithms in comparison of their correlation coefficient and the root mean square error.
Keywords :
Stock Price , Bayesian network , Uniform clustering , ward method
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications