Canadian Center of Science and Education
Bayesian network is the graphical model which can represent the stochastic dependency of the random variables via the acyclic directed graph. In this paper, Bayesian network is applied for the up/down analysis of the stock index. The up/down rates of the daily stock indexes in three major markets are taken as the network nodes and then, the network is determined by K2 algorithm with the K2 metric as the prediction accuracy of the network. The present algorithm is applied for predicting the up/down analysis of the daily stock indeies in 2007 and the results are compared with the traditional algorithms; Psychological line and trend estimation, which are popular algorithms which are well-known by the traders.