Bayesian network is the graphical model which can represent the stochastic dependency of the random variables via the acyclic directed graph. In this study, 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. Their accuracy comparison shows that the average correction rate of the present algorithm is almost 60%, which is almost equal or higher than them of the traditional algorithms such as the psychological line (50-59%) and the trend estimation (50-52%). Moreover, the vertical trading results reveal that the profit of the present algorithm is much greater than the others. Keywords: Bayesian network, stock index, K2 algorithm, K2 metric, psychlogical line, trend estimation Day trading refers to the practice of buying and selling financial instruments within the same trading day such that all positions are usually closed before the market close for the trading day. Traders who participate in day trading are simply called day traders. Some of the more commonly day-traded financial instruments are stocks, stock options, currencies, and a host of futures contracts such as equity index futures, interest rate futures, and commodity futures. In the day trading of the stock indexes, the most important information for the day trader is not the exact future stock price but the up/down information of the future stock price. In this study, Bayesian network is applied for the up/down analysis of the stock index.
REF presented a Bayesian network technique to predict the up/down analysis of the daily stock indexes and the result were compared with the psychological line and trend estimation technical analyses.
Up/Down Analysis of Stock Index by Using Bayesian Network
Engineering Management Research
Economics