摘要：Saudi Basic Industries Corporation (SABIC) is one of the largest industrial entity producing different types of products in Saudi Arabia. The share price of these products affects the price structures in the local as well as in the international market. The main purpose of this research was to investigate the role of two classification methods, i.e. Linear Discriminant Analysis (LDA) and the Logit Model (LM), for predicting day-to-day Up/Down direction of SABIC, the largest stock company on the Saudi Stock Exchange (SSE). These two widely used statistical techniques were chosen as the first trial involving the SSE. The study utilized both the technical (historical price and volume) and fundamental data (Dow Jones Index, Oil Price and Saudi stock index). The results were back-tested for both in- and out-of-sample data with hit rate criterion. The correct prediction ranged from 54.7-59.2%. Analysis of classification tables revealed different distribution of errors for linear discriminant analysis and logistic regression. Walds test showed that predictions from both the models differ from the original data.
