As the financial crisis which began in 2008 illustrates, the global stock markets influence each other. Forecasting changes in the stock market index has been an important subject for many years. In the past, data mining techniques were used to predict changes in the stock market index, but dependency of global stock market has not been seriously considered. In this paper we propose the analysis of association rule for predicting changes in the Korea Composite Stock Price Index (KOSPI) based on the time series data of various interrelated world stock market indices. According to the results of this study, the KOSPI tends to move in the same direction as the stock market indices in USA and Europe, whereas the KOSPI moves in a direction opposite to those in other East Asian countries, such as Hong Kong and Japan, which have a competitive relationship with Korea. This study is expected to facilitate effective investment decision making.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence