A stable stock market is essential to the entire financial market and economy stressing the significance of monitoring the stability of the stock market. In this paper, we propose stock market stability index (SMSI), which monitors market stability through a statistical model. SMSI is based on the idea that the proper statistical model for the past stable period would significantly fail when the current market becomes unstable (see also Kim et al. ). To construct SMSI, the behavior of the regular stock market index on the past stable period is investigated with the asymptotic stationary autoregressive model (ASAR) proposed mainly for non-stationary time series by Kim et al. . Major advantage of this approach is to provide the probability (or p-value) of the current stock market's stability. As an empirical example, SMSI for the Korean stock market is developed in order to demonstrate its potential application.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Vision and Pattern Recognition
- Artificial Intelligence