However, these factor-based methods, although effective to some extent, simply rely on the correlation between the value of the index and limited number of exogenous variables (factors) and basically ignore the inherent rules of the variation of the time series. As a time series itself contains significant amount of information, often more than a limited number of factors can do, time series-based models are often more effective in the field of prediction than factor-based models.