Abstract: Only distance factor is considered in the granular algorithm of granular support vector regression. Temporal factor was introduced simultaneously in granular algorithm. Hierarchical granular support vector regression based on distance and temporal factors(DTHGSVR) was proposed which is applicable for financial time series. The training samples were mapped into the high-dimensional space by mercer kernel， and the samples were divided into some granules initially. Then， the granules which have more regression information was found by measuring the distances between the granules and regression hyperplane and the granule’s temporal factor. By computing the radius， density of granules and the temporal factor， the deeper hierarchical granulation process was executed until no granules was needed to be granulated. Finally， those granules in different granulation levels were trained by SVR. Fund net was forecast by the hierarchical granular support vector regression based on distance and temporal factors. Experimental results showed the generalization performance of regression had been improved.

Key words: granular support vector regression, temporal;financial time series;forecasting;generalization