应用自回归条件异方差模型研究我国水力发电量

Hydropower Generating Capacity Forecasting Based on Auto-Regressive Conditional Heteroskedasticity Model

为了研究水力发电量条件方差的变化规律及残差的统计分布特征,引入自回归条件异方差模型,建立基于正态分布假设的同阶自回归条件异方差模型对我国2001年1月到2016年2月的水力发电量进行实证分析,研究得出该模型对发电量的估计与预测具有良好的效果。

The regularity of conditional variance variation and the statistical distribution characteristic of residual error of hydropower generating capacity（hgc） in hydropower market are researched. On this basis, by means of leading in the generalized auto-regressive conditional heteroskedasticity （GARCH） model, a GARCH model based on the Normal distribution is proposed to research the variation regularity of HGC. Taking the actual data from HGC market in China as samples, both GARCH model and the proposed GARCH model are tested. The testing results show that the GARCH model can offer good estimation and forecasting results of HGC.