因此，如何有效地刻画金融时间序列波动的动态行为一直是金融计量学研究的热点问题。

Therefore, how to describe the dynamic behavior of the financial time series' fluctuation well is always a hot research point in Financial Econometrics.

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广义自回归条件异方差(GARCH)模型具有描述时间序列波动性的能力。

The generalized autoregressive conditional heteroscedasticity (GARCH) model has the ability to describe the volatility of time series.

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研究了负荷时间序列波动性，考虑方差时变特征，提出了基于随机波动（SV）模型的短期负荷预测方法。

The volatility of load time series is analyzed, and the short-term load forecasting based on SV(Stochastic Volatility) models is presented with the consideration of the time-varying characteristics.

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