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.
本文通过自回归条件异方差(ARCH)模型证明了亚洲金融危机后中国汇市在干预下的弹性。
This paper proves the elasticity of China's exchange market under interference after the Asian financial crisis by adopting Autoregressive Conditional Heteroscedasticity (ARCH) model.
因此，评估可由广义自回归条件异方差(GARCH模型)，这可能使避险比率意味着出随时间变化。
Therefore, evaluation could be carried out by means of Generalized Autoregressive Conditional Heteroscedasticity (GARCH), which could make hedge ratio vary with time.
通过对上证指数的统计分析表明，上证指数的收益率分布表现出非正态性，并存在自回归条件异方差的特征。
According to statistical analysis on Shanghai stock index, the distribution of the rate of return is non-positive skewed, and there exists an autoregressive heteroskedasticity in the rate of return.
通过对我国股价指数的统计描述，表明我国金融资产收益率存在自回归条件异方差特征，并表现出非正态性。
Statistic descriptions indicate that the benefit of financial capitals in China has the characteristic of autoregressive conditional heteroskedasticity and abnormality.
然后，利用自回归条件异方差模型系统研究了我国封闭式基金市场的价格波动特性，分析了基金市场的风险特征。
Then, it studies the characteristic of price volatility and risk in closed-end securities investment fund market by use of ARCH models.
股票价格的频繁波动是股票市场最明显的特征之一，自回归条件异方差类模型可以很好地预测金融资产收益率的方差。
Frequent volatility is a feature of stock market. Autoregressive Conditional Heteroscedasticity (ARCH) model is often used to forecast the variance of the benefit of financial capitals.
以市场换手率度量交易量，采用自回归广义自回归条件异方差（AR-GARCH）模型研究了中国股市交易量的时间系列。
The turnover was used to measure the trading volume which was analyzed using the Autoregressive- Generalized Autoregressive Conditional Heteroskedasticity (AR- GARCH) model.
本文分两节对门限自回归模型中自回归条件异方差的广义谱密度检验进行了讨论。在第一节中，我们介绍了广义谱密度检验。
This thesis is composed of two sections in which we discuss generalized spectral density test of conditional autoregressive heteroscedasticity for threshold autoregressive model.
本文分两节对门限自回归模型中自回归条件异方差的广义谱密度检验进行了讨论。在第一节中，我们介绍了广义谱密度检验。
This thesis is composed of two sections in which we discuss generalized spectral density test of conditional autoregressive heteroscedasticity for threshold autoregressive model.
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