...据的尖峰厚尾性和波动集群性，Engle 于1982 年首次提出自 回归条件异方差模型（Autoregressive conditional heteroskedasticity, ARCH）。
基于2个网页-相关网页
自回归条件异方差模型 ARCH ; Autoregressive Conditional Heteroskedasticity ; Autoregressive Conditional Heteroskedasticity Model
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.
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.
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.
应用推荐