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1)  generalized autoregressive conditional heteroscedasticity (GARCH)
广义自回归条件异方差(GARCH)
2)  GARCH
广义自回归条件异方差模型(GARCH)
3)  GARCH
广义自回归条件异方差
1.
This paper estimated the hedge ratios of crude oil futures at four kinds of models: ordinary least square(OLS),Bivariate-vector autoregression(B-VAR),error correction model(ECM) and ECM-GARCH model,then compared the hedging performances obtained from different models.
本文利用普通最小二乘法(OLS)、双变量向量自回归(B-VAR)、误差修正(ECM)和广义自回归条件异方差结合误差修正(ECM-GARCH)4个模型和套期保值绩效的衡量指标,对原油期货的套期保值比率和绩效进行实证研究。
2.
The regime switching model is combined with generalized autoregressive conditional heteroskedasticity(GARCH) model to analyse empirically Shanghai stock index and Shenzhen constituent index,to capture the characteristics of regime shifts and volatility persistence in China′s stock market and to solve pseudo-persistence in sigle-regime GARCH model.
将体制转换模型与广义自回归条件异方差(GARCH)模型相结合,用以对上证综合指数和深圳成分指数进行实证分析。
3.
In this article,the two tools were combined to compute VAR,then draw a conclusion that the MC-GARCH-VAR is better than others.
分别用样本标准差和广义自回归条件异方差(GARCH)作为参数代入几何布朗运动方程中,并把计算结果进行比较,得出各模型的适用范围。
4)  generalized autoregressive conditional(heteroscedasticity)(GARCH)
广义自回归条件方差
5)  GARCH
广义自回归条件异方差模型
1.
Bsaed on the mathematical inference with the mixture of distribution hypothesis(MDH) theory,we take the stock index of Shanghai and Shenzhen markets as the research object and introduce the real trading volume and the trading volume considering the autocorrelation and the day-ofthe-week effect into the generalized autoregressive conditional heteroskedasticity(GARCH) model.
基于分布混合假说(MDH)理论的数学推导,以我国深沪股市的大盘指数为研究对象,检验原始交易量、包含自相关性的交易量对广义自回归条件异方差模型(GARCH)效应的解释效果,并分析日历效应对交易量与股价波动性关系的特殊影响。
6)  mixture generalized autoregressive conditional heteroscedastic model
混合广义自回归条件异方差模型
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