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1)  conditional variance
条件方差
1.
Dummy variable is introduced to TGARCH model so as to reflect simultaneously the asymmetry and week effect in waving of conditional variance,which is used to analyse waving of in the Shanghai and Shenzhen stock index.
在TGARCH模型中引入哑变量以同时反映条件方差波动的不对称性和星期特征,并运用其对沪深股指波动特征进行了实证分析。
2.
Based on the RV-ARMA model,it is discussed that the persistence of conditional variances has a effect on capital asset pric.
在“已实现”波动自回归移动平均模型基础上,从条件方差持续性的角度,讨论了条件方差的持续性对资产资本定价模型的影响。
3.
In this paper we firstly introduce the conceptions and the properties of conditional mean, conditional variance and the persistence of autoregressive conditional.
文章首先介绍了条件均值、条件方差以及在自回归条件异方差的基础上介绍了方差持续性的有关概念和性质,并将之用于资本资产定价模型的研究,讨论了条件方差持续性对资本资产定价模型的影响,并且进一步讨论了在多资产条件下向量GARCH模型持续性对组合投资的影响。
2)  conditional heteroscedasticity
条件异方差
1.
This model could better describe the conditional heteroscedasticity of the stock prices,and it was used to fit and forecast the prices of the stock.
通过对股票收盘价格的历史数据进行处理分析,建立GARCH模型,此模型较好的描述股票价格的条件异方差性,同时用此方法对股票价格进行拟合和预测,利用预测数据分析股票较好的买卖时机。
2.
The generalized autoregressive conditional heteroscedasticity (GARCH) model has the ability to describe the volatility of time series.
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。
3.
The shape changing feature of conditional distributions makes the MARMA model capable of modeling time series with asymmetric,multimodal distribution,and conditional heteroscedasticity,and so on.
该模型条件分布富于变化的特点使得它能够描述非对称、多峰、以及条件异方差等非Gauss特征。
3)  Conditional Heteroskedasticity
条件异方差
1.
In this paper, we discuss the existence of high order moment for a stable nonlinear autoregressive series, which satisfies nonlinear autoregressive model with conditional heteroskedasticity.
本文研究平稳非线性自回归序列的高阶矩的存在性问题,此序列满足带条件异方差的非线性自回归模型。
2.
This paper researches on the daily returns of Shanghai Stock Index and Shenzhen Component index, applies GARCH and TARCH models to analyze conditional heteroskedasticity and non-symmetry of the daily returns, and reveals the different volatility characteristics between the two stock indexes.
本文以上证综指和深成分指数的最新日收益率为研究对象,应用GARCH、TARCH模型理论,进一步分析了日收益率波动的条件异方差性、非对称性,同时比较了两个股票市场的不同波动特征。
3.
Autoregressive conditional heteroskedasticity process is a new stochastic process, which is used (extensively) to research time array and shows the characteristic of array variable along with time changing.
利用广义的自回归条件异方差模型,对中国银行间同业拆借利率随时间变化的特征进行了实证分析,发现加入结构转换变量的利率期限结构模型更适合描述中国金融市场上的利率行为特征。
4)  uncondional variance
无条件方差
5)  Conditional covariance
条件协方差
6)  conditional g-variance
条件g-方差
补充资料:并合方差
分子式:
CAS号:

性质:是按加权方式计算出的各组的共同方差,当试验分m组进行,总的测定方差s2由m组的方差si2(i=1,2, …,m)共同决定。总方差,式中ni、fi和xi;分别为第i组的测定次数、自由度和平均值,xij是第i组的第j次测定值。

说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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