Besides, GARCH model could solve the problem of the clustered rate of return.
对于收益率簇集性的特点，GARCH模型很好得解决了这个问题。
First, get the equity return's conditional standard volatility by GARCH model;
首先，利用GARCH模型求得权益收益的条件标准差；
Finally, this paper USES GARCH model regressing the portfolio return time series.
文章最后用GARCH模型对组合收益率时间序列进行了模拟。
The results show that the GARCH model can be a good fit to the weekly return series of Shenzhen Stock Index.
结果表明，深证成指周收益率序列的波动性可以用GARCH模型进行很好的拟合。
The results show the method of calculation VaR of GARCH model is effective in risk management of China's stock market.
实证研究表明，GARCH模型的V aR计算方法对我国股市风险的管理有较好的效果。
The paper makes use of Granger causality test and GARCH model to tests the return spillover and volatility spillover effect.
本文将利用两步法的GARCH模型对股票市场和权证市场的均值溢出和波动溢出进行检验。
Out-of-sample returns and risks in other sections show that portfolio hedging MS-DCC-GARCH model used by bank has better performance.
外显示样品返回和在其他章节的风险投资组合对冲的MS -催化裂解-GARCH模型的银行具有更好的性能使用。
To verify hedging statistic significance, this paper USES DM test to know which kind of GARCH model is the best hedging model for Banks.
为了验证对冲统计学意义，本文采用德国马克测试知道哪个GARCH模型，就是最好的避险模型银行。
The paper applies GARCH model to forecast stock volatility in Chinese stock markets. The conclusion reveals that the model predicts well.
应用GARCH模型对我国股票波动率进行应用预测分析，结果表明模型对波动率进行了很好的预测。
Therefore, from Table 11 we know that bank enjoys better hedging performance while using portfolio hedging MS-DCC-GARCH model but not others.
因此，从表11我们知道，银行享有更好的性能，同时利用组合套期保值对冲的MS -催化裂解-GARCH模型而不是其他人。
Based on this conclusion, the authors set up an AR-GARCH model of issuing scale of national debt. This model has high accuracy and strong capacity of prediction.
据此基本结论建立的国债发行规模的AR - GARCH模型精度高，有很强的预测功能。
In this article, the author concerned with a better description of the volatility and correlations under multivariate GARCH model compared with univariate GARCH model.
在这篇文章里，笔者主要关注当同时考察多支金融时间序列的波动时，多元GARCH模型相比于一元GARCH模型而言，对相关系数和波动性的更好的描述。
Then the movement feature of the market is analyzed with the GARCH model, and whether the market return follows non-linear and leptokurtic heavy tail feature is validated.
文章还采用GARCH模型对市场的运行特征做了分析，对市场收益率是否服从非线性和尖峰胖尾的特征进行验证。
By the tools, volatility and GARCH model, this chapter chooses the stock market of Taiwan and Japan as the study objects to test the effect of introducing stock index futures.
运用波动率和GARCH模型两个工具，结合所获得数据的具体情况对日本和台湾进行实证分析，分析股指期货推出前后股票现货市场的波动情况。
First of all, the author discusses the extension from univariate GARCH to multivariate GARCH model and the important role of the MGARCH model in the modern financial research.
笔者首先讨论了在金融时间序列的考察中从一元GARCH模型扩展到多元GARCH模型的必要性。分析了多元GARCH模型在金融建模中的重要作用。
In particular, it has been demonstrated that the conventional GARCH model can exaggerate volatility persistence compared to the (true) volatility process perceived by the market.
特别是，相对于被市场所发现的真实波动过程来说，传统的GARCH模型夸大了波动的持续性。
The results show that the model is instability in the long run, most coefficient is non-stationary, and we can preferably forecast the coefficient by using the ARMA, GARCH model.
结果表明三因素模型结构不稳定，但短期比长期结构稳定性要高；大部分组合回归系数时序稳定性较差，同时ARMA和GARCH模型对每个回归系数时间序列进行预测显示有较好的预测能力。
This article USES data from Shanghai a type stock market and originally measures the conditional expectation of correlation risk and idiosyncratic volatility by DCC-MV GARCH model.
本文采用上海A股市场的月收益率数据，率先使用DCC - MVGARCH模型，刻画了时变的个股间预期条件相关性和个股的预期条件特质波动率。
The paper constructs market confidence index and market activity index, and then analyzes the relations of these information variables and the volatility by dint of GARCH-M model.
在构建市场信心指数和市场活跃指数的基础上，借助于GARCH-M模型对市场的信息变量与波动性的关系进行研究。
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。
High-level ARCH effect is certification in the BDI logarithm process by ARCH LM test, GARCH(1,1)model is used to eliminate the conditional heteroscedasticity.
通过ARCHLM检验认为BD I对数序列存在高阶ARCH效应，并用GARCH（1，1）模型消除残差序列的条件异方差性。
Then we test the relation between expected returns and expected risk with the GARCH-M model.
然后，应用均值GARCH (GARCH - M)模型检验预期收益与预期风险的关系。
This paper simulates the volatility of Shanghai stock index by ARCH Models and the result shows that GARCH (1, 1) model is effective in the simulation of the volatility of Shanghai stock index.
利用ARCH类模型对上证指数的波动进行了拟合，结果表明GARCH（1，1）模型对上证指数波动具有较好的拟合效果。
The turnover was used to measure the trading volume which was analyzed using the Autoregressive- Generalized Autoregressive Conditional Heteroskedasticity (AR- GARCH) model.
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。
Future price model is introduced based on the model of EWMA and GARCH, which offers a new computing method for the determination of the future markets.
在EWMA和GARCH模型思想的基础上，提出基于GARCH - EWMA的期货价格预测模型，为期货市场合约价格的预测提供新的预测方法。
As to the estimating process of GARCH (1, 1) model, the author adopted Maximum Likelihood Estimation and BHHH algorithm to get unknown parameters' value.
至于GARCH(1,1)模型的估计过程，本文用最大似然估计法和BHHH算法求未知参数值。
As to the estimating process of GARCH (1, 1) model, the author adopted Maximum Likelihood Estimation and BHHH algorithm to get unknown parameters' value.
至于GARCH(1,1)模型的估计过程，本文用最大似然估计法和BHHH算法求未知参数值。
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