资讯

腾讯网4 个月
金融波动率的多模型建模研究：GARCH族与HAR模型的Python实现与对比分析
本文着重探讨三种主流波动率建模方法：广义自回归条件异方差模型(GARCH)、Glosten-Jagannathan-Runkle-GARCH模型(GJR-GARCH)以及异质自回归模型(HAR)。本文将 ...
新浪网3 个月
【华安证券·金融工程】专题报告：ETF的资产配置与再平衡：样本协 ...
主要比较了三种模型：（a）样本协方差或等权重模型，（b）指数加权移动平均（EWMA）模型，以及（c）广义自回归条件异方差（GARCH）（1,1 ...
新浪网2 个月
常见的预测波动率模型之GARCH模型
常见的预测波动率模型有EWMA模型和 GARCH模型等。 GARCH模型 自从Engle(1982)提出ARCH模型分析时间序列的异方差性以后，T.Boller-slev(1986)又提出了 ...
Risk4 年
Old-fashioned parametric models are still the best: a comparison of value-at-risk ...
We present backtesting results for 1% and 2.5% VaR of six indexes from emerging and developed countries using several of the best-known VaR models, including generalized autoregressive conditional ...
Risk9 年
Risk model validation for BRICS countries: a value-at-risk, expected shortfall and extreme ...
A family of generalized autoregressive conditional heteroscedasticity (GARCH) models, extreme value theory (EVT) and a dynamic bivariate technique are considered to demonstrate different volatility ...
Investopedia4 年
What Is the GARCH Process? How It's Used in Different Forms
Investopedia / Julie Bang The generalized autoregressive conditional heteroskedasticity (GARCH) process is an econometric term developed in 1982 by Robert F. Engle, an economist and 2003 winner of ...
Seeking Alpha11 年
Forecasting Volatility With GARCH
When we take the square root and annualize we have volatility. As we move closer to forecasting volatility with GARCH we need to observe a few characteristics of historical volatility. The first ...