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Markov Switching Component ARCH Model: Stability and Forecasting
ARCH models Markov process Stability Component GARCH models Forecasting Bayesian inference Griddy Gibbs sampling
2013/4/28
This paper introduces an extension of the Markov switching ARCH model where the volatility in each state is a convex combination of two different ARCH components with time varying weights with differe...
A Functional Version of the ARCH Model
ARCH financial data functional time series high-frequency data weak-dependence
2011/6/16
Improvements in data acquisition and processing techniques have lead to an almost continuous
flow of information for financial data. High resolution tick data are available and can be quite convenien...
Mixing properties of ARCH and time-varying ARCH processes
2-mixing absolutely regular (β-mixing) ARCH(∞) conditional densities strong mixing (α-mixing) time-varying ARCH
2011/3/21
There exist very few results on mixing for non-stationary processes. However, mixing is often required in statistical inference for non-stationary processes such as time-varying ARCH (tvARCH) models. ...
The Cusum Test for Parameter Change in Regression Models with ARCH Errors
Brownian bridge regression models with ARCH errors residual cusum test test for parameter change weak convergence
2009/3/10
In this paper we consider the problem of testing for a parameter change in regression models with ARCH errors based on the residual cusum test. It is shown that the limiting distribution of the residu...
在金融时间序列分析中,检验ARCH效果和决定合适的阶是ARCH模型的重要研究主题,在贝叶斯框架下,本文使用贝叶斯因子来检验ARCH效果和选择ARCH模型合适的阶。在路径抽样的基础上,提出了计算ARCH模型贝叶斯因子的方法。最后,我们用一个具体的实例来论证了所提方法的有效性。