摘要
ARCH模型为最近15年里发展起来的关于时间序列的模型.由于它反映了随机过程的一种特殊特性:方差随时间而变化,从而在金融市场预测和决策中取得了显著成果.本文在分析金融市场数据特性的基础上,较为详细地介绍了ARCH模型的形式与分类、参数估计和模型假设检验等若干理论问题,并适当地探讨了ARCH模型在金融市场研究中的应用前景.
ARCH model, Autoregressive conditional heteroskedasticity, is a model for time sequence analysis which developed after 1982. In this paper, on the analysis of data character in finance markets, we present detaily the form and classes of ARCH, and its parameter estimation, hopothesis test, and some others theories. According to this discussion, we have approached the application foreground of ARCH model in finance markets preseach.
出处
《系统工程》
CSCD
1997年第1期43-46,29,共5页
Systems Engineering
基金
国防预研基金部份资助
关键词
金融
预测
ARCH
金融市场
条件异方差
Finance, Forecast predict, ARCH, Finance market, Conditional het eroskedasticity
