可加模型及其在金融市场波动率估计中的应用  

Additive Model and Its Application in the Estimation of Financial Market Volatility

作　　者：王相宁[1] 邹佳[1] 

机构地区：[1]中国科学技术大学统计与金融系,合肥230026

出　　处：《系统管理学报》2009年第1期82-88,共7页Journal of Systems & Management

摘　　要：放宽了传统GARCH模型参数形式的假定,将可加模型引入条件方差的估计,改进了Bühlmann和McNeil提出的迭代算法,并将其用于可加GARCH模型的估计。通过能够模拟真实波动率的数学实验,以及新加坡股市和不同市场股市比较的实证算例,发现可加GARCH模型不仅在估计现有参数模型无法刻画的复杂序列波动率时具有更好的估计效果,而且与一般非参数模型相比也有较好的估计效果。因此,可加GARCH模型对研究新兴市场股市或诸如金融危机等存在复杂波动特征的金融市场有着非常现实的意义。Using additive model, we broaden the restrictions on the parametric form of the conventional GARCH model. An additive GARCH model and its estimation algorithm based on Bühlmann and McNeil have been proposed to estimate volatility. Through mathematical method which can simulate real volatility and the empirical reserch of Singapore stock market and the comparison of different stock markets, we find that the additive GARCH models not only performance better than the traditional GARCH models, but also exceed general nonparametric models. The additive GARCH model is meaningful in the study of the volatilities of emerging stock markets and the financial markets which have complex volatility structure such as the financial crisis.

关 键 词：金融时间序列 可加模型 GARCH 波动率 异方差性 

分 类 号：F830.9[经济管理—金融学]