CAJ | 학술논문

针对时间序列分布特征的高峰厚尾性，提出了一类分位回归 ARCH 模型。在贝叶斯理论框架下，通过选择适当的先验分布，并基于非对称 Laplace分布构建模型的似然函数，实现了模型的贝叶斯推断。仿真试验和分析表明，该分位回归 ARCH模型可全面刻画时间序列的非对称性和高峰厚尾性。
침대시간서렬분포특정적고봉후미성，제출료일류분위회귀 ARCH 모형。재패협사이론광가하，통과선택괄당적선험분포，병기우비대칭 Laplace분포구건모형적사연함수，실현료모형적패협사추단。방진시험화분석표명，해분위회귀 ARCH모형가전면각화시간서렬적비대칭성화고봉후미성。
Since many time series with asymmetric and heavier tails,we adapt the quantile regression ideas to the ARCH models.In the framework of Bayesian theory,we employ the proper prior,the likelihood function based on the asymmetric Laplace distribution was employed irrespective of the original distribution of the data, and derive the posterior distribution of the model parameters.The simulation result shows that the quantile ARCH models are effective to capture the diversity of time series distribution.