具有动态潜变量的ARCH-M模型的贝叶斯分析

IF 2 Q2 ECONOMICS
Zefang Song , Xinyuan Song , Yuan Li
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引用次数: 1

摘要

研究了一个具有动态潜变量的时变系数ARCH-M模型。联合模型通过考虑潜在变量的动态结构来扩展现有的ARCH-M模型,以检验对时变风险-收益关系的潜在影响。提出了一种与马尔可夫链蒙特卡罗算法相结合的贝叶斯方法,对模型参数和潜在变量进行联合估计。仿真结果表明,所提出的推理过程性能良好。介绍了该方法在中国股票市场金融研究中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian Analysis of ARCH-M model with a dynamic latent variable

A time-varying coefficient ARCH-in-mean (ARCH-M) model with a dynamic latent variable that follows an AR process is considered. The joint model extends the existing ARCH-M model by considering a dynamic structure of latent variable for examining a latent effect on the time-varying risk–return relationship. A Bayesian approach coped with Markov Chain Monte Carlo algorithm is developed to perform the joint estimation of model parameters and the latent variable. Simulation results show that the proposed inference procedure performs satisfactorily. An application of the proposed method to a financial study of the Chinese stock market is presented.

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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
84
期刊介绍: Econometrics and Statistics is the official journal of the networks Computational and Financial Econometrics and Computational and Methodological Statistics. It publishes research papers in all aspects of econometrics and statistics and comprises of the two sections Part A: Econometrics and Part B: Statistics.
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