建议密度自适应的GARCH模型的Bayes估计
Bayesian estimation of GARCH model with an adaptive proposal density
摘要：
采用Metropolis-Hastings算法，对美元/日元汇率的GARCH模型进行贝叶斯估计，并给出了自适应构造方案的建议密度.在自适应建设计划的建议密度被假定为采取一种形式的多元学生的t-分布和其参数进行评估，通过使用采样数据和更新自适应马尔可夫链蒙特卡罗模拟。我们发现，自适应建设计划采样的数据之间的自相关时间大大减少。我们的结论是，自适应构造方案的有效工作的GARCH模型的贝叶斯推理。
英文摘要：
A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the Metropolis-Hastings algorithm with a proposal density given by the adaptive construction scheme. In the adaptive construction scheme the proposal density is assumed to take a form of a multivariate Student's t-distribution and its parameters are evaluated by using the sampled data and updated adaptively during Markov Chain Monte Carlo simulations. We find that the autocorrelation times between the data sampled by the adaptive construction scheme are considerably reduced. We conclude that the adaptive construction scheme works efficiently for the Bayesian inference of the GARCH model.
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