基于自适应构造方案的QGARCH模型贝叶斯推断
Bayesian Inference on QGARCH Model Using the Adaptive Construction Scheme
摘要：
我们研究了自适应构造方案的性能贝叶斯推理的二次GARCH模型，它引入了时间序列动态的不对称性。在自适应构造方案中，Metropolis-Hastings算法中的建议密度是通过改变密度的参数来适应后验密度而自适应地构造的。我们利用人工QGARCH数据，通过将自适应构造方案应用于QGARCH模型的贝叶斯推断来推断QGARCH参数。我们发现，自适应的建设计划的样本QGARCH参数有效，即采样数据之间的相关性非常小。我们的结论是，自适应构造方案是一种有效的方法，贝叶斯估计的QGRESS模型。
英文摘要：
We study the performance of the adaptive construction scheme for a Bayesian inference on the Quadratic GARCH model which introduces the asymmetry in time series dynamics. In the adaptive construction scheme a proposal density in the Metropolis-Hastings algorithm is constructed adaptively by changing the parameters of the density to fit the posterior density. Using artificial QGARCH data we infer the QGARCH parameters by applying the adaptive construction scheme to the Bayesian inference of QGARCH model. We find that the adaptive construction scheme samples QGARCH parameters effectively, i.e. correlations between the sampled data are very small. We conclude that the adaptive construction scheme is an efficient method to the Bayesian estimation of the QGARCH model.
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