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IAER Seminar 2020-15:费毅捷

报告题目:Multivariate Stochastic Volatility Model with Flexible Dynamic Correlations and Realized Measures

报 告 人:费毅捷

报告时间: 2020年09月25日(周五)15:00-16:30

报告地点:腾讯会议(会议ID:517 167 322)

主办单位:高等经济研究院

【报告人简介】

pk10彩票下载费毅捷,博士毕业于新加坡管理大学经济学院。主要研究领域为金融计量经济学和时间序列分析,曾在Economics Letters期刊发表文章。

【内容摘要】

pk10彩票下载Extending stochastic volatility models to multivariate case is not straightforward, especially when correlation structure is allowed to be dynamic. The challenges come from both model setup and parameter inference. In this paper, we make three contributions to this literature. First, we consider a new multivariate stochastic volatility (MSV) model, applying a recently proposed novel parameterization of correlation matrix. This modeling design is a generalization of Fisher's z-transformation to high-dimensional cases and it is fully flexible as the validity of resulting correlation matrix is guaranteed automatically. This allows us to separate the driving factors of volatilies and correaltions. Second, we propose to use a different estimation tool. Like most existing literature on MSV, we work within a Bayesian framework and hence rely on Markov Chain Monte Carlo (MCMC) sampler. However, when dealing with latent variables, traditional single-move or multi-move sampler is replaced by a novel technique called Particle Gibbs Ancestor Sampling (PGAS), which is built upon Sequential Monte Carlo (SMC). Third, we incorporate the information contained in intra-daily realized measures and propose to use a two-stage approach to reduce the estimation bias of some weakly identified parameters. Extensive simulation studies are conducted to confirm the applicability of this method under the current setup and provide guidance on the tradeoff between estimation accuracy and computational cost. The new model is then implemented using two financial datasets and comparison with existing models is discussed.

【参会方式】

腾讯会议  会议ID:517 167 322

方式一:下载“腾讯会议”客户端,输入“会议ID”加入会议

方式二:点击参会链接加入会议

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撰稿:王杰 审核:齐鹰飞 单位:高等经济研究院