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山东大学 王汉超教授: M-estimation for Jump-diffusion Models with Nonstationary High Frequency Data
2022-11-18 09:56  

报告题目:M-estimation for Jump-diffusion Models with Nonstationary High Frequency Data

报告人:王汉超(山东大学)

时间:2022.11.23(周三)14:00-15:00

腾讯会议:950-941-580

报告摘要:In this talk, we introduce the estimation for integrated jump- diffusion models with nonstationary high frequency data. As using the original data directly to estimate the unknown parameters in the models makes theoretical analysis almost not possible, we use a local approximation to derive desired estimation based on the original data. Moreover, as extreme jumps easily produce outliers, M-estimation procedure is considered for infinitesimal coefficients associated with integrated jump-diffusion models. However, the classical M-estimation can not possess the estimation consistency, the asymptotic normality and the rate of convergence, so we pro- pose a lag-1-based local M-estimation procedure to derive these important results. As a by-product, the designed conditions for these asymptotic results can even be weaker than those for classical independent identically distributed settings in the literature. The numerical studies suggest the ad- vantages of our method in bias reduction and computational efficiency. A real data example about the returns for stock index under five-minute high sampling frequency is analyzed for illustration.


王汉超,男,汉族,山东大学金融研究院教授,博士生导师。2011年于浙江大学数学系概率论与数理统计专业博士毕业。 主要从事概率统计极限理论及其应用的研究,特别在弱收敛,集中不等式与金融统计等领域发表了若干文章。与林正炎教授合作,在新加坡世界科技出版社出版专著Weak Convergence and Its Applications。与于志勇教授合作,在高等教育出版社出版教材《应用随机分析》。近几年来,在概率论,数理统计,计量经济等领域权威期刊上发表论文近二十篇。主持国家自然科学基金两项,作为骨干成员,参加国家重点研发计划项目两项。



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