报告题目：Two classes of Z-valued INAR(1) models with financial applications

报告时间：2025年7月2日上午9：00

报告地点：北湖东区主楼527室

主办单位：激情视频

报告人：康尧

报告人简介：康尧，西安交通大学副教授，硕士生导师，2020年6月于吉林大学获得博士学位，2020年7月进入西安交通大学激情视频 工作。目前主要从事时间序列分析、统计过程控制和保险精算等方面的研究，以第一作者和通讯作者身份于TEST、The Canadian Journal of Statistics和Economics Letters等统计学和经济学期刊发表SCI/SSCI论文16篇，先后主持国家自然科学基金青年项目、中国博士后面上项目等5项，担任中国现场统计研究会大数据统计分会、中国现场统计研究会贝叶斯统计分会理事，承担Statistical Papers和Journal of Statistical Computation and Simulation、Methodology and Computing in Applied Probability和Journal of Systems Science and Complexity等期刊的审稿工作。

摘要：Z-valued time series, defined on the set of integers Z = {..., −2, −1, 0, 1, 2,…}, are commonly observed in economics and finance. Z-valued versions of integer-valued autoregressive (INAR) models are frequently employed to fit Z-valued time series. However, the existing Z-valued INAR models encounter difficulties in data generation mechanism and statistical inference. To enhance the modeling and prediction of Z-valued time series, this talk introduces two classes of Z-valued INAR(1) models from new perspective and studies the related statistical inference problem. Empirically, applications to financial datasets demonstrate that our models offer satisfactory performance in economics and finance.