報告題目： A random coefficient absolute autoregressive model with application to bubble
報 告 人：李東 副教授 清華大學
報告時間：2023年6月20日 9：00-10：00
報告地點：騰訊會議 ID：373776267
校内聯系人：趙世舜 zhaoss@jlu.edu.cn
報告摘要：
Financial time series can feature locally explosive behavior when a bubble is formed. The financial bubble, especially its dynamics, is an intriguing topic that has been attracting longstanding attention. To illustrate the dynamics of the local explosion itself, the paper presents a new time series model, called random coefficient absolute autoregressive model, which is always strictly stationary and geometrically ergodic and can create long swings or persistence observed in many macroeconomic variables. When the parameter
, the model has periodically explosive behaviors and can then be used to portray the bubble dynamics. Further, the quasi-maximum likelihood estimation (QMLE) of our model is considered, and its strong consistency and asymptotic normality are established under minimal assumptions on innovation. A new model diagnostic checking statistic is developed for model fitting adequacy. Four reference rules dating collapses of bubble process are heuristically provided from an empirical perspective. Monte Carlo simulation studies are conducted to assess the performance of the QMLE and reference rules in finite samples. Finally, the usefulness of the model is illustrated by an empirical application to the monthly Hang Seng Index.
報告人簡介：李東，清華大學統計學研究中心(長聘)副教授，2010年12月畢業于香港科技大學，2013年9月加入清華大學。主要從事計量經濟學、金融計量學、時間序列分析、網絡數據與大數據分析、機器學習等方面的研究。在統計學和計量統計學雜志上共發表研究論文40餘篇。目前擔任中國數學會概率統計分會常務理事等.
