伟德线上平台、所2024年系列學術活動（第048場）：朱柯 副教授 香港大學
報告題目：Matrix GARCH Model: Inference and Application
報 告 人：朱柯 副教授 香港大學
報告時間：2024年5月20日 9:00-10:00
報告地點： #騰訊會議：192-671-313
校内聯系人：朱複康 fzhu@jlu.edu.cn
報告摘要：Matrix-variate time series data are largely available in applications. However, no attempt has been made to study their conditional heteroskedasticity that is often observed in economic and financial data. To address this gap, we propose a novel matrix generalized autoregressive conditional heteroskedasticity (GARCH) model to capture the dynamics of conditional row and column covariance matrices of matrix time series. The key innovation of the matrix GARCH model is the use of a univariate GARCH specification for the trace of conditional row or column covariance matrix, which allows for the model identification. Moreover, we introduce a quasi-maximum likelihood estimator (QMLE) for model estimation and develop a portmanteau test for model diagnostic checking. Simulation studies are conducted to assess the finite-sample performance of the QMLE and portmanteau test. To handle large dimensional matrix time series, we also propose a matrix factor GARCH model. Finally, we demonstrate the superiority of the matrix GARCH and matrix factor GARCH models over existing multivariate GARCH-type models in volatility forecasting and portfolio allocations using three applications on credit default swap prices, global stock sector indices, and future prices.
報告人簡介：朱柯博士2011年獲得香港科技大學統計學博士學位，同年進入中國科學院數學與系統科學研究院從事研究工作，曆任助理研究員、副研究員。2016年加入香港大學任助理教授、副教授。朱柯博士的研究興趣包括時間序列分析、計量經濟、金融大數據等領域。他是International Statistical Institute和Journal of Econometrics的會員。
