2022
03.08
暨南经院学术活动之统计学Seminar第96期:李元(广州大学)
主 题:LADE-based inferences for autoregressivemodels with heavy-tailed G-GARCH(1,1)noise主讲人:李元(广州大学)主持人:王国长(暨南大学)会议时间:2022年3月9日下午17:10-18:10会议地点:暨南大学经济学院(中惠楼)208室摘 要We explore the least absolute deviation(LAD) estimator of the autoregressive model with heavy-tailed G-GARCH(1,1)noise. When the tail index α∈(1,2], it is shown that the LAD estimator asymptotically convergesto a linear function of a series of α-stable random vectors with a rate ofconvergencen 1−1/α. The result is significantly differe