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A0376
Title: On the quasi-maximum likelihood estimation of threshold GARCH Models Authors:  Yaxing Yang - Xiamen University (China) [presenting]
Dong Li - Tsinghua University (China)
Shiqing Ling - HKUST (China)
Abstract: The asymptotic theory is studied for the quasi-maximum likelihood estimation (QMLE) for a threshold GARCH model. Under some mild condition, it is shown that the estimated threshold is $n$-consistent and converges weakly to the smallest minimizer of a two-sided compound Poisson process. The remaining parameters are $\sqrt{n}$-consistent and asymptotically normal. Simulation study is carried out to access the performance of the QMLE in finite sample and a real example is given.