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M-estimation for Periodic GARCH Model with High-frequency Data

M-estimation for Periodic GARCH Model with High-frequency Data
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摘要 This paper studies an M-estimator of a proxy periodic GARCH (p, q) scaling model and establishes its consistency and asymptotic normality. Simulation studies are carried out to assess the performance of the estimator. The numerical results show that our M-estimator is more efficient and robust than other estimators without the use of high-frequency data. This paper studies an M-estimator of a proxy periodic GARCH (p, q) scaling model and establishes its consistency and asymptotic normality. Simulation studies are carried out to assess the performance of the estimator. The numerical results show that our M-estimator is more efficient and robust than other estimators without the use of high-frequency data.
出处 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2017年第3期717-730,共14页 应用数学学报(英文版)
基金 Supported by the National Natural Science Foundation of China(No.71673315) Foundation of Beijing Technology and Business University(LKJJ2016-03) Capital Circulation Research Base(JD-YB-2017-016)
关键词 asymptotic normality CONSISTENCY high-frequency data PGARCH model M-ESTIMATOR asymptotic normality consistency high-frequency data PGARCH model M-estimator
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