A New Method For Multivariate ARCH Parameter Estimation
Publish place: 16th Iranian Conference on Electric Engineering
Publish Year: 1387
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICEE16_198
تاریخ نمایه سازی: 6 اسفند 1386
Abstract:
This paper discusses the asymptotic properties of two-stage least-squares (TSLS) estimator of the parameters of multivariate autoregressive
conditional heteroscedasticity (ARCH) model. The estimator is easy to obtain since it involves solving sets of linear equations. It will be shown that, under som conditions, this TSLS estimator is asymptotically consistent and its rate of convergence is the same as that of quasi maximum likelihood estimator (QMLE). At the same time, the computational load of TSLS estimator is extremely lower than that of QMLE. The performance of the TSLS estimator will be evaluated and compared with QMLE using simulations. Simulation results show that the performances of the two estimators are comparable even for small data records.
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Authors
Saman Mousazadeh
Shiraz University-Shiraz-Iran
Mahmood Karimi
Shiraz University-Shiraz-Iran