Nonlinear Least Squares Estimation of Log-ACD Models
| Autor: | Christina Dan Wang, Yaohua Wu, Wei Liu, Zhao Chen, Wuqing Wu |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Logarithm
Applied Mathematics Autoregressive conditional duration 05 social sciences Strong consistency Estimator Inference Asymptotic distribution 01 natural sciences Moment (mathematics) 010104 statistics & probability 0502 economics and business Applied mathematics 0101 mathematics Nonlinear least squares estimation 050205 econometrics Mathematics |
| Zdroj: | Acta Mathematicae Applicatae Sinica, English Series. 34:516-533 |
| ISSN: | 1618-3932 0168-9673 |
| DOI: | 10.1007/s10255-018-0766-6 |
| Popis: | This paper studies a nonlinear least squares estimation method for the logarithmic autoregressive conditional duration (Log-ACD) model. We establish the strong consistency and asymptotic normality for our estimator under weak moment conditions suitable for applications involving heavy-tailed distributions. We also discuss inference for the Log-ACD model and Log-ACD models with exogenous variables. Our results can be easily translated to study Log-GARCH models. Both simulation study and real data analysis are conducted to show the usefulness of our results. |
| Databáze: | OpenAIRE |
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