Nonlinear Least Squares Estimation of Log-ACD Models |
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| Authors: | Zhao?Chen,Wei?Liu,Christina?Dan?Wang,Wu-qing?Wu mailto:wwq@ruc.edu.cn" title=" wwq@ruc.edu.cn" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author,Yao-hua?Wu |
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| Affiliation: | 1.School of Data Science,Fudan University,Shanghai,China;2.Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing,China;3.New York University Shanghai,Shanghai,China;4.School of Business,Renmin University of China,Beijing,China;5.Department of Statistics and Finance,University of Science and Technology of China,Hefei,China |
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| Abstract: | ![]()
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. |
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