Estimation and forecasting with logarithmic autoregressive conditional duration models: A comparative study with an application

作者：

Highlights：

• Efficient estimation of Log-ACD models using the estimating functions (EF) method.

• Study the finite sample behavior of new estimators through a simulation study.

• Compare the results via the EF and maximum likelihood (ML) methods.

• Apply the EF and ML methods for duration data for ACD models.

• Compare forecast abilities for ACD models through the EF and ML methods.

摘要

•Efficient estimation of Log-ACD models using the estimating functions (EF) method.•Study the finite sample behavior of new estimators through a simulation study.•Compare the results via the EF and maximum likelihood (ML) methods.•Apply the EF and ML methods for duration data for ACD models.•Compare forecast abilities for ACD models through the EF and ML methods.

论文关键词：Duration data,Conditional duration,Log-ACD,Estimating function,Maximum likelihood

论文评审过程：Available online 5 December 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.11.024