Abstract: We consider the Autoregressive Conditional Marked Duration (ACMD) model and apply it to 16 stocks traded in Hong Kong Stock Exchange (SEHK). By examining the orderings of appropriate sets of model parameters, market microstructure phenomena can be explained. To substantiate these conclusions, likelihood ratio test is used for testing the significance of the parameter orderings of the ACMD model. While some of our results resolve a few controversial market microstructure hypotheses and echo some of the existing empirical evidence, we discover some interesting market microstructure phenomena that may be characteristic to SEHK.link_to_OA_fulltex
This paper proposes a Generalized Logarithmic Autoregressive Conditional Duration (GLACD) model to e...
This paper highlights the importance of timing specifications in empirical market microstructure stu...
We propose a new framework for modelling time dependence in duration processes on financial markets....
This paper uses a restricted factor model to estimate the HICP index excluding relative prices chang...
This paper introduces the logarithmic autoregressive conditional duration model (Log-ACD model). The...
The main goal of this paper is to compare the microstructure of selected stocks listed on theFrankfu...
Abstract. In this paper, we suggest and evaluate specification tests to test the validity of the con...
Financial market activity via trade durations and price dynamics are investigated by means of ultra ...
This study presents a novel model for analyzing duration data, called the smooth transition autoregr...
This is the final version. Available on open access from Elsevier via the DOI in this recordWe estab...
A new model for the analysis of durations, the stochastic conditional duration (SCD) model, is intro...
This study is concerned with the autoregressive conditional duration model (ACD) and its application...
This paper investigates the persistent pattern in the Helsinki Exchanges. The persistent pattern is ...
Financial market price formation and exchange activity can be investigated by means of ultra-high fr...
We propose a new framework for modeling time dependence in duration processes. The ACD approach intr...
This paper proposes a Generalized Logarithmic Autoregressive Conditional Duration (GLACD) model to e...
This paper highlights the importance of timing specifications in empirical market microstructure stu...
We propose a new framework for modelling time dependence in duration processes on financial markets....
This paper uses a restricted factor model to estimate the HICP index excluding relative prices chang...
This paper introduces the logarithmic autoregressive conditional duration model (Log-ACD model). The...
The main goal of this paper is to compare the microstructure of selected stocks listed on theFrankfu...
Abstract. In this paper, we suggest and evaluate specification tests to test the validity of the con...
Financial market activity via trade durations and price dynamics are investigated by means of ultra ...
This study presents a novel model for analyzing duration data, called the smooth transition autoregr...
This is the final version. Available on open access from Elsevier via the DOI in this recordWe estab...
A new model for the analysis of durations, the stochastic conditional duration (SCD) model, is intro...
This study is concerned with the autoregressive conditional duration model (ACD) and its application...
This paper investigates the persistent pattern in the Helsinki Exchanges. The persistent pattern is ...
Financial market price formation and exchange activity can be investigated by means of ultra-high fr...
We propose a new framework for modeling time dependence in duration processes. The ACD approach intr...
This paper proposes a Generalized Logarithmic Autoregressive Conditional Duration (GLACD) model to e...
This paper highlights the importance of timing specifications in empirical market microstructure stu...
We propose a new framework for modelling time dependence in duration processes on financial markets....