This article develops a method for testing the goodness-of-fit of a given parametric autoregressive conditional duration model against unspecified nonparametric alternatives. The test statistics are functions of the residuals corresponding to the quasi maximum likelihood estimate of the given parametric model, and are easy to compute. The limiting distributions of the test statistics are not free from nuisance parameters. Hence, critical values cannot be tabulated for general use. A bootstrap procedure is proposed to implement the tests, and its asymptotic validity is established. The finite sample performances of the proposed tests and several other competing ones in the literature, were compared using a simulation study. The tests propose...
Abstract. In this paper we suggest model specification tests for autoregressive conditional duration...
Doubly truncated data are commonly encountered in areas like medicine, astronomy, economics, among o...
Doubly truncated data are commonly encountered in areas like medicine, astronomy, economics, among o...
The class of nonlinear time series models known as autoregressive conditional duration [ACD] models ...
This paper contains two novelties. First, a unified framework for testing and evaluating the adequac...
We consider a goodness-of-fit test for certain parametrizations of conditionally heteroscedastic tim...
This paper deals with the testing of autoregressive conditional duration (ACD) models by gauging the...
This article contains two novelties. First, a unified framework for testing and evaluating the adequ...
We propose specification tests for the innovation distribution in conditional duration models. The n...
This paper deals with the estimation and testing of conditional duration models by looking at the de...
This paper deals with the estimation and testing of conditional duration models by looking at the de...
Abstract. In this paper, we suggest and evaluate specification tests to test the validity of the con...
We derive the asymptotic distribution of residual autocorrelations for the Weibull autoregressive co...
This paper deals with the estimation and testing of conditional duration models by looking at the de...
We derive a nonparametric test for discriminating between generalized autoregressive models. This te...
Abstract. In this paper we suggest model specification tests for autoregressive conditional duration...
Doubly truncated data are commonly encountered in areas like medicine, astronomy, economics, among o...
Doubly truncated data are commonly encountered in areas like medicine, astronomy, economics, among o...
The class of nonlinear time series models known as autoregressive conditional duration [ACD] models ...
This paper contains two novelties. First, a unified framework for testing and evaluating the adequac...
We consider a goodness-of-fit test for certain parametrizations of conditionally heteroscedastic tim...
This paper deals with the testing of autoregressive conditional duration (ACD) models by gauging the...
This article contains two novelties. First, a unified framework for testing and evaluating the adequ...
We propose specification tests for the innovation distribution in conditional duration models. The n...
This paper deals with the estimation and testing of conditional duration models by looking at the de...
This paper deals with the estimation and testing of conditional duration models by looking at the de...
Abstract. In this paper, we suggest and evaluate specification tests to test the validity of the con...
We derive the asymptotic distribution of residual autocorrelations for the Weibull autoregressive co...
This paper deals with the estimation and testing of conditional duration models by looking at the de...
We derive a nonparametric test for discriminating between generalized autoregressive models. This te...
Abstract. In this paper we suggest model specification tests for autoregressive conditional duration...
Doubly truncated data are commonly encountered in areas like medicine, astronomy, economics, among o...
Doubly truncated data are commonly encountered in areas like medicine, astronomy, economics, among o...