In this paper, we consider the minimum density power divergence estimator for the tail index of heavy tailed distributions in strong mixing processes. It is shown that the estimator is consistent and asymptotically normal under regularity conditions. The simulation results demonstrate that the...

type="main" xml:id="jtsa12098-abs-0001"Many empirical findings show that volatility in financial time series exhibits high persistence. Some researchers argue that such persistency is due to volatility shifts in the market, while others believe that this is a natural fluctuation explained by...

We propose the Gaussian quasi-maximum likelihood estimator (QMLE) to detect and locate multiple volatility shifts. Our Gaussian QMLE is shown to be consistent under suitable conditions and the rate of convergence is provided. It is also shown that the binary segmentation procedure provides a...

In this paper, we study the entropy test for the goodness of fit test in (nonlinear) autoregressive conditional duration (ACD) models. To implement a test, we first explore the null limiting distribution of the residual empirical process from ACD models and verify that it has an asymptotic...

This paper aims to detect the presence of local non-stationarity of nonlinear autoregressive processes with heteroskedastic errors. A Bayesian test is developed to test for the unit root in multi-regime threshold autoregression with heteroskedasticity. To implement a test, a posterior odds...

The robust estimation for Poisson autoregressive models is studied. As a robust estimator, a minimum density power divergence estimator (MDPDE) is considered. It is shown that under regularity conditions, the MDPDE is strongly consistent and asymptotically normal. Simulation results are provided...

In this paper, we propose a goodness of fit test based on maximum entropy. As an extension of the result on the simple versus simple hypothesis case handled by Lee et al. (2011), a composite hypothesis case is taken into consideration. To eliminate the parameter estimation effect, we apply the...

In this paper, a goodness of fit (gof) test for discrete random variables is studied. For the test, the empirical process gof test constructed based on the Khmaladze transformation method is considered to remove the parameter estimation effect. Further, the approach of the continuous extension...

In this paper, we study the robust estimation for the covariance matrix of stationary multivariate time series. As a robust estimator, we propose to use a minimum density power divergence estimator (MDPDE) designed by Basu et al. (1998). To supplement the result of Kim and Lee (2011), we employ...