For a zero-mean Gaussian process, the covariances of zero crossings can be expressed as the sum of quadrivariate normal orthant probabilities. In this paper, we demonstrate the evaluation of zero crossing covariances using one-dimensional integrals. Furthermore, we provide asymptotics of zero crossing covariances for large time lags and derive bounds and approximations. Based on these results, ...

Time series and their methods of analysis are important subjects in statistics. Most of time series have a linear behavior and can be modelled by linear ARIMA models. However, some of realized time series have a nonlinear behavior and for modelling them one needs nonlinear models. For this, many good parametric nonlinear models such as bilinear model, exponential autoregressive model, threshold...

Using a multivariate generalized autoregressive conditional heteroskedasticity (GARCH-M) model, we investigate volatility spillovers in six Southeast Asian stock markets around the time of the 1997 Asian crisis. We focus on interactions with the U.S. market as a world financial market, and with the Japanese market as a regional financial market. We also use bivariate GARCH-M models to examine t...

Whether better infrastructure influences Chinese export sophistication (ES) and diversification (ED) is an important question, which surprisingly remains unaddressed. The current study contributes to the ES ED literature by capturing symmetric asymmetric effect of on ED. We employ a robust dynamically simulated autoregressive distributed lag (DYS-ARDL) dynamic method, extended version NARDL ARD...

This study aims to determine the influence of internal and external factors on liquidity Islamic banks. The research observation period was from January 2015 April 2019 using autoregressive distributed lag (ARDL) data processing method. ARDL is used short-term long-term independent variables variable. results found that CAR has a significant negative effect FDR, but it not in short term. Likewi...

The testing problem on the first-order autoregressive parameter in finite sample case is considered. The innovations are distributed according to the exponential distribution. The aim of this paper is to study how much the size of this test changes when, at some time k, an innovation outlier contaminant occurs. We show that the test is rather sensitive to these changes.