The paper suggests a nonlinear and multivariate time series model framework that enables the study of simultaneity in returns and in volatilities, as well as asymmetric effects arising from shocks and an outside stock exchange. Using daily data 2000-2006 for the Baltic state stock exchanges and...

The asymmetric moving average model (asMA) is extended to allow for asymmetric quadratic conditional heteroskedasticity (asQGARCH). The asymmetric parametrization of the conditional variance encompasses the quadratic GARCH model of Sentana (1995). We introduce a framework for testing asymmetries...

The impact of news of the Moscow and New York stock market exchanges on the <p> returns and volatilities of the Baltic state stock market indices is studied using daily <p> return data for the period of 2000-2005. A nonlinear time series model that accounts <p> for asymmetries in the conditional mean and...</p></p></p>

The paper considers conditional duration models in which durations are in continuous time but measured in grouped or discretized form. This feature of recorded durations in combination with a frequently traded stock is expected to negatively influence the performance of conventional estimators....

The paper advances the log-generalized gamma distribution as a suitable generator of conditional skewness. Based on the NYSE composite daily returns an asMA-asQGARCH model along with skewness dynamics is estimated. The results indicate a skewness that varies between sizeable negative skewness...

The integer-valued moving average model is advanced to model the number of transactions in intra-day data of stocks. The conditional mean and variance properties are discussed and model extensions to include, e.g., explanatory variables are offered. Least squares and generalized method of moment...