We develop a Markov-Switching Autoregressive Conditional Intensity (MS-ACI) model with time-varying transitional parameters, and show that it can be reliably estimated via the Stochastic Approximation Expectation-Maximization algorithm. Applying our model to high-frequency transaction data, we...

This study is designed to model and forecast Nigeria's stock market using the AllShare Index (ASI) as a proxy. By employing the Markov regime-switching autore-gressive (MS-AR) model with data from April 2005 to September 2019, the studyanalyzes the stock market volatility in three distinct...

It is a widely known fact that the intraday seasonality of trading intervals for financial transactions such as stocks is short at the beginning of business hours and long in the middle of the day. In this paper, we extend the stochastic conditional duration (SCD) model to capture the pattern of...