This paper investigates the existence of long memory in the volatility of the Mexican stock market. We use a stochastic volatility (SV) model to derive statistical test for changes in volatility. In this case, estimation is carried out through the Kalman filter (KF) and the improved quasi-maximum likelihood (IQML). We also test for both persistence and long memory by using a long-memory stochas...

Scrub typhus, an infectious disease caused by a bacterium transmitted “chigger” mites, constitutes public health problem in Thailand. Predicting epidemic peaks would allow implementing preventive measures locally. This study analyses the predictability of time series incidence scrub typhus aggregated at provincial level. After stationarizing series, evaluation Hurst exponents indicates province...

We investigate the impact of the European Central Bank’s monetary policy communication on the level and volatility of the EUR-US Dollar exchange rate employing an AR-FIGARCH specification. Using high-frequency data we estimate the individual and complementary effects of the release of the interest rate decision, the ECB’s introductory statement and the question and answer session. Surprise inte...

The aim of this paper is to surround the volatility dynamics on the Tunisian stock market via an approach founded on the detection of persistence phenomenon and longterm memory presence. More specifically, our object is to test whether long-term dependent processes are appropriated for modelling Tunisian stock market volatility. The empirical investigation has been driven on the two Tunisian st...

The scientific community still struggles to understand the magnitude of worldwide infections and deaths induced by COVID-19, partly ignoring financial consequences. In this paper, using autoregressive fractionally integrated moving average (ARFIMA)—general conditional heteroskedasticity (GARCH) model, we quantify show impact COVID-19 spread in Italy, utilizing data for stock market. Using infor...