Modelling Seasonal Volatility and Level Shift in Fractionally Integrated Processes

This unit presents a class of migratory incompletely joined autoregressive mobile average-statement dependent heteroscedasticity (SARFIMAGARCH) models, accompanying level shift type invasion that are fit conquering together four key looks momentary order: seasonality, long range reliance, excitability and level shift. The main focus act forming migratory level shift (SLS) in incompletely joined and explosive processes. A normal continuation of the seasonal level shift discovery test of the mean for a achievement momentary order fulfilling SLS-SARFIMA and SLS-GARCH models was derivative. Test enumerations that are beneficial to test if migratory level shift in an SARFIMA-GARCH model is statistically believable were made acquainted. Estimation of SLS-SARFIMA and SLS-GARCH limits are likewise likely.

Author(s) Details:

Lawrence Dhliwayo,
Department of Statistics, University of Zimbabwe, Harare, Zimbabwe.

Florance Matarise,
Department of Statistics, University of Zimbabwe, Harare, Zimbabwe.

Charles Chimedza,
School of Statistics and Actuarial Science, University of Witwatersrand, Johannesburg, South Africa.

Please see the link here: https://stm.bookpi.org/RHMCS-V2/article/view/8659

Keywords: Seasonality, fractional integration, long-memory, level shift,                SLS-SARFIMA, SLS-GARCH, volatility