Vector Autoregressive Integrating Moving Average (Varima) Model of COVID-19 Pandemic and Oil Price

Purpose: A coronavirus associated with severe respiratory syndrome has created Coronavirus Disease 2019 (COVID-19), a highly contagious illness that affects the entire world population. On other hand, COVID-19 is having direct impact on human life because of its proliferation. So, study's goal to forecast and analyze pandemic oil price utilizing multiple time series analysis methods (VARIMA model). Theoretical framework: Recent literature reported multivariate robust model for forecasting analyzing dynamic relationship between series, while univariate ARIMA been generalized include vector variables, an extension capabilities. The VAR (p) analyzes interdependence two or more but does not take into account shocks at various variable delays. Design/methodology/approach: This study uses VARMA (p, q) which links set variables their prior iterations as well those same variables. Sample data concerning was globally provided. It contains daily observations them years 2020-2022. Findings: best VARIMA (2,1,2), results shown only influenced by itself also Covid-19 pandemic. Moreover, standard error grows over forecast. Research, Practical & Social implications: sound short-term unstable long-term forecasting. Future researchers can integrate factors across areas. Include tourism demand industry in modeling. Originality/value: Collecting modern high predicted level accuracy these order predict effects estimate interaction most recent value this study, then offers merchants chance comprehend throughout covid-19 risks.