Fitting ARIMA model for volatility insurance time series data

Abstract

The volatility of stock market data have contributed an essential section in risk study and it is very serious problem especially in emerging markets. Previously it is measured by standard deviation of the return. Therefore, in this article the volatility data will be predicted based on Autoregressive Integrated Moving Average model (ARIMA) using insurance stock market data from Amman Stock Exchange (ASE) from January 2019 to December 2019. As a result this article shows that the ARIMA model has significant results for short-term prediction. Therefore, These results will be helpful for the investments.