Short Term Predicting Volatility Service Jordanian Sector

Abstract

Stock market volatility have added an important section in risk scholarship and it is actual  problem particularly in emerging markets. Earlier, it is measured by standard deviation of the  return. Consequently, in this research the volatility data will be predicted based on ARIMA model (Autoregressive Integrated Moving Average model) of the service sector  in Amman Stock Exchange (ASE) from January 2019 to December 2019. Consequently this article shows that the ARIMA model has important results in prediction. Therefore, These outcomes will be helpful for the investments.

Keywords: ARIMA model, forecasting, Service sector.

DOI: 10.7176/EJBM/11-36-14

Publication date: December 31^st 2019