MODELING DAILY AMMAN STOCK EXCHANGE VOLATILITY FOR SERVICES SECTOR

Year 2016, , 339 - 349, 30.09.2016

Salih Turan Katircioglu

https://doi.org/10.17261/Pressacademia.2016321976

Abstract

There are many  forecasting techniques that can be used to
help the investment community in building their 
policies in the future, which lead to an appropriate choices of the assets
involved in the portfolios, managing it , and pricing these assets accurately.
In this paper we are trying to afford one of these methods recognized as ARIMA
model, which is used in analyzing 
financial time series data. The 
target of this paper is 
forecasting  services sector
volatility in Amman Stock Exchange . As a result investment community can rely
on this type of analysis to make the future prospects of selling and
buying  financial securities.  Using 
historical indices data 
accumulated daily from the web site of Amman Stock Exchange for period
3/1/2010-10/5/2015. Stationarity achieved at level for  services sector , and then use a minimum mean
square error, t-statistics value and p-statistics value to choose the best
ARIMA models at 95% confidence interval. The resulted models for this study for
services sector is ARIMA(0,0,1), lastly, the best ARIMA model was formed and
tabulated in the entire paper.  

Keywords

Volatility, ARIMA Model, Financial Time Series, Forecasting

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