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.
Bölüm | Articles |
---|---|
Yazarlar | |
Yayımlanma Tarihi | 30 Eylül 2016 |
Yayımlandığı Sayı | Yıl 2016 |
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