Improving Volatility Risk Forecasting Accuracy in Industry Sector
Author
Source
International Journal of Mathematics and Mathematical Sciences
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-07
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Recently, the volatility of financial markets has contributed a necessary part to risk management.
Volatility risk is characterized as the standard deviation of the constantly compound return per day.
This paper presents forecasting of volatility for the Jordanian industry sector after the crisis in 2009.
ARIMA and ARIMA-Wavelet Transform (WT) have been conducted in order to select the best forecasting model in the content of industry stock market data collected from Amman Stock Exchange (ASE).
As a result, the researcher found that ARIMA-WT has more accuracy than ARIMA directly.
The results have been introduced using MATLAB 2010a and R programming.
American Psychological Association (APA)
Al Wadi, S.. 2017. Improving Volatility Risk Forecasting Accuracy in Industry Sector. International Journal of Mathematics and Mathematical Sciences،Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1167699
Modern Language Association (MLA)
Al Wadi, S.. Improving Volatility Risk Forecasting Accuracy in Industry Sector. International Journal of Mathematics and Mathematical Sciences No. 2017 (2017), pp.1-6.
https://search.emarefa.net/detail/BIM-1167699
American Medical Association (AMA)
Al Wadi, S.. Improving Volatility Risk Forecasting Accuracy in Industry Sector. International Journal of Mathematics and Mathematical Sciences. 2017. Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1167699
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1167699