Improving Volatility Risk Forecasting Accuracy in Industry Sector
Clicks: 212
ID: 70047
2017
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.
| Reference Key |
wadi2017improvinginternational
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| Authors | Wadi, S. Al; |
| Journal | international journal of mathematics and mathematical sciences |
| Year | 2017 |
| DOI | DOI not found |
| URL | |
| Keywords |
Engineering (General). Civil engineering (General)
Information technology
Computer applications to medicine. Medical informatics
neurosciences. biological psychiatry. neuropsychiatry
business
economics as a science
finance
computer engineering. computer hardware
mathematics
bibliography. library science. information resources
accounting. bookkeeping
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