Improving Volatility Risk Forecasting Accuracy in Industry Sector

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ID: 70047
2017
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Abstract
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 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors S. Al Wadi
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Journal international journal of mathematics and mathematical sciences
Year 2017
DOI
DOI not found
URL
http://dx.doi.org/10.1155/2017/1749106
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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