Value at risk measure on oil price by using extreme value theory approach
The oil market is well known for its unpredictable market trend and volatility, which makes the trading risk in this market high and can lead to huge losses. The purpose of this study is to measure the risk of extreme returns in the oil market. Effective risk management can avoid investors from s...
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| Format: | Article |
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Malaysian Mathematical Science Society
2022
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| _version_ | 1825938730856218624 |
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| author | Jajiman, Putra Nor Hakimi Ling, Wendy Shinyie Buliah, Nur Amirah |
| author_facet | Jajiman, Putra Nor Hakimi Ling, Wendy Shinyie Buliah, Nur Amirah |
| author_sort | Jajiman, Putra Nor Hakimi |
| collection | UPM |
| description | The oil market is well known for its unpredictable market trend and volatility, which makes the trading risk in this market high and can lead to huge losses. The purpose of this study is to measure the risk of extreme returns in the oil market. Effective risk management can avoid investors from suffering huge losses. The data used in this study is 10-year daily return futures price of the two most traded commodities on the oil market, West Texas Intermediate (WTI) and Brent Crude Oil. This study utilises Value at Risk (VaR) as a measure of risk. Extreme Value Theory (EVT) is used to improve the reliability of the risk measurement. As the extreme values in the data series are limited, the peaks over threshold (POT) method is used to extract all values above a certain threshold,which is considered as the limit value in the process of parameter estimation and modelling. By fitting the excesses to Generalized Pareto distribution (GPD), we can obtain the estimation of the risk measure. The model is then assessed by backtesting to identify whether the estimated risk measure can capture the risk accurately. The backtesting methods used in this study are the Christoffersen test and the Basel backtesting. The findings show that Extreme-VaR captured the risk perfectly. Therefore, this approach can be used by investors as a risk management tool in the portfolio management. |
| first_indexed | 2024-04-09T03:50:43Z |
| format | Article |
| id | upm.eprints-102581 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-04-09T03:50:43Z |
| publishDate | 2022 |
| publisher | Malaysian Mathematical Science Society |
| record_format | dspace |
| spelling | upm.eprints-1025812024-03-12T04:09:03Z http://psasir.upm.edu.my/id/eprint/102581/ Value at risk measure on oil price by using extreme value theory approach Jajiman, Putra Nor Hakimi Ling, Wendy Shinyie Buliah, Nur Amirah The oil market is well known for its unpredictable market trend and volatility, which makes the trading risk in this market high and can lead to huge losses. The purpose of this study is to measure the risk of extreme returns in the oil market. Effective risk management can avoid investors from suffering huge losses. The data used in this study is 10-year daily return futures price of the two most traded commodities on the oil market, West Texas Intermediate (WTI) and Brent Crude Oil. This study utilises Value at Risk (VaR) as a measure of risk. Extreme Value Theory (EVT) is used to improve the reliability of the risk measurement. As the extreme values in the data series are limited, the peaks over threshold (POT) method is used to extract all values above a certain threshold,which is considered as the limit value in the process of parameter estimation and modelling. By fitting the excesses to Generalized Pareto distribution (GPD), we can obtain the estimation of the risk measure. The model is then assessed by backtesting to identify whether the estimated risk measure can capture the risk accurately. The backtesting methods used in this study are the Christoffersen test and the Basel backtesting. The findings show that Extreme-VaR captured the risk perfectly. Therefore, this approach can be used by investors as a risk management tool in the portfolio management. Malaysian Mathematical Science Society 2022-12 Article PeerReviewed Jajiman, Putra Nor Hakimi and Ling, Wendy Shinyie and Buliah, Nur Amirah (2022) Value at risk measure on oil price by using extreme value theory approach. Menemui Matematik (Discovering Mathematics), 44 (2). 109 - 120. ISSN 0126-9003 https://myjms.mohe.gov.my/index.php/dismath/article/view/20703 |
| spellingShingle | Jajiman, Putra Nor Hakimi Ling, Wendy Shinyie Buliah, Nur Amirah Value at risk measure on oil price by using extreme value theory approach |
| title | Value at risk measure on oil price by using extreme value theory approach |
| title_full | Value at risk measure on oil price by using extreme value theory approach |
| title_fullStr | Value at risk measure on oil price by using extreme value theory approach |
| title_full_unstemmed | Value at risk measure on oil price by using extreme value theory approach |
| title_short | Value at risk measure on oil price by using extreme value theory approach |
| title_sort | value at risk measure on oil price by using extreme value theory approach |
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