Volatility forecasting in the Chinese commodity futures market with intraday data
Given the unique institutional regulations in the Chinese commodity futures market as well as the characteristics of the data it generates, we utilize contracts with three months to delivery, the most liquid contract series, to systematically explore volatility forecasting for aluminum, copper, fuel...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Springer
2016
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| Online Access: | https://eprints.nottingham.ac.uk/34280/ |
| _version_ | 1848794815424102400 |
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| author | Ying, Jiang Shamin, Ahmed Xiaoquan, Liu |
| author_facet | Ying, Jiang Shamin, Ahmed Xiaoquan, Liu |
| author_sort | Ying, Jiang |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Given the unique institutional regulations in the Chinese commodity futures market as well as the characteristics of the data it generates, we utilize contracts with three months to delivery, the most liquid contract series, to systematically explore volatility forecasting for aluminum, copper, fuel oil, and sugar at the daily and three intraday sampling frequencies. We adopt popular volatility models in the literature and assess the forecasts obtained via these models against alternative proxies for the true volatility. Our results suggest that the long memory property is an essential feature in the commodity futures volatility dynamics and that the ARFIMA model consistently produces the best forecasts or forecasts not inferior to the best in statistical terms. |
| first_indexed | 2025-11-14T19:22:11Z |
| format | Article |
| id | nottingham-34280 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:22:11Z |
| publishDate | 2016 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-342802017-11-15T01:43:18Z https://eprints.nottingham.ac.uk/34280/ Volatility forecasting in the Chinese commodity futures market with intraday data Ying, Jiang Shamin, Ahmed Xiaoquan, Liu Given the unique institutional regulations in the Chinese commodity futures market as well as the characteristics of the data it generates, we utilize contracts with three months to delivery, the most liquid contract series, to systematically explore volatility forecasting for aluminum, copper, fuel oil, and sugar at the daily and three intraday sampling frequencies. We adopt popular volatility models in the literature and assess the forecasts obtained via these models against alternative proxies for the true volatility. Our results suggest that the long memory property is an essential feature in the commodity futures volatility dynamics and that the ARFIMA model consistently produces the best forecasts or forecasts not inferior to the best in statistical terms. Springer 2016-05-03 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/34280/1/Jiang_Ahmed_Liu%202016%20RQFA.pdf Ying, Jiang, Shamin, Ahmed and Xiaoquan, Liu (2016) Volatility forecasting in the Chinese commodity futures market with intraday data. Review of Quantitative Finance and Accounting . ISSN 1573-7179 Out-of-sample predictability; Long memory time series; Futures market regulation; Realized volatility; Econometric models http://link.springer.com/article/10.1007/s11156-016-0570-4 doi:10.1007/s11156-016-0570-4 doi:10.1007/s11156-016-0570-4 |
| spellingShingle | Out-of-sample predictability; Long memory time series; Futures market regulation; Realized volatility; Econometric models Ying, Jiang Shamin, Ahmed Xiaoquan, Liu Volatility forecasting in the Chinese commodity futures market with intraday data |
| title | Volatility forecasting in the Chinese commodity futures market with intraday data |
| title_full | Volatility forecasting in the Chinese commodity futures market with intraday data |
| title_fullStr | Volatility forecasting in the Chinese commodity futures market with intraday data |
| title_full_unstemmed | Volatility forecasting in the Chinese commodity futures market with intraday data |
| title_short | Volatility forecasting in the Chinese commodity futures market with intraday data |
| title_sort | volatility forecasting in the chinese commodity futures market with intraday data |
| topic | Out-of-sample predictability; Long memory time series; Futures market regulation; Realized volatility; Econometric models |
| url | https://eprints.nottingham.ac.uk/34280/ https://eprints.nottingham.ac.uk/34280/ https://eprints.nottingham.ac.uk/34280/ |