Economic forecasting based on copula quantile curves and beliefs
© 2014 by the Mathematical Association of Thailand. All rights reserved. This paper applies belief functions-based copula quantile curves model to capture dependence structure between crude oil and corn returns, and quantify uncertainty of the corn returns at one step period. We employ the time-vary...
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th-cmuir.6653943832-391372015-06-16T08:07:42Z Economic forecasting based on copula quantile curves and beliefs Liu,J. Sriboonchitta,S. Mathematics (all) © 2014 by the Mathematical Association of Thailand. All rights reserved. This paper applies belief functions-based copula quantile curves model to capture dependence structure between crude oil and corn returns, and quantify uncertainty of the corn returns at one step period. We employ the time-varying copulas, including Gaussian, T and Clayton, which can be used to capture dynamic correlations between variables. We forecast their correlation ahead of one period, and the uncertainty of corn returns ahead of one period is measured under p-th copula quantile curves. The empirical results show the range of corn returns and its uncertainties under 5% and 95% copula quantile curves. In addition, the time-varying T copula describes the dependence structure between crude oil and corn returns quite well. 2015-06-16T08:07:42Z 2015-06-16T08:07:42Z 2014-01-01 Article 16860209 2-s2.0-84907244609 http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84907244609&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39137 Chiang Mai University |
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Mathematics (all) Liu,J. Sriboonchitta,S. Economic forecasting based on copula quantile curves and beliefs |
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© 2014 by the Mathematical Association of Thailand. All rights reserved. This paper applies belief functions-based copula quantile curves model to capture dependence structure between crude oil and corn returns, and quantify uncertainty of the corn returns at one step period. We employ the time-varying copulas, including Gaussian, T and Clayton, which can be used to capture dynamic correlations between variables. We forecast their correlation ahead of one period, and the uncertainty of corn returns ahead of one period is measured under p-th copula quantile curves. The empirical results show the range of corn returns and its uncertainties under 5% and 95% copula quantile curves. In addition, the time-varying T copula describes the dependence structure between crude oil and corn returns quite well. |
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Liu,J. Sriboonchitta,S. |
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Liu,J. Sriboonchitta,S. |
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Liu,J. |
title |
Economic forecasting based on copula quantile curves and beliefs |
title_short |
Economic forecasting based on copula quantile curves and beliefs |
title_full |
Economic forecasting based on copula quantile curves and beliefs |
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Economic forecasting based on copula quantile curves and beliefs |
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Economic forecasting based on copula quantile curves and beliefs |
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economic forecasting based on copula quantile curves and beliefs |
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Chiang Mai University |
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2015 |
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http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84907244609&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/39137 |
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