Measuring parametric and semiparametric downside risks of selected agricultural commodities
In this paper, we evaluate the downside risk of six major agricultural commodities - corn, wheat, soybeans, soybean meal, soybean oil and oats. For research purposes, we first use an optimal generalised autoregressive conditional heteroscedasticity (GARCH) model to create residuals, which we later u...
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| Format: | Article |
| Language: | English |
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Czech Academy of Agricultural Sciences
2021-08-01
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| Series: | Agricultural Economics (AGRICECON) |
| Subjects: | |
| Online Access: | https://agricecon.agriculturejournals.cz/artkey/age-202108-0001_measuring-parametric-and-semiparametric-downside-risks-of-selected-agricultural-commodities.php |
| _version_ | 1828009324713082880 |
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| author | Dejan Živkov Marijana Joksimović Suzana Balaban |
| author_facet | Dejan Živkov Marijana Joksimović Suzana Balaban |
| author_sort | Dejan Živkov |
| collection | DOAJ |
| description | In this paper, we evaluate the downside risk of six major agricultural commodities - corn, wheat, soybeans, soybean meal, soybean oil and oats. For research purposes, we first use an optimal generalised autoregressive conditional heteroscedasticity (GARCH) model to create residuals, which we later use for measuring downside risks via parametric and semiparametric approaches. Modified value-at-risk (mVaR) and modified conditional value-at-risk (mCVaR) provide more accurate downside risk results than do ordinary value-at-risk (VaR) and conditional value-at-risk (CVaR). We report that soybean oil has the lowest mVaR and mCVaR because it has two very favourable features - skewness around zero and low kurtosis. The second-best commodity is soybeans. The worst-performing downside risk results are in wheat and oats, primarily because of their very high kurtosis values. On the basis of the results, we propose to investors and various agents involved with these agricultural assets that they reduce the risk of loss by combining these assets with other financial or commodity assets that have low risk. |
| first_indexed | 2024-04-10T08:36:56Z |
| format | Article |
| id | doaj.art-54732b2b247548a78bac32ace6199af1 |
| institution | Directory Open Access Journal |
| issn | 0139-570X 1805-9295 |
| language | English |
| last_indexed | 2024-04-10T08:36:56Z |
| publishDate | 2021-08-01 |
| publisher | Czech Academy of Agricultural Sciences |
| record_format | Article |
| series | Agricultural Economics (AGRICECON) |
| spelling | doaj.art-54732b2b247548a78bac32ace6199af12023-02-23T03:25:32ZengCzech Academy of Agricultural SciencesAgricultural Economics (AGRICECON)0139-570X1805-92952021-08-0167830531510.17221/148/2021-AGRICECONage-202108-0001Measuring parametric and semiparametric downside risks of selected agricultural commoditiesDejan Živkov0Marijana Joksimović1Suzana Balaban2Novi Sad School of Business, University of Novi Sad, Novi Sad, SerbiaFaculty of Finances, Banking and Audit, Alfa University, Belgrade, SerbiaFaculty of Finances, Banking and Audit, Alfa University, Belgrade, SerbiaIn this paper, we evaluate the downside risk of six major agricultural commodities - corn, wheat, soybeans, soybean meal, soybean oil and oats. For research purposes, we first use an optimal generalised autoregressive conditional heteroscedasticity (GARCH) model to create residuals, which we later use for measuring downside risks via parametric and semiparametric approaches. Modified value-at-risk (mVaR) and modified conditional value-at-risk (mCVaR) provide more accurate downside risk results than do ordinary value-at-risk (VaR) and conditional value-at-risk (CVaR). We report that soybean oil has the lowest mVaR and mCVaR because it has two very favourable features - skewness around zero and low kurtosis. The second-best commodity is soybeans. The worst-performing downside risk results are in wheat and oats, primarily because of their very high kurtosis values. On the basis of the results, we propose to investors and various agents involved with these agricultural assets that they reduce the risk of loss by combining these assets with other financial or commodity assets that have low risk.https://agricecon.agriculturejournals.cz/artkey/age-202108-0001_measuring-parametric-and-semiparametric-downside-risks-of-selected-agricultural-commodities.phpcornish-fisher expansiongeneralised autoregressive conditional heteroscedasticity (garch) modelgrains |
| spellingShingle | Dejan Živkov Marijana Joksimović Suzana Balaban Measuring parametric and semiparametric downside risks of selected agricultural commodities Agricultural Economics (AGRICECON) cornish-fisher expansion generalised autoregressive conditional heteroscedasticity (garch) model grains |
| title | Measuring parametric and semiparametric downside risks of selected agricultural commodities |
| title_full | Measuring parametric and semiparametric downside risks of selected agricultural commodities |
| title_fullStr | Measuring parametric and semiparametric downside risks of selected agricultural commodities |
| title_full_unstemmed | Measuring parametric and semiparametric downside risks of selected agricultural commodities |
| title_short | Measuring parametric and semiparametric downside risks of selected agricultural commodities |
| title_sort | measuring parametric and semiparametric downside risks of selected agricultural commodities |
| topic | cornish-fisher expansion generalised autoregressive conditional heteroscedasticity (garch) model grains |
| url | https://agricecon.agriculturejournals.cz/artkey/age-202108-0001_measuring-parametric-and-semiparametric-downside-risks-of-selected-agricultural-commodities.php |
| work_keys_str_mv | AT dejanzivkov measuringparametricandsemiparametricdownsiderisksofselectedagriculturalcommodities AT marijanajoksimovic measuringparametricandsemiparametricdownsiderisksofselectedagriculturalcommodities AT suzanabalaban measuringparametricandsemiparametricdownsiderisksofselectedagriculturalcommodities |