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 use for measuring downside risks via parametric and semiparametric … celý popis
Uloženo v:
Podrobná bibliografie
- Hlavní autor
- Další autoři
- Typ dokumentu
- Články
- Fyzický popis
- 12 ilustrací
- Publikováno v
- Agricultural Economics. -- ISSN 0139-570X. -- Roč. 67, č. 8 (2021), s. 305-315
- Témata
- Popis jednotky
- 6 grafů, 6 tabulek
- Bibliografie
- Seznam literatury na s. 314-315 (19 záznamů)
Instituce:
Česká zemědělská a potravinářská bibliografie
MARC
| LEADER | 00000naa a2200000 i 4500 | ||
|---|---|---|---|
| 001 | czpb000187508 | ||
| FMT | A | N | |
| LDR | 0 | 0 | |0 0naa a22 i 4500 |
| 003 | CZ PrUZP | ||
| 005 | 20230418142444.0 | ||
| 007 | ta | ||
| 007 | cr cn ||||| | ||
| 008 | 211011s2021 xr ad f b 000 0 eng d | ||
| 040 | |a ABA009 |b cze |e rda | ||
| 043 | |a e-rb--- | ||
| 072 | 7 | |a 631 |x Zemědělství. Pedologie. Agrotechnika. Agroekologie |2 Konspekt |9 24 | |
| 072 | 7 | |a 339 |x Obchod |2 Konspekt |9 4 | |
| 080 | |a 631.57 |2 MRF | ||
| 080 | |a 339.15.054.22/.23 |2 MRF | ||
| 100 | 1 | |a Živkov, Dejan, |u University of Novi Sad, Novi Sad School of Business, Novi Sad, Serbia |4 aut | |
| 245 | 1 | 0 | |a Measuring parametric and semiparametric downside risks of selected agricultural commodities / |c Dejan Živkov, Marijana Joksimović, Suzana Balaban |
| 300 | |b 12 ilustrací | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a bez média |b n |2 rdamedia | ||
| 338 | |a svazek |b nc |2 rdacarrier | ||
| 500 | |a 6 grafů, 6 tabulek | ||
| 504 | |a Seznam literatury na s. 314-315 (19 záznamů) | ||
| 520 | 3 | 9 | |a 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 incen y 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. |9 eng |
| 530 | |a Dostupné též na internetu | ||
| 546 | |a Anglický text, anglický abstrakt | ||
| 650 | 0 | 9 | |a Serbia |2 agrovoc |
| 650 | 0 | 9 | |a MAIZE |2 agrovoc |
| 650 | 0 | 9 | |a WHEATS |2 agrovoc |
| 650 | 0 | 9 | |a SOYBEANS |2 agrovoc |
| 650 | 0 | 9 | |a SOYBEAN FLOUR |2 agrovoc |
| 650 | 0 | 9 | |a SOYBEAN OIL |2 agrovoc |
| 650 | 0 | 9 | |a OATS |2 agrovoc |
| 650 | 0 | 9 | |a Agricultural prices |2 agrovoc |
| 650 | 0 | 9 | |a risk analysis |2 agrovoc |
| 650 | 0 | 9 | |a finance |2 agrovoc |
| 650 | 0 | 9 | |a ASSETS |2 agrovoc |
| 650 | 0 | 9 | |a Economic losses |2 agrovoc |
| 650 | 0 | 9 | |a ECONOMETRIC MODELS |2 agrovoc |
| 650 | 0 | 9 | |a QUANTITATIVE ANALYSIS |2 agrovoc |
| 650 | 0 | 9 | |a calculation |2 agrovoc |
| 653 | 0 | |a fluktuace cen | |
| 650 | 0 | 7 | |a Srbsko |2 agrovoc |
| 650 | 0 | 7 | |a kukuřičné zrno |2 agrovoc |
| 650 | 0 | 7 | |a pšenice |2 agrovoc |
| 650 | 0 | 7 | |a sója |2 agrovoc |
| 650 | 0 | 7 | |a sójová mouka |2 agrovoc |
| 650 | 0 | 7 | |a sójový olej |2 agrovoc |
| 650 | 0 | 7 | |a ovsy |2 agrovoc |
| 650 | 0 | 7 | |a ceny zemědělských produktů |2 agrovoc |
| 650 | 0 | 7 | |a analýza rizika |2 agrovoc |
| 650 | 0 | 7 | |a finance |2 agrovoc |
| 650 | 0 | 7 | |a aktiva |2 agrovoc |
| 650 | 0 | 7 | |a ekonomické ztráty |2 agrovoc |
| 650 | 0 | 7 | |a ekonometrické modely |2 agrovoc |
| 650 | 0 | 7 | |a kvantitativní analýza |2 agrovoc |
| 650 | 0 | 7 | |a výpočet |2 agrovoc |
| 700 | 1 | |a Joksimović, Marijana, |u Alfa University, Faculty of Finances, Banking and Audit, Belgrade, Serbia |4 aut | |
| 700 | 1 | |a Balaban, Suzana, |u Alfa University, Faculty of Finances, Banking and Audit, Belgrade, Serbia |4 aut | |
| 773 | 0 | |t Agricultural Economics |x 0139-570X |g Roč. 67, č. 8 (2021), s. 305-315 |q 67:8 |9 2021 | |
| 856 | 4 | 1 | |u https://agricecon.agriculturejournals.cz/pdfs/age/2021/08/01.pdf |4 N |9 HTM |
| LKR | |a ITM |b 97018 |l UZP50 |y 2021 | ||
| 910 | |a ABA009 |t rs | ||
| CAS | |a a | ||
| SIF | |z DN |d 20211011 | ||