Coherent Quantitative Analysis of Risks in Agribusiness: Case of Ukraine
Modern methods of quantitative risk analysis, specifically value-at-risk and expected shortfall approach, provide comprehensive and coherent risk evaluation throughout entire distribution of outcomes and can take agricultural business from the realm of uncertainty to specific, quantified risks. Monte Carlo simulation with autocorrelation of standard deviation shows the best results in risk modeling and is used for this research. The analysis showed that production risk is systemic within climatic regions of Ukraine with coefficients of correlation ranging from 0.25 to 0.85. Yield correlation among crops in several oblasts is low to negative, creating opportunities for diversification. However, positive price-yield correlation is dominant for agricultural products in Ukraine due to high dependency on global prices and a large share of export. It is hypothesized that price-yield correlation is directly proportional to the share of countryâ€™s international trade in that agricultural product.
Volume (Year): 3 (2011)
Issue (Month): 4 (December)
|Contact details of provider:|| Postal: Kamycka 129, 165 21 Praha 6 - Suchdol|
Web page: http://online.agris.cz/
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Harwood, Joy L. & Heifner, Richard G. & Coble, Keith H. & Perry, Janet E. & Somwaru, Agapi, 1999. "Managing Risk in Farming: Concepts, Research, and Analysis," Agricultural Economics Reports 34081, United States Department of Agriculture, Economic Research Service.
- Wyn Morgan & John Cotter & Kevin Dowd, 2012.
"Extreme Measures of Agricultural Financial Risk,"
Journal of Agricultural Economics,
Wiley Blackwell, vol. 63(1), pages 65-82, 02.
- Cotter, John & Dowd, Kevin & Morgan, C. Wyn, 2008. "Extreme Measures of Agricultural Financial Risk," Miscellaneous Papers 101971, Agecon Search.
- John Cotter & Kevin Dowd & Wyn Morgan, 2011. "Extreme Measures of Agricultural Financial Risk," Papers 1103.5962, arXiv.org.
- Danielsson, Jon & Jorgensen, Bjorn N. & Sarma, Mandira & de Vries, Casper G., 2006. "Comparing downside risk measures for heavy tailed distributions," Economics Letters, Elsevier, vol. 92(2), pages 202-208, August.
- Jon Danielsson & Bjørn N. Jorgensen & Mandira Sarma & C. G. de Vries, 2005. "Comparing downside risk measures for heavy tailed distribution," LSE Research Online Documents on Economics 24671, London School of Economics and Political Science, LSE Library.
- Casper G. de Vries & Bjørn N. Jorgensen & Sarma Mandira & Jon Danielsson, 2005. "Comparing Downside Risk Measures for Heavy Tailed Distributions," FMG Discussion Papers dp551, Financial Markets Group.
- Ibrahim Onour, "undated". "Forecasting Volatility in Global Food Commodity Prices," API-Working Paper Series 1101, Arab Planning Institute - Kuwait, Information Center.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Yamai, Yasuhiro & Yoshiba, Toshinao, 2005. "Value-at-risk versus expected shortfall: A practical perspective," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 997-1015, April.
- Filip Iorgulescu, 2009. "Value at Risk: A Comparative Analysis," Advances in Economic and Financial Research - DOFIN Working Paper Series 25, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:ags:aolpei:120240. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.