Agric. Econ. - Czech, 2023, 69(3):109-118 | DOI: 10.17221/371/2022-AGRICECON

How to reduce the extreme risk of losses in corn and soybean markets? Construction of a portfolio with European stock indicesOriginal Paper

Dejan Živkov1, Biljana Stankov1, Nataša Papić-Blagojević1, Jelena Damnjanović1, Željko Račić1
1 Department of Economics, Novi Sad School of Business, University of Novi Sad, Novi Sad, Serbia

Because of the COVID-19 pandemic and the war in Ukraine, agricultural commodities had significant price increases, which inevitably implies high risk. In this article, we try to mitigate the extreme risk of corn and soybeans by constructing multivariate portfolios with developed and emerging European stock indices. We measured extreme risk via conditional value at risk. To address different goals that investors might prefer, we produced portfolios with the lowest risk and highest return-to-risk ratio. According to the results, corn and soybeans had relatively high portfolio shares. However, they are the riskiest assets because they have a very low pairwise correlation with the stock indices. Portfolios with emerging European indices had better risk-reducing results, considering both agricultural commodities because these indices are less risky than developed indices. In particular, the risk reductions of corn were 38% and 50% in the portfolios with developed and emerging stock indices, respectively, whereas, for soybeans, the results were 28% and 41%, respectively. In optimal portfolios, emerging European stock indices had the upper hand in most cases.

Keywords: agricultural commodities; portfolio optimisation; risk-minimising optimal portfolios

Received: December 5, 2022; Accepted: February 6, 2023; Prepublished online: March 10, 2023; Published: March 30, 2023  Show citation

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Živkov D, Stankov B, Papić-Blagojević N, Damnjanović J, Račić Ž. How to reduce the extreme risk of losses in corn and soybean markets? Construction of a portfolio with European stock indices. Agric. Econ. - Czech. 2023;69(3):109-118. doi: 10.17221/371/2022-AGRICECON.
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References

  1. Alexakis C., Bagnarosa G., Dowling M. (2017): Do cointegrated commodities bubble together? The case of hog, corn, and soybean. Finance Research Letters, 23: 96-102. Go to original source...
  2. Altun E., Alizadeh M., Ozel G., Tatlidil H., Maksayi N. (2017): Forecasting Value-at-Risk with two-step method: GARCH-exponentiated odd log-logistic normal model. Romanian Journal of Economic Forecasting, 20: 97-115.
  3. Chenarides L., Grebitus C., Lusk J.L., Printezis I. (2021): Food consumption behavior during the COVID-19 pandemic. Agribusiness, 37: 44-81. Go to original source... Go to PubMed...
  4. Elliott L., Elliott M., Slaa C.T., Wang Z. (2020): New generation grain contracts in corn and soybean commodity markets. Journal of Commodity Markets, 20: 100113. Go to original source...
  5. FAO (2022). Food and Agriculture Organisation of the United Nations. Available at https://www.fao.org/home/en (accessed Nov 1, 2022).
  6. Li J., Huang H., Xiao X. (2012): The sovereign property of foreign reserve investment in China: A CVaR approach. Economic Modelling, 29: 1524-1536. Go to original source...
  7. Luan F., Zhang W., Liu Y. (2022): Robust international portfolio optimisation with worst-case mean-CVaR. European Journal of Operational Research, 303: 877-890. Go to original source...
  8. Markowitz H (1952): Portfolio selection. Journal of Finance, 7: 77-91. Go to original source...
  9. Martin D., Rachev S.T., Siboulet F. (2003): Phi-Alpha optimal portfolios and extreme risk management. Wilmott, 6: 70-83. Go to original source...
  10. Massahi M., Mahootchi M., Khamseh A.A. (2020): Development of an efficient cluster-based portfolio optimisation model under realistic market conditions. Empirical Economics, 59: 2423-2442. Go to original source...
  11. Minondo A. (2021): Impact of COVID-19 on the trade of goods and services in Spain. Applied Economic Analysis, 29: 58-76. Go to original source...
  12. Moncarz P.E., Barone S.V. (2020): Rising commodity prices and welfare in Brazil: A simulation of medium-term effects using a SAM price model. International Journal of Emerging Markets, 15: 1029-1060. Go to original source...
  13. Naeem M.A., Hasan M., Arif M., Suleman M.T., Kang S.H. (2022): Oil and gold as a hedge and safe-haven for metals and agricultural commodities with portfolio implications. Energy Economics, 105: 105758 Go to original source...
  14. Palanska T. (2020): Measurement of volatility spillovers and asymmetric connectedness on commodity and equity markets. Czech Journal of Economics and Finance, 70: 42-69.
  15. Rockafellar R.T., Uryasev S. (2002): Conditional Value-at-Risk for general loss distributions. Journal of Banking and Finance, 26: 1443-1471. Go to original source...
  16. Saâdaoui F., Jabeur S.B., Goodell J.W. (2022): Causality of geopolitical risk on food prices: Considering the Russo-Ukrainian conflict. Finance Research Letters, 49: 103103. Go to original source...
  17. Sajjad R., Coakley J., Nankervis J.C. (2008): Markov-Switching GARCH modelling of Value-at-Risk. Studies in Nonlinear Dynamics and Econometrics, 12: 1-31. Go to original source...
  18. Stooq (2022): Stooq. [Dataset]. Available at https://stooq.com/q/?s=zc.c (accessed Nov 1, 2022).
  19. Vo D.H., Pham T.N., Pham T.T.V., Truong L.M., Nguyen T.C. (2019): Risk, return and portfolio optimisation for various industries in the ASEAN region. Borsa Istanbul Review, 19: 132-138. Go to original source...
  20. Wu F., Guan Z., Myers R. (2011): Volatility spillover effects and cross hedging in corn and crude oil futures. Journal of Futures Markets, 31: 1052-1075. Go to original source...
  21. Zhu N.J., Feng Y.L. (2017): Optimal change-loss reinsurance contract design under tail risk measures for catastrophe insurance. Economic Computation and Economic Cybernetics Studies and Research, 51: 225-242.
  22. Živkov D., Balaban P., Kuzman B. (2021): How to combine precious metals with corn in a risk-minimising two-asset portfolio? Agricultural Economics - Czech, 67: 60-6 Go to original source...

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