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Does the substitution effect lead to feedback effect linkage between ethanol, crude oil, and soft agricultural commodities?

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  • Kumar, Pawan
  • Singh, Vipul Kumar
  • Rao, Sandeep

Abstract

Despite increased demand for cleaner fuel alternatives such as ethanol in recent decades, portfolio weight allocation has become challenging due to the complex interlinkage amongst crude, ethanol and soft agricultural commodities that form part of the value chain. As a result, portfolio returns face three trade-offs in terms of risk: dispersion across mean, risk arising due to market interconnectedness, and risk arising due to global shocks for assets sharing common macroeconomic fundamentals. This study proposes an optimal weight allocation portfolio strategy, encapsulating the three risk measures and returns, estimated using state-of-the-art multi-objective elitist Non-Dominated Sorting Algorithm II (NSGA-II). Our proposed strategy performs well for newly constituted objectives against the Markowitz Mean-Variance approach and Global Minimum Variance. A balanced diversification escapes the feedback spillover loop trap at the same time. Our results indicate that soybean oil, sugar, and rice offer a better reward to risk, aiding portfolio immunisation to extreme market movements. Furthermore, using GJR-GARCH volatility to capture the volatility asymmetry effect, the Generalized Forecast Error Variance Decomposition (GFEVD) shows the existence of a strong triplet pair Crude-Ethanol-Soybean as a breeding ground for the feedback effect to occur. Moreover, replacing crude weight with ethanol depicts a fall in spillover risk up to a threshold of 30% Ethanol weight, after which the feedback effect kicks in.

Suggested Citation

  • Kumar, Pawan & Singh, Vipul Kumar & Rao, Sandeep, 2023. "Does the substitution effect lead to feedback effect linkage between ethanol, crude oil, and soft agricultural commodities?," Energy Economics, Elsevier, vol. 119(C).
  • Handle: RePEc:eee:eneeco:v:119:y:2023:i:c:s0140988323000725
    DOI: 10.1016/j.eneco.2023.106574
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    as
    1. Coudert, Virginie & Mignon, Valérie, 2016. "Reassessing the empirical relationship between the oil price and the dollar," Energy Policy, Elsevier, vol. 95(C), pages 147-157.
    2. Teresa Serra & David Zilberman & José Gil, 2011. "Price volatility in ethanol markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 38(2), pages 259-280, June.
    3. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    5. Jiang, Yonghong & Fu, Yuyuan & Ruan, Weihua, 2019. "Risk spillovers and portfolio management between precious metal and BRICS stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    6. Anthony Paris, 2018. "On the link between oil and agricultural commodity prices: Do biofuels matter?," International Economics, CEPII research center, issue 155, pages 48-60.
    7. Trujillo-Barrera, Andres & Mallory, Mindy L. & Garcia, Philip, 2012. "Volatility Spillovers in U.S. Crude Oil, Ethanol, and Corn Futures Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-16, August.
    8. Dario Caldara & Matteo Iacoviello, 2022. "Measuring Geopolitical Risk," American Economic Review, American Economic Association, vol. 112(4), pages 1194-1225, April.
    9. Chang, Chia-Lin & McAleer, Michael & Wang, Yu-Ann, 2018. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn spot and futures prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1002-1018.
    10. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    11. David C. Broadstock & Ioannis Chatziantoniou & David Gabauer, 2022. "Minimum Connectedness Portfolios and the Market for Green Bonds: Advocating Socially Responsible Investment (SRI) Activity," Springer Books, in: Christos Floros & Ioannis Chatziantoniou (ed.), Applications in Energy Finance, chapter 0, pages 217-253, Springer.
    12. Herskovic, Bernard & Kelly, Bryan & Lustig, Hanno & Van Nieuwerburgh, Stijn, 2016. "The common factor in idiosyncratic volatility: Quantitative asset pricing implications," Journal of Financial Economics, Elsevier, vol. 119(2), pages 249-283.
    13. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    14. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    15. Gomez-Gonzalez, Jose E. & Hirs-Garzon, Jorge & Uribe, Jorge M., 2022. "Spillovers beyond the variance: Exploring the higher order risk linkages between commodity markets and global financial markets," Journal of Commodity Markets, Elsevier, vol. 28(C).
    16. Dahl, Roy Endré & Oglend, Atle & Yahya, Muhammad, 2020. "Dynamics of volatility spillover in commodity markets: Linking crude oil to agriculture," Journal of Commodity Markets, Elsevier, vol. 20(C).
    17. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    18. Deaton, Angus & Laroque, Guy, 1995. "Estimating a Nonlinear Rational Expectations Commodity Price Model with Unobservable State Variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(S), pages 9-40, Suppl. De.
    19. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    20. Nam, Kyungsik, 2021. "Investigating the effect of climate uncertainty on global commodity markets," Energy Economics, Elsevier, vol. 96(C).
    21. Ben Ameur, Hachmi & Ftiti, Zied & Louhichi, Waël, 2021. "Intraday spillover between commodity markets," Resources Policy, Elsevier, vol. 74(C).
    22. Singh, Vipul Kumar & Kumar, Pawan & Nishant, Shreyank, 2019. "Feedback spillover dynamics of crude oil and global assets indicators: A system-wide network perspective," Energy Economics, Elsevier, vol. 80(C), pages 321-335.
    23. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    24. Christopher Gilbert & Wyn Morgan, 2010. "Has food price volatility risen?," Department of Economics Working Papers 1002, Department of Economics, University of Trento, Italia.
    25. Chiu, Fan-Ping & Hsu, Chia-Sheng & Ho, Alan & Chen, Chi-Chung, 2016. "Modeling the price relationships between crude oil, energy crops and biofuels," Energy, Elsevier, vol. 109(C), pages 845-857.
    26. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    27. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Yoon, Seong-Min, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 225-243.
    28. Antonakakis, Nikolaos & Gabauer, David, 2017. "Refined Measures of Dynamic Connectedness based on TVP-VAR," MPRA Paper 78282, University Library of Munich, Germany.
    29. Tim Bollerslev & Julia Litvinova & George Tauchen, 2006. "Leverage and Volatility Feedback Effects in High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 353-384.
    30. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    31. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    32. Natanelov, Valeri & Alam, Mohammad J. & McKenzie, Andrew M. & Van Huylenbroeck, Guido, 2011. "Is there co-movement of agricultural commodities futures prices and crude oil?," Energy Policy, Elsevier, vol. 39(9), pages 4971-4984, September.
    33. Kumar, Pawan & Singh, Vipul Kumar, 2022. "Does crude oil fire the emerging markets currencies contagion spillover? A systemic perspective," Energy Economics, Elsevier, vol. 116(C).
    34. Pham, Linh & Do, Hung Xuan, 2022. "Green bonds and implied volatilities: Dynamic causality, spillovers, and implications for portfolio management," Energy Economics, Elsevier, vol. 112(C).
    35. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    36. Just, Małgorzata & Echaust, Krzysztof, 2022. "Dynamic spillover transmission in agricultural commodity markets: What has changed after the COVID-19 threat?," Economics Letters, Elsevier, vol. 217(C).
    37. Zibin Zhang & Luanne Lohr & Cesar Escalante & Michael Wetzstein, 2009. "Ethanol, Corn, and Soybean Price Relations in a Volatile Vehicle-Fuels Market," Energies, MDPI, vol. 2(2), pages 1-20, June.
    38. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    39. Fernandez-Perez, Adrian & Frijns, Bart & Tourani-Rad, Alireza, 2016. "Contemporaneous interactions among fuel, biofuel and agricultural commodities," Energy Economics, Elsevier, vol. 58(C), pages 1-10.
    40. Christos Floros & Ioannis Chatziantoniou (ed.), 2022. "Applications in Energy Finance," Springer Books, Springer, number 978-3-030-92957-2, December.
    41. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adewuyi, Adeolu O. & Lee, Chien-Chiang, 2022. "Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Energy Economics, Elsevier, vol. 113(C).
    42. Engle, Robert F. & Campos-Martins, Susana, 2023. "What are the events that shake our world? Measuring and hedging global COVOL," Journal of Financial Economics, Elsevier, vol. 147(1), pages 221-242.
    43. Khalfaoui, Rabeh & Sarwar, Suleman & Tiwari, Aviral Kumar, 2019. "Analysing volatility spillover between the oil market and the stock market in oil-importing and oil-exporting countries: Implications on portfolio management," Resources Policy, Elsevier, vol. 62(C), pages 22-32.
    44. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
    45. Chang, Ting-Huan & Su, Hsin-Mei, 2010. "The substitutive effect of biofuels on fossil fuels in the lower and higher crude oil price periods," Energy, Elsevier, vol. 35(7), pages 2807-2813.
    46. Liu, Li, 2014. "Cross-correlations between crude oil and agricultural commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 293-302.
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    2. Subrata K. Mitra & Debdatta Pal, 2024. "Role of Crude Oil in Determining the Price of Corn in the United States: A Non-parametric Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 22(2), pages 395-420, June.

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    More about this item

    Keywords

    Crude oil; Ethanol; Systemic risk; COVOL; Feedback effect;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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