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Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices

Author

Listed:
  • Chia-Lin Chang

    (Department of Applied Economics Department of Finance National Chung Hsing University, Taiwan)

  • Michael McAleer

    (Department of Quantitative Finance National Tsing Hua University, Taiwan)

  • Yu-Ann Wang

    (Department of Applied Economics National Chung Hsing University Taichung, Taiwan)

Abstract

The recent and rapidly growing interest in biofuel as a green energy source has raised concerns about its impact on the prices, returns and volatility of related agricultural commodities. Analyzing the spillover effects on agricultural commodities and biofuel helps commodity suppliers hedge their portfolios, and manage the risk and co-risk of their biofuel and agricultural commodities. There have been many papers concerned with analyzing crude oil and agricultural commodities separately. The purpose of this paper is to examine the volatility spillovers for spot and futures returns on bio-ethanol and related agricultural commodities, specifically corn and sugarcane. The diagonal BEKK model is used as it is the only multivariate conditional volatility model with well-established regularity conditions and known asymptotic properties. The daily data used are from 31 October 2005 to 14 January 2015. The empirical results show that, in 2 of 6 cases for the spot market, there were significant negative co-volatility spillover effects: specifically, corn on subsequent sugarcane co-volatility with corn, and sugarcane on subsequent corn co-volatility with sugarcane. In the other 4 cases, there are no significant co-volatility spillover effects. There are significant positive co-volatility spillover effects in all 6 cases, namely between corn and sugarcane, corn and ethanol, and sugarcane and ethanol, and vice-versa, for each of the three pairs of commodities. It is clear that the futures prices of bio-ethanol and the two agricultural commodities, corn and sugarcane, have stronger co-volatility spillovers than their spot price counterparts. These empirical results suggest that the bio-ethanol and agricultural commodities should be considered as viable futures products in financial portfolios for risk management.

Suggested Citation

  • Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices," Documentos de Trabajo del ICAE 2017-04, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Handle: RePEc:ucm:doicae:1704
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    Cited by:

    1. Chia-Lin Chang & Chia-Ping Liu & Michael McAleer, 2016. "Volatility Spillovers for Spot, Futures, and ETF Prices in Energy and Agriculture," Tinbergen Institute Discussion Papers 16-046/III, Tinbergen Institute.
    2. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2018. "Latent Volatility Granger Causality and Spillovers in Renewable Energy and Crude Oil ETFs," Documentos de Trabajo del ICAE 2018-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    3. Chia-Lin Chang & Michael McAleer & Guangdong Zuo, 2017. "Volatility Spillovers and Causality of Carbon Emissions, Oil and Coal Spot and Futures for the EU and USA," Sustainability, MDPI, Open Access Journal, vol. 9(10), pages 1-22, October.
    4. repec:gam:jrisks:v:6:y:2018:i:4:p:120-:d:175263 is not listed on IDEAS
    5. Chia-Lin Chang & Michael McAleer & Chien-Hsun Wang, 2017. "An Econometric Analysis of ETF and ETF Futures in Financial and Energy Markets Using Generated Regressors," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 6(1), pages 1-24, December.
    6. repec:gam:jsusta:v:10:y:2018:i:11:p:4307-:d:184277 is not listed on IDEAS
    7. repec:gam:jeners:v:11:y:2018:i:6:p:1595-:d:153161 is not listed on IDEAS
    8. Michael mcAleer, 2017. "Stationarity and Invertibility of a Dynamic Correlation Matrix," Tinbergen Institute Discussion Papers 17-082/III, Tinbergen Institute.
    9. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, Open Access Journal, vol. 11(6), pages 1-19, June.
    10. Chang, Chia-Lin & McAleer, Michael & Wang, Yanghuiting, 2018. "Testing Co-Volatility spillovers for natural gas spot, futures and ETF spot using dynamic conditional covariances," Energy, Elsevier, vol. 151(C), pages 984-997.
    11. Chang, C-L. & Hsu, S.-H. & McAleer, M.J., 2018. "Risk Spillovers in Returns for Chinese and International Tourists to Taiwan," Econometric Institute Research Papers 18-031/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Chia-Lin Chang & Michael McAleer & Jiarong Tian, 2016. "Modelling and Testing Volatility Spillovers in Oil and Financial Markets for USA, UK and China," Tinbergen Institute Discussion Papers 16-053/III, Tinbergen Institute.
    13. Chia-Lin Chang & Michael McAleer, 2018. "The Fiction of Full BEKK: Pricing Fossil Fuels and Carbon Emissions," Documentos de Trabajo del ICAE 2018-08, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    14. repec:gam:jjrfmx:v:11:y:2018:i:4:p:58-:d:172906 is not listed on IDEAS
    15. repec:eee:appene:v:215:y:2018:i:c:p:630-642 is not listed on IDEAS
    16. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(4), pages 1-25, September.
    17. Chang, C-L. & Hsu, S.-H. & McAleer, M.J., 2018. "An Event Study of Chinese Tourists to Taiwan," Econometric Institute Research Papers 2018-003/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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    Keywords

    BBiofuel; Spot prices; Futures prices; Returns; Volatility; Risk; Co-risk; Bio-ethanol; Corn; Sugarcane; Diagonal BEKK model; Co-volatility spillover effects; Hedging; Risk management.;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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