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Forecasting Changes in Copper Futures Volatility with GARCH Models Using an Iterated Algorithm

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  • Smith, Kenneth L
  • Bracker, Kevin

Abstract

There is a gap in the literature regarding the out-of-sample forecasting ability of GARCH-type models applied to derivatives. A practitioner-oriented method (iterated cumulative sum of squares) is applied to detecting breakpoints in the variance of two copper futures series. Short-, intermediate-, and long-term out-of-sample forecasts of copper future series are compared to forecasts from a benchmark random walk model for each series. Not only do the GARCH-type models dominate the random walk model, but the relative improvement is fairly consistent across series, forecast horizon, and GARCH-type model. The evidence makes clear that, with few exceptions, the forecast improvement of the GARCH-type models over the RW model lies somewhere between 20-30 percent. It is particularly true that for the long-term close to close forecasts, there is great coherence among the forecasts. These all fall within a fairly narrow range. Copyright 2003 by Kluwer Academic Publishers

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  • Smith, Kenneth L & Bracker, Kevin, 2003. "Forecasting Changes in Copper Futures Volatility with GARCH Models Using an Iterated Algorithm," Review of Quantitative Finance and Accounting, Springer, vol. 20(3), pages 245-265, May.
    • Handle: RePEc:kap:rqfnac:v:20:y:2003:i:3:p:245-65
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    Citations

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    Cited by:

    1. Chan, Wing Hong & Young, Denise, 2009. "A New Look at Copper Markets: A Regime-Switching Jump Model," Working Papers 2009-13, University of Alberta, Department of Economics.
    2. Joe Brocato & Kenneth Smith, 2012. "Sudden equity price declines and the flight-to-safety phenomenon: additional evidence using daily data," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(3), pages 712-727, July.
    3. Shawkat M.Hammoudeh & Yuan Yuan & Michael McAleer, 2010. "Exchange Rate and Industrial Commodity Volatility Transmissions, Asymmetries and Hedging Strategies," Working Papers in Economics 10/33, University of Canterbury, Department of Economics and Finance.
    4. Zian Wang & Xinyi Lu, 2024. "COMEX Copper Futures Volatility Forecasting: Econometric Models and Deep Learning," Papers 2409.08356, arXiv.org.
    5. Shawkat M. Hammoudeh & Yuan Yuan & Michael McAleer, 2009. "Exchange Rate and Industrial Commodity Volatility Transmissions and Hedging Strategies," CARF F-Series CARF-F-172, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    6. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    7. Phillip A. Cartwright & Natalija Riabko, 2019. "Do spot food commodity and oil prices predict futures prices?," Review of Quantitative Finance and Accounting, Springer, vol. 53(1), pages 153-194, July.
    8. Wang, Chao & Zhang, Xinyi & Wang, Minggang & Lim, Ming K. & Ghadimi, Pezhman, 2019. "Predictive analytics of the copper spot price by utilizing complex network and artificial neural network techniques," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    9. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2021. "Economic drivers of commodity volatility: The case of copper," Resources Policy, Elsevier, vol. 73(C).
    10. Farooq Malik, 2015. "Revisiting the relationship between risk and return," Review of Quantitative Finance and Accounting, Springer, vol. 44(1), pages 25-40, January.
    11. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2020. "A random walk through the trees: Forecasting copper prices using decision learning methods," Resources Policy, Elsevier, vol. 69(C).
    12. Tapia, Carlos & Coulton, Jeff & Saydam, Serkan, 2020. "Using entropy to assess dynamic behaviour of long-term copper price," Resources Policy, Elsevier, vol. 66(C).
    13. Guo, Jin, 2018. "Co-movement of international copper prices, China's economic activity, and stock returns: Structural breaks and volatility dynamics," Global Finance Journal, Elsevier, vol. 36(C), pages 62-77.
    14. Zian Wang & Xinshu Li, 2024. "On the macroeconomic fundamentals of long-term volatilities and dynamic correlations in COMEX copper futures," Papers 2409.08355, arXiv.org.

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