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Financial Crises, Financialization of Commodity Markets and Correlation of Agricultural Commodity Index with Precious Metal Index and S&P500

Author

Listed:
  • M.Fatih Oztek

    (Department of Economics, METU)

  • Nadir Ocal

    (Department of Economics, METU)

Abstract

This paper tests and models time varying correlations among agricultural commodity, precious metal and S&P500 indices to uncover whether rising trend among these markets is a result of financialization of commodity markets and/or financial crisis. We particularly investigate the roles of market news, global and market volatility on the nature and dynamics of the correlation. Empirical results show that high volatility during financial crisis is the main source of high correlation of agricultural commodity index with S&P500 and precious metal index, and plays crucial role in correlation between precious metal index and S&P500, possibly due to increasing engagement of financial market investors in commodity markets during financial crisis. Hence, heterogeneous structure of commodity markets delivers better portfolio diversification opportunities during calm periods compared to turmoil periods of financial crisis.

Suggested Citation

  • M.Fatih Oztek & Nadir Ocal, 2013. "Financial Crises, Financialization of Commodity Markets and Correlation of Agricultural Commodity Index with Precious Metal Index and S&P500," ERC Working Papers 1302, ERC - Economic Research Center, Middle East Technical University, revised Feb 2013.
    • Handle: RePEc:met:wpaper:1302
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    File URL: https://erc.metu.edu.tr/sites/erc.metu.edu.tr/files/menu/series13/1302.pdf
    File Function: First version, 2013
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    References listed on IDEAS

    as
    1. Ke Tang & Wei Xiong, 2012. "Index Investment and the Financialization of Commodities," Financial Analysts Journal, Taylor & Francis Journals, vol. 68(6), pages 54-74, November.
    2. AfDB AfDB, . "AfDB Group Annual Report 2007," Annual Report, African Development Bank, number 63 edited by Koua Louis Kouakou.
    3. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    4. Annastiina Silvennoinen & Timo Teräsvirta, 2009. "Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 373-411, Fall.
    5. Nadir Ocal & Denise R. Osborn, 2000. "Business cycle non-linearities in UK consumption and production," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 27-43.
    6. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    7. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    8. Silvennoinen, Annastiina & Teräsvirta, Timo, 2005. "Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations," SSE/EFI Working Paper Series in Economics and Finance 577, Stockholm School of Economics, revised 01 Oct 2005.
    9. Oecd, 2008. "RFID Guidance and Reports," OECD Digital Economy Papers 150, OECD Publishing.
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    Citations

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    Cited by:

    1. Adam Zaremba, 2015. "Portfolio Diversification with Commodities in Times of Financialization," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 4(1), pages 18-36, January.
    2. Srivastava, Mrinalini & Rao, Amar & Parihar, Jaya Singh & Chavriya, Shubham & Singh, Surendar, 2023. "What do the AI methods tell us about predicting price volatility of key natural resources: Evidence from hyperparameter tuning," Resources Policy, Elsevier, vol. 80(C).

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    Keywords

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    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
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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