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Financial stress and realized volatility: The case of agricultural commodities

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  • Bonato, Matteo
  • Cepni, Oguzhan
  • Gupta, Rangan
  • Pierdzioch, Christian

Abstract

Given recent debates about the financialization of commodity markets, we analyze the predictive power of financial stress for the realized volatility of agricultural commodity price returns. We estimate realized volatility from high-frequency intra-day data, where the sample period ranges from 2009 to 2020. We study the in-sample and out-of-sample predictability of realized volatility using variants of the popular heterogeneous autoregressive (HAR) model for realized volatility. We analyze the predictive value of financial stress by region of origin and by financial source, and we also control for various realized moments (leverage, realized skewness, realized kurtosis, realized jumps, realized upside tail risk, and realized downside tail risk). We find for several commodities evidence of in-sample predictive value of financial stress for realized volatility, consistent with the financialization hypothesis. This in-sample evidence, however, does not necessarily extend to an out-of-sample forecasting environment.

Suggested Citation

  • Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2024. "Financial stress and realized volatility: The case of agricultural commodities," Research in International Business and Finance, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:riibaf:v:71:y:2024:i:c:s0275531924002356
    DOI: 10.1016/j.ribaf.2024.102442
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    More about this item

    Keywords

    Realized volatility; Agricultural commodities; Financialization; Realized moments; Predictability;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General

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