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Dynamics between trading volume, volatility and open interest in agricultural futures markets: A Bayesian time-varying coefficient approach

Author

Listed:
  • Robert Czudaj

    (Department of Economics, Chemnitz University of Technology)

Abstract
The dynamics between trading volume and volatility for seven agricultural futures markets are examined by drawing on the large literature for equity markets and by allowing for heterogeneity of investors beliefs proxied by open interest. In addition, time-varying effects on the transmission mechanism of shocks are also accounted for by implementing a Bayesian VAR model, which allows for time-variation stemming from both the coefficients and the variance covariance structure of the model's disturbances. This is important since it accounts for changes in the number of trades and the size of trades across different periods, which can have different effects on the volatility-volume relation. The results show that the Granger causality and the reaction to shocks varies substantially over time. This highlights the importance to allow for time-variation when modeling the relationship between volatility, trading volume and open interest for agricultural futures markets. In general, the findings indicate that volatility of agricultural futures markets is driven by previous period's trading volume and open interest. However, the reversed relationship from lagged volatility to trading volume and open interest is limited to certain periods of time.

Suggested Citation

  • Robert Czudaj, 2019. "Dynamics between trading volume, volatility and open interest in agricultural futures markets: A Bayesian time-varying coefficient approach," Chemnitz Economic Papers 030, Department of Economics, Chemnitz University of Technology, revised May 2019.
    • Handle: RePEc:tch:wpaper:cep030
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    More about this item

    Keywords

    Agricultural futures markets; open interest; time-varying Bayesian VAR; trading volume; volatility;
    All these keywords.

    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
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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