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Internet, noise trading and commodity prices

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  • Massimo PERI
  • Daniela VANDONE
  • Lucia BALDI

Abstract

We study the effect of an increased noise trading caused by easier access to information on agricultural futures prices. The theoretical framework is the Mixture Distribution Hypothesis (MDH), that posits a joint dependence of return volatility and information. We use two different proxies for the observed component of information flows, which allows to separate the effect of supply and demand of information. We analyse the effect of information demand using the Internet Search Volume from Google Insight. Empirical results support the MDH and highlight that the search of information on internet by noise traders can amplify volatility.

Suggested Citation

  • Massimo PERI & Daniela VANDONE & Lucia BALDI, 2012. "Internet, noise trading and commodity prices," Departmental Working Papers 2012-07, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    • Handle: RePEc:mil:wpdepa:2012-07
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    References listed on IDEAS

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    Cited by:

    1. Baldi, Lucia & Peri, Massimo & Vandone, Daniela, 2016. "Stock markets’ bubbles burst and volatility spillovers in agricultural commodity markets," Research in International Business and Finance, Elsevier, vol. 38(C), pages 277-285.
    2. Li, Jinfang, 2014. "Multi-period sentiment asset pricing model with information," International Review of Economics & Finance, Elsevier, vol. 34(C), pages 118-130.
    3. Massimo Peri & Daniela Vandone & Lucia Baldi, 2017. "Volatility Spillover between Water, Energy and Food," Sustainability, MDPI, vol. 9(6), pages 1-16, June.

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    More about this item

    Keywords

    Noise trading; commodity futures prices; information; mixture distribution hypothesis; egarch;
    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
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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