IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v33y2014icp82-89.html
   My bibliography  Save this article

Internet, noise trading and commodity futures prices

Author

Listed:
  • Peri, Massimo
  • Vandone, Daniela
  • Baldi, Lucia

Abstract

This paper relates to internet, noise trading and commodity 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 internet searches and information published in newspapers. We analyse the effect of information from the internet 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

  • Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2014. "Internet, noise trading and commodity futures prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 82-89.
    • Handle: RePEc:eee:reveco:v:33:y:2014:i:c:p:82-89
    DOI: 10.1016/j.iref.2014.03.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056014000471
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2014.03.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Hal R. Varian, 2007. "The Economics of Internet Search," 'Angelo Costa' Lectures Serie, SIPI Spa, issue Lect. VII.
    4. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    5. Dwight R. Sanders & Scott H. Irwin, 2010. "A speculative bubble in commodity futures prices? Cross‐sectional evidence," Agricultural Economics, International Association of Agricultural Economists, vol. 41(1), pages 25-32, January.
    6. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    7. Irwin, Scott H. & Sanders, Dwight R. & Merrin, Robert P., 2009. "Devil or Angel? The Role of Speculation in the Recent Commodity Price Boom (and Bust)," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 41(2), August.
    8. Jose M. Marin & Jacques P. Olivier, 2008. "The Dog That Did Not Bark: Insider Trading and Crashes," Journal of Finance, American Finance Association, vol. 63(5), pages 2429-2476, October.
    9. Meulbroek, Lisa K, 1992. "An Empirical Analysis of Illegal Insider Trading," Journal of Finance, American Finance Association, vol. 47(5), pages 1661-1699, December.
    10. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    11. Brad M. Barber & Terrance Odean, 2001. "The Internet and the Investor," Journal of Economic Perspectives, American Economic Association, vol. 15(1), pages 41-54, Winter.
    12. Mitchell, Mark L & Mulherin, J Harold, 1994. "The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-950, July.
    13. Guo, Jian-Feng & Ji, Qiang, 2013. "How does market concern derived from the Internet affect oil prices?," Applied Energy, Elsevier, vol. 112(C), pages 1536-1543.
    14. Ederington, Louis H & Lee, Jae Ha, 1993. "How Markets Process Information: News Releases and Volatility," Journal of Finance, American Finance Association, vol. 48(4), pages 1161-1191, September.
    15. van der Wijst,Nico, 2013. "Finance," Cambridge Books, Cambridge University Press, number 9781107029224, January.
    16. Laura L. Veldkamp, 2006. "Media Frenzies in Markets for Financial Information," American Economic Review, American Economic Association, vol. 96(3), pages 577-601, June.
    17. Matthew Rabin, 2002. "Inference by Believers in the Law of Small Numbers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(3), pages 775-816.
    18. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    19. Kao, Erin H. & Fung, Hung-Gay, 2012. "Intraday trading activities and volatility in round-the-clock futures markets," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 195-209.
    20. Stephan Meier & Charles Sprenger, 2007. "Impatience and credit behavior: evidence from a field experiment," Working Papers 07-3, Federal Reserve Bank of Boston.
    21. Leslie A. Jeng & Andrew Metrick & Richard Zeckhauser, 2003. "Estimating the Returns to Insider Trading: A Performance-Evaluation Perspective," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 453-471, May.
    22. Massimo Peri & Lucia Baldi & Daniela Vandone, 2013. "Price discovery in commodity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 20(4), pages 397-403, March.
    23. Nam, Jouahn & Wang, Jun & Zhang, Ge, 2008. "Strategic trading against retail investors with loss-aversion," International Review of Economics & Finance, Elsevier, vol. 17(1), pages 45-55.
    24. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    25. 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.
    26. Matthias Bank & Martin Larch & Georg Peter, 2011. "Google search volume and its influence on liquidity and returns of German stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 239-264, September.
    27. Ke, Bin & Huddart, Steven & Petroni, Kathy, 2003. "What insiders know about future earnings and how they use it: Evidence from insider trades," Journal of Accounting and Economics, Elsevier, vol. 35(3), pages 315-346, August.
    28. Smith, Geoffrey Peter, 2012. "Google Internet search activity and volatility prediction in the market for foreign currency," Finance Research Letters, Elsevier, vol. 9(2), pages 103-110.
    29. Syed, Azmat A & Liu, Pu & Smith, Stanley D, 1989. "The Exploitation of Inside Information at the Wall Street Journal: A Test of Strong Form Efficiency," The Financial Review, Eastern Finance Association, vol. 24(4), pages 567-579, November.
    30. Chen, Chun-nan & Wu, Chunchi, 2009. "Small trades and volatility increases after stock splits," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 592-610, October.
    31. Alwathainani, Abdulaziz M., 2012. "Consistent winners and losers," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 210-220.
    32. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    33. Eric Zivot, 2008. "Practical Issues in the Analysis of Univariate GARCH Models," Working Papers UWEC-2008-03-FC, University of Washington, Department of Economics.
    34. Cooke, Bryce & Robles, Miguel, 2009. "Recent food prices movements: A time series analysis," IFPRI discussion papers 942, International Food Policy Research Institute (IFPRI).
    35. Scott H. Irwin & Dwight R. Sanders, 2011. "Index Funds, Financialization, and Commodity Futures Markets," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 1-31.
    36. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    37. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    38. Sanders, Dwight R. & Irwin, Scott H. & Leuthold, Raymond M., 2003. "The Theory Of Contrary Opinion: A Test Using Sentiment Indices In Futures Markets," Journal of Agribusiness, Agricultural Economics Association of Georgia, vol. 21(1), pages 1-26.
    39. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    40. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    41. Black, Fischer, 1986. "Noise," Journal of Finance, American Finance Association, vol. 41(3), pages 529-543, July.
    42. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2013. "Investor sentiment effect in stock markets: Stock characteristics or country-specific factors?," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 572-591.
    43. Harris, Lawrence, 1987. "Transaction Data Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(2), pages 127-141, June.
    44. Read, Daniel & Loewenstein, George & Rabin, Matthew, 1999. "Choice Bracketing," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 171-197, December.
    45. Kalev, Petko S. & Liu, Wai-Man & Pham, Peter K. & Jarnecic, Elvis, 2004. "Public information arrival and volatility of intraday stock returns," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1441-1467, June.
    46. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. González-Fernández, Marcos & González-Velasco, Carmen, 2018. "Can Google econometrics predict unemployment? Evidence from Spain," Economics Letters, Elsevier, vol. 170(C), pages 42-45.
    2. Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2019. "Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 180-197, February.
    3. Xing Gao & Daniel Ladley, 2022. "Noise trading and market stability," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1283-1301, October.
    4. Alessandro Banterle & Daniela Vandone, 2019. "Price volatility and risk management: The case of rice in the EU," Economia agro-alimentare, FrancoAngeli Editore, vol. 21(2), pages 255-274.
    5. Qingjie Zhou & Panpan Zhu & You Wu & Yinpeng Zhang, 2022. "Research on the Volatility of the Cotton Market under Different Term Structures: Perspective from Investor Attention," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    6. 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.
    7. González-Fernández, Marcos & González-Velasco, Carmen, 2020. "An alternative approach to predicting bank credit risk in Europe with Google data," Finance Research Letters, Elsevier, vol. 35(C).
    8. Marcos González-Fernández & Carmen González-Velasco, 2019. "An approach to predict Spanish mortgage market activity using Google data," Economics and Business Letters, Oviedo University Press, vol. 8(4), pages 209-214.
    9. Wu, Ming-Hung & Tsai, Wei-Che & Lu, Chia-Chi & Zhang, Hang, 2022. "Google searches around analyst recommendation revision announcements: Evidence from the Taiwan stock market," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 75-97.
    10. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2015. "Sentiment-prone investors and volatility dynamics between spot and futures markets," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 180-196.
    11. Xiao, Jihong & Wen, Fenghua & He, Zhifang, 2023. "Impact of geopolitical risks on investor attention and speculation in the oil market: Evidence from nonlinear and time-varying analysis," Energy, Elsevier, vol. 267(C).
    12. González-Fernández, Marcos & González-Velasco, Carmen, 2020. "A sentiment index to measure sovereign risk using Google data," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 406-418.
    13. Xiao, Jihong & Wang, Yudong, 2022. "Good oil volatility, bad oil volatility, and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 953-966.
    14. Sun, Hang & Bos, Jaap.W.B. & Rodrigues, Paulo, 2023. "Destabilizing or passive? The impact of commodity index traders on equilibrium prices," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 271-285.
    15. Massimo Peri & Daniela Vandone & Lucia Baldi, 2017. "Volatility Spillover between Water, Energy and Food," Sustainability, MDPI, vol. 9(6), pages 1-16, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2012. "Information Demand and Agriculture Commodity Prices," 2012 International European Forum, February 13-17, 2012, Innsbruck-Igls, Austria 144973, International European Forum on System Dynamics and Innovation in Food Networks.
    3. Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2019. "Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 180-197, February.
    4. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    5. Moussa, Faten & Delhoumi, Ezzeddine & Ouda, Olfa Ben, 2017. "Stock return and volatility reactions to information demand and supply," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 54-67.
    6. Massimiliano Caporin & Francesco Poli, 2017. "Building News Measures from Textual Data and an Application to Volatility Forecasting," Econometrics, MDPI, vol. 5(3), pages 1-46, August.
    7. Sam Howison & David Lamper, 2001. "Trading volume in models of financial derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 8(2), pages 119-135.
    8. Semen Son Turan, 2014. "Internet Search Volume and Stock Return Volatility: The Case of Turkish Companies," Information Management and Business Review, AMH International, vol. 6(6), pages 317-328.
    9. Robert F. Engle & Martin Klint Hansen & Asger Lunde, 2012. "And Now, The Rest of the News: Volatility and Firm Specific News Arrival," CREATES Research Papers 2012-56, Department of Economics and Business Economics, Aarhus University.
    10. Zhang, Yongjie & Feng, Lina & Jin, Xi & Shen, Dehua & Xiong, Xiong & Zhang, Wei, 2014. "Internet information arrival and volatility of SME PRICE INDEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 70-74.
    11. SENARATHNE W Chamil & JIANGUO Wei, 2018. "Do Investors Mimic Trading Strategies Of Foreign Investors Or The Market: Implications For Capital Asset Pricing," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 13(3), pages 171-205, December.
    12. Tripathi, Abhinava & Pandey, Ashish, 2021. "Information dissemination across global markets during the spread of COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 103-115.
    13. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
    14. Shen, Dehua & Zhang, Wei & Xiong, Xiong & Li, Xiao & Zhang, Yongjie, 2016. "Trading and non-trading period Internet information flow and intraday return volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 519-524.
    15. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    16. Strohsal, Till & Weber, Enzo, 2015. "Time-varying international stock market interaction and the identification of volatility signals," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 28-36.
    17. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    18. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021, January-A.
    19. Semen Son-Turan, 2016. "The Impact of Investor Sentiment on the "Leverage Effect"," International Econometric Review (IER), Econometric Research Association, vol. 8(1), pages 4-18, April.
    20. Loredana Ureche-Rangau & Quiterie de Rorthays, 2009. "More on the volatility-trading volume relationship in emerging markets: The Chinese stock market," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 779-799.

    More about this item

    Keywords

    Noise trading; Corn price volatility; 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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reveco:v:33:y:2014:i:c:p:82-89. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.