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Effects of investor attention on commodity futures markets

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  • Kou, Yi
  • Ye, Qiang
  • Zhao, Feng
  • Wang, Xiaolin

Abstract

China has recently seen surging retail investor participation in commodity futures markets and rapid adoption of mobile Internet interface. We study two questions with these developments using search frequency from Baidu, the leading Chinese Internet search engine, as a measure of retail investor attention. First we examine whether the relation between retail investor attention and stock returns exists for futures markets where short-selling constraint faced by retail investors is relaxed. Second, we investigate whether mobile Internet searches serve as an effective attention measure as traditional PC-based Internet searches. We find that higher attention predicts larger positive and negative returns in the futures markets, consistent with the argument of short-selling constraint in stock market. We also find that the predictive power of search frequency is mainly from PC-based searches and not from mobile searches.

Suggested Citation

  • Kou, Yi & Ye, Qiang & Zhao, Feng & Wang, Xiaolin, 2018. "Effects of investor attention on commodity futures markets," Finance Research Letters, Elsevier, vol. 25(C), pages 190-195.
  • Handle: RePEc:eee:finlet:v:25:y:2018:i:c:p:190-195
    DOI: 10.1016/j.frl.2017.10.014
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    1. 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.
    2. 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.
    3. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    4. Wang, Xiaolin & Ye, Qiang & Zhao, Feng, 2016. "Trading activity and price behavior in Chinese agricultural futures markets," Finance Research Letters, Elsevier, vol. 18(C), pages 52-59.
    5. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    6. Joseph Engelberg & Caroline Sasseville & Jared Williams, 2012. "Market Madness? The Case of Mad Money," Management Science, INFORMS, vol. 58(2), pages 351-364, February.
    7. David Hirshleifer & Sonya S. Lim & Siew Hong Teoh, 2011. "Limited Investor Attention and Stock Market Misreactions to Accounting Information," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 1(1), pages 35-73.
    8. Ding, Rong & Hou, Wenxuan, 2015. "Retail investor attention and stock liquidity," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 12-26.
    9. 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.
    10. Dzielinski, Michal, 2012. "Measuring economic uncertainty and its impact on the stock market," Finance Research Letters, Elsevier, vol. 9(3), pages 167-175.
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    4. Wenwen Liu & Jinyu Yang & Jingrui Chen & Lei Xu, 2023. "How Social-Network Attention and Sentiment of Investors Affect Commodity Futures Market Returns: New Evidence From China," SAGE Open, , vol. 13(1), pages 21582440231, January.
    5. Gao, Ya & Xiong, Xiong & Feng, Xu & Li, Youwei & Vigne, Samuel A., 2019. "A new attention proxy and order imbalance: Evidence from China," Finance Research Letters, Elsevier, vol. 29(C), pages 411-417.
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    11. Xu Gong & Mengjie Li & Keqin Guan & Chuanwang Sun, 2023. "Climate change attention and carbon futures return prediction," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1261-1288, September.
    12. Oguzhan Cepni, Duc Khuong Nguyen, and Ahmet Sensoy, 2022. "News Media and Attention Spillover across Energy Markets: A Powerful Predictor of Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
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