IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v74y2021ics0301420721003421.html
   My bibliography  Save this article

Attention-return relation in the gold market and market states

Author

Listed:
  • Piccoli, Pedro
  • de Castro, Jessica

Abstract

We document that the attention-return relation in the gold spot market is sensitive to market states since we identify a positive (negative) association between returns and contemporaneous attention during bull (bear) markets. This sensitivity is influenced by the magnitude of the returns, since the significance of the relation, based on a quantile model, increases almost monotonically as the return distribution moves away from the median. We further find that investor attention is influenced by recent gold spot price trends in both market states. Overall, these results suggest that gold return past performance attracts the attention of individual investors who, in turn, trade to profit from the trend, reinforcing the price movement, which is consistent with the time-series momentum framework.

Suggested Citation

  • Piccoli, Pedro & de Castro, Jessica, 2021. "Attention-return relation in the gold market and market states," Resources Policy, Elsevier, vol. 74(C).
  • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420721003421
    DOI: 10.1016/j.resourpol.2021.102333
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420721003421
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.resourpol.2021.102333?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. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    2. Baur, Dirk G. & Dimpfl, Thomas, 2016. "Googling gold and mining bad news," Resources Policy, Elsevier, vol. 50(C), pages 306-311.
    3. Han, Liyan & Xu, Yang & Yin, Libo, 2017. "Does investor attention matter? The attention-return relation in gold futures market," Economics Discussion Papers 2017-37, Kiel Institute for the World Economy (IfW Kiel).
    4. Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 254-265.
    5. Yao, Ting & Zhang, Yue-Jun & Ma, Chao-Qun, 2017. "How does investor attention affect international crude oil prices?," Applied Energy, Elsevier, vol. 205(C), pages 336-344.
    6. Jain, Anshul & Biswal, Pratap Chandra, 2019. "Does internet search interest for gold move the gold spot, stock and exchange rate markets? A study from India," Resources Policy, Elsevier, vol. 61(C), pages 501-507.
    7. Goddard, John & Kita, Arben & Wang, Qingwei, 2015. "Investor attention and FX market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 79-96.
    8. Liyan Han & Ziying Li & Libo Yin, 2017. "The effects of investor attention on commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(10), pages 1031-1049, October.
    9. Wu, You & Han, Liyan & Yin, Libo, 2019. "Our currency, your attention: Contagion spillovers of investor attention on currency returns," Economic Modelling, Elsevier, vol. 80(C), pages 49-61.
    10. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    11. Barberis, Nicholas & Xiong, Wei, 2012. "Realization utility," Journal of Financial Economics, Elsevier, vol. 104(2), pages 251-271.
    12. Eom, Cheoljun & Kaizoji, Taisei & Kang, Sang Hoon & Pichl, Lukas, 2019. "Bitcoin and investor sentiment: Statistical characteristics and predictability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 511-521.
    13. Daniel Andrei & Michael Hasler, 2015. "Investor Attention and Stock Market Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 33-72.
    14. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    15. Papailias, Fotis & Liu, Jiadong & Thomakos, Dimitrios D., 2021. "Return signal momentum," Journal of Banking & Finance, Elsevier, vol. 124(C).
    16. Bijl, Laurens & Kringhaug, Glenn & Molnár, Peter & Sandvik, Eirik, 2016. "Google searches and stock returns," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 150-156.
    17. Vozlyublennaia, Nadia, 2014. "Investor attention, index performance, and return predictability," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 17-35.
    18. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    19. 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.
    20. Dastgir, Shabbir & Demir, Ender & Downing, Gareth & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "The causal relationship between Bitcoin attention and Bitcoin returns: Evidence from the Copula-based Granger causality test," Finance Research Letters, Elsevier, vol. 28(C), pages 160-164.
    21. Moskowitz, Tobias J. & Ooi, Yao Hua & Pedersen, Lasse Heje, 2012. "Time series momentum," Journal of Financial Economics, Elsevier, vol. 104(2), pages 228-250.
    22. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
    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. Tsai, I-Chun & Chen, Han-Bo & Lin, Che-Chun, 2024. "The ability of energy commodities to hedge the dynamic risk of epidemic black swans," Resources Policy, Elsevier, vol. 89(C).
    2. de Castro, Jessica & Piccoli, Pedro, 2023. "Do online searches actually measure future retail investor trades?," International Review of Financial Analysis, Elsevier, vol. 86(C).
    3. Matheus Pereira Libório & Petr Iakovlevitch Ekel & Carlos Augusto Paiva Martins, 2023. "Economic analysis through alternative data and big data techniques: what do they tell about Brazil?," SN Business & Economics, Springer, vol. 3(1), pages 1-16, January.

    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. de Castro, Jessica & Piccoli, Pedro, 2023. "Do online searches actually measure future retail investor trades?," International Review of Financial Analysis, Elsevier, vol. 86(C).
    2. Martina Halouskov'a & Daniel Stav{s}ek & Mat'uv{s} Horv'ath, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Papers 2205.05985, arXiv.org, revised Aug 2022.
    3. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    4. Chaiyuth Padungsaksawasdi & Sirimon Treepongkaruna & Robert Brooks, 2019. "Investor Attention and Stock Market Activities: New Evidence from Panel Data," IJFS, MDPI, vol. 7(2), pages 1-19, June.
    5. Goodell, John W. & Kumar, Satish & Li, Xiao & Pattnaik, Debidutta & Sharma, Anuj, 2022. "Foundations and research clusters in investor attention: Evidence from bibliometric and topic modelling analysis," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 511-529.
    6. Ramos, Sofia B. & Latoeiro, Pedro & Veiga, Helena, 2020. "Limited attention, salience of information and stock market activity," Economic Modelling, Elsevier, vol. 87(C), pages 92-108.
    7. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    8. Papadamou, Stephanos & Fassas, Athanasios & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2020. "Direct and Indirect Effects of COVID-19 Pandemic on Implied Stock Market Volatility: Evidence from Panel Data Analysis," MPRA Paper 100020, University Library of Munich, Germany.
    9. Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
    10. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
    11. Smales, L.A., 2021. "Investor attention and global market returns during the COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 73(C).
    12. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    13. Dong, Dayong & Wu, Keke & Fang, Jianchun & Gozgor, Giray & Yan, Cheng, 2022. "Investor attention factors and stock returns: Evidence from China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    14. Ebert, Sebastian & Hilpert, Christian, 2019. "Skewness preference and the popularity of technical analysis," Journal of Banking & Finance, Elsevier, vol. 109(C).
    15. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    16. Christophe Desagre & Catherine D'Hondt, 2020. "Googlization and retail investors' trading activity," LIDAM Discussion Papers LFIN 2020004, Université catholique de Louvain, Louvain Finance (LFIN).
    17. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    18. Qadan, Mahmoud & Zoua’bi, Maher, 2019. "Financial attention and the demand for information," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 82(C).
    19. Peltomäki, Jarkko & Graham, Michael & Hasselgren, Anton, 2018. "Investor attention to market categories and market volatility: The case of emerging markets," Research in International Business and Finance, Elsevier, vol. 44(C), pages 532-546.
    20. Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.

    More about this item

    Keywords

    Gold; Market states; Investor attention; Google trends;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q37 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Issues in International Trade

    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:jrpoli:v:74:y:2021:i:c:s0301420721003421. 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/30467 .

    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.