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Google attention and target price run ups

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  • Siganos, Antonios

Abstract

We explore the increase in the share prices of target firms before their merger announcements. We use a novelty Google search volume to proxy the market expectation hypothesis according to which firms with an abnormal upward change in Google searches are identified as firms with potential merger activity. We find that Google indicators can explain a larger percentage of the price increase in target firms before their mergers than the Financial Times. However even the Google proxy of the market expectation hypothesis can only explain at best 36% of the target price run ups.

Suggested Citation

  • Siganos, Antonios, 2013. "Google attention and target price run ups," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 219-226.
    • Handle: RePEc:eee:finana:v:29:y:2013:i:c:p:219-226
    DOI: 10.1016/j.irfa.2012.11.002
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    Cited by:

    1. Reyes, Tomas, 2018. "Limited attention and M&A announcements," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 201-222.
    2. Vicente, María Rosalía & López-Menéndez, Ana J. & Pérez, Rigoberto, 2015. "Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing?," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 132-139.
    3. González-Fernández, Marcos & González-Velasco, Carmen, 2018. "Can Google econometrics predict unemployment? Evidence from Spain," Economics Letters, Elsevier, vol. 170(C), pages 42-45.
    4. Duc Dang Thi Viet & Hoai Nguyen Thu & Nguyen Van Phuoc & Nguyen Dang Phong & Anh Nguyen Huong & Hai Ho Hong, 2024. "Google Search intensity and stock returns in frontier markets: Evidence from the Vietnamese market," Economics and Business Review, Sciendo, vol. 10(1), pages 30-56, April.
    5. 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.
    6. ap Gwilym, O. & Kita, A. & Wang, Q., 2014. "Speculate against speculative demand," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 212-221.
    7. Muradoglu, Gulnur & Peng, Ni & Qin, Huai & Xia, Chunling, 2024. "Investor attention and market reactions to early announcements in mergers and acquisitions," International Review of Financial Analysis, Elsevier, vol. 91(C).
    8. Minjian Ye & Guangzhong Li, 2017. "Internet big data and capital markets: a literature review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-18, December.
    9. Adra, Samer & Barbopoulos, Leonidas G., 2020. "Do corporations learn from mispricing? Evidence from takeovers and corporate performance," International Review of Financial Analysis, Elsevier, vol. 68(C).
    10. 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.

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    More about this item

    Keywords

    Target price run ups; Mergers; Market anticipation; Google search volume;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance

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