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Market Reaction to iPhone Rumors

Author

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  • Chong, Terence Tai Leung
  • Wu, Zhang
  • Liu, Yuchen

Abstract

The paper studies the effects of new product rumors about the iPhone on the stock price of the Apple company. We scrape iPhone rumors from Macrumors.com, and obtain a dataset covering 1,264 articles containing 180 words on average bet-ween January 2002 and December 2015. Moreover, we construct a market-decided lexicon to transform qualitative information into quantitative data, and analyze what type of words and what information embedded in the rumors are apt to impact on Apple's stock price. Unlike previous studies, we do not rely on the widely-adopted Harvard-IV-4 dictionary, as the coefficients of the words from the dictionary are neither significant nor consistent with their polarities, compared with our results. The paper obtains three main findings. First, the spread of rumors has a significant impact on the stock price. Second, positive words, rather than negative words, play an important role in affecting the stock price. Third, the stock price is highly sensitive to the words related to the appearance of the iPhone.

Suggested Citation

  • Chong, Terence Tai Leung & Wu, Zhang & Liu, Yuchen, 2019. "Market Reaction to iPhone Rumors," MPRA Paper 92014, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:92014
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    References listed on IDEAS

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    1. Dan Horsky & Patrick Swyngedouw, 1987. "Does it Pay to Change Your Company's Name? A Stock Market Perspective," Marketing Science, INFORMS, vol. 6(4), pages 320-335.
    2. Sanjiv R. Das & Mike Y. Chen, 2007. "Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web," Management Science, INFORMS, vol. 53(9), pages 1375-1388, September.
    3. Yan Carrière‐Swallow & Felipe Labbé, 2013. "Nowcasting with Google Trends in an Emerging Market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(4), pages 289-298, July.
    4. Olivier J. Blanchard & Jean-Paul L'Huillier & Guido Lorenzoni, 2013. "News, Noise, and Fluctuations: An Empirical Exploration," American Economic Review, American Economic Association, vol. 103(7), pages 3045-3070, December.
    5. Eckbo, B. Espen, 1983. "Horizontal mergers, collusion, and stockholder wealth," Journal of Financial Economics, Elsevier, vol. 11(1-4), pages 241-273, April.
    6. Malatesta, Paul H. & Thompson, Rex, 1985. "Partially anticipated events: A model of stock price reactions with an application to corporate acquisitions," Journal of Financial Economics, Elsevier, vol. 14(2), pages 237-250, June.
    7. Pinches, George E & Singleton, J Clay, 1978. "The Adjustment of Stock Prices to Bond Rating Changes," Journal of Finance, American Finance Association, vol. 33(1), pages 29-44, March.
    8. Pound, John & Zeckhauser, Richard J, 1990. "Clearly Heard on the Street: The Effect of Takeover Rumors on Stock Prices," The Journal of Business, University of Chicago Press, vol. 63(3), pages 291-308, July.
    9. Mikkelson, Wayne H. & Partch, M. Megan, 1986. "Valuation effects of security offerings and the issuance process," Journal of Financial Economics, Elsevier, vol. 15(1-2), pages 31-60.
    10. Chaney, Paul K & Devinney, Timothy M & Winer, Russell S, 1991. "The Impact of New Product Introductions on the Market Value of Firms," The Journal of Business, University of Chicago Press, vol. 64(4), pages 573-610, October.
    11. Kiymaz, Halil, 2001. "The effects of stock market rumors on stock prices: evidence from an emerging market," Journal of Multinational Financial Management, Elsevier, vol. 11(1), pages 105-115, February.
    12. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    13. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    14. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    15. David O. Lucca & Emanuel Moench, 2015. "The Pre-FOMC Announcement Drift," Journal of Finance, American Finance Association, vol. 70(1), pages 329-371, February.
    16. Simeon Vosen & Torsten Schmidt, 2011. "Forecasting private consumption: survey‐based indicators vs. Google trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(6), pages 565-578, September.
    17. Jeeman Jung & Robert J. Shiller, 2005. "Samuelson's Dictum and the Stock Market," Economic Inquiry, Western Economic Association International, vol. 43(2), pages 221-228, April.
    18. Fama, Eugene F, et al, 1969. "The Adjustment of Stock Prices to New Information," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(1), pages 1-21, February.
    19. Paul Smith, 2016. "Google's MIDAS Touch: Predicting UK Unemployment with Internet Search Data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(3), pages 263-284, April.
    20. Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
    21. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    22. Chan, Wesley S., 2003. "Stock price reaction to news and no-news: drift and reversal after headlines," Journal of Financial Economics, Elsevier, vol. 70(2), pages 223-260, November.
    23. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    24. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    25. A. Craig MacKinlay, 1997. "Event Studies in Economics and Finance," Journal of Economic Literature, American Economic Association, vol. 35(1), pages 13-39, March.
    26. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    27. McQueen, Grant & Roley, V Vance, 1993. "Stock Prices, News, and Business Conditions," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 683-707.
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    More about this item

    Keywords

    stock price; iPhone; rumors; market-decided lexicon;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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