IDEAS home Printed from https://ideas.repec.org/a/eee/jebusi/v108y2020ics0148619519302772.html
   My bibliography  Save this article

GDP announcements and stock prices

Author

Listed:
  • Funashima, Yoshito
  • Iizuka, Nobuo
  • Ohtsuka, Yoshihiro

Abstract

Timely GDP announcements seem to be a useful approach for communicating immediate macroeconomic conditions; however, inaccuracy might instead trigger financial market turmoil. This study examines the stock market response to GDP announcements in Japan and provides several insights into the trade-off between timeliness and accuracy. First, the effect of the initial GDP announcement on stock price is tenuous at best, suggesting little useful information in the provisional estimates. Second, the stock market responds keenly to the first revision, but poorly to the second revision. Finally, depending on the expenditure components of GDP, the revisions cause over- and under-reactions, and thus, are different destabilizing factors in stock prices.

Suggested Citation

  • Funashima, Yoshito & Iizuka, Nobuo & Ohtsuka, Yoshihiro, 2020. "GDP announcements and stock prices," Journal of Economics and Business, Elsevier, vol. 108(C).
  • Handle: RePEc:eee:jebusi:v:108:y:2020:i:c:s0148619519302772
    DOI: 10.1016/j.jeconbus.2019.105872
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148619519302772
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jeconbus.2019.105872?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. S. Borağan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 319-340, March.
    2. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    3. Paul Beaudry & Franck Portier, 2014. "News-Driven Business Cycles: Insights and Challenges," Journal of Economic Literature, American Economic Association, vol. 52(4), pages 993-1074, December.
    4. Hiraga, Kazuki & Kozuka, Masafumi & Miyazaki, Tomomi, 2018. "Public capital and asset prices: Time-series evidence from Japan," Finance Research Letters, Elsevier, vol. 25(C), pages 172-176.
    5. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    6. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    7. Lubos Pástor & Pietro Veronesi, 2012. "Uncertainty about Government Policy and Stock Prices," Journal of Finance, American Finance Association, vol. 67(4), pages 1219-1264, August.
    8. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    9. Pástor, Ľuboš & Veronesi, Pietro, 2013. "Political uncertainty and risk premia," Journal of Financial Economics, Elsevier, vol. 110(3), pages 520-545.
    10. Savor, Pavel G., 2012. "Stock returns after major price shocks: The impact of information," Journal of Financial Economics, Elsevier, vol. 106(3), pages 635-659.
    11. Fama, Eugene F, 1981. "Stock Returns, Real Activity, Inflation, and Money," American Economic Review, American Economic Association, vol. 71(4), pages 545-565, September.
    12. Beaudry, Paul & Portier, Franck, 2004. "An exploration into Pigou's theory of cycles," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1183-1216, September.
    13. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    14. Joelle Liebermann, 2014. "Real-Time Nowcasting of GDP: A Factor Model vs. Professional Forecasters," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(6), pages 783-811, December.
    15. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1593-1636.
    16. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
    17. Arbatli Saxegaard, Elif C. & Davis, Steven J. & Ito, Arata & Miake, Naoko, 2022. "Policy uncertainty in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 64(C).
    18. Frank, Murray Z. & Sanati, Ali, 2018. "How does the stock market absorb shocks?," Journal of Financial Economics, Elsevier, vol. 129(1), pages 136-153.
    19. Toshiaki Watanabe, 2004. "A multi-move sampler for estimating non-Gaussian time series models: Comments on Shephard & Pitt (1997)," Biometrika, Biometrika Trust, vol. 91(1), pages 246-248, March.
    20. Paul C. Tetlock, 2010. "Does Public Financial News Resolve Asymmetric Information?," Review of Financial Studies, Society for Financial Studies, vol. 23(9), pages 3520-3557.
    21. Casares, Miguel & Vázquez, Jesús, 2016. "Data Revisions In The Estimation Of Dsge Models," Macroeconomic Dynamics, Cambridge University Press, vol. 20(7), pages 1683-1716, October.
    22. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    23. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    24. Beaudry, Paul & Portier, Franck, 2005. "The "news view" of economic fluctuations: Evidence from aggregate Japanese data and sectoral US data," Journal of the Japanese and International Economies, Elsevier, vol. 19(4), pages 635-652, December.
    25. Patterson, Kerry D & Heravi, Saeed M, 1991. "Data Revisions and the Expenditure Components of GDP," Economic Journal, Royal Economic Society, vol. 101(407), pages 887-901, July.
    26. 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.
    27. Michael P. Clements & Ana Beatriz Galvão, 2017. "Predicting Early Data Revisions to U.S. GDP and the Effects of Releases on Equity Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 389-406, July.
    28. Galvão, Ana Beatriz, 2017. "Data revisions and DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 215-232.
    29. Balvers, Ronald J & Cosimano, Thomas F & McDonald, Bill, 1990. "Predicting Stock Returns in an Efficient Market," Journal of Finance, American Finance Association, vol. 45(4), pages 1109-1128, September.
    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. Seok, Sangik & Cho, Hoon & Ryu, Doojin, 2022. "Scheduled macroeconomic news announcements and intraday market sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    2. Man Wang & Yihan Cheng, 2022. "Forecasting value at risk and expected shortfall using high‐frequency data of domestic and international stock markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1595-1607, December.
    3. Ivan Mužić & Ivan Gržeta, 2022. "Expectations of Macroeconomic News Announcements: Bitcoin vs. Traditional Assets," Risks, MDPI, vol. 10(6), pages 1-15, 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. Emilia Tomczyk, 2013. "End of sample vs. real time data: perspectives for analysis of expectations," Working Papers 68, Department of Applied Econometrics, Warsaw School of Economics.
    2. Clements, Michael P. & Galvão, Ana Beatriz, 2021. "Measuring the effects of expectations shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 124(C).
    3. Marek RUSNAK, 2013. "Revisions to the Czech National Accounts: Properties and Predictability," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(3), pages 244-261, July.
    4. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    5. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    6. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
    7. Dean Croushore, 2009. "Commentary on Estimating U.S. output growth with vintage data in a state-space framework," Review, Federal Reserve Bank of St. Louis, vol. 91(Jul), pages 371-382.
    8. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.
    9. Michael P. Clements, 2014. "Anticipating Early Data Revisions to US GDP and the Effects of Releases on Equity Markets," ICMA Centre Discussion Papers in Finance icma-dp2014-06, Henley Business School, University of Reading.
    10. Carlo Altavilla & Matteo Ciccarelli, 2011. "Monetary Policy Analysis in Real-Time. Vintage Combination from a Real-Time Dataset," CESifo Working Paper Series 3372, CESifo.
    11. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
    12. Casares, Miguel & Vázquez, Jesús, 2016. "Data Revisions In The Estimation Of Dsge Models," Macroeconomic Dynamics, Cambridge University Press, vol. 20(7), pages 1683-1716, October.
    13. Galvao, Ana Beatriz & Mitchell, James, 2019. "Measuring Data Uncertainty : An Application using the Bank of England’s “Fan Charts” for Historical GDP Growth," EMF Research Papers 24, Economic Modelling and Forecasting Group.
    14. Clements, Michael P., 2019. "Do forecasters target first or later releases of national accounts data?," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1240-1249.
    15. Caroline Flodberg & Pär Österholm, 2017. "A Statistical Anaysis of Revisions in Swedish National Accounts Data," Finnish Economic Papers, Finnish Economic Association, vol. 28(1), pages 10-33, Autumn.
    16. Valentina Raponi & Cecilia Frale, 2014. "Revisions in official data and forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 451-472, August.
    17. Harrison, Richard & Kapetanios, George & Yates, Tony, 2005. "Forecasting with measurement errors in dynamic models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 595-607.
    18. Kishor, N. Kundan, 2011. "Data revisions in India: Implications for monetary policy," Journal of Asian Economics, Elsevier, vol. 22(2), pages 164-173, April.
    19. Francisco Castro & Javier J. P√Ârez & Marta Rodr√Çguez-Vives, 2013. "Fiscal Data Revisions in Europe," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(6), pages 1187-1209, September.
    20. Borup, Daniel & Schütte, Erik Christian Montes, 2022. "Asset pricing with data revisions," Journal of Financial Markets, Elsevier, vol. 59(PB).

    More about this item

    Keywords

    GDP announcements; Data revisions; Stock prices;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:jebusi:v:108:y:2020:i:c:s0148619519302772. 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: https://www.journals.elsevier.com/journal-of-economics-and-business .

    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.