IDEAS home Printed from https://ideas.repec.org/p/gra/wpaper/08-17.html
   My bibliography  Save this paper

Effects of Macroeconomic Announcements on Stock Returns across Volatility Regimes

Author

Listed:
  • Henry Aray

    (Department of Economic Theory and Economic History, University of Granada.)

Abstract

Based on a simple Markov regime switching model, this article presents evidence on the effects of macroeconomic announcements on individual stocks returns. The model specification allows two regimes to be distinguished: one with high volatility and the other with low volatility. Considering the level of significance at 5%, the response of stock returns to macroeconomic announcements is much stronger in the low volatility regime. However, the effects of the Fama-French factors on individual stock returns is unambiguously significant in both regimes.

Suggested Citation

  • Henry Aray, 2008. "Effects of Macroeconomic Announcements on Stock Returns across Volatility Regimes," ThE Papers 08/17, Department of Economic Theory and Economic History of the University of Granada..
  • Handle: RePEc:gra:wpaper:08/17
    as

    Download full text from publisher

    File URL: http://www.ugr.es/~teoriahe/RePEc/gra/wpaper/thepapers08_17.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    3. Gardeazabal, Javier & Regulez, Marta, 2004. "A factor model of seasonality in stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 224-236, May.
    Full references (including those not matched with items on IDEAS)

    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. Carol Alexander & Anca Dimitriu, 2005. "Indexing, cointegration and equity market regimes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(3), pages 213-231.
    2. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    3. Cowan, Adrian M. & Joutz, Frederick L., 2006. "An unobserved component model of asset pricing across financial markets," International Review of Financial Analysis, Elsevier, vol. 15(1), pages 86-107.
    4. Peixin (Payton) Liu & Kuan Xu & Yonggan Zhao, 2011. "Market regimes, sectorial investments, and time‐varying risk premiums," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 7(2), pages 107-133, April.
    5. De Santis, Paola & Drago, Carlo, 2014. "Asimmetria del rischio sistematico dei titoli immobiliari americani: nuove evidenze econometriche [Systematic Risk Asymmetry of the American Real Estate Securities: Some New Econometric Evidence]," MPRA Paper 59381, University Library of Munich, Germany.
    6. Massimo Guidolin & Giovanna Nicodano, 2009. "Small caps in international equity portfolios: the effects of variance risk," Annals of Finance, Springer, vol. 5(1), pages 15-48, January.
    7. Ahmad, Wasim & Kutan, Ali M. & Chahal, Rishman Jot Kaur & Kattumuri, Ruth, 2021. "COVID-19 Pandemic and firm-level dynamics in the USA, UK, Europe, and Japan," International Review of Financial Analysis, Elsevier, vol. 78(C).
    8. Ang, Andrew & Gu, Li & Hochberg, Yael V., 2007. "Is Ipo Underperformance a Peso Problem?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(3), pages 565-594, September.
    9. Kalimipalli, Madhu & Nayak, Subhankar & Perez, M. Fabricio, 2013. "Dynamic effects of idiosyncratic volatility and liquidity on corporate bond spreads," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2969-2990.
    10. Henry Aray, 2006. "The Latin American and Spanish Stock markets," ThE Papers 06/12, Department of Economic Theory and Economic History of the University of Granada..
    11. Jieting Chen & Yuichiro Kawaguchi, 2018. "Multi-Factor Asset-Pricing Models under Markov Regime Switches: Evidence from the Chinese Stock Market," IJFS, MDPI, vol. 6(2), pages 1-19, May.
    12. Cheema, Muhammad A. & Scrimgeour, Frank, 2019. "Oil prices and stock market anomalies," Energy Economics, Elsevier, vol. 83(C), pages 578-587.
    13. West, Jason, 2012. "Catastrophes and Insurance Stocks – A Benchmarking Approach for Measuring Efficiency," Annals of Actuarial Science, Cambridge University Press, vol. 6(1), pages 103-136, March.
    14. Battulga Gankhuu, 2022. "Parameter Estimation Methods of Required Rate of Return on Stock," Papers 2206.09657, arXiv.org, revised Jul 2022.
    15. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.
    16. Matthew Wang & Yi-Hong Lin & Ilya Mikhelson, 2020. "Regime-Switching Factor Investing with Hidden Markov Models," JRFM, MDPI, vol. 13(12), pages 1-15, December.
    17. Stafylas, Dimitrios & Anderson, Keith & Uddin, Moshfique, 2018. "Hedge fund performance attribution under various market conditions," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 221-237.
    18. Carlo Rosa, 2022. "Understanding intraday momentum strategies," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2218-2234, December.
    19. Billio, Monica & Getmansky, Mila & Pelizzon, Loriana, 2012. "Dynamic risk exposures in hedge funds," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3517-3532.
    20. Vendrame, Vasco & Guermat, Cherif & Tucker, Jon, 2018. "A conditional regime switching CAPM," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 1-11.

    More about this item

    Keywords

    Markov Switching Model; Macroeconomic announcements; Stock Returns.;
    All these keywords.

    JEL classification:

    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:gra:wpaper:08/17. 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: Angel Solano Garcia. (email available below). General contact details of provider: https://edirc.repec.org/data/dtugres.html .

    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.