IDEAS home Printed from https://ideas.repec.org/p/fda/fdaddt/2008-19.html
   My bibliography  Save this paper

Financial Analysts impact on Stock Volatility. A Study on the Pharmaceutical Sector

Author

Listed:
  • Clara I. Gonzalez
  • Ricardo Gimeno

Abstract

The arrival of new information helps financial markets to value assets, but it may has the side-effect of increasing their volatilities. A better knowledge of the mechanism that links relevant news and stock prices would help both private and institutional agents to improve the calibration of the risks implies in a given asset. Financial analysts play a key role in distinguishing which news are relevant for the valuation of a particular asset, and the changes in their recommendations are signals of new information in the market. This paper studies the impact those buy or sell recommendations have on returns and also on volatility instead of the traditional literature that focuses only on prices. The pharmaceutical companies in the New York Stock Exchange are especially suited for this type of analysis given the frequent discontinuities in their expected profits derived from the success or failure in the development of new drugs. Twenty stocks are daily tracked for five years along with the recommendations given by financial analysts. We have modeled stock returns by a Markov Regime Switching model as in Schaller and van Norden (1997) and found two states of low and high volatilities. We have also found strong evidence that the probability of being in the estate of high volatility increases when a Financial Analyst changes his recommendation.

Suggested Citation

  • Clara I. Gonzalez & Ricardo Gimeno, 2008. "Financial Analysts impact on Stock Volatility. A Study on the Pharmaceutical Sector," Working Papers 2008-19, FEDEA.
    • Handle: RePEc:fda:fdaddt:2008-19
    as

    Download full text from publisher

    File URL: https://documentos.fedea.net/pubs/dt/2008/dt-2008-19.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kon, Stanley J, 1984. "Models of Stock Returns-A Comparison," Journal of Finance, American Finance Association, vol. 39(1), pages 147-165, March.
    2. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 61-82, Suppl. De.
    3. Turner, Christopher M. & Startz, Richard & Nelson, Charles R., 1989. "A Markov model of heteroskedasticity, risk, and learning in the stock market," Journal of Financial Economics, Elsevier, vol. 25(1), pages 3-22, November.
    4. Womack, Kent L, 1996. "Do Brokerage Analysts' Recommendations Have Investment Value?," Journal of Finance, American Finance Association, vol. 51(1), pages 137-167, March.
    5. Pearce, Douglas K & Roley, V Vance, 1985. "Stock Prices and Economic News," The Journal of Business, University of Chicago Press, vol. 58(1), pages 49-67, January.
    6. Castanias, Richard P, II, 1979. "Macroinformation and the Variability of Stock Market Prices," Journal of Finance, American Finance Association, vol. 34(2), pages 439-450, May.
    7. DiMasi, Joseph A. & Hansen, Ronald W. & Grabowski, Henry G. & Lasagna, Louis, 1991. "Cost of innovation in the pharmaceutical industry," Journal of Health Economics, Elsevier, vol. 10(2), pages 107-142, July.
    8. Simon van Norden & Huntley Schaller & ), 1995. "Regime Switching in Stock Market Returns," Econometrics 9502002, University Library of Munich, Germany.
    9. Ederington, Louis H & Lee, Jae Ha, 1993. "How Markets Process Information: News Releases and Volatility," Journal of Finance, American Finance Association, vol. 48(4), pages 1161-1191, September.
    10. 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.
    11. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    12. Engle, Robert F., 1984. "Wald, likelihood ratio, and Lagrange multiplier tests in econometrics," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 13, pages 775-826, Elsevier.
    13. Tomas J. Philipson, 2002. "The Regulation of Medical Innovation and Pharmaceutical Markets," Journal of Law and Economics, University of Chicago Press, vol. 45(S2), pages 583-586.
    14. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    15. Danzon, Patricia M & Chao, Li-Wei, 2000. "Does Regulation Drive out Competition in Pharmaceutical Markets?," Journal of Law and Economics, University of Chicago Press, vol. 43(2), pages 311-357, October.
    16. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    17. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    18. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    19. DiMasi, Joseph A. & Hansen, Ronald W. & Grabowski, Henry G., 2003. "The price of innovation: new estimates of drug development costs," Journal of Health Economics, Elsevier, vol. 22(2), pages 151-185, March.
    20. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Hassan Heidari & Arash Refah Kahriz & Yousef Mohammadzadeh, 2019. "Stock market behavior of pharmaceutical industry in Iran and macroeconomic factors," Economic Change and Restructuring, Springer, vol. 52(3), pages 255-277, August.

    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. Sean D. Campbell, 2002. "Specification Testing and Semiparametric Estimation of Regime Switching Models: An Examination of the US Short Term Interest Rate," Working Papers 2002-26, Brown University, Department of Economics.
    2. Kim, Chang-Jin & Morley, James C. & Nelson, Charles R., 2001. "Does an intertemporal tradeoff between risk and return explain mean reversion in stock prices?," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 403-426, September.
    3. Don U.A. Galagedera & Roland Shami, 2003. "Association between Markov regime-switching market volatility and beta risk: Evidence from Dow Jones industrial securities," Monash Econometrics and Business Statistics Working Papers 20/03, Monash University, Department of Econometrics and Business Statistics.
    4. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Advances in Econometrics, in: Missing Data Methods: Time-Series Methods and Applications, pages 1-86, Emerald Group Publishing Limited.
    5. Vanden, Joel M., 2005. "Equilibrium analysis of volatility clustering," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 374-417, June.
    6. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    7. Georgios Kouretas & Manolis Syllignakis, 2012. "Switching Volatility in Emerging Stock Markets and Financial Liberalization: Evidence from the new EU Member Countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 65-93, June.
    8. Billio, Monica & Pelizzon, Loriana, 2000. "Value-at-Risk: a multivariate switching regime approach," Journal of Empirical Finance, Elsevier, vol. 7(5), pages 531-554, December.
    9. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
    10. Kodjovi G. Assoe, 1998. "Regime-Switching in Emerging Stock Market Returns," Multinational Finance Journal, Multinational Finance Journal, vol. 2(2), pages 101-132, June.
    11. Sen, Rituparna & Hsieh, Fushing, 2009. "A note on testing regime switching assumption based on recurrence times," Statistics & Probability Letters, Elsevier, vol. 79(24), pages 2443-2450, December.
    12. Aloui, Chaker & Jammazi, Rania, 2009. "The effects of crude oil shocks on stock market shifts behaviour: A regime switching approach," Energy Economics, Elsevier, vol. 31(5), pages 789-799, September.
    13. Azamat Abdymomunov & James Morley, 2011. "Time variation of CAPM betas across market volatility regimes," Applied Financial Economics, Taylor & Francis Journals, vol. 21(19), pages 1463-1478.
    14. Sung Ik Kim, 2022. "ARMA–GARCH model with fractional generalized hyperbolic innovations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    15. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    16. Jiang, George J. & Lo, Ingrid, 2014. "Private information flow and price discovery in the U.S. treasury market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 118-133.
    17. Timmermann, Allan, 2000. "Moments of Markov switching models," Journal of Econometrics, Elsevier, vol. 96(1), pages 75-111, May.
    18. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    19. Wasim Ahmad & N. Bhanumurthy & Sanjay Sehgal, 2015. "Regime dependent dynamics and European stock markets: Is asset allocation really possible?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(1), pages 77-107, February.
    20. Timmermann, Allan, 1999. "Moments of Markov switching models," LSE Research Online Documents on Economics 119124, London School of Economics and Political Science, LSE Library.

    More about this item

    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:fda:fdaddt:2008-19. 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: Carmen Arias (email available below). General contact details of provider: https://www.fedea.net .

    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.