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

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  • 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
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    References listed on IDEAS

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    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. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    9. 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.
    10. 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.
    11. 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.
    12. Simon van Norden & Huntley Schaller & ), 1995. "Regime Switching in Stock Market Returns," Econometrics 9502002, University Library of Munich, Germany.
    13. 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.
    14. 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.
    15. 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.
    16. 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..
    17. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    18. 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.
    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.
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    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.

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