IDEAS home Printed from https://ideas.repec.org/p/hoh/hohdip/244.html
   My bibliography  Save this paper

Dividend Yields for Forecasting Stock Market Returns - An ARDL Cointegration Analysis for Germany

Author

Listed:

Abstract

This paper empirically assesses the ability of dividend yields to predict future tock returns in Germany assuming efficient markets and rational expectations. Since the order of integration of repressors are not exactly known, a bound procedure, namely a n autoregressive distributed lag (ARDL) model, is applied to test for cointegrating relationships among future stock returns and today’s divided yields. It is also capable of dealing with the controversial issue of exogeneity of the dividend yield. ARDL and error-correction models are estimated for (future) stock returns and the dividend yield based on consistent estimates and standard normal asymptotic theory.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Ansgar Belke & Thorsten Polleit, 2004. "Dividend Yields for Forecasting Stock Market Returns - An ARDL Cointegration Analysis for Germany," Diskussionspapiere aus dem Institut für Volkswirtschaftslehre der Universität Hohenheim 244/2004, Department of Economics, University of Hohenheim, Germany.
  • Handle: RePEc:hoh:hohdip:244
    as

    Download full text from publisher

    File URL: http://www.uni-hohenheim.de/RePEc/hoh/papers/244.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Peter C. B. Phillips & Bruce E. Hansen, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(1), pages 99-125.
    2. Kremers, Jeroen J M & Ericsson, Neil R & Dolado, Juan J, 1992. "The Power of Cointegration Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 325-348, August.
    3. Fama, Eugene F, 1981. "Stock Returns, Real Activity, Inflation, and Money," American Economic Review, American Economic Association, vol. 71(4), pages 545-565, September.
    4. Fama, Eugene F. & Schwert, G. William, 1977. "Asset returns and inflation," Journal of Financial Economics, Elsevier, vol. 5(2), pages 115-146, November.
    5. Ricardo Faria, Joao & Leon-Ledesma, Miguel, 2003. "Testing the Balassa-Samuelson effect: Implications for growth and the PPP," Journal of Macroeconomics, Elsevier, vol. 25(2), pages 241-253, June.
    6. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    7. Pesaran, M Hashem, 1997. "The Role of Economic Theory in Modelling the Long Run," Economic Journal, Royal Economic Society, vol. 107(440), pages 178-191, January.
    8. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    9. 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.
    10. J. Benson Durham, 2003. "Does monetary policy affect stock prices and Treasury yields? An error correction and simultaneous equation approach," Finance and Economics Discussion Series 2003-10, Board of Governors of the Federal Reserve System (U.S.).
    11. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    12. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-386.
    13. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    14. Cuthbertson, Keith & Hayes, Simon & Nitzsche, Dirk, 1997. "The Behaviour of UK Stock Prices and Returns: Is the Market Efficient?," Economic Journal, Royal Economic Society, vol. 107(443), pages 986-1008, July.
    15. Muhammad Islam, 2004. "The long run relationship between openness and government size: evidence from bounds test," Applied Economics, Taylor & Francis Journals, vol. 36(9), pages 995-1000.
    16. Paresh Kumar Narayan, 2005. "New evidence on purchasing power parity from 17 OECD countries," Applied Economics, Taylor & Francis Journals, vol. 37(9), pages 1063-1071.
    17. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    18. Cavanagh, Christopher L. & Elliott, Graham & Stock, James H., 1995. "Inference in Models with Nearly Integrated Regressors," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1131-1147, October.
    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. Belke Ansgar, 2010. "Die Auswirkungen der Geldmenge und des Kreditvolumens auf die Immobilienpreise – Ein ARDL-Ansatz für Deutschland / Money, Credit and House Prices – An ARDL-Approach for Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(2), pages 138-162, April.
    2. Ansgar Belke, 2009. "Die Auswirkungen der Geldmenge und des Kreditvolumens auf die Immobilienpreise: ein ARDL-Ansatz für Deutschland," Discussion Papers of DIW Berlin 953, DIW Berlin, German Institute for Economic Research.

    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. Ansgar Belke & Thorsten Polleit, 2005. "(How) Do Stock Market Returns React to Monetary Policy? - An ARDL Cointegration Analysis for Germany," Diskussionspapiere aus dem Institut für Volkswirtschaftslehre der Universität Hohenheim 253/2005, Department of Economics, University of Hohenheim, Germany.
    2. Kothari, Pratik & O’Doherty, Michael S., 2023. "Job postings and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 64(C).
    3. John Y. Campbell, 2008. "Viewpoint: Estimating the equity premium," Canadian Journal of Economics, Canadian Economics Association, vol. 41(1), pages 1-21, February.
    4. Long Chen & Lu Zhang, 2009. "The stock market and aggregate employment," NBER Working Papers 15219, National Bureau of Economic Research, Inc.
    5. Ansgar Belke & Thorsten Polleit, 2006. "Monetary policy and dividend growth in Germany: long-run structural modelling versus bounds testing approach," Applied Economics, Taylor & Francis Journals, vol. 38(12), pages 1409-1423.
    6. Yu, Jialin, 2011. "Disagreement and return predictability of stock portfolios," Journal of Financial Economics, Elsevier, vol. 99(1), pages 162-183, January.
    7. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
    8. Bakshi, Gurdip & Panayotov, George & Skoulakis, Georgios, 2011. "Improving the predictability of real economic activity and asset returns with forward variances inferred from option portfolios," Journal of Financial Economics, Elsevier, vol. 100(3), pages 475-495, June.
    9. Chen, Long & Zhang, Lu, 2011. "Do time-varying risk premiums explain labor market performance?," Journal of Financial Economics, Elsevier, vol. 99(2), pages 385-399, February.
    10. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.
    11. Qureshi, Fiza & Khan, Habib Hussain & Rehman, Ijaz Ur & Ghafoor, Abdul & Qureshi, Saba, 2019. "Mutual fund flows and investors’ expectations in BRICS economies: Implications for international diversification," Economic Systems, Elsevier, vol. 43(1), pages 130-150.
    12. Xia, Yihong, 2000. "Learning About Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation," University of California at Los Angeles, Anderson Graduate School of Management qt3167f8mz, Anderson Graduate School of Management, UCLA.
    13. Hahn, Jaehoon & Lee, Hangyong, 2006. "Interpreting the predictive power of the consumption-wealth ratio," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 183-202, March.
    14. Demetrescu, Matei & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023. "Transformed regression-based long-horizon predictability tests," Journal of Econometrics, Elsevier, vol. 237(2).
    15. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    16. Erik Hjalmarsson, 2006. "Inference in Long-Horizon Regressions," International Finance Discussion Papers 853, Board of Governors of the Federal Reserve System (U.S.).
    17. Yacine AÏT‐SAHALI & Michael W. Brandt, 2001. "Variable Selection for Portfolio Choice," Journal of Finance, American Finance Association, vol. 56(4), pages 1297-1351, August.
    18. Kothari, S. P., 2001. "Capital markets research in accounting," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 105-231, September.
    19. Zhang, Yuzhao, 2014. "Contrarian flows, consumption and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 101-111.
    20. Maio, Paulo & Santa-Clara, Pedro, 2012. "Multifactor models and their consistency with the ICAPM," Journal of Financial Economics, Elsevier, vol. 106(3), pages 586-613.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • 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:hoh:hohdip:244. 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: Ulrike Berberich (email available below). General contact details of provider: https://edirc.repec.org/data/ivhohde.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.