IDEAS home Printed from https://ideas.repec.org/a/taf/irapec/v19y2005i3p359-368.html
   My bibliography  Save this article

Time variation in the cointegrating relationship between stock prices and economic activity

Author

Listed:
  • David McMillan

Abstract

The present paper examines whether there exists a long-run cointegrating relationship between a stock market index and output and interest rates. Moreover, estimation is conducted over the full sample and both a recursive and rolling sample to examine any time variation in the nature of the relationship. The results support evidence of a single cointegrating vector, where stock prices typically exhibit a positive relationship with industrial production and a negative relationship with interest rates. However, there is significant time variation and periods of time where contrary results are observed. As such any model of stock prices needs to account for such time variation

Suggested Citation

  • David McMillan, 2005. "Time variation in the cointegrating relationship between stock prices and economic activity," International Review of Applied Economics, Taylor & Francis Journals, vol. 19(3), pages 359-368.
    • Handle: RePEc:taf:irapec:v:19:y:2005:i:3:p:359-368
    DOI: 10.1080/02692170500119862
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/02692170500119862
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02692170500119862?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. Campbell, John Y & Hamao, Yasushi, 1992. "Predictable Stock Returns in the United States and Japan: A Study of Long-Term Capital Market Integration," Journal of Finance, American Finance Association, vol. 47(1), pages 43-69, March.
    2. Søren Johansen & Rocco Mosconi & Bent Nielsen, 2000. "Cointegration analysis in the presence of structural breaks in the deterministic trend," Econometrics Journal, Royal Economic Society, vol. 3(2), pages 216-249.
    3. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    4. Cheung, Yin-Wong & Ng, Lilian K., 1998. "International evidence on the stock market and aggregate economic activity," Journal of Empirical Finance, Elsevier, vol. 5(3), pages 281-296, September.
    5. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    6. Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
    7. Maysami, Ramin Cooper & Koh, Tiong Sim, 2000. "A vector error correction model of the Singapore stock market," International Review of Economics & Finance, Elsevier, vol. 9(1), pages 79-96, February.
    8. 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.
    9. Ferson, Wayne E & Harvey, Campbell R, 1993. "The Risk and Predictability of International Equity Returns," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 527-566.
    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. Khaled Hussainey & Le Khanh Ngoc, 2009. "The impact of macroeconomic indicators on Vietnamese stock prices," Journal of Risk Finance, Emerald Group Publishing, vol. 10(4), pages 321-332, August.
    2. Jalal, Rubia & Gopinathan, R., 2022. "Time-varying and asymmetric impact of exchange rate on oil prices in India: Evidence from a multiple threshold nonlinear ARDL model," Finance Research Letters, Elsevier, vol. 50(C).
    3. Gazi Mainul Hassan & Hisham M. Al refai, 2012. "Can macroeconomic factors explain equity returns in the long run? The case of Jordan," Applied Financial Economics, Taylor & Francis Journals, vol. 22(13), pages 1029-1041, July.
    4. Maria Grazia Miele, 2013. "The effects of capital requirements on real economy: a cointegrated VAR approach for US commercial banks," Working Papers in Public Economics 163, University of Rome La Sapienza, Department of Economics and Law.
    5. Ogunsanya, Ibukun & Wasiu Adamson, Temitope, 2024. "Exchange Rate Movement And Stock Returns In Most Capitalised Economies In Sub-Saharan Africa," Ilorin Journal of Economic Policy, Department of Economics, University of Ilorin, vol. 11(1), pages 18-37, June.
    6. Fromentin, Vincent, 2022. "Time-varying causality between stock prices and macroeconomic fundamentals: Connection or disconnection?," Finance Research Letters, Elsevier, vol. 49(C).
    7. Gupta, Rakesh & Yuan, Tian & Roca, Eduardo, 2016. "Linkages between the ADR market and home country macroeconomic fundamentals: Evidence in the context of the BRICs," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 230-239.
    8. R. Gopinathan & S. Raja Sethu Durai, 2019. "Stock market and macroeconomic variables: new evidence from India," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-17, December.

    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. David G. McMillan, 2003. "Non‐linear Predictability of UK Stock Market Returns," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(5), pages 557-573, December.
    2. McMillan, David G., 2001. "Nonlinear predictability of stock market returns: Evidence from nonparametric and threshold models," International Review of Economics & Finance, Elsevier, vol. 10(4), pages 353-368, December.
    3. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    4. David McMillan, 2004. "Non-linear predictability of UK stock market returns," Money Macro and Finance (MMF) Research Group Conference 2003 63, Money Macro and Finance Research Group.
    5. Thomas D. Tallarini, Jr. & Harold H. Zhang, 2005. "External Habit and the Cyclicality of Expected Stock Returns," The Journal of Business, University of Chicago Press, vol. 78(3), pages 1023-1048, May.
    6. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.
    7. Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.
    8. Andreas Humpe & Peter Macmillan, 2009. "Can macroeconomic variables explain long-term stock market movements? A comparison of the US and Japan," Applied Financial Economics, Taylor & Francis Journals, vol. 19(2), pages 111-119.
    9. Klein, B. D. & Rossin, D. F., 1999. "Data quality in neural network models: effect of error rate and magnitude of error on predictive accuracy," Omega, Elsevier, vol. 27(5), pages 569-582, October.
    10. Najeeb, Faiq & Masih, Mansur, 2016. "Macroeconomic variables and stock returns: evidence from Singapore," MPRA Paper 98778, University Library of Munich, Germany.
    11. Angela J. Black & David G. McMillan, 2004. "Non‐linear Predictability of Value and Growth Stocks and Economic Activity," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(3‐4), pages 439-474, April.
    12. McMillan, David G., 2007. "Non-linear forecasting of stock returns: Does volume help?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 115-126.
    13. David McMillan & Mark Wohar, 2011. "Sum of the parts stock return forecasting: international evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 21(12), pages 837-845.
    14. Tania Morris & Jules Comeau, 2020. "Portfolio creation using artificial neural networks and classification probabilities: a Canadian study," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 133-163, June.
    15. Bekaert, Geert & Harvey, Campbell R., 1997. "Emerging equity market volatility," Journal of Financial Economics, Elsevier, vol. 43(1), pages 29-77, January.
    16. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
    17. R. Gopinathan & S. Raja Sethu Durai, 2019. "Stock market and macroeconomic variables: new evidence from India," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-17, December.
    18. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
    19. Haque Mahfuzul & Hassan M. Kabir & Maroney Neal C & Sackley William H, 2004. "An Empirical Examination of Stability, Predictability, and Volatility of Middle Eastern and African Emerging Stock Markets," Review of Middle East Economics and Finance, De Gruyter, vol. 2(1), pages 18-41, April.
    20. Pallegedara, Asankha, 2012. "Dynamic relationships between stock market performance and short term interest rate Empirical evidence from Sri Lanka," MPRA Paper 40773, University Library of Munich, Germany.

    More about this item

    Keywords

    Stock Prices; cointegration; time variation; JEL Classification: C22; G12;
    All these keywords.

    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

    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:taf:irapec:v:19:y:2005:i:3:p:359-368. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CIRA20 .

    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.