IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/558.html
   My bibliography  Save this paper

Nonlinear Links between Stock Returns and Exchange Rate Movements

Author

Listed:
  • Hartmann, Daniel
  • Pierdzioch, Christian

Abstract

Empirical evidence suggests that the link between exchange rate movements and stock returns may be nonlinear. This evidence could reflect fundamental economic effects like, for example, transaction costs in international goods market arbitrage. It could also reflect market inefficiencies if investors could exploit the nonlinearity to systematically improve the performance of simple trading rules. Using monthly data for major North-American and European industrial countries for the period 1973-2006, we found that it would have been difficult for an investor to use information on nonlinearities to improve the performance of a simple trading rule based on out-of-sample forecasts of stock returns.

Suggested Citation

  • Hartmann, Daniel & Pierdzioch, Christian, 2006. "Nonlinear Links between Stock Returns and Exchange Rate Movements," MPRA Paper 558, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:558
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/558/1/MPRA_paper_558.pdf
    File Function: original version
    Download Restriction: no
    File URL: https://mpra.ub.uni-muenchen.de/2918/1/MPRA_paper_2918.pdf
    File Function: revised version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Di Iorio, Amalia & Faff, Robert, 2000. "An analysis of asymmetry in foreign currency exposure of the Australian equities market," Journal of Multinational Financial Management, Elsevier, vol. 10(2), pages 133-159, June.
    2. Robert J. Shiller, 1984. "Stock Prices and Social Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 15(2), pages 457-510.
    3. Taylor, Mark P & Peel, David A & Sarno, Lucio, 2001. "Nonlinear Mean-Reversion in Real Exchange Rates: Toward a Solution to the Purchasing Power Parity Puzzles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1015-1042, November.
    4. William F. Sharpe, 1965. "Mutual Fund Performance," The Journal of Business, University of Chicago Press, vol. 39, pages 119-119.
    5. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-565, October.
    6. Bartram, Sohnke M., 2004. "Linear and nonlinear foreign exchange rate exposures of German nonfinancial corporations," Journal of International Money and Finance, Elsevier, vol. 23(4), pages 673-699, June.
    7. Cumby, Robert E. & Modest, David M., 1987. "Testing for market timing ability : A framework for forecast evaluation," Journal of Financial Economics, Elsevier, vol. 19(1), pages 169-189, September.
    8. Krugman, Paul, 1989. "The Case for Stabilizing Exchange Rates," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 5(3), pages 61-72, Autumn.
    9. Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-191, January.
    10. Griffin, John M & Stulz, Rene M, 2001. "International Competition and Exchange Rate Shocks: A Cross-Country Industry Analysis of Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 215-241.
    11. Baldwin, Richard E. & Lyons, Richard K., 1994. "Exchange rate hysteresis? Large versus small policy misalignments," European Economic Review, Elsevier, vol. 38(1), pages 1-22, January.
    12. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    13. Taylor, Mark P. & Peel, David A., 2000. "Nonlinear adjustment, long-run equilibrium and exchange rate fundamentals," Journal of International Money and Finance, Elsevier, vol. 19(1), pages 33-53, February.
    14. Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
    15. 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.
    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. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "Some thoughts on accurate characterization of stock market indexes trends in conditions of nonlinear capital flows during electronic trading at stock exchanges in global capital markets," MPRA Paper 49921, University Library of Munich, Germany.

    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. Hartmann, Daniel & Pierdzioch, Christian, 2007. "Exchange rates, interventions, and the predictability of stock returns in Japan," Journal of Multinational Financial Management, Elsevier, vol. 17(2), pages 155-172, April.
    2. Daniel Hartmann & Christian Pierdzioch, 2007. "International equity flows and the predictability of US stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 583-599.
    3. Hartmann, Daniel & Kempa, Bernd & Pierdzioch, Christian, 2008. "Economic and financial crises and the predictability of U.S. stock returns," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 468-480, June.
    4. Christian Pierdzioch & Daniel Hartmann, 2013. "Forecasting Eurozone real-estate returns," Applied Financial Economics, Taylor & Francis Journals, vol. 23(14), pages 1185-1196, July.
    5. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    6. Aysun, Uluc & Guldi, Melanie, 2011. "Exchange rate exposure: A nonparametric approach," Emerging Markets Review, Elsevier, vol. 12(4), pages 321-337.
    7. Döpke, Jörg & Hartmann, Daniel & Pierdzioch, Christian, 2008. "Real-time macroeconomic data and ex ante stock return predictability," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 274-290.
    8. Pierdzioch, Christian & Schertler, Andrea, 2008. "Investing in European stock markets for high-technology firms," Global Finance Journal, Elsevier, vol. 18(3), pages 400-415.
    9. Hanan Naser & Fatema Alaali, 2018. "Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach," Empirical Economics, Springer, vol. 55(4), pages 1757-1777, December.
    10. 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.
    11. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2014. "Does the Macroeconomy Predict UK Asset Returns in a Nonlinear Fashion? Comprehensive Out-of-Sample Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 510-535, August.
    12. Christian Pierdzioch, 2012. "Macroeconomic Factors and the German Real Estate Market: A Stock-Market-Based Forecasting Experiment," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 87-96, May.
    13. Pierdzioch, Christian & Döpke, Jörg & Hartmann, Daniel, 2008. "Forecasting stock market volatility with macroeconomic variables in real time," Journal of Economics and Business, Elsevier, vol. 60(3), pages 256-276.
    14. Muller, Aline & Verschoor, Willem F.C., 2006. "Foreign exchange risk exposure: Survey and suggestions," Journal of Multinational Financial Management, Elsevier, vol. 16(4), pages 385-410, October.
    15. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    16. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    17. repec:wyi:journl:002068 is not listed on IDEAS
    18. Massimo Guidolin & Alexei G. Orlov & Manuela Pedio, 2018. "How good can heuristic-based forecasts be? A comparative performance of econometric and heuristic models for UK and US asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 139-169, January.
    19. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    20. Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian & Wohar, Mark E., 2017. "Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 276-284.
    21. Pesaran, M. Hashem & Timmermann, Allan, 2002. "Market timing and return prediction under model instability," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 495-510, December.

    More about this item

    Keywords

    Stock returns; exchange rate movements; nonlinearities;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    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:pra:mprapa:558. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.