IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Detecting Predictable Non-linear Dynamics in Dow Jones Industrial Average and Dow Jones Islamic Market Indices using Nonparametric Regressions

  • Marcos Álvarez-Díaz

    ()

    (Department of Economics, University of Vigo, Galicia, Spain)

  • Shawkat Hammoudeh

    ()

    (Lebow College of Business, Drexel University, Philadelphia, USA)

  • Rangan Gupta

    ()

    (Department of Economics, University of Pretoria)

This study performs the challenging task of examining the forecastability behavior of the stock market returns for the Dow Jones Industrial Average (DJIA) and the Dow Jones Islamic (DJIM) market indices, using non-parametric regressions. These indices represent different markets in terms of institutional and balance sheet characteristics. The empirical results posit that stock market indices are difficult to predict accurately. However, our results reveal some point forecasting capacity for a 15-week horizon at the 95 per cent confidence level for the DJIA index, and for nine- week horizon at the 99 per cent confidence for the DJIM index, using the non-parametric regressions. On the other hand, the ratio of the correctly predicted signs (the success ratio) shows a percentage above 60 per cent for both indices which is evidence of predictability for those indices. This predictability is however statistically significant only four-weeks ahead for the DJIM case, and twelve weeks ahead for the DJIA as their NMSE is different from one. In sum, the forecastability of DJIM is better than that of DJIA. This result on the forecastability of DJIM add to its other findings in the literature that cast doubts on its suitability in hedging and asset allocation in portfolios that contain conventional stocks.

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 201385.

as
in new window

Length: 27 pages
Date of creation: Dec 2013
Date of revision:
Handle: RePEc:pre:wpaper:201385
Contact details of provider: Postal: PRETORIA, 0002
Phone: (+2712) 420 2413
Fax: (+2712) 362-5207
Web page: http://www.up.ac.za/economics

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Francis X. Diebold & James M. Nason, 1989. "Nonparametric exchange rate prediction?," Finance and Economics Discussion Series 81, Board of Governors of the Federal Reserve System (U.S.).
  2. Agnon, Yehuda & Golan, Amos & Shearer, Matthew, 1999. "Nonparametric, nonlinear, short-term forecasting: theory and evidence for nonlinearities in the commodity markets," Economics Letters, Elsevier, vol. 65(3), pages 293-299, December.
  3. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
  4. Guidolin, Massimo & Timmermann, Allan, 2007. "Asset allocation under multivariate regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3503-3544, November.
  5. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
  6. Jaditz Ted & Riddick Leigh A., 2000. "Time-Series Near-Neighbor Regression," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(1), pages 1-11, April.
  7. Evzen Kocenda, 2001. "An Alternative To The Bds Test: Integration Across The Correlation Integral," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 337-351.
  8. Rangan Gupta & Shawkat Hammoudeh & Beatrice D. Simo-Kengne & Soodabeh Sarafrazi, 2014. "Can the Sharia-based Islamic stock market returns be forecasted using large number of predictors and models?," Applied Financial Economics, Taylor & Francis Journals, vol. 24(17), pages 1147-1157, September.
  9. 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.
  10. 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, 08.
  11. John Barkoulas & Christopher F. Baum & Atreya Chakraborty, 1996. "Nearest-Neighbor Forecasts of U.S. Interest Rates," Boston College Working Papers in Economics 313., Boston College Department of Economics, revised 01 Apr 2003.
  12. Marcos Alvarez-Diaz, 2008. "Exchange rates forecasting: local or global methods?," Applied Economics, Taylor & Francis Journals, vol. 40(15), pages 1969-1984.
  13. Leung, Mark T. & Daouk, Hazem & Chen, An-Sing, 2000. "Forecasting stock indices: a comparison of classification and level estimation models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 173-190.
  14. Darrat, Ali F & Zhong, Maosen, 2000. "On Testing the Random-Walk Hypothesis: A Model-Comparison Approach," The Financial Review, Eastern Finance Association, vol. 35(3), pages 105-24, August.
  15. Hsieh, David A, 1989. "Testing for Nonlinear Dependence in Daily Foreign Exchange Rates," The Journal of Business, University of Chicago Press, vol. 62(3), pages 339-68, July.
  16. Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-77, December.
  17. Marcos Alvarez-Diaz & Alberto Alvarez, 2010. "Forecasting exchange rates using local regression," Applied Economics Letters, Taylor & Francis Journals, vol. 17(5), pages 509-514.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:pre:wpaper:201385. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Rangan Gupta)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.