Detecting Predictable Non-linear Dynamics in Dow Jones Industrial Average and Dow Jones Islamic Market Indices using Nonparametric Regressions
AbstractThis 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.
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Bibliographic InfoPaper provided by University of Pretoria, Department of Economics in its series Working Papers with number 201385.
Length: 27 pages
Date of creation: Dec 2013
Date of revision:
Islamic and conventional equity markets; forecasting; nonparametric regressions; point prediction; success ratio;
Find related papers by JEL classification:
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2014-01-17 (All new papers)
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- 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.
- 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.
- 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.
- Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009.
"Non-linear predictability in stock and bond returns: when and where is it exploitable?,"
2008-010, Federal Reserve Bank of St. Louis.
- 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.
- Evzen Kocenda, 2003.
"An Alternative to the BDS Test: Integration Across The Correlation Integral,"
- 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.
- 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.
- 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.
- Massimo Guidolin & Allan Timmerman, 2006. "Asset allocation under multivariate regime switching," Working Papers 2005-002, Federal Reserve Bank of St. Louis.
- 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.
- 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.
- Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
- Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2010. "Does the macroeconomy predict U.K. asset returns in a nonlinear fashion? comprehensive out-of-sample evidence," Working Papers 2010-039, Federal Reserve Bank of St. Louis.
- Diebold, Francis X. & Nason, James A., 1990.
"Nonparametric exchange rate prediction?,"
Journal of International Economics,
Elsevier, vol. 28(3-4), pages 315-332, May.
- 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.
- 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.
- Rangan Gupta & Shawkat Hammoudeh & Beatrice D. Simo-Kengne & Soodabeh Sarafrazi, 2013. "Can the Sharia-Based Islamic Stock Market Returns be Forecasted Using Large Number of Predictors and Models?," Working Papers 201381, University of Pretoria, Department of Economics.
- Marcos Alvarez-Diaz, 2008. "Exchange rates forecasting: local or global methods?," Applied Economics, Taylor & Francis Journals, vol. 40(15), pages 1969-1984.
- Marcos Alvarez-Diaz & Alberto Alvarez, 2010. "Forecasting exchange rates using local regression," Applied Economics Letters, Taylor & Francis Journals, vol. 17(5), pages 509-514.
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