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Nonlinearity, data-snooping, and stock index ETF return predictability

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  • Yang, Jian
  • Cabrera, Juan
  • Wang, Tao

Abstract

This paper examines daily return predictability for eighteen international stock index ETFs. The out-of-sample tests are conducted, based on linear and various popular nonlinear models and both statistical and economic criteria for model comparison. The main results show evidence of predictability for six of eighteen ETFs. A simple linear autoregression model, and a nonlinear-in-variance GARCH model, but not several popular nonlinear-in-mean models help outperform the martingale model. The allowance of data-snooping bias using White's Reality Check also substantially weakens otherwise apparently strong predictability.

Suggested Citation

  • Yang, Jian & Cabrera, Juan & Wang, Tao, 2010. "Nonlinearity, data-snooping, and stock index ETF return predictability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 498-507, January.
    • Handle: RePEc:eee:ejores:v:200:y:2010:i:2:p:498-507
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    1. Gleason, Kimberly C. & Mathur, Ike & Peterson, Mark A., 2004. "Analysis of intraday herding behavior among the sector ETFs," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 681-694, December.
    2. James M. Poterba & John B. Shoven, 2002. "Exchange-Traded Funds: A New Investment Option for Taxable Investors," American Economic Review, American Economic Association, vol. 92(2), pages 422-427, May.
    3. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    4. McQueen, Grant & Thorley, Steven, 1991. "Are Stock Returns Predictable? A Test Using Markov Chains," Journal of Finance, American Finance Association, vol. 46(1), pages 239-263, March.
    5. Ratner, Mitchell & Leal, Ricardo P. C., 1999. "Tests of technical trading strategies in the emerging equity markets of Latin America and Asia," Journal of Banking & Finance, Elsevier, vol. 23(12), pages 1887-1905, December.
    6. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2005. "Evidence on the speed of convergence to market efficiency," Journal of Financial Economics, Elsevier, vol. 76(2), pages 271-292, May.
    7. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    8. Chaudhuri, Kausik & Wu, Yangru, 2003. "Random walk versus breaking trend in stock prices: Evidence from emerging markets," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 575-592, April.
    9. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    10. Yang, Jian & Su, Xiaojing & Kolari, James W., 2008. "Do Euro exchange rates follow a martingale? Some out-of-sample evidence," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 729-740, May.
    11. Yongmiao Hong & Tae-Hwy Lee, 2003. "Inference on Predictability of Foreign Exchange Rates via Generalized Spectrum and Nonlinear Time Series Models," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1048-1062, November.
    12. Cai, Zongwu & Fan, Jianqing & Yao, Qiwei, 2000. "Functional-coefficient regression models for nonlinear time series," LSE Research Online Documents on Economics 6314, London School of Economics and Political Science, LSE Library.
    13. Anita K. Pennathur & Natalya Delcoure & Dwight Anderson, 2002. "Diversification Benefits of iShares and Closed‐End Country Funds," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 25(4), pages 541-557, December.
    14. Gencay, Ramazan, 1998. "The predictability of security returns with simple technical trading rules," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 347-359, October.
    15. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November.
    16. Patro, Dilip K. & Wu, Yangru, 2004. "Predictability of short-horizon returns in international equity markets," Journal of Empirical Finance, Elsevier, vol. 11(4), pages 553-584, September.
    17. Kim, E Han & Singal, Vijay, 2000. "Erratum [Stock Market Openings: Experience of Emerging Economies]," The Journal of Business, University of Chicago Press, vol. 73(4), October.
    18. Granger, Clive W. J., 1992. "Forecasting stock market prices: Lessons for forecasters," International Journal of Forecasting, Elsevier, vol. 8(1), pages 3-13, June.
    19. Michael Monoyios & Lucio Sarno, 2002. "Mean reversion in stock index futures markets: A nonlinear analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(4), pages 285-314, April.
    20. Kim, E Han & Singal, Vijay, 2000. "Stock Market Openings: Experience of Emerging Economies," The Journal of Business, University of Chicago Press, vol. 73(1), pages 25-66, January.
    21. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
    22. Hsieh, David A., 1993. "Implications of Nonlinear Dynamics for Financial Risk Management," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(1), pages 41-64, March.
    23. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    24. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-590, June.
    25. Gencay, Ramazan, 1999. "Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules," Journal of International Economics, Elsevier, vol. 47(1), pages 91-107, February.
    26. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-275, July.
    27. Dong-Hyun Ahn & Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 2002. "Partial Adjustment or Stale Prices? Implications from Stock Index and Futures Return Autocorrelations," The Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 655-689, March.
    28. Harris, Richard D. F. & Kucukozmen, C. Coskun, 2001. "Linear and nonlinear dependence in Turkish equity returns and its consequences for financial risk management," European Journal of Operational Research, Elsevier, vol. 134(3), pages 481-492, November.
    29. Moreno, David & Olmeda, Ignacio, 2007. "Is the predictability of emerging and developed stock markets really exploitable?," European Journal of Operational Research, Elsevier, vol. 182(1), pages 436-454, October.
    30. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    31. Tabak, Benjamin M. & Lima, Eduardo J.A., 2009. "Market efficiency of Brazilian exchange rate: Evidence from variance ratio statistics and technical trading rules," European Journal of Operational Research, Elsevier, vol. 194(3), pages 814-820, May.
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    7. Argel S. Masa & John Francis T. Diaz, 2017. "Long-memory Modelling and Forecasting of the Returns and Volatility of Exchange-traded Notes (ETNs)," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(1), pages 23-53, February.
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