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A Stochastic Nonlinear Regression Estimator Using Wavelets

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  • Pan, Zuohong
  • Wang, Xiaodi

Abstract

A new wavelet-based estimator is introduced which combines the state-space model with the wavelet transform in an effort to explore the stock market inefficiency. The new estimator possesses some superior qualities that are illustrated through its actual performance in forecasting the S&P 500. Citation Copyright 1998 by Kluwer Academic Publishers.

Suggested Citation

  • Pan, Zuohong & Wang, Xiaodi, 1998. "A Stochastic Nonlinear Regression Estimator Using Wavelets," Computational Economics, Springer;Society for Computational Economics, vol. 11(1-2), pages 89-102, April.
    • Handle: RePEc:kap:compec:v:11:y:1998:i:1-2:p:89-102
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    Cited by:

    1. Huang, Shian-Chang, 2011. "Wavelet-based multi-resolution GARCH model for financial spillover effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2529-2539.
    2. Lin Shinn-Juh & Stevenson Maxwell, 2001. "Wavelet Analysis of the Cost-of-Carry Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(1), pages 1-17, April.
    3. Kim Sangbae & In Francis Haeuck, 2003. "The Relationship Between Financial Variables and Real Economic Activity: Evidence From Spectral and Wavelet Analyses," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-18, December.
    4. Tse, Y.K. & Anh, V.V. & Tieng, Q., 2002. "Maximum likelihood estimation of the fractional differencing parameter in an ARFIMA model using wavelets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 59(1), pages 153-161.

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