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Nonlinear Behavior of the US Stock Price-Dividend: Evidence from Threshold Unit Root Tests

Author

Listed:
  • Shu-Ching Cheng

    (Department of Economics, Feng Chia University, Taichung, Taiwan.)

  • Tsung-Pao Wu

    (Department of Finance, Feng Chia University, Taichung, Taiwan.)

Abstract

This study investigates the behavior of US stock price–dividend relationships over the period 1871:01 to 2012:03 using a two-regime Threshold Autoregressive (TAR) model with an autoregressive unit root developed by Caner and Hansen (2001), which allows for simultaneously testing nonlinearity and non-stationary. Our findings indicate that the US stock price-dividend is a nonlinear series that is characterized by a unit root process in a particular month; the stock price-dividend ratio shows a decrease by more than 7.17% between the previous year and the previous fourth month.

Suggested Citation

  • Shu-Ching Cheng & Tsung-Pao Wu, 2013. "Nonlinear Behavior of the US Stock Price-Dividend: Evidence from Threshold Unit Root Tests," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 82-93, December.
    • Handle: RePEc:rjr:romjef:v::y:2013:i:4:p:82-93
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    References listed on IDEAS

    as
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    5. Choudhry, Taufiq, 1997. "Stochastic Trends in Stock Prices: Evidence from Latin American Markets," Journal of Macroeconomics, Elsevier, vol. 19(2), pages 285-304, April.
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    More about this item

    Keywords

    threshold autoregressive (TAR); US stock price-dividend; regime change;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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