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Bidirectional relationship between investor sentiment and excess returns: New evidence from the wavelet perspective

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  • Marczak, Martyna
  • Beissinger, Thomas

Abstract

This paper sheds new light on the mutual relationship between investor sentiment and excess returns corresponding to the bubble component of stock prices. We propose to use the wavelet concept of the phase angle to determine the lead-lag relation between these variables. The wavelet phase angle allows for decoupling short- and long-run relations and is additionally capable of identifying time-varying comovement patterns. By applying this concept to excess returns of the monthly S&P500 index and two alternative monthly US sentiment indicators we find that in the short run (until 3 months) sentiment is leading returns whereas for periods above 3 months the opposite can be observed.

Suggested Citation

  • Marczak, Martyna & Beissinger, Thomas, 2015. "Bidirectional relationship between investor sentiment and excess returns: New evidence from the wavelet perspective," Hohenheim Discussion Papers in Business, Economics and Social Sciences 06-2015, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
  • Handle: RePEc:zbw:hohdps:062015
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    References listed on IDEAS

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    More about this item

    Keywords

    wavelet phase angle; wavelet analysis; sentiment indicator; excess returns; speculative bubble; stock market;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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

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