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An analysis of the effect of investor sentiment in a heterogeneous switching transition model for G7 stock markets

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  • Jawadi, Fredj
  • Namouri, Hela
  • Ftiti, Zied

Abstract

In line with Chiarella and He (2000) and Boswijk et al. (2007), this study examines the stock market dynamics in a behavioural heterogeneity framework. In particular, we analyse the stock return dynamics in G7 countries over recent decades while considering the effect of heterogeneous investor sentiment. We develop an empirical and nonlinear heterogeneous stock price specification allowing for the presence of two types of investors (arbitrageurs and noise traders) and two regimes. With reference to the heterogeneous smooth transition regression model, we enable the price to switch smoothly between regimes after accounting for an endogenous change in investor sentiment. Our findings do not reject the hypothesis of the nonlinear investor sentiment effect on stock returns. Further, we show that two regimes characterize the stock price dynamics for which the price is closely governed by fundamentals in the first one, while investor sentiment drives the price in the second one. Our model, therefore, captures the main stylized facts observed in the market and shows good in- and out-of-sample forecasting power.

Suggested Citation

  • Jawadi, Fredj & Namouri, Hela & Ftiti, Zied, 2018. "An analysis of the effect of investor sentiment in a heterogeneous switching transition model for G7 stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 469-484.
  • Handle: RePEc:eee:dyncon:v:91:y:2018:i:c:p:469-484
    DOI: 10.1016/j.jedc.2017.10.004
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    More about this item

    Keywords

    Stock return dynamics; Investor sentiment; Nonlinearity; Smooth Transition Regression; Forecasting;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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