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Nonlinear Stock Price Adjustment in the G7 Countries

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  • Fredj Jawadi
  • Georges Prat

Abstract

This paper seeks to address the stock price adjustment toward fundamentals. Using the class of Switching Transition Error Correction Models (STECMs), we show that two regimes describe the dynamics of stock price deviations from fundamentals in the G7 countries over the period 1969-2005. Deviations appear to follow a quasi random walk in the central regime when prices are near fundamentals (i.e. transaction costs being greater than expected gains, the mean reversion mechanism is inactive), while they approach a white noise in the outer regimes (i.e. transaction costs being lower than expected gains, the mean reversion works). As expected when transaction costs are heterogeneous, the STECM shows that stock price adjustments are smooth, implying that the convergence speed is time-varying according to the size of the deviation. Finally, using appropriate indicators, both the magnitudes of under- and overvaluation of stock price and the speed of the mean reversion are exhibited per date in the G7 countries, showing that the dynamics of stock price adjustment is highly dependent on the date and on the country under consideration.

Suggested Citation

  • Fredj Jawadi & Georges Prat, 2009. "Nonlinear Stock Price Adjustment in the G7 Countries," EconomiX Working Papers 2009-21, University of Paris Nanterre, EconomiX.
  • Handle: RePEc:drm:wpaper:2009-21
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    Cited by:

    1. Fredj Jawadi & Ricardo M. Sousa, 2013. "Modelling money demand: further evidence from an international comparison," Applied Economics Letters, Taylor & Francis Journals, vol. 20(11), pages 1052-1055, July.
    2. Fredj Jawadi, 2009. "Essay in dividend modelling and forecasting: does nonlinearity help?," Applied Financial Economics, Taylor & Francis Journals, vol. 19(16), pages 1329-1343.
    3. repec:kap:rqfnac:v:49:y:2017:i:3:d:10.1007_s11156-016-0604-y is not listed on IDEAS
    4. Prat, Georges, 2013. "Equity risk premium and time horizon: What do the U.S. secular data say?," Economic Modelling, Elsevier, vol. 34(C), pages 76-88.
    5. Lucia BALDI & Massimo PERI & Daniela VANDONE, 2010. "Is wine a financial parachute?," Departmental Working Papers 2010-01, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    6. Fredj Jawadi & Georges Prat, 2017. "Equity prices and fundamentals: a DDM–APT mixed approach," Review of Quantitative Finance and Accounting, Springer, vol. 49(3), pages 661-695, October.
    7. Jawadi, Fredj & Sousa, Ricardo M., 2013. "Money demand in the euro area, the US and the UK: Assessing the role of nonlinearity," Economic Modelling, Elsevier, vol. 32(C), pages 507-515.
    8. Fredj Jawadi & Mondher Bellalah, 2011. "Nonlinear mean reversion in oil and stock markets," Review of Accounting and Finance, Emerald Group Publishing, vol. 10(3), pages 316-326, August.
    9. Jawadi, Fredj & Khanniche, Sabrina, 2012. "Modeling hedge fund exposure to risk factors," Economic Modelling, Elsevier, vol. 29(4), pages 1003-1018.
    10. Arouri, Mohamed & Jawadi, Fredj & Nguyen, Duc Khuong, 2013. "What can we tell about monetary policy synchronization and interdependence over the 2007–2009 global financial crisis?," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 175-187.
    11. Jawadi, Fredj & Leoni, Patrick, 2009. "Threshold cointegration relationships between oil and stock markets," Discussion Papers of Business and Economics 3/2009, University of Southern Denmark, Department of Business and Economics.
    12. Mohamed E AROURI & Fredj JAWADI & Duc K NGUYEN, 2012. "Nonlinear modeling of oil and stock price dynamics: segmentation or time-varying integration?," Economics Bulletin, AccessEcon, vol. 32(3), pages 2481-2489.
    13. Jawadi Fredj & Ureche-Rangau Loredana, 2013. "Threshold linkages between volatility and trading volume: evidence from developed and emerging markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 313-333, May.

    More about this item

    Keywords

    Price; heterogeneous transaction costs; STECMs;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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