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On the statistical and economic performance of stock return predictive regression models: an international perspective

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  • Pierre Giot
  • Mikael Petitjean

Abstract

The predictability of stock returns is assessed in 10 countries using the linear predictive regression framework. We use recently developed out-of-sample statistical tests and include both valuation ratios and interest rates as predictive variables. Contrary to previous studies, we explicitly address the issue of the small-sample bias, deal with trading profitability, and employ several risk-adjusted metrics. When statistical forecastability is found, it cannot be exploited to consistently deliver abnormal returns across countries and investment horizons. We hold the view that returns are predictable to some extent, but show that such forecasts are not useful for portfolio advice.

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  • Pierre Giot & Mikael Petitjean, 2011. "On the statistical and economic performance of stock return predictive regression models: an international perspective," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 175-193.
    • Handle: RePEc:taf:quantf:v:11:y:2011:i:2:p:175-193
    DOI: 10.1080/14697680903468971
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    Cited by:

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    2. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2017. "International stock return predictability: Evidence from new statistical tests," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 97-113.
    3. Farias Nazário, Rodolfo Toríbio & e Silva, Jéssica Lima & Sobreiro, Vinicius Amorim & Kimura, Herbert, 2017. "A literature review of technical analysis on stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 115-126.
    4. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2017. "Forecasting market returns: bagging or combining?," International Journal of Forecasting, Elsevier, vol. 33(1), pages 102-120.
    5. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2016. "Can commodity returns forecast Canadian sector stock returns?," International Review of Economics & Finance, Elsevier, vol. 41(C), pages 172-188.
    6. Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.
    7. Zhao, Albert Bo & Cheng, Tingting, 2022. "Stock return prediction: Stacking a variety of models," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 288-317.
    8. Tissaoui, Kais & Azibi, Jamel, 2019. "International implied volatility risk indexes and Saudi stock return-volatility predictabilities," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 65-84.

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