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Low-frequency components and the Weekend effect revisited: Evidence from Spectral Analysis


  • Francois-Éric Racicot

    () (Chaire d'information financière et organisationnelle ESG-UQAM, Laboratory for Research in Statistics and Probability, and UQO)


We revisit the well-known weekend anomaly (Gibbons and Hess, 1981; Harris, 1986; Smirlock and Straks, 1986; Connolly, 1989; Giovanis, 2010) using an established macroeconometric technique known as spectral analysis (Granger, 1964; Sargent, 1987). Our findings show that using regression analysis with dichotomous variables, spectral analysis helps establishing the robustness of the estimated parameters based on a sample of the S&P500 for the 1972-1973 period. As further evidence of cycles in financial times series, we relate our application of spectral analysis to the recent literature on low-frequency components in asset returns (Barberis et al., 2001; Grüne and Semmler, 2008; Semmler et al., 2009). We suggest investment practitioners to consider using spectral analysis for establishing the ‘stylized facts’ of the financial time series under scrutiny and for regression models validation purposes.

Suggested Citation

  • Francois-Éric Racicot, 2011. "Low-frequency components and the Weekend effect revisited: Evidence from Spectral Analysis," RePAd Working Paper Series UQO-DSA-wp052011, Département des sciences administratives, UQO.
  • Handle: RePEc:pqs:wpaper:052011

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    References listed on IDEAS

    1. Francois-Éric Racicot & Raymond Théoret, 2008. "Optimal Instrumental Variables Generators Based on Improved Hausman Regression, with an Application to Hedge Funds Returns," RePAd Working Paper Series UQO-DSA-wp012008, Département des sciences administratives, UQO.
    2. Keim, Donald B., 1983. "Size-related anomalies and stock return seasonality : Further empirical evidence," Journal of Financial Economics, Elsevier, vol. 12(1), pages 13-32, June.
    3. Francois-Éric Racicot, 2007. "Techniques alternatives d’estimation et tests en présence d’erreurs de mesure sur les variables explicatives," RePAd Working Paper Series UQO-DSA-wp022007, Département des sciences administratives, UQO.
    4. Francois-Éric Racicot, 2000. "Estimation et tests en présence d'erreurs de mesure sur les variables explicatives : vérification empirique par la méthode de simulation Monte Carlo," RePAd Working Paper Series UQO-DSA-wp022008, Département des sciences administratives, UQO.
    5. Coen, Alain & Racicot, Francois-Eric, 2007. "Capital asset pricing models revisited: Evidence from errors in variables," Economics Letters, Elsevier, vol. 95(3), pages 443-450, June.
    6. Grüne, Lars & Semmler, Willi, 2008. "Asset pricing with loss aversion," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3253-3274, October.
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    Cited by:

    1. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun, 2016. "The weekend effect: an exploitable anomaly in the Ukrainian stock market?," Journal of Economic Studies, Emerald Group Publishing, vol. 43(6), pages 954-965, November.
    2. Guglielmo Maria Caporale & Luis Gil-Alana & Alex Plastun & Inna Makarenko, 2014. "The Weekend Effect: A Trading Robot and Fractional Integration Analysis," Discussion Papers of DIW Berlin 1386, DIW Berlin, German Institute for Economic Research.

    More about this item


    Spectral Analysis; Weekend Anomaly; Financial Cycles; Low-frequency Components; Asset Returns.;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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