Low-Frequency Components and the weekend Effect Revisited: Evidence from Spectral Analysis

• Autores: François-Eric Racicot
• Localización: Aestimatio: The IEB International Journal of Finance, ISSN 2173-0164, Nº. 3, 2011, págs. 2-19
• Idioma: inglés
• Enlaces
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• Resumen

  • 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

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