Low-frequency components and the Weekend effect revisited: Evidence from Spectral Analysis
AbstractWe 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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Bibliographic InfoPaper provided by Département des sciences administratives, UQO in its series RePAd Working Paper Series with number UQO-DSA-wp052011.
Length: 18 pages
Date of creation: 30 May 2011
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Spectral Analysis; Weekend Anomaly; Financial Cycles; Low-frequency Components; Asset Returns.;
Find related papers by 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-06-11 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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CESifo Working Paper Series
4849, CESifo Group Munich.
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