Abstract
In this study we try to briefly revise the day of the week effect (DOW) and to examine why there are conflicting empirical results through the time. Moreover, we try to add a new-alternative view to the specific area of study, adding a further possible explanation in calendar anomalies field of study. Specifically, we try to examine if investors’ weekday behavior changes depend on the financial trend. For example, let suppose that there are evidence that Mondays are positive returns days, but there are signs for an upcoming financial crisis. Could this general believed practical rule be strong enough in order to be sustainable even during financial crisis period or does it change? In order to analyze this issue providing empirical support, we examine the US stock market and the S&P index for the time period 2000–2013. The results confirm our assumption that the financial trend influences the weekly stock returns’ pattern, which may be an alternative explanation for the conflicting empirical findings that have been documented in the literature up today.
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- 1.
Usually turn of the month days are defined as the last day of a month and the first three trading days of the following month.
- 2.
This study examines latter data questions Sias and Starks (1995) findings.
- 3.
The term day of the week is generally used because quite often in the literature is reported a week pattern which is not the weekend effect (e.g. positive return day Tuesday and negative Wednesday).
- 4.
- 5.
Ülkü and Prodan (2013) suggest that when today’s closing price (Pt) crosses the n-days moving average MA(n) from below we buy, but when the Pt crosses the MA(n) from above we sell. n is the time period for which we calculate the moving average. This period could be short-term (n < 10), medium term (10 < n < 150) or long term (n > 150).
- 6.
Local maximum is a mathematical term for the peak.
- 7.
Friedrich Nietzsche’s said “The future influences the present just as much as the past”. Following this quote we thought that investors forecasts influence their current behavior and this was the starting point which finally helped us resolve the financial trend definition issue.
- 8.
The 4th sub-period’s max value, according to the data which we had available, is the 18/9/2013 (1725.52), but we use as end of period date 16/10/2013 (1721.54) in order to make some more observations and because the difference was not significant enough to change our conclusions (we run the model taking the 18/9/2013 as period-end date). All these data are available upon request.
- 9.
This partly confirms our prior characterization for the total period as no-trend period.
- 10.
The leptokurtosis of these three distributions is a sign that linear models may not be adequate to explain the specific time series’ behavior (Vasileiou 2015).
- 11.
We run the OLS models and we find significant ARCH effect problems. Moreover, if we adopt the OLS (assuming that the ARCH effect does not exist) the results are different than the final. These data are available upon request. The appropriate model selection is crucial, because (i) through time some studies which report the weekend effect fade, are called in question due to the violations of the OLS assumptions in the returns (Connolly 1989; Alford and Guffey 1996) and (ii) may be the reason for the conflicting findings.
- 12.
- 13.
These data are available upon request.
- 14.
The Akaike and Schwartz criterions present better results if we use the t-statistics instead of the Generalized Error Distribution (GED) proposed by Nelson (1991).
- 15.
Generally, similar to related studies when the two criteria suggest different models, lag orders the SIC is preferred to the AIC because: (i) it corrects the over-fitting nature of the AIC, and (ii) it is asymptotically consistent (Koehler and Murphree 1988). However, in most of the cases both criteria suggest similar results.
- 16.
More statistical information are available upon request.
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Vasileiou, E. (2017). Calendar Anomalies in Stock Markets During Financial Crisis: The S&P 500 Case. In: Hacioğlu, Ü., Dinçer, H. (eds) Global Financial Crisis and Its Ramifications on Capital Markets. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-47021-4_34
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