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While the final months of the year have just begun, the scoreboard for Mondays is not at all good so far. It suggests a short-term trading strategy that consists of being short on Mondays (where risks are still greatest) and being long on later weekdays. For the time being there is stickiness to this profitable trade.

Here we look at the daily index return for the past several weeks, since September 20th, when investors pivoted from the September 18th FOMC meeting, to the October debt ceiling contention. There have been 21 trading days from September 20, through yesterday October 21.

The S&P 500 index (NYSEARCA:SPY) is up 2%, during this time. But this return ignores the risk from the 4% drop, from September 18, through October 8. Most of that drop was during the past 21 trading days. Now Mondays were down 60% of the time (or 80% if we consider yesterday an actual loss on a risk-calibrated basis). While other weekdays had a lower risk rate that was less than half the time, at 44%.

We show, in the illustration below, that the average Monday performance (in red) was poor, at -0.3%, with a relatively tight standard deviation of just less than 0.5%. As an overall contrast, the other days (in green) collectively performed better, at +0.2%. The breakout of results by weekday will be shown in a table at the bottom.

(Click to enlarge)

Now neither of the portion differences noted earlier, nor the performance illustration above, are able to be considered statistically significant in isolation. However they fit the directional theme of Mondays being a more risky trading day (on either a risk neutral or absolute measurement basis) in recent weeks, and the results above taken together show to be more statistically significant.

We also show the ANOVA output below, in order to test the analysis of means. The results here, and even an advanced test for the difference of medians, both validate the description and significance of the results we just described. Notice the typical variation between weekdays is just slightly greater than the typical variation within weekdays. Also note that these raw units can be converted to percent by multiplying by 100, so for example, -0.003 would equal -0.3%. While the analysis moves with each passing day, it is clear with significance at this point that one can be short on Mondays and be long the S&P 500 index on later weekdays. For the time being there is stickiness to this profitable trade.

| Summary of DailyChange
Weekday | Mean Std. Dev. Freq.
Mon. (1) | -.00303257 .00506192 5
Tue. (2) | -.00353137 .00865051 4
Wed. (3) | .00272263 .00746272 4
Thu. (4) | .00569407 .01258733 4
Fri. (5) | .00393512 .00535415 4
Total | .00095805 .00822574 21

Analysis of Variance
Source SS df MS F Prob > F
Between groups .000297871 4 .000074468 1.13 0.3778
Within groups .001055387 16 .000065962
Total .001353258 20 .000067663

Bartlett's test for equal variances: chi2(4) = 3.3571 Prob>chi2 = 0.500

Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.