Here is a very interesting study by TradingMarkets on consecutive up days and down days in individual stocks.

Philip J. McDonnell comments: 

Some concerns:

They state that mean 1-day, 2-day and 1-week moves are their "benchmarks," but they never again refer to the 1-day and 2-day moves, which makes one at least a little suspicious about data snooping. It's better to say something like, "We looked at 1-day and 2-day moves, but there weren't any significant differences."

Speaking of significance, they don't provide standard deviations for their benchmarks or counts for total stocks in the x-day up/down groups, so one cannot calculate the significance of the sub-groups' deviations from the means of the overall group. The means of the sub-groups look interesting and convincing, but one would want to know that the differences are not created by a small number of highly volatile outliers.

And that brings up a broader issue: Are the benchmarks appropriate at all? TradingMarkets states:

We looked at over seven million trades from 1/1/95 to 6/30/06. The table below shows the average percentage gain/loss for all stocks during our test period over a 1-day, 2-day, and 1-week (5-days) period.

Of what relevance is this average 5-day move for these seven million trades? This is neither a cap-weighted nor an equal-weighted index, or any reproducible ex-ante yardstick, but just an artifact of their database, conflating the performance of all types of companies in all sorts of market conditions and creating an "average."

To paraphrase, TradingMarkets is saying that the stocks that went down five straight days in week[zero] did better in week[+1] than the overall "average" 5-day move. So what? The question needs to be: If stock XYZ went down five straight days in week[zero], and then went up in week[+1], how did this up move compare to some other benchmark for week[+1]?

It's easy to imagine that the sub-groups in the study select out highly-volatile stocks that are subject to wide swings in value and strings of up and down days. It might be more fruitful to compare these stocks to their own history, to determine whether multi-day moves are predictive for that individual stock. One might find differences between highly volatile stocks and relatively sedate stocks.





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