Just a thought for the statistically inclined of you... I was bored this weekend and did smth for fun. I simulated 50,000 random walks 200 time periods each. No drift nothing. Just pure normal/gaussian noise. Then I cumulated the returns and sorted everything according to the cumulative returns as of the 100th period. Not surprisingly, given the size of the sample, there were some that wondered up/down quite a bit halfway through the sample time. Surprisingly, however, when I looked at the cumulative returns of the top/bottom 100 pseudo stocks from that point and on till the end, there was some stong evidence of reversals. The 100 "stocks" that were the biggest gainers as of the 100th interval had an average return that was negative and was economically and statistically significant at all conventional levels. The p-value was like 0.001 or something if I remember correctly. I looked at the losers as of time 100 and they preceeded to gain from that point until time 200. Also statiscially/economically significant. Now, had I not known the series were random, I might have concluded there is evidence of reversals. (overreaction, etc etc). Is there? Randomness may seem so misleading... The reason I'm posting this in the TA subsection is b/c I think a lot of what the conventional TA techniques may find is probably in the randomness that seems systematic category and the users should be very careful... Good luck to all.