Variance Ratio: A measure of the randomness of a return series. Variance ratio is computed by dividing the variance of returns estimated from longer intervals by the variance of returns estimated from shorter intervals, (for the same measurement period), and then normalizing this value to one by dividing it by the ratio of the longer interval to the shorter interval. A variance ratio that is greater than one suggests that the returns series is positively serially correlated or that the shorter interval returns trend within the duration of the longer interval. A variance ratio that is less than one suggests that the return series is negatively serially correlated or that the shorter interval returns tend toward mean reversion within the duration of the longer interval. Anyone use this to screen symbols? Seems like a good way to find "trendy" stocks.. I highly doubt you'll ever find any that mean-revert. Here are 2 symbols over 2 days and the corresponding variance ratio profiles: Blue and green are the same symbol, a few days apart and they are nearly equally "trendy" over both days.. the other symbol is trendy one day and completely random the next. Problem is, you can't tell in advance when a stock is going to trend or be completely random at the beginning of the day. However, if the level of randomness is steady over many many days one can make an assumption.. Now here are 4 random walks generated by taking the cumulative sum of a normal distribution with mean 0 variance 1. As you can see the variance ratio is pretty good at showing that the truly random series are indeed random. Are there any similiar methods, or better ones for detecting deviations from pure randomness?