Seeing as Bollinger Bands are computed by adding and subtracting x*stdev(array,periods) from the MA you only need to find the standard deviation (stdev) of the price information in the first place. The stdev() data can be compared against any other company stdev(). Have a look in the Users Manual regarding construction of Bollinger Bands, it will give you insight into how to compare the data of different stocks. If you want to normalise the stdev data for all stocks in a folder/portfolio (or normalize - depends where you are from) then you are in for a very complicated process, that only Patrick and his amazing Dll will be able to solve (if he writes it!) Hope this helps. wabbit :D

[Whats up with the system tonight? - Missing data in posts, cannot re-post or edit??] Try again... Seeing as Bollinger Bands are computed by adding and subtracting x*stdev(array,periods) from the MA you only need to find the standard deviation (stdev) of the price information in the first place. The stdev() data can be compared against any other company stdev(). [edit] [lost most of this paragraph somehow??] The stdev() data can be compared against any other company stdev() by dividing each by the company price data array; i.e. stdev(c,20)/c. This can be easily scaled by multiplying by a constant, like 100, to return 100*stdev(c,20)/c. However, my preference is to divide by the MA used as the comparative difference in the first place.... just a preference, 100*stdev(c,20)/mov(c,20,s) Have a look in the Users Manual regarding construction of Bollinger Bands, it will give you insight into how to compare the data of different stocks. If you want to normalise the stdev data for all stocks in a folder/portfolio (or normalize - depends where you are from) then you are in for a very complicated process, that only Patrick and his amazing Dll will be able to solve (if he writes it!) Hope this helps. wabbit :D