Yes I have also long suspected that looking at data in frequency representation should, in theory be much much much more useful than a history of price over time. But I am thinking of it perhaps differently... Set up a routine that identifies fluctuations in price (or some other parameter) occurring over a certain period of time (this then becomes the "frequency"), use a matrix calc (I'm thinking Matlab comes in handy here) to do this for many time lengths, and somehow the result can be parced over a range of frequencies. For example the "parameter" could be mean reversion of price. Using layman charts, this is for example the price excitation away from a rolling average (yup moving average), count time, revert to rolling average, stop count, mark, parse into bin... Data is time for the oscillation, magnitude (max), whatever else
To be clear, if you have access to data in milliseconds you are not in my league.
Edit: As price fluctuations are essentially random the results you have resembling white noise seem correct (?)