  For the pedestrian observer, financial markets look completely random with
erratic and uncontrollable behavior. To a large extend, this is correct. At
first approximation the difference between real price changes and the random
walk model is too small to be detected using traditional time series analysis.
However, we show in the following that this difference between real financial
time series and random walks, as small as it is, is detectable using modern
statistical multivariate analysis, with several triggers encoded in trading
systems. This kind of analysis are based on methods widely used in nuclear
physics, with large samples of data and advanced statistical inference.
Considering the movements of the Euro future contract at high frequency, we
show that a part of the non-random content of this series can be inferred,
namely the trend-following content depending on volatility ranges.
