  In this paper we study automatically recognized trends and investigate their
statistics. To do that we introduce the notion of a wavelength for time series
via cross correlation and use this wavelength to calibrate the 1-2-3 trend
indicator of Maier-Paape [Automatic One Two Three, Quantitative Finance, 2013]
to automatically find trends. Extensive statistics are reported for EUR-USD,
DAX-Future, Gold and Crude Oil regarding e.g. the dynamic, duration and
extension of trends on different time scales.
