Abstract
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.
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