Directional-change intrinsic time

Directional-change intrinsic time is an event-based operator to dissect a data series into a sequence of alternating trends of defined size ${\displaystyle \delta }$.

Figure 1: A financial market price curve (grey) dissected by a set of directional-changes (grey squares). The size of the threshold of the operator is shown in the middle of the figure. Local extremes are marked by grey circles. The timeline contains intervals of equal length in physical time and the length of the intervals based on the  directional-change operator.

The directional-change intrinsic time operator was developed for the analysis of financial market data series. It is an alternative methodology to the concept of continuous time.[1] Directional-change intrinsic time operator dissects a data series into a set of drawups and drawdowns or up and down trends that alternate with each other. An established trend comes to an end as soon as a trend reversal is observed. A price move that extends a trend is called overshoot and leads to new price extremes.

Figure 1 provides an example of a price curve dissected by the directional change intrinsic time operator.

The frequency of directional-change intrinsic events maps (1) the volatility of price changes conditional to (2) the selected threshold ${\displaystyle \delta }$. The stochastic nature of the underlying process is mirrored in the non-equal number of intrinsic events observed over equal periods of physical time.

Directional-change intrinsic time operator is a noise filtering technique. It identifies regime shifts, when trend changes of a particular size occur and hides price fluctuations that are smaller than the threshold ${\displaystyle \delta }$.