There are different approaches for the detection of market phase changes in stock markets. Most

of them utilize various assumptions and constraints which makes these methods somewhat arbitrary.

This paper develops an algorithm which identifies bull and bear markets retrospectively in

a very robust way without using exogenous parameters. At the same time the algorithm is very

easy to execute, can be applied to several time series frequencies and is intended to identify rather

longer subperiods than shorter ones. Knowing the different phases one can investigate a multitude

of characteristics of bull and bear markets.