  This study proposes the segmentation procedure of univariate time series
based on Fisher's exact test. We show that an adequate change point can be
detected as the minimum value of p-value. It is shown that the proposed
procedure can detect change points for an artificial time series. We apply the
proposed method to find segments of the foreign exchange rates recursively. It
is also applied to randomly shuffled time series. It concludes that the
randomly shuffled data can be used as a level to determine the null hypothesis.
