Given one stock, what value would there be in clustering the individual sample observations within that stock's historical prices series, or its return series? is univariate clustering done in finance?
Clustering would allow the formation of a distance matrix that shows how far pairs of observations within that univariate time series are from one another, grouped together by similarity rather than the chaotic randomness seen in their original form, likely causing similar market regimes within that stock's history to be clumped together (or not). Why would this be useful or not useful?
and which dataset makes more sense, clustering observations of prices or returns?