Investigation of economic data is often a posterior analysis. Clearly, among applied techniques the main difference is between methods able to (reasonably) capture past issues in inherent modeling approach or not. In the present contribution, a quite recent multibreakpoint analysis of time series is proposed with the aim to overcome traditional constraints the researcher has to face. As a matter of fact, common applied methods are able to identify one (or at best two) structural break(s) in time series. By investigating oil crude prices, we propose a quite different approach applying a not (at the moment) widespread econometric technique to detect more than a single structural break in empirical data analysis. Hence, a brief discussion is developed to compare resulting outcomes with real historical facts. The aim is to test endogenous capability of the technique in pairing changes in statistical properties of oil price time series with salient chronological events.