Summarizing the paper very very briefly (check the paper for better details), the original fund's returns time series is reduced to a zero-alpha time series, which is then modelled by means of market benchmarks, and finally the bootstrapping technique is applied to randomly generate a very high number of time series with the same statistical properties as the original zero-alpha fund's returns time series. If many of these simulated random time series show an alpha higher than the original non-zero-alpha time series, then the probability of having obtained that alpha just by chance is relatively high. Too much chance does not speak in favor of the fund manager's skills.
I modelled the whole process with KNIME and R, using R mainly for the bootstrapping part and I am now analyzing a few top performer funds with this technique. Are they top performers because of luck or skills?
Let's see what comes out.