I am reading paper "Tactical Investment Algorithms" (link) (NOTE: you can download the paper without registration, just press "Download" and then "Download without registration") by the famous Marcos López de Prado. On the page 8 he writes
In practice, it takes only a few recent observations for the estimated distribution of probability to narrow down the likely DGPs. The reason is, we are comparing two samples, where the synthetic one is comprised of potentially millions of datapoints, and it typically does not take many observations to discard what DGPs are inconsistent with recent observations.
Another possibility is to create a basket of securities with a returns distribution that matches the distribution of a given DGP. Under this alternative implementation, rather than estimating the probability that a security follows a DGP (Data Generating Process), we create a synthetic security (as a basket of securities) for which a given algorithm is optimal.
What does "estimating the probability that a security follows a DGP" mean? What is the probability that the sample is from the distribution?