Validation methodology from HKMA CA-G-4(3)

repeating theprocedures k times, the targeted test statisticacross all k trials is then computed;

−“bootstrapping” means a resampling technique withreplacement of the data sampled, aiming togenerate information on the distribution of theunderlying data set;

−“in-sample validation” means validation of a ratingsystem employing observations that have beenused for developing the rating system;

−“out-of-sample validation” means validation of arating system employing observations that have notbeen used for developing the rating system;

−“out-of-time validation” means validation of a ratingsystem employing observations that are notcontemporary with the data used for developing therating system;

Besides, the HKMA CA-G-4 also mentioned the validation methodology which AI should consider due to the data limitations is described as below:

If out-of-sample and out-oftimevalidations cannot be conducted due to dataconstraints, AIs will be expected to employ statisticaltechniques such as k-fold cross validation orbootstrapping for this purpose.