The word "backtesting" refers to calculating the results of a trading strategy on a historical dataset. In our case, we will use the same dataset because of which we will overestimate the effectiveness, as our statistical models were optimized on exactly the same data. In the real life, we might go for a different time period or a different group of equities (or both) to measure efficiency more objectively.

No matter how we got the best performers separated, testing the investment idea follows the same logic. You translate the result into rules, pick the firms (normally from a different sample) that fulfill the requirements and place them into one cluster, and then create another cluster to contain all the other companies. Finally, compare the mean and/or median performance of the two groups.

To test the selection rules of the decision tree, we have to create a subset of firms that fulfil the requirements of having a cash ratio above 1.6, fixed asset ratio exceeding 12.3 percent...