  We study the possibility of completing data bases of a sample of governance,
diversification and value creation variables by providing a well adapted method
to reconstruct the missing parts in order to obtain a complete sample to be
applied for testing the ownership-structure/diversification relationship. It
consists of a dynamic procedure based on wavelets. A comparison with Neural
Networks, the most used method, is provided to prove the efficiency of the
here-developed one. The empirical tests are conducted on a set of French firms.
