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

Wavelet-Based Prediction for Governance, Diversification and Value Creation Variables