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

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  • Ines Kahloul
  • Anouar Ben Mabrouk
  • Slah-Eddine Hallara

Abstract

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.

Suggested Citation

  • Ines Kahloul & Anouar Ben Mabrouk & Slah-Eddine Hallara, 2010. "Wavelet-Based Prediction for Governance, Diversification and Value Creation Variables," Papers 1011.5020, arXiv.org.
    • Handle: RePEc:arx:papers:1011.5020
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    References listed on IDEAS

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    8. Anouar Ben Mabrouk & Hedi Kortas & Samir Ben Ammou, 2009. "Wavelet Estimators For Long Memory In Stock Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 297-317.
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    Cited by:

    1. Olfa Zaafrane & Anouar Ben Mabrouk, 2011. "A dynamic hybrid model based on wavelets and fuzzy regression for time series estimation," Papers 1102.3702, arXiv.org.
    2. Majed S. Balalaa & Anouar Ben Mabrouk & Habiba Abdessalem, 2021. "A Wavelet-Based Method for the Impact of Social Media on the Economic Situation: The Saudi Arabia 2030-Vision Case," Mathematics, MDPI, vol. 9(10), pages 1-21, May.

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