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Variable selection in forecasting models for default risk

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Alessandra Amendola

    (University of Salerno, Dept. of Economics and Statistics)

  • Marialuisa Restaino

    (University of Salerno, Dept. of Economics and Statistics)

  • Luca Sensini

    (University of Salerno, Dept. of Management Research)

Abstract

The aim of the paper is to investigate different aspects involved in developing prediction models in default risk analysis. In particular, we focused on the comparison of different statistical methods addressing several issues such as the structure of the data-base, the sampling procedure and the selection of financial predictors by means of different variable selection techniques. The analysis is carried out on a data-set of accounting ratios created from a sample of industrial firms annual reports. The reached findings aim to contribute to the elaboration of efficient prevention and recovery strategies.

Suggested Citation

  • Alessandra Amendola & Marialuisa Restaino & Luca Sensini, 2012. "Variable selection in forecasting models for default risk," Springer Books, in: Cira Perna & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 11-18, Springer.
    • Handle: RePEc:spr:sprchp:978-88-470-2342-0_2
    DOI: 10.1007/978-88-470-2342-0_2
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