Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence
S. Sievers, J. Klobucnik, D. Miersch, Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence, 2017.
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| Published
| English
Author
Sievers, SönkeLibreCat;
Klobucnik, Jan;
Miersch, David
Abstract
This study proposes a simple theoretical framework that allows for assessing financial distress up to five years in advance. We jointly model financial distress by using two of its key driving factors: declining cash-generating ability and insufficient liquidity reserves. The model is based on stochastic processes and incorporates firm-level and industry-sector developments. A large-scale empirical implementation for US-listed firms over the period of 1980-2010 shows important improvements in the discriminatory accuracy and demonstrates incremental information content beyond state-of-the-art accounting and market-based prediction models. Consequently, this study might provide important ex ante warning signals for investors, regulators and practitioners.
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84
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Sievers S, Klobucnik J, Miersch D. Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence.; 2017. doi:10.2139/ssrn.2237757
Sievers, S., Klobucnik, J., & Miersch, D. (2017). Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence. https://doi.org/10.2139/ssrn.2237757
@book{Sievers_Klobucnik_Miersch_2017, title={Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence}, DOI={10.2139/ssrn.2237757}, author={Sievers, Sönke and Klobucnik, Jan and Miersch, David}, year={2017} }
Sievers, Sönke, Jan Klobucnik, and David Miersch. Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence, 2017. https://doi.org/10.2139/ssrn.2237757.
S. Sievers, J. Klobucnik, and D. Miersch, Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence. 2017.
Sievers, Sönke, et al. Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence. 2017, doi:10.2139/ssrn.2237757.
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