Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence

84 Pages Posted: 23 Mar 2013 Last revised: 2 Nov 2017

See all articles by Jan Klobucnik

Jan Klobucnik

University of Cologne

David Miersch

Cologne Graduate School in Management, Economics and Social Sciences (CGS)

Soenke Sievers

Paderborn University

Date Written: October 31, 2017

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.

Keywords: Financial distress prediction, probability of default, accounting information, stochastic processes, simulation

JEL Classification: C63, C52, C53, G33, M41

Suggested Citation

Klobucnik, Jan and Miersch, David and Sievers, Soenke, Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence (October 31, 2017). Available at SSRN: https://ssrn.com/abstract=2237757 or http://dx.doi.org/10.2139/ssrn.2237757

Jan Klobucnik

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

David Miersch

Cologne Graduate School in Management, Economics and Social Sciences (CGS) ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

HOME PAGE: http://www.uni-koeln.de/

Soenke Sievers (Contact Author)

Paderborn University ( email )

Warburger Str. 100
Paderborn, 33098
Germany

HOME PAGE: http://www.upb.de/accounting

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