---
res:
  bibo_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. @eng'
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Jan
      foaf_name: Klobucnik, Jan
      foaf_surname: Klobucnik
  - foaf_Person:
      foaf_givenName: David
      foaf_name: Miersch, David
      foaf_surname: Miersch
  - foaf_Person:
      foaf_givenName: Sönke
      foaf_name: Sievers, Sönke
      foaf_surname: Sievers
  dct_date: 2017^xs_gYear
  dct_language: eng
  dct_subject:
  - Financial distress prediction
  - probability of default
  - accounting information
  - stochastic processes
  - simulation
  dct_title: 'Predicting Early Warning Signals of Financial Distress: Theory and Empirical
    Evidence@'
...