Open AccessA Chaos Approach To Bankruptcy Prediction
Author(s) -
David H. Lindsay,
Annhenrie Campbell
Publication year - 2011
Publication title -
journal of applied business research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.149
H-Index - 22
eISSN - 2157-8834
pISSN - 0892-7626
DOI - 10.19030/jabr.v12i4.5779
Subject(s) - bankruptcy , lyapunov exponent , univariate , chaos (operating system) , chaotic , econometrics , mathematics , chaos theory , bankruptcy prediction , multivariate statistics , control theory (sociology) , statistical physics , computer science , economics , statistics , artificial intelligence , finance , physics , control (management) , computer security
Chaotic systems, although deterministic and predictable over short horizons, appear to be random. This study applied chaos theory to bankruptcy prediction using a pair-matched sample of bankrupt firms. Given that healthy systems exhibit more chaos than unhealthy ones, it was hypothesized that the returns of firms nearing bankruptcy would exhibit significantly less chaos, measured with Lyapunov exponents, than at an earlier period. Successful univariate and multivariate bankruptcy prediction models were then constructed using the obtained Lyapunov exponents.