(The Effect of the Skewness and Kurtosis of Stock Returns on the Bankruptcy and Default Probabilities)

Abstract

Purpose – The aim of this study is to increase the predictive power of bankruptcy and default models based on financial ratios by additionally using the first four moments of company stock returns (mean, volatility, kurtosis and skewness). Design/methodology/approach – In this study, a multinomial logistic model is estimated to explain the statistical probabilities of bankruptcy, default, and financial distress for approximately 10,000 publicly traded American companies between 1980 and 2011. Findings – The results show that the first four moments of stock returns and their lagged values can effectively predict the bankruptcy and default probabilities of publicly traded American companies. Discussion – The bankruptcy and default probabilities of companies are volatile and can change in a short period of time. While financial ratios used in the estimation of these probabilities are updated quarterly, stock returns can be updated more frequently (for example, updated every minute). For this reason, the use of stock returns in addition to financial ratios in bankruptcy and default models can significantly improve the predictive power of these models.