Survival analysis of companies’ delisting time in Indonesian stock exchange using Bayesian multiple-period logit approach

Dedy Dwi Prastyo, Titis Miranti, Nur Iriawan

Abstract


Multiple-period logit model is equivalent to hazard model. This model is able to accommodate time varying predictor. In this work, the parameters of multiple-period model are estimated by using Bayesian inferences. There are three prior distributions used, i.e. improper uniform distribution, multivariate normal distribution, and Cauchy distribution. Criterion which is used to evaluate the proposed technique is C-index. The proposed method is applied to model the delisting time of companies listed in Indonesian Stock Exchange. The survival (delisting) time is driven by firm-specific predictors, i.e. financial ratios, that are calculated from quarterly financial report of companies in manufacturing sector span from the first quarter of 1990 until the third quarter of 2015. Two macroeconomic indicators are also considered as predictors. The empirical results show that the most appropriate prior is multivariate normal distribution. In addition, the proposed model is applied on windowing scheme by reducing the interval time as window in which the model estimator perform by its best.


Keywords


Survival; multiple-period logit; Bayesian; delisting; C-index

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DOI: https://doi.org/10.11113/mjfas.v13n4-1.864

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