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Predicting Corporate Financial Failure Using Macroeconomic Variables and Accounting Data

机译:使用宏观经济变量和会计数据预测公司财务失败

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摘要

Recent studies of the prediction of corporate financial failure have taken into account many factors, mostly corresponding to financial ratios derived from firms' annual accounts. Nevertheless, the current crisis and the consequent exponential increase in rates of insolvency have made it clear that the phenomenon of bankruptcy cannot be explained without reference to macroeconomic variables; thus, the overall condition of the economy, and not just the internal financial ratios of firms, must be addressed. In this paper, focusing on the Spanish construction sector from 1995 to 2011, we analyse selected econometric models for predicting bankruptcy, in which both macroeconomic variables and financial ratios are employed. In view of the large number of variables with these characteristics, which are frequently correlated with each other, and the consequent enormous number of models that would be obtained, we decided to focus on just five optimal econometric models for predicting the financial failure of firms, at 1, 2, 3, 4 and 5 years in advance, with a limited number of explanatory factors, to be selected by an automatic statistical procedure, guided solely by the data and based on a genetic algorithm. The empirical results obtained show that these econometric models are capable of achieving high rates of predictive success, both for in-sample and for out-of-sample predictions. In the latter case, failure and non-failure firms were classified with success rates of 98.5 and 82.5%, respectively, 1 year in advance. This predictive quality is maintained at 2, 3 and even 4 years in advance.
机译:对公司财务失败的预测的最新研究已考虑到许多因素,其中大部分与公司年度账目得出的财务比率相对应。然而,当前的危机以及随之而来的破产率呈指数增长,这清楚地表明,如果不参照宏观经济变量,就无法解释破产现象。因此,必须解决经济的整体状况,而不仅仅是企业的内部财务比率。在本文中,我们以1995年至2011年的西班牙建筑业为重点,分析了一些用于预测破产的计量经济学模型,其中同时采用了宏观经济变量和财务比率。鉴于大量具有这些特征的变量之间经常相互关联,并且随之而来的是数量众多的模型,因此,我们决定仅关注五个用于预测企业财务失败的最佳计量经济学模型,可以提前1、2、3、4和5年,并通过有限的解释因素,由自动统计程序选择,仅根据数据指导,并基于遗传算法。获得的经验结果表明,这些计量经济学模型能够对样本内和样本外预测实现较高的预测成功率。在后一种情况下,提前1年对失败和非失败公司进行了分类,成功率分别为98.5和82.5%。这种预测质量可以提前2年,3年甚至4年保持。

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