基于指数平滑预测和模式识别的业务失败预测

Tang Bao-jun, Qiu Wanhua, Sun Xing
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引用次数: 3

摘要

虽然其中一些方法所产生的模型在区分健康企业和破产企业方面具有令人满意的能力,但它们也存在一些局限性,通常是由于它们只能发出警报,而不能进行预测。这就是为什么我们进行了一项旨在削弱这些限制的研究。我们提出了一种指数平滑预测和模式识别(ESFPR)方法,并说明了如何将ESFPR应用于业务失败预测建模。结果令人鼓舞,证明了该方法对破产预测的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Business Failure Prediction Using Exponential Smoothing Forecasting and Pattern Recognition
Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt firms, they suffer from some limitations, often due to only give an alarm, but cannot forecast. This is why we have undertaken a research aiming at weakening these limitations. We propose an Exponential Smoothing Forecasting and Pattern Recognition (ESFPR) approach and illustrate how ESFPR can be applied to business failure prediction modeling. The results are very encouraging, and prove the usefulness of the proposed method for bankruptcy prediction.
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