Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/14530
Title: | Predicting shifts in the mean of a multivariate time series process: An application in predicting business failures | Authors: | Theodossiou, Panayiotis | metadata.dc.contributor.other: | Θεοδοσίου, Παναγιώτης | Major Field of Science: | Social Sciences | Field Category: | Economics and Business | Keywords: | Bankruptcy prediction;Business failure prediction models;Discriminant analysis;Multivariate cumulative sum procedure;Serial correlation;Sequential procedure | Issue Date: | Jun-1993 | Source: | Journal of the American Statistical Association, 1993, vol. 88, no. 422, pp. 441-449 | Volume: | 88 | Issue: | 422 | Start page: | 441 | End page: | 449 | Journal: | Journal of the American Statistical Association | Abstract: | A firm in the early stages of financial distress exhibits characteristics different from those of healthy firms. As the economic condition of a firm worsens, its financial characteristics shift toward those of failed firms. Practitioners in the financial sector have long been interested in the early detection of a firm’s slide toward insolvency. Several models have been developed with this purpose in mind, but these older models are static in nature. Therefore, a need exists for the development of business failure prediction models that assess the financial condition of firms sequentially over time. This article addresses this need by presenting a sequential business failure prediction model. | URI: | https://hdl.handle.net/20.500.14279/14530 | ISSN: | 01621459 | DOI: | 10.1080/01621459.1993.10476294 | Rights: | © Taylor & Francis | Type: | Article | Affiliation : | Rutgers University-Camden campus | Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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