Faculty Digital Archive

Archive@NYU >
Stern School of Business >
Finance Working Papers >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2451/28297

Title: Post-Chapter 11 Bankruptcy Performance: Avoiding Chapter 22
Authors: Altman, Edward
Kant, Tushar
Rattanaruengyot, Thongchai
Issue Date: 3-Sep-2009
Series/Report no.: FIN-09-013
Abstract: Forty years ago, I developed a method of predicting bankruptcies by U.S. [public] companies that makes use of equity market values as well as fundamental financial and operating data. Since that time, my “Z-Score” model has become one of the most widely used methods for assessing the creditworthiness of manufacturing companies throughout the world. And it continues to be used by both finance scholars and practitioners in a variety of ways, including credit and debt analysis, investment decisions, merger and acquisition screens, audit-risk analysis, and receivables management. It has also been used by corporate managers and their advisers when managing turnarounds of distressed companies. This article extends the use of bankruptcy prediction models to a new application: the assessment of the health of industrial companies as they emerge from the Chapter 11 bankruptcy process, including the probability that the companies will have to file for bankruptcy again—the so-called “Chapter 22” phenomenon. Using a modified Z-Score model, I find significant economic differences between those companies that emerge from Ch. 11 and survive as going concerns and those that later file again. In particular, companies that filed a second Chapter 11 had significantly higher leverage and lower profitability shortly after emerging the first time. The predictive ability of this modified Z-Score suggests it can be used as a effective tool for evaluating the quality and efficacy of the bankruptcy reorganization plan.
URI: http://hdl.handle.net/2451/28297
Appears in Collections:Finance Working Papers

Files in This Item:

File Description SizeFormat
wp13.pdf159.81 kBAdobe PDFView/Open

Items in Faculty Digital Archive are protected by copyright, with all rights reserved, unless otherwise indicated.

 

The contents of the FDA may be subject to copyright, be offered under a Creative Commons license, or be in the public domain.
Please check items for rights statements. For information about NYU’s copyright policy, see http://www.nyu.edu/footer/copyright-and-fair-use.html 
Valid XHTML 1.0 | CSS