Using Cash Flow Ratios to Predict Business Failures

Abstract

Cash flow may be viewed as the lifeblood of a corporation and the essence of its very existence. Numerous empirical studies that use financial and accounting measures to predict business performance (i.e., success or failure) emphasize the importance of cash flow information in predicting bankrupt and nonbankrupt firms (Bernard and Stober, 1989; Gentry, 1984 and 1985; BarNiv, 1990, Carslaw and Mills, 1991). Most of those studies conclude that the level of cash inflows and outflows from various activities are highly interrelated. A failure of any part of the system to operate may endanger or cause the entire firm to fail (Largay and Stickney, 1980). The primary objective of this study is to assess the usefulness of cash flow disclosures as required by Statement of Financial Accounting Standards No. 95 (SFAS 95) in the prediction of bankruptcy, and whether cash flow data provide a superior prediction of business failure over the models employing conventional accrual accounting data. The business failure prediction criterion was used for two reasons: (1) Business success or failure has been causally linked to the volume of net cash inflow and outflow components from various activities (Gentry, 1985). For example, the inability of a firm to generate enough cash from its operations may force the firm to borrow more money or to dispose of its capital investments to meet its obligations. If this situation persists over an extended period of time, it may lead to an involuntary bankruptcy. (2) This criterion, which is empirically testable, has been successfully used for investigating the usefulness of accounting information in other studies (Altman and Spivack, 1983). A second objective of this study is to present some new financial ratios derived from cash flow data and to highlight their potential use in financial analysis and prediction of business performance. Some of these are new ratios which have not been used in other studies. MOTIVATION The motivation for this study came from two important developments in the business world: (1) the multitude of business failures across all types of business, and (2) the emphasis placed on cash flow information by the Financial Accounting Standards Board in SFAS 95. Could the use of cash flow data help predict business failure and thus help prevent business failure? The link between cash flow data and corporation net worth has been established in earlier research (Rayburn, 1986). However, these studies were done before the issuance of SFAS 95 and used different measures of cash flow from operations. Numerous studies show that financial ratios based on accrual accounting data possess significant ability to predict bankruptcy (Altman and Spivack, 1983; Beaver, 1966, 1968; Libby, 1975; Ohlson, 1980). Most of these studies concluded that companies with weak and unstable financial indicators (ratios) are more likely to fail than those companies with stronger and more stable financial indicators (ratios). However, these models did not emphasize cash flow data. An ideal approach is probably an integrated one, such as the approach suggested in this study. This paper provides evidence on the usefulness of cash flow data in the prediction of business failure and whether the integration of cash flow data with accrual accounting data can provide a superior measure over accrual accounting data alone for predicting bankruptcy. It should be noted that this study does not suggest overlooking these earlier predictive methods, but rather it addresses whether cash flow information can complement the information already provided by accrual accounting data. There are at least four key differences between the prior studies and this study. First, financial ratios based on conventional accrual accounting are modified to include cash flow information. Second, while prior studies use different approaches to measure cash flow from operations, this study bases its measures of cash from operations on those criteria required by SFAS 95. …

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 52 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.