Harlan D. Platt

Probabilistic Neural Networks in Bankruptcy Prediction

Abstract Prior application of neural networks in finance and accounting, notably in bankruptcy prediction, are limited to back-propagation neural networks. Their well-known disadvantages, however, limit the practical usefulness of neural discriminant models. Instead, a probabilistic neural network with fewer of these difficulties is proposed. Using data from the U.S. oil and gas industry, alternate methodologies are compared. Whereas probabilistic neural networks without pattern normalization and Fisher discriminant analysis achieve the best overall estimation results, discriminant analysis produces superior results for bankrupt companies.

A note on the use of industry-relative ratios in bankruptcy prediction

Abstract The potential for industry-relative financial ratios to improve the prediction of firms in financial distress motivated this comparison of model specifications based on either unadjusted or industry-relative ratios. Both specifications yielded stable parameter estimates over the time periods examined. However, the industry-relative specification appeared to add incremental information not contained in the model based on the unadjusted financial ratios; the converse case did not hold. In addition, with the industry-relative specification, ex post forecast accuracy was slightly improved relative to the ex ante forecast, while with the unadjusted model specification, ex post forecast accuracy declined from that obtained ex ante.

Predicting corporate financial distress: Reflections on choice-based sample bias

Financial distress precedes bankruptcy. Most financial distress models actually rely on bankruptcy data, which is easier to obtain. We obtained a dataset of financially distressed but not yet bankrupt companies supplying a major auto manufacturer. An early warning model successfully discriminated between these distressed companies and a second group of similar but healthy companies. Previous researchers argue the matched-sample design, on which some earlier models were built, causes bias. To test for bias, the dataset was partitioned into smaller samples that approach equal groupings. We statistically confirm the presence of a bias and describe its impact on estimated classification rates.

Business cycle effects on state corporate failure rates

Abstract The effects of economic conditions, business costs, and new business formations on business failures were estimated for the time period 1969–1982. A cross-sectionally correlated and temporally autoregressive model was used to estimate model parameters. Significant differences were uncovered in the causes of business failure across the 48 states in the continental U.S. and Washington, DC. Four subgroups of states with common business failure conditions form the core of the analysis. Within each subgroup of states, economic conditions, business costs, and new business formations were found to be significant determinants of corporate failure rates with common parameter estimates.

The determinants of interindustry failure

Abstract Industry failure rates were shown to be related to the economic cycle, differences in industry financial conditions, and to the “spillover” of failure rates between vertically associated industries. The 1967 input-output table for the U.S. economy was used to determine potential spillovers of industry failure rates. Of the 128 industries with significant trading relationships, there were 30 industries whose failure rates were associated. Sixteen industry failure rate models were developed using quarterly data over the sample period 1950–1981. Parameter estimates were derived using three-stage least squares.

Sustainable growth rate of firms in financial distress

Sustainable growth rate defines the rate at which a company’s sales and assets can grow if the company sells no new equity and wishes to maintain its capital structure. The traditional formula assumes that the firm can increase its indebtedness. Many private firms and most firms in financial distress have limited or no access to debt markets. While distressed firms may prefer a no growth strategy, external pressures such as inflation or demand increases may cause their sales to rise exogenously. A new sustainable growth rate formula is developed that describes how much growth the firm with no new debt capacity can endure.

A note on identifying likely IPO bankruptcies: A symphonic paradox

This paper analyzes prospectus data for initial public offerings (IPOs) to develop an analytical tool to predict IPO survival beyond the first three years following the year of issuance. A logit regression yielded four significant ratios, three of which are related to capital structure decisions. The model correctly classified 31 percent of bankrupt IPOs and over 90 percent of survivors. Prediction of IPO failure within three years is difficult because IPOs are often “packaged” to sell.

A Re-examination of the Effectiveness of the Bankruptcy Process

As an increasing number of companies go bankrupt, society grows concerned with the processs efficacy. In contrast to previous research, we find that relatively healthy companies emerge from bankruptcy as evidenced by their operating and equity performance post bankruptcy. While we find a substantial degree of variation in the forecast accuracy of sales, EBIT and net income, we find that forecast errors are not statistically significant and are smaller than had been thought. We provide evidence to support the argument that the economys health affects operating and equity outcomes post bankruptcy. Copyright Blackwell Publishers Ltd 2002.

Free Cash Flow, Enterprise Value, and Investor Caution

By analyzing actual cash flows in comparison with enterprise values (market capitalization plus debt minus cash), this article documents that the market dramatically undervalues companies. The findings suggest that the equity market has an extraordinarily high discount rate that negates future earnings in the calculus of company value. That is, the discount rate is so high that the vast majority of future cash flows are virtually ignored. The research finds that stock prices do not reflect future corporate earnings. This contrasts with the well-known statement in finance textbooks that “the value of a firm equals the present discounted value of future cash flows.” While the DCF method is normally applied to “estimated” cash flows, it provides a familiar framework with which to test the equity market values against actual cash flows. The authors find that enterprise values are substantially less than the present discounted value of actual future cash flows. A one-dollar increase in actual future cash flows produces only a 75-cent increase in a company?s enterprise value (only 15 cents per dollar of future cash flows when company size is controlled). The implication is clear: companies are worth far more than the market believes. This provides strong support to the private equity industry. Yes, of late private equity firms have overpaid for acquisitions and may lose their entire investment during the current phase of deleveraging. Yet if private equity firms acquire companies at reasonable prices using less debt, they are likely to create substantial value as a consequence of the fact that companies are so undervalued by the market relative to their cash flows. There are no previous research efforts following the authors’ methodological design based on actual cash flows. Rather, prior research studies have focused on the relationship between forecasted cash flows (by market analysts) and enterprise value. The approach of this article focuses on a different question: the relationship between discounted actual future cash flows and the current market value.

The Private Equity Myth

Private equity has become a huge force in American business, but how is it creating value. The paper shows that private equity firms in recent years have paid high prices for acquired companies, leveraging them up, and then hoping to sell them to someone else. Doubts are raised as to whether this is a good strategy for investors or the nation.