Bankruptcy prediction: Application of the Taylor's expansion in logistic regression

The purpose of the present study is to test whether Taylor's series expansion can be used to solve the problem associated with the functional form of bankruptcy prediction models. To avoid the problems associated with the normality of variables, the logistic model to describe the insolvency risk is applied. Taylor's expansion is then used to approximate the exponent of the logistic function, or the logit. The cash to total assets, cash flow to total assets, and shareholder's equity to total assets ratios operationalize the factors affecting the insolvency risk. The usefulness of Taylor's model in bankruptcy prediction is evaluated applying the logistic regression model to the data from the Compustat database. The classification accuracy in the test data for the first and second years before bankruptcy show that the classification accuracy of a simple financial ratio model can be increased using the second-order and interaction terms of these ratios. However, in the third year, for the test data, Taylor's expansion is not able to increase the classification accuracy when compared with the first-order model.     

Cash Management Behavior and Failure Prediction

The purpose of this study is to evaluate the information contained in static and dynamic inventory cash management models to predict failure in a sample of 41 small and middle-sized Finnish bankrupt firms and their nonbankrupt counterparts. The results indicate that the estimates of the (scale) elasticity of cash balance with respect to the volume of transactions (approximated by net sales) is significantly lower for the failed firms. Furthermore, only the scale elasticity appears to be a statistically significant discriminating variable, and only in the first year before bankruptcy. This estimate remarkably increased the Lachenbruch validated classification accuracy based on traditional financial variables.     

A MULTIPERIOD MEAN-VARIANCE MODEL OF OPTIMAL CAPITAL STRUCTURE

The continuing interest in the capital structure issue among financial researchers is evidenced by the stream of capital structure models that have appeared in the literature. Much of this research has used a risk-neutral and/or a single-period framework. In this paper, we develop a capital structure model for multiperiod firms and allow for the firm's cash flows to grow over time, for the firm to issue new debt, and for two types of bankruptcy costs to occur. The types of bankruptcy costs that occur are determined by the firm's uncertain operating cash flows and negotiations between the firm and creditors. Risk is priced via the Sharpe-Lintner capital asset pricing model. Multiperiod risk-priced models, we argue, realistically represent actual firms and are thus an important step toward the development of more testable and usable models of capital structure. We execute a demonstration example in which the value of the levered firm achieves a maximum and discuss the steps the firm would take to maximize shareholder wealth within this example. The example illustrates that the value of the firm passes through an interior optimum as the promised debt payment is increased. A simulation of the effect of changes in firm-specific parameters shows that the model exhibits expected and appealing relationships between these parameters and the value of the levered firm.     

Prediction of Operating Cash Flows: Further Evidence from Australia

This paper examines empirically the relative abilities of current operating cash flows (hereafter OCF) and earnings in predicting future operating cash flows in Australia. It extends prior Australian research on cash flow prediction ( Percy and Stokes 1992 ; Clinch, Sidhu and Sing 2002 ; Farshadfar, Ng and Brimble 2009 ) by examining future cash flow predictions for one‐, two‐ and three‐year‐ahead forecast horizons; incorporating additional contextual variables likely to affect the predictive association between current cash flows or earnings and future cash flows; and comparing cross‐sectional versus time series‐based prediction models to ascertain the relative superiority of one approach over the other. Regression results reveal that the cash flow‐based models are more accurate in predicting future operating cash flows than earnings‐based models. This result, however, is moderated by firm‐specific contextual factors like firm size, negative versus positive cash flow pattern, cash flow variability and firm operating cycle. Finally, a comparison between cross‐sectional and time series approaches reveals that the cross‐sectional model outperforms the time series model for both the operating cash flows and earnings models in most of the forecast years.     

On long-term credit risk assessment and rating: towards a new set of models

Institutional investors are supposed to assess credit risk by using a combination of quantitative information such as option models and qualitative assessments. Although option models can be easily constructed, they are not so suitable for the assessment of long-term credit risk that is required by institutional investors. This is mainly because the probability of bankruptcy varies so widely depending on the timing of assessment. We propose a new set of assessment models for long-term credit risk which does not necessarily use stock prices and may incorporate business cycles. The new grand model consists of the two pillars: a long-term cash flow prediction model and a credit risk spread assessment model. The calculated values derived from these models are effectively usable for reasonable calculation of risk spreads. It is quite interesting to see that our investigation indicates that rating bias may exist in the credit risk assessment of the market.     

THE SIGNIFICANCE OF BASE YEAR IN DEVELOPING FAILURE PREDICTION MODELS

Most failure prediction models developed over the past fifteen years have been based on firms' financial characteristics one year before they collapsed. This article reports the results of a study employing multiple discriminant analysis on a sample of fifty-three British companies which failed over the period 1960–1971. Models were developed on various financial ratios and an industry indicator for each of the five years, prior to failure, and the results in fact show that the model developed from data five years before failure performed at least as well as that derived one year prior to bankruptcy.     

Corporate bankruptcy prediction in Japan

The purpose of this study is to highlight the financial characteristics of failed firms in Japan, and to construct corporate bankruptcy prediction models with greater prediction accuracy. Our principal component analysis indicated that failed firms in Japan could be classified into two groups: a group having negative financial structures and a group having a declining flow of funds. Additionally, they can be classified into two other different categories of groups: one whose financial position during three years before shows a ‘V’ shape and another group that shows a ‘XXX’ shape.Our discriminant analysis indicated that improved prediction accuracy could be obtained by using, as predictor variables, both ratios and absolute amounts based on cash base financial statement data three years before failure. This data was adjusted to properly reflect the exceptions, reservations, and qualifications appearing in the audit reports and those based on accrual base financial statement data.     

Conflicts of Interest and Market Illiquidity in Bankruptcy Auctions: Theory and Tests

I develop and estimate a model of cash auction bankruptcy using data on 205 Swedish firms. The results challenge arguments that cash auctions, as compared to reorganizations, are immune to conflicts of interest between claimholders but lead to inefficient liquidations. I show that a sale of the assets back to incumbent management is a common bankruptcy outcome. Sale-backs are more likely when they favor the bank at the expense of other creditors. On the other hand, inefficient liquidations are frequently avoided through sale-backs when markets are illiquid, that is, when industry indebtedness is high and the firm has few nonspecific assets.     

Beyond bankruptcy: Does the US bankruptcy code provide a fresh start to entrepreneurs?

This paper assesses the extent to which the US bankruptcy system is effective in providing small businesses a “fresh start” after a bankruptcy filing. I use data from the 1993, 1998 and 2003 National Survey of Small Business Finances to explore how firms fare after a bankruptcy filing. On the positive side, previously bankrupt firms are not any more burdened than the average small firm by problems relating to profitability, cash flow, health insurance costs, or taxes. Further, the fact that these firms are surviving several years after the filing is itself a testament to the efficient functioning of the US bankruptcy system. It suggests that the bankruptcy system goes a long way toward helping businesses recover after a bankruptcy filing.     

Bankruptcy, Warrants, and State-Contingent Changes in the Ownership of Control

We consider the design of securities that govern the distribution of cash flows and control rights for an investment project. An entrepreneur, endowed with managerial talent, contracts with an outside investor for required capital. Optimal contracts stipulate that the ownership of control and the distribution of cash flows are specified on a state contingent basis to manage the distortions that develop from the use of outside financing and so make the best use of the advantage in project management enjoyed by insiders. Our results illustrate that the use of warrants and convertible securities, which transfer control of the firm to outsiders in good states, and bankruptcy, which transfers control to outsiders in bad states, are related features of optimal contracts. Our model also indicates that firms will benefit from direct access to two types of bankruptcy processes resembling Chapter 7 and Chapter 11 (including deviations from absolute priority) of the bankruptcy code. This results differs from observed practices since stockholders cannot waive their rights for protection under Chapter 11. We show that when direct access to Chapter 7 is highly valuable, market participants have found clever ways to obtain it.Journal of Economic LiteratureClassification Numbers: G32 and G33.     

Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline

Using large amounts of data from small and medium‐sized industrial firms, this study examines two aspects of bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline. The results show that especially models generated from the final annual report published prior to bankruptcy were less successful in the timely prediction of failure. Furthermore, it was found that economic decline coincided with the deterioration of a model's performance. With respect to the methods used, we found that neural networks had a somewhat better overall performance than multiple discriminant analysis. Copyright © 2005 John Wiley & Sons, Ltd.     

Switching to a poor business activity: optimal capital structure, agency costs and covenant rules

We address the issue of modeling and quantifying the asset substitution problem in a setting where equityholders decisions alter both the volatility and the return of the firm cash flows. Our results contrast with those obtained in models where the agency problem is reduced to a pure risk-shifting problem. We find larger agency costs and lower optimal leverages. We identify the bankruptcy trigger written in debt indenture, which maximizes ex-ante firm value, given that equityholders will ex-post be able to risk-shift. Our model highlights the tradeoff between ex-post inefficient behavior of equityholders and inefficient covenant restrictions.      

Corporate Insiders and the Death of the Firm: Evidence on the Incidence of Insider Trading in Corporate Dissolutions

To date, little attention has been devoted to the relationship between the transactions of corporate insiders in the periods preceding corporate dissolutions and the form of dissolution taken. This study examines the transactions of corporate insiders preceding two forms of dissolution: bankruptcy and voluntary liquidation. The evidence suggests that prior to voluntary liquidations corporate insiders have been heavy net purchasers of their firms' shares. In contrast, heavy selling by corporate insiders was observed for a sample of firms that filed for bankruptcy.     

Do corporate payouts signal going-concern risk for auditors? Evidence from audit reports for companies in financial distress

We examine the association between payout policy changes and going-concern decisions for financially distressed clients. Extant auditing standards indicate that payout reductions, which offer a prospect of short-term cash relief, can potentially mitigate going-concern uncertainty, whereas economic theory suggests payout decreases (increases) convey mixed but mostly negative (positive) signals about a company’s future financial status. We find that, compared with a bankruptcy prediction model over short (not to exceed 1 year) and long (2–3 years) horizons, auditors seem to significantly underreact to payout decreases (i.e., negative signals) but react appropriately to payout increases (i.e., positive signals) in their going-concern decisions. Moreover, auditors are three times more likely to make Type II misclassification errors in payout-decreasing firms than in payout-increasing and no-change firms. We also find that auditors take longer to determine the appropriate opinion for clients with payout changes, especially for those who cut their payouts. Overall, our findings suggest that auditors respond differently to positive and negative signals about companies’ future prospects, reflecting the mixed nature of payout decreases relative to payout increases and the professional standards’ emphasis on the prospect of short-term cash relief from payout reductions.     

Predicting bankruptcy using the discrete-time semiparametric hazard model

The usual bankruptcy prediction models are based on single-period data from firms. These models ignore the fact that the characteristics of firms change through time, and thus they may suffer from a loss of predictive power. In recent years, a discrete-time parametric hazard model has been proposed for bankruptcy prediction using panel data from firms. This model has been demonstrated by many examples to be more powerful than the traditional models. In this paper, we propose an extension of this approach allowing for a more flexible choice of hazard function. The new method does not require the assumption of a parametric model for the hazard function. In addition, it also provides a tool for checking the adequacy of the parametric model, if necessary. We use real panel datasets to illustrate the proposed method. The empirical results confirm that the new model compares favorably with the well-known discrete-time parametric hazard model.     

Empirical comparison of hazard models in predicting SMEs failure

This study aims to shed light on the debate concerning the choice between discrete-time and continuous-time hazard models in making bankruptcy or any binary prediction using interval censored data. Building on the theoretical suggestions from various disciplines, we empirically compare widely used discrete-time hazard models (with logit and clog-log links) and the continuous-time Cox Proportional Hazards (CPH) model in predicting bankruptcy and financial distress of the United States Small and Medium-sized Enterprises (SMEs). Consistent with the theoretical arguments, we report that discrete-time hazard models are superior to the continuous-time CPH model in making binary predictions using interval censored data. Moreover, hazard models developed using a failure definition based jointly on bankruptcy laws and firms’ financial health exhibit superior goodness of fit and classification measures, in comparison to models that employ a failure definition based either on bankruptcy laws or firms’ financial health alone.     

Earnings Management in Chapter 11 Bankruptcy

We study the impact of earnings management prior to bankruptcy filing on the passage of firms through Chapter 11. Using data on public US firms, we construct three measures of earnings management: a real activities manipulation measure (abnormal operating cash flows) and two accounting manipulation measures (discretionary accruals and abnormal working capital accruals). We find that, controlling for the impact of factors known to influence earnings management and firm survival in bankruptcy, earnings management prior to bankruptcy significantly reduces the likelihood of Chapter 11 plan confirmation and emergence from Chapter 11. The results are driven primarily by extreme values of earnings management, characterized by one or two standard deviations above or below the mean. The findings are consistent with creditors reacting positively to unduly conservative earnings reports and negatively to overly optimistic earnings reports. We also find that the presence of a Big 4 auditor is associated with a higher incidence of confirmation and switching to a Big 4 auditor before filing increases the incidence of emergence.     

Financing and takeovers

This paper analyzes the interaction between financial leverage and takeover activity. We develop a dynamic model of takeovers in which the financing strategies of bidding firms and the timing and terms of takeovers are jointly determined. In the paper, capital structure plays the role of a commitment device, and determines the outcome of the acquisition contest. We demonstrate that there exists an asymmetric equilibrium in financing policies with endogenous leverage, bankruptcy, and takeover terms, in which the bidder with the lowest leverage wins the takeover contest. Based on the resulting equilibrium, the model generates a number of new predictions. In particular, the model predicts that the leverage of the winning bidder is below the industry average and that acquirers should lever up after the takeover consummation. The model also relates the dispersion in leverage ratios to various industry characteristics, such as cash flow volatility or bankruptcy costs.     

Forum-Shopping and Personal Bankruptcy

The dramatic increase in U.S. personal bankruptcy filings of the last fifteen years has focused attention on the wide disparities between different states' personal bankruptcy exemptions. These differences have been criticized both on the grounds of equity and also because they provide an incentive to move to a state with a higher exemption before declaring bankruptcy, that is to forum-shop. This paper focuses on the latter of these objections. Using data from the Panel Study of Income Dynamics (PSID), we estimate a Nested Logit model of the household migration decision. Our econometric approach specifically avoids the problem of endogenously induced bankruptcy filings by examining the effect of filing propensity, rather than the actual event of filing, on the tendency to migrate to a higher exemption state. We conclude that while there is indeed evidence that considerations of bankruptcy laws do influence interstate migration, the actual effect is relatively modest. We estimate that, in any given year, roughly one percent of moves to higher-exemption states are motivated by considerations of differences in bankruptcy laws; by way of comparison, this is roughly comparable to the magnitude of recent estimates of welfare-induced migration. This suggests that the emphasis on differences in exemptions which has been a feature of recent attempts to reform the bankruptcy code is somewhat exaggerated.     

What is behind the magic of O-Score? An alternative interpretation of Dichev’s (1998) bankruptcy risk anomaly

Using Ohlson’s (J Account Res 18(1):109–131, 1980) measure of bankruptcy risk (O-Score), Dichev (J Fin 53(3):1131–1147, 1998) documents a bankruptcy risk anomaly in which firms with high bankruptcy risk earn lower than average returns. This study first demonstrates that the negative association between bankruptcy risk and returns does not generalize to an alternative measure of bankruptcy risk. Then, by examining the nine individual components of O-Score, I find that funds from operations (FFO) is the only component that is associated with returns. Furthermore, I show that the return-predictive power of FFO is due to cash flows from operations. Taken as a whole, this study provides evidence that Dichev’s bankruptcy risk anomaly is a manifestation of investors’ under (over)-pricing of cash flows (accrual) component of earnings, i.e., the accrual anomaly documented by Sloan (Account Rev 71(3):289–316, 1996).