Variable selection and corporate bankruptcy forecasts

We investigate the relative importance of various bankruptcy predictors commonly used in the existing literature by applying a variable selection technique, the least absolute shrinkage and selection operator (LASSO), to a comprehensive bankruptcy database. Over the 1980–2009 period, LASSO admits the majority of Campbell et al. (2008) predictive variables into the bankruptcy forecast model. Interestingly, by contrast with recent studies, some financial ratios constructed from only accounting data also contain significant incremental information about future default risk, and their importance relative to that of market-based variables in bankruptcy forecasts increases with prediction horizons. Moreover, LASSO-selected variables have superior out-of-sample predictive power and outperform (1) those advocated by Campbell et al. (2008) and (2) the distance to default from Merton’s (1974) structural model.     

Do risk exposures explain accounting anomalies? A new testing method

I quantitatively evaluate how much of the cross-sectional return predictive ability of a range of accounting anomalies can be attributed to firm-specific stock return covariances with market risk factors. Using a novel two-step regression-based testing method, I find robust evidence that the risk factor exposures do not explain a meaningful fraction of the time-series variations in the return predictive coefficients of the anomaly variables. Out-of-sample tests further confirm that it is the mispricing component of the accounting anomalies that is mainly responsible for the return predictability.     

LIFO-FIFO, ACCOUNTING RATIOS AND MARKET RISK: A RE-ASSESSMENT

This paper re-examines the effect of the inventory costing method on the association between accounting risk measures (ARMs) and market risk, and extends earlier research in several respects. The groups of FIFO and LIFO firms are matched on the basis of various financial characteristics to reduce selfselection bias, and the effect of inventory costing methods on the usefulness of ARMs in predicting market risk is investigated. The findings indicate that predictions based on FIFO show an improvement on market based predictions, but predictions based on LIFO fail to show such an improvement.     

Twenty‐five years of the Taffler z‐score model: Does it really have predictive ability?

Although copious statistical failure prediction models are described in the literature, appropriate tests of whether such methodologies really work in practice are lacking. Validation exercises typically use small samples of non‐failed firms and are not true tests of ex ante predictive ability, the key issue of relevance to model users. This paper provides the operating characteristics of the well‐known Taffler (1983) UK‐based z‐score model for the first time and evaluates its performance over the 25‐year period since it was originally developed. The model is shown to have clear predictive ability over this extended time period and dominates more naïve prediction approaches. This study also illustrates the economic value to a bank of using such methodologies for default risk assessment purposes. Prima facie, such results also demonstrate the predictive ability of the published accounting numbers and associated financial ratios used in the z‐score model calculation.     

RISK AND HEDGING BEHAVIOR: THE ROLE AND DETERMINANTS OF LATENT HETEROGENEITY

The notion of heterogeneous behavior is well grounded in economic theory. Recently it has been shown in a hedging context that the influence of risk attitudes and risk perceptions varies for different segments using a generalized mixture regression model. Here, using recently developed individual risk attitude measurement techniques and experimental and accounting data from investors with differing decision environments, we examine the determinants of heterogeneity in hedging behavior in a concomitant mixture regression framework. Allowing for latent heterogeneity, we find that risk attitudes and risk perceptions do not influence behavior uniformly and that the heterogeneity is influenced by manager's focus on shareholder value and the firm's capital structure.     

Using earnings forecasts to simultaneously estimate firm-specific cost of equity and long-term growth

A growing body of literature in accounting and finance relies on implied cost of equity (COE) measures. Such measures are sensitive to assumptions about terminal earnings growth rates. In this paper we develop a new COE measure that is more accurate than existing measures because it incorporates endogenously estimated long-term growth in earnings. Our method extends Easton et al. (J Account Res, 40, 657–676, 2002) method of simultaneously estimating sample average COE and growth. Our method delivers COE (growth) estimates that are significantly positively associated with future realized stock returns (future realized earnings growth). Moreover, the predictive ability of our COE measure subsumes that of other commonly used COE measures and is incremental to commonly used risk characteristics. Our implied growth measure fills the void in the earnings forecasting literature by robustly predicting earnings growth beyond the five-year horizon.     

Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach

We develop a state-of-the-art fraud prediction model using a machine learning approach. We demonstrate the value of combining domain knowledge and machine learning methods in model building. We select our model input based on existing accounting theories, but we differ from prior accounting research by using raw accounting numbers rather than financial ratios. We employ one of the most powerful machine learning methods, ensemble learning, rather than the commonly used method of logistic regression. To assess the performance of fraud prediction models, we introduce a new performance evaluation metric commonly used in ranking problems that is more appropriate for the fraud prediction task. Starting with an identical set of theory-motivated raw accounting numbers, we show that our new fraud prediction model outperforms two benchmark models by a large margin: the Dechow et al. logistic regression model based on financial ratios, and the Cecchini et al. support-vector-machine model with a financial kernel that maps raw accounting numbers into a broader set of ratios.     

Do geographically nearby major customers mitigate suppliers’ stock price crash risk?

This study examines the impact of geographically nearby major customers on suppliers' stock price crash risk. Using a sample of Chinese A-share listed firms and their top five (major) customers during the period 2008–2019, we find a significantly negative association. This association is robust in a series of robustness checks, including the use of instrumental variables estimations, propensity score matching procedure, and Heckman two-step sample selection model. The mitigating effect of supplier?customer proximity on crash risk is more pronounced for suppliers with lower corporate transparency and greater operational uncertainty. Finally, we identify two possible mechanisms through which geographically nearby major customers reduce suppliers’ crash risk: fewer financial restatements and higher accounting conservatism of suppliers. The findings of this study indicate that listed firms may choose geographically nearby customers to reduce crash risk.     

Tests of a rational expectations-structural neutrality model with persistent effects of monetary disturbances

This paper describes tests of a rational expectations-structural neutrality (RESN) model capable of accounting for the persistent effects of aggregate demand shocks. The model imposes the identifying restriction that only contemporaneous shocks to aggregate demand affect a vector stochastic process of highly cyclic real variables. Tests are performed using a well-known measure of unanticipated monetary change as the demand disturbance. The results suggest that RESN models, observationally inequivalent from Keynesian models, can be constructed in such a way as to account for observable relationships between monetary and real variables.     

Financial Forecasting,Risk and Valuation: Accounting for the Future

Valuation involves forecasting payoffs and discounting expected payoffs for risk. Forecasting is often seen as the province of the statistician, risk determination the province of asset pricing. This paper elaborates on the idea that financial forecasting, risk determination and valuation are a matter of accounting. Accounting not only provides information to forecast payoffs but also specifies the payoffs to be forecasted. Further, accounting determines the transition from the present to the future and thus implicitly the evolutionary parameters that a statistician might estimate for forecasting. Accounting also bears on risk determination in the way it handles uncertainty. Accordingly, accounting is involved in both the numerator and the denominator of a valuation model. Indeed, a valuation model is a model of accounting for the future, and the effectiveness of a valuation model rides on the accounting principles employed.     

Dynamic risk, accounting-based valuation and firm fundamentals

This study extends the accounting-based valuation framework of Ohlson (Contemp Acc Res 11(2):661–687, 1995) and Feltham and Ohlson (Acc Rev 74(2):165–183, 1999) to incorporate dynamic expectations about the level of systematic risk in the economy. Our model explains recent empirical findings documenting a strong negative association between changes in economy-wide risk and future stock returns. Importantly, the model also generates costs of capital that are solely a linear function of accounting variables and other firm fundamentals, including the book-to-market ratio, the earnings-to-price ratio, the forward earnings-to-price ratio, size and the dividend yield. This result provides a theoretical rationale for the inclusion of these popular variables in cost of capital (expected return) computations by the accounting and finance literatures and obviates the need to estimate costs of capital from unobservable (future) covariances. The model also generates an accounting return decomposition in the spirit of Vuolteenaho (J Finance 57(1):233–264, 2002). Empirically, we find that costs of capital generated by our model are significantly associated with future returns both in and out of sample in contrast to standard benchmark models. We further obtain significantly lower valuation errors in out-of-sample tests than traditional models that ignore dynamic risk expectations.     

Financial distress and bankruptcy prediction among listed companies using accounting,market and macroeconomic variables

Using a sample of 23,218 company-year observations of listed companies during the period 1980–2011, the paper investigates empirically the utility of combining accounting, market-based and macro-economic data to explain corporate credit risk. The paper develops risk models for listed companies that predict financial distress and bankruptcy. The estimated models use a combination of accounting data, stock market information and proxies for changes in the macro-economic environment. The purpose is to produce models with predictive accuracy, practical value and macro dependent dynamics that have relevance for stress testing. The results show the utility of combining accounting, market and macro-economic data in financial distress prediction models for listed companies. The performance of the estimated models is benchmarked against models built using a neural network (MLP) and against Altman's (1968) original Z-score specification.     

A comparison of V-I-E model predictions: A cross-national study in professional accounting firms

Behavioral research in accounting has largely ignored the impact of cross-national differences. This paper deviates from that trend and reports the results of a study comparing the predictive ability of the Valence-Instrumentality-Expectancy (V-I-E) model of motivation in two cultural settings: Australia and the United States of America. Data was collected from a matched sample of 45 staff-level auditors drawn from a large public accounting firm in each of the two respective countries. The findings indicate that few differences exist between the two groups with respect to personal value structures, motivation levels, and perceptions of the work environment. The results are significant both as a systematic cross-national comparison of accounting groups and as an extension of current V-I-E research in accounting.     

Constructing an ‘efficient frontier’ of accounting journal quality

This paper reports the construction of an ‘efficient frontier’ of the perceived quality attributes of academic accounting journals. The analysis is based on perception data from two web-based surveys of Australasian and British academics.The research reported here contributes to the existing literature by augmenting the commonly supported single dimension of quality with an additional measure indicating the variation of perceptions of journal quality. The result of combining these factors is depicted diagrammatically in a manner that reflects the risk and return trade-off as conceptualised in the capital market model of an efficient frontier of investment opportunities. This conceptualisation of a ‘market’ for accounting research provides a context in which to highlight the complex issues facing academics in their roles as editors, researchers and authors.The analysis indicates that the perceptions of the so-called ‘elite’ US accounting journals have become unsettled particularly in Australasia, showing high levels of variability in perceived quality, while other traditionally highly ranked journals (ABR, AOS, CAR) have a more ‘efficient’ combination of high-quality ranking and lower dispersion of perceptions. The implications of these results for accounting academics in the context of what is often seen as a market for accounting research are discussed.     

Disclosure of fair value measurement in goodwill impairment test and audit fees

Recent increases in the occurrence and magnitude of goodwill impairment charges highlight the increasing importance of the role of the auditor in goodwill accounting. This study examines the association between disclosures about the fair value measurement of goodwill and audit fees. We find that goodwill-related disclosures are positively related to audit fees, consistent with the idea that auditors increase their audit efforts to mitigate potential reputational and litigation losses (“audit risk effect”). Additionally, our results indicate that the information asymmetry and investor scrutiny moderate the association between goodwill-related disclosures and audit fees. One possible explanation is that auditors take goodwill-related disclosures as a signal of truthful goodwill accounting and this “signaling effect” partially offsets the “audit risk effect” of goodwill-related disclosures when information asymmetry or investor scrutiny is perceived as high.     

Measuring securities litigation risk

Extant research commonly uses indicator variables for industry membership to proxy for securities litigation risk. We provide evidence on the construct validity of this measure by reporting on the predictive ability of alternative models of litigation risk. While the industry measure alone does a relatively poor job of predicting litigation, supplementing this variable with measures of firm characteristics (such as size, growth, and stock volatility) considerably improves predictive ability. Additional variables such as those that proxy for corporate governance quality and managerial opportunism do not add much to predictive ability and so do not meet the cost–benefit test for inclusion.     

Problem directors on the audit committee and financial reporting quality

The objective of this paper is to examine empirically the consequences for financial reporting quality of having audit committees that include problem directors, that is, directors with prior involvement in corporate bankruptcies, major accounting restatements, or other accounting scandals. An ordinary least squares regression model is used to examine the association between problem directors on the audit committee and financial reporting quality as proxied by accruals and real earnings management. Results reveal that there is a positive association between the presence of problem directors on the audit committee and real earnings management, and this association is more pronounced in cases where those problem directors have been involved in prior instances of accounting restatements and fraudulent reporting practices.     

Municipal bond market recognition of pension reporting practices

The purpose of this study was to examine the usefulness of current municipal pension accounting disclosures for assessing municipal bond risks and returns. An empirical assessment of the association between various pension ratios and bond ratings, bond yields, and market risk revealed little explanatory power in the pension variables. We posit that the results probably stem from current practices that reduce the relevance and reliability of pension accounting numbers. Thus, standardization of practices and increased disclosures as proposed by the NCGA may have positive effects on the usefulness of pension disclosures for creditor decisions.     

Accounting measures and international pricing models: Justifying accounting homogeneity

We study the importance of homogeneous accounting data when testing international versions of asset pricing models. Specifically, we focus on a pricing model commonly used by practitioners – the Fama–French three-factor model – which uses accounting information and has traditionally performed poorly at the cross-country level. We show that international versions of the model perform significantly better if the accounting information is homogeneous across firms. We apply the model to a set of firms that follow common accounting standards – the IAS/IFRS – and also to firms that have issued ADRs in the US – and therefore must report following both US GAAP and their own domestic standards. In both cases our results show that the accounting dimension is relevant: the use of homogeneous accounting measures allows for much higher goodness-of-fit of international versions of the three-factor model, at levels similar to those of domestic versions and superior to those of non-homogeneous versions. This suggests that further accounting homogeneity could lead to more accurate pricing and valuation of international assets and to an improvement of the efficiency of international fund allocation.     

CORPORATIZATION AND THE REGULATION OF ACCOUNTING SERVICES

The litigation explosion in the professional practice environment of accountants is contributing to changes in the ownership structure of accounting firms. The changes have, however, been implemented with little debate. This paper examines the impact that ownership structure of accounting firms has on the ability of the profession to self-regulate, especially when the firm, rather than the individual professional, takes responsibility for the services provided. It is shown that the corporatization of professional practice could seriously impede the profession's ability to self-regulate. Since self-regulation is an important function of a professional association, the paper highlights the need for further debate and research on the effects of corporatization.