Detecting earnings management using cross-sectional abnormal accruals models

This paper examines specification and power issues in relation to three models used to estimate abnormal accruals. In contrast to the majority of prior work evaluating models estimated in time-series, we examine the performance of cross-sectionally estimated models. In addition to testing the standard-Jones (Jones, 1991) and modified-Jones (Dechow et al., 1995) models, we also develop and test a new specification, labelled the ‘margin model’. Consistent with prior US research employing time-series specifications of the two Jones models, our findings suggest that each of the three cross-sectional models are well specified when applied to a random sample of firm-years. However, the margin model appears to generate relatively better specified estimates of abnormal accruals when cash flow performance is extreme. Analysis of the models' ability to detect artificially induced earnings management indicates that all three procedures are capable of generating relatively powerful tests for economically plausible levels of accruals management (e.g., less than 10% of lagged total assets). Regarding their relative performance, the standard-Jones and modified-Jones models are found to be more powerful for revenue and bad debt manipulations. In contrast, the margin appears to be more powerful at detecting non-bad debt expense manipulations.     

An empirical investigation of earnings restatements by Australian firms

From 1970 to 2003, we document earnings restatements for the top 500 Australian firms, examine the characteristics of restating firms, and test whether restatements are value relevant. Of the 195 earnings restatements, 49 per cent decrease prior‐period earnings (negative restatements). Negative restatements are relatively larger than positive restatements. We identify three reasons for earnings restatements; namely, accounting policy changes, revision of estimates, and errors and unknown, and they comprise 49, 40 and 11 per cent of the sample, respectively. Restatement firms have higher growth opportunities and are smaller than non‐restating firms from the same industry. Restatements are generally negatively associated with market and non‐market value.     

Negative earnings,positive earnings and stock return predictability: An empirical examination of market timing

We examine the predictive ability of earnings-price ratios or yields for the S&P 500 index. We decompose the aggregate earnings-price ratio into its positive and negative components (“winners” vs “losers”) and find that the negative component has the most predictive ability. We also find that the earnings-price measures forecast both future returns and earnings growth. Our models display substantial variation in explanatory power over time with forecast power resurfacing in the latter 1990s. We conclude that to the extent that earnings-price yields predict future S&P 500 returns, the negative earnings component is the driving factor.     

An empirical comparison of bankruptcy models

Four types of bankruptcy prediction models based on financial statement ratios, cash flows, stock returns, and return standard deviations are compared. Based on a sample of bankruptcies from 1980 to 1991, results indicate that no existing model of bankruptcy adequately captures the data. During the last fiscal year preceding bankruptcy, none of the individual models may be excluded without a loss in explanatory power. If considered in isolation, the cash flow model discriminates most consistently two to three years before bankruptcy. By comparison, the ratio model is the best single model during the year immediately preceding bankruptcy. Quasi-jack-knifing procedures suggest that none of the models can reliably predict bankruptcy more than two years in advance.     

An empirical assessment of reinsurance risk

We analyse the effect of failing reinsurance cover on the stability of Dutch insurers. As insurers often reinsure themselves with other (re)insurers, a firm's loss could spread contagiously through the sector. Using a unique and confidential data set on reinsurance exposures, we gain insight into the reinsurance market structure and perform a scenario analysis to measure contagion risks. Considering entities on a standalone basis, we find no evidence of systemic risk in the Netherlands, even if multiple reinsurance companies fail simultaneously. At group level our analysis points to the contagion risk of in-house reinsurance structures, given that such in-house reinsurance parties are generally not higher capitalised than other group members.     

An empirical analysis of multivariate copula models

Since the pioneering work of Embrechts and co-authors in 1999, copula models have enjoyed steadily increasing popularity in finance. Whereas copulas are well studied in the bivariate case, the higher-dimensional case still offers several open issues and it is far from clear how to construct copulas which sufficiently capture the characteristics of financial returns. For this reason, elliptical copulas (i.e. Gaussian and Student-t copula) still dominate both empirical and practical applications. On the other hand, several attractive construction schemes have appeared in the recent literature promising flexible but still manageable dependence models. The aim of this work is to empirically investigate whether these models are really capable of outperforming its benchmark, i.e. the Student-t copula and, in addition, to compare the fit of these different copula classes among themselves.     

An evaluation of alternative proxies for the market's assessment of unexpected earnings

This study examines the association between abnormal returns and five alternative proxies for the market's assessment of unexpected quarterly earnings. We examine the role that measurement error potentially has in multiple regression tests of abnormal returns (occuring around the time of earnings announcements) on an unexpected earnings proxy and other non-earnings variables. The results indicate a potential measurement error interpretation of such multiple regression tests. We examine three procedures which reduce, to an unknown degree, the measurement error problem. Our procedures appear to be more (less) effective at reducing measurement error for small (large) firms and recent (non-recent) forecasts.     

An empirical assessment of the residual income valuation model

This paper provides an empirical assessment of the residual income valuation model proposed in Ohlson (Ohlson, J.A., 1995. Earnings, book values and dividends in security valuation. Contemporary Accounting Research 11, 661–687). We point out that existing empirical research relying on Ohlson's model is similar to past research relying explicitly on the dividend-discounting model. We establish that the key original empirical implications of Ohlson's model stem from the information dynamics that link current information to future residual income. Our empirical results generally support Ohlson's information dynamics. However, we find that our empirical implementation of Ohlson's model provides only minor improvements over existing attempts to implement the dividend-discounting model by capitalizing short-term earnings' forecasts in perpetuity.     

An empirical comparison of GARCH option pricing models

Recent empirical studies have shown that GARCH models can be successfully used to describe option prices. Pricing such contracts requires knowledge of the risk neutral cumulative return distribution. Since the analytical forms of these distributions are generally unknown, computationally intensive numerical schemes are required for pricing to proceed. Heston and Nandi (2000) consider a particular GARCH structure that permits analytical solutions for pricing European options and they provide empirical support for their model. The analytical tractability comes at a potential cost of realism in the underlying GARCH dynamics. In particular, their model falls in the affine family, whereas most GARCH models that have been examined fall in the non-affine family. This article takes a closer look at this model with the objective of establishing whether there is a cost to restricting focus to models in the affine family. We confirm Heston and Nandi's findings, namely that their model can explain a significant portion of the volatility smile. However, we show that a simple non affine NGARCH option model is superior in removing biases from pricing residuals for all moneyness and maturity categories especially for out-the-money contracts. The implications of this finding are examined. JEL Classification G13     

International bank-industry relations: An empirical assessment

This paper examines the determinants of the provision of banking services in host countries of multinational companies, based on an empirical study of these relationships in the case of France. Factors evaluated include: the traditional banking relationships in the multinational's home country, the strengths and weaknesses of indigenous and foreign banks in the host environment, the specific nature of the banking service required, and the nature of bank reputation in the host country.     

An empirical investigation of multiperiod tail risk forecasting models

In the context of multiperiod tail risk (i.e., VaR and ES) forecasting, we provide a new semiparametric risk model constructed based on the forward-looking return moments estimated by the stochastic volatility model with price jumps and the Cornish–Fisher expansion method, denoted by SVJCF. We apply the proposed SVJCF model to make multiperiod ahead tail risk forecasts over multiple forecast horizons for S&P 500 index, individual stocks and other representative financial instruments. The model performance of SVJCF is compared with other classical multiperiod risk forecasting models via various backtesting methods. The empirical results suggest that SVJCF is a valid alternative multiperiod tail risk measurement; in addition, the tail risk generated by the SVJCF model is more stable and thus should be favored by risk managers and regulatory authorities.     

An empirical analysis of the effects of monitoring intensity on the relation between equity incentives and earnings management

Prior studies suggest that equity incentives inherently have both an interest alignment effect and an opportunistic financial reporting effect. Using three distinct proxies for earnings management we find evidence consistent with the incentive alignment (opportunistic financial reporting) effect of equity incentives increasing as monitoring intensity increases (decreases). Furthermore, using the accrual-based earnings management and meet/beat analyst forecast models we find that the opportunistic financial reporting effect of equity incentives dominates the incentive alignments effect for firms with low monitoring intensity. Using proxies for real earnings management, we find that the incentive alignment effect dominates the opportunistic financial reporting effect for high and moderate monitoring intensity firms. However, for low monitoring intensity firms the opportunistic reporting effect mitigates, but does not completely offset, the benefits of the incentive alignment effect. Overall, these findings are consistent with the level of monitoring affecting the relation between equity incentives and earnings management.     

Earnings characteristics and analysts’ differential interpretation of earnings announcements: An empirical analysis

This study provides empirical evidence on factors that drive differential interpretation of earnings announcements. We document that Kandel and Pearson's forecast measures of differential interpretation are decreasing in proxies for earnings quality and pre‐announcement information quality. This evidence yields new and useful insights regarding which earnings announcements are less likely to generate newfound disagreement among analysts and investors. Recent research suggests that investor disagreement can increase investment risk, increase the cost of capital, and cause stock prices to deviate from fundamental value. Therefore, our results support prior intuition that increasing the quality of earnings and pre‐announcement information can improve the efficiency of capital markets.     

Asymmetric information in securitization: An empirical assessment

Asymmetric information in securitization deals is analyzed based on a unique dataset comprising a million mortgages, both securitized and not, and using a methodology, previously applied to insurance data, that looks at the correlation between risk transfer and default probability. The main finding is that, for given observable characteristics, securitized mortgages have a lower default probability than non-securitized ones. We show that this finding is consistent with banks caring about their reputation for not selling lemons.     

Spreading the sin: An empirical assessment from corporate takeovers

An acquisition of a company involved in socially undesirable activities can have important value implications. On the one hand, stocks in sin industries can be undervalued, and positive wealth effects might be created through risk sharing and a halo effect. On the other hand, acquiring sin stocks could increase litigation risk and the chance of product boycotts, and could hurt relations with employees and other stakeholders. Moreover, many investors avoid investments in sin stocks by applying negative screening. This article empirically establishes that shareholders of acquirer firms on average discount sin acquisitions. The negative wealth effects are stronger in countries with a greater focus on corporate social responsibility and for deals that are more likely to receive public attention. The article concludes that the costs of “sin” are considerable.     

The impact of abnormal real earnings management to meet earnings benchmarks on future operating performance

Motivated by agency conflicts of real earnings management (e.g., opportunistic and signalling perspectives), this study investigates the association between firms that manipulate their business operations to meet earnings benchmarks (i.e., zero earnings, last year's earnings) and subsequent operating performance. We examine the effects of the magnitude of real earnings management on firms' future performance for the period 2009 to 2015 for UK firms. Our analysis shows that the manipulation of operating activities such as sales, discretionary expenditures, and production costs to meet earnings benchmarks has a significantly positive consequence for firms' subsequent operating performance and signals firms' good future performance. We also find that firms that manipulate their operating activities in the absence of meeting earnings benchmarks experience a decline in their subsequent operating performance. The findings of this research lend support to our understanding of the process that management follows to evaluate costs and benefits of real earnings management.     

An empirical assessment of commercial web-based professor evaluation services

We examined the validity of data found on a popular web-based, user-created commercial professor evaluation service, RateMyProfessors.com (RMP), in business school settings. We compared publicly available RMP data for two business schools with official faculty evaluations unavailable to the public. We find that students rate professors significantly lower on RMP than on official university evaluations. However, we also find that the rankings of official university evaluations and RMP are significantly correlated (p < .001), with correlation values high enough to provide useful data to students.     

An empirical evaluation of alternative fundamental models of credit spreads

This study conducts an empirical comparison of how well alternative models of credit spreads explain CDS prices on 145 companies over the 2008–2019 interval. The results indicate that credit spreads are most closely related to theories which incorporate the likelihood of income insolvency into measures of the risk of jumps to default, with over half of individual CDS prices being explained, both during the financial crisis and thereafter. Out-of-sample tests using the same parameters estimated in-sample for all companies across time indicate that models which integrate the probability of income, cash, and valuation insolvency explain over 70% of spreads.     

An empirical comparison of continuous-time models of implied volatility indices

We explore the ability of alternative popular continuous-time diffusion and jump-diffusion processes to capture the dynamics of implied volatility indices over time. The performance of the various models is assessed under both econometric and financial metrics. To this end, data are employed from major European and American implied volatility indices and the rapidly growing CBOE volatility futures market. We find that the addition of jumps is necessary to capture the evolution of implied volatility indices under both metrics. Mean reversion is of second-order importance though. The results are consistent across the various metrics, markets, and construction methodologies.