This article makes an attempt to empirically examine the relationship between financial distress and earnings management with reference to selected Indian firms. Our sample consists of 150 financially distressed firms during the post-recession period from 2009 to 2014. The present study uses discretionary accruals (DA) as a proxy for earnings management. Multiple regression analysis has been used for this purpose. The study uses cross-sectional modified Jones model to estimate DA, a proxy for earnings management. Altman's Z-score (Z-score) and distance-to-default (DD) have been used as two alternative measures for financial distress. The study finds that less distressed firms are engaged in higher earnings management. Cash flow coverage (CFC) is found to have a significant negative relationship with earnings management implying that firms with higher CFC have lesser incentive to manage their earnings through DA. The findings are consistent with several prior studies. The findings of the study have important implications for lenders, investors and managers. Lenders and investors need to be wary of the fact that firms experiencing even low levels of distress might be more prone to concealing their true financial condition. This provides deeper insights into the reliability of accounting information in assessing the creditworthiness of a firm.

This article is an attempt to explore the usefulness of a model that uses the Piotroski's F-score and its individual components for predicting the risk of default for a sample of Indian firms. The study uses logistic regression as the prediction technique. The Piotroski's F-score is found to be statistically significant in predicting defaults. Higher values of the score are associated with lower probability of default. Among the individual components of the score, change in leverage is found to be statistically significant in predicting defaults. Increases in leverage are associated with higher probability of default. The model using the individual components of the score is found to have better prediction accuracy as compared to the model using the aggregate score. The findings of the study hold important implications for investment and lending decisions. The study contributes to the existing literature on default prediction by making available yet another measure which has so far not been explicitly used for distress prediction.

Purpose – This paper aims to examine the impact of initial public offering (IPO) grading on earnings management by Indian companies in their IPOs. Specifically, it investigates whether earnings management significantly differs in the pre-IPO grading regime and post-IPO grading regime. Further, it examines whether earnings management significantly differs between high-graded and low-graded IPOs. Design/methodology/approach – The cross-sectional modified Jones model is used to obtain the discretionary accruals, a proxy for earnings management. The impact of IPO grading on earnings management is assessed using multiple regression analysis. Findings – Earnings management is significantly lower in graded IPOs as compared to the ones that are not graded. Further, among the graded IPOs, the high-graded IPOs exhibit lower earnings management as compared to the low-graded IPOs. The findings are robust to the use of an alternative measure for discretionary accruals. Originality/value – IPO grading in India is a unique certification mechanism, introduced for the first time in any market. This paper establishes the efficacy of this mandatory certification mechanism in reducing earnings management. The findings could be valuable to issuer companies, investors and market regulators.

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2006),"Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches", If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -This paper aims to find out significant macroeconomic variables, incorporated as sensitivity variables (macroeconomic sensitivities), affecting financial distress for a sample of listed Indian firms. Design/methodology/approach -The study uses a matched pair sample of defaulting and non-defaulting listed Indian firms. It uses two alternative statistical techniques, viz., logistic regression and multiple discriminant analysis. The macroeconomic sensitivities are estimated by regressing the monthly stock return of the individual firm on the monthly changes in each macroeconomic variable. Findings -Sensitivity to changes in the stock market (stock market sensitivity) and sensitivity to changes in inflation [Consumer Price Index (CPI) sensitivity] have a significant impact on the default probability of a firm. Stock market sensitivity has a significant positive relationship with the probability of default, and CPI sensitivity has a significant negative relationship with the probability of default. Originality/value -The study links the developments in the external environment to the firm's susceptibility to default. Furthermore, it highlights the significance of sensitivity of a firm to uncertainties in the macroeconomic environment and its impact on default risk. This establishes the fact that each firm is uniquely affected by the changes in the overall macroeconomic environment. The findings could be valuable to lenders such as banks and financial institutions, investors and policymakers.