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The purpose of this paper is to investigate the association between gross profit percentage, abnormal market returns, revenue surprises and earnings surprises. Gross margin is relied upon by various market participants, as its predictive power is incremental and distinct from revenue and earnings signals; however, gross margin has received little researcher attention.

General regression specifications found in the prior literature are extended to assess the informational content of changes in gross margin percentage. In addition, various portfolios are created based around the nature of the signals (positive or negative), provided by each income statement metrics (revenue, gross margin and earnings). A sample of 5,582 quarterly observations of S & P 500 firms is compiled. The main regressions are exposed to three robustness tests that focus on industry sub-groupings, institutional ownership and fourth-quarter observations.

The main findings reveal that gross margin percentage changes and earnings surprises are significantly related to abnormal market returns in the short window around the earnings announcement date and persist into a wider window measured as the quarter after the earnings announcement date. The relationship between gross margin percentage changes and abnormal returns is more pronounced when positive (negative) changes in gross margin percentage are accompanied by positive (negative) revenue and earnings surprises.

This study relies upon S & P 500 firms which are all relatively large firms. Therefore, the results may not be generalizable to smaller firms. In addition, the gross margin change is measured as the quarter-over-quarter percentage change because there is no analyst expectation for gross margin.

This paper extends the prior literature by developing three testable hypotheses that investigate the linkages between abnormal market returns, gross margin and revenue and earnings surprises. This is the first known study to investigate the informational content of changes in gross margin percentage.

The paper aims to examine the rounding phenomenon in reported earnings and revenues of Japanese publicly listed firms to achieve key reference points. The paper also examines the changes of rounding behavior among Japanese publicly listed firms around the asset bubble burst in 1990.

To test the null hypothesis of no managerial effort to round earnings and revenues, the paper compared the observed frequency of each number in the second place of earnings and revenues numbers to the expected occurrences of the number as predicted by Benford's law.

The paper finds that rounding manipulation is prevalent in the reporting of both earnings and revenues among the firms. The paper also documents that rounding manipulation is more severe in reported earnings than that in reported revenues. The paper finds constant rounding manipulation behavior in reported earnings upon the asset bubble bursting in 1990; however, the magnitude of rounding manipulation in reported revenues decreases significantly after the bubble burst. This finding supports the argument that Japanese firms tend to focus more on short-term performance in the post-bubble era.

This paper is the first study to focus on rounding behavior in reported revenues of Japanese firms. As important as the earnings are on firms' valuation and contractual measures, revenues deserve intensive awareness in the financial studies. The study also explores the changes of Japanese managers' rounding manipulation behavior since the asset bubble burst in 1990. Documentation of the structural changes in the lost decades in Japan can provide valuable lessons for other countries in similar situations.

The purpose of this paper is to evaluate if there are any momentum patterns in stock and sectoral returns and if they can be explained by the risk factors.

The methodology involves portfolio generation based on company characteristics and short‐term prior return (six to 12 months). The characteristic‐sorted portfolios are then regressed on risk factors using one‐factor (CAPM) and multi‐factor model (Fama French model and four‐factor model involving three Fama French factors and an additional sectoral momentum factor).

The authors find momentum profits in Indian context for prior return portfolios which are stronger for 6‐6 compared to 12‐12 strategies. These momentum profits are larger for some characteristic‐sorted portfolios. Risk models such as CAPM and Fama French model fail to capture momentum profits. In fact, winner portfolios generally comprise large firm and high P/B stocks, thus defying the risk story. Some zero investment momentum‐based trading strategies do provide significant payoffs. The authors also observe momentum profits in sectoral returns. A part of stock momentum profits is captured by sectoral factor, thus implying that it may mainly be an outcome of sectoral momentum.

The findings are pertinent for portfolio managers and investment analysts who are continuously in pursuit of trading strategies that provide extra normal returns. From an academic point of view, the authors suggest that sectoral factor should be used in the multi‐factor framework for explaining asset returns.

The study contributes to the asset pricing and behavioral literature from emerging markets.

The purpose of this paper is to analyze long-term prior return patterns in stock returns for India.

The methodology involves portfolio generation based on company characteristics and long-term prior return (24-60 months). The characteristic sorted portfolios are then regressed on risk factors using one factor (capital asset pricing model (CAPM)) and multi-factor model (Fama-French (FF) model and four factor model involving three FF factors and an additional sectoral momentum factor).

After controlling for short-term momentum (up to 12 months) as documented by Sehgal and Jain (2011), the authors observe that weak reversals emerge for the sample stocks. The risk model CAPM fails to account for these long-run prior return patterns. FF three-factor model is able to explain long-term prior return patterns in stock returns with the exception of 36-12-12 strategy. The value factor plays an important role while the size factor does not explain cross-section of average returns. Momentum patterns exist in long-term sector returns, which are stronger for long-term portfolio formation periods. Further, the authors construct sector factor and observe that prior returns patterns in stock returns are partially absorbed by this factor.

The findings are relevant for investment analysts and portfolio managers who are continuously tracking global markets, including India, in pursuit of extra normal returns.

The study contributes to the asset pricing and behavioral literature from emerging markets.

The paper aims to examine the value relevance of alternative accounting performance measures in Australia. It also documents the relative and incremental value relevance of revenue vis‐à‐vis earnings and the longitudinal changes in such value relevance. Finally, the impact of certain firm characteristics including firm life cycle on the value relevance of revenue and earnings information is investigated.

The paper utilises data on Australian listed companies from 1992 to 2005 on the level of and changes in seven alternative accounting performance measures. Standard ordinary least square regression is conducted.

Results reveal that: the coefficient estimates on all the performance measures are much higher for large firms compared to their small firm counterpart; the explanatory power of incremental revenue in explaining stock returns has declined significantly over the sample period; and life cycle analysis shows that the combined coefficients for both revenue and earnings are significant in the growth and maturity stages of the firm life cycle.

When making equity valuation decisions investors consider firms' fundamentals as reflected in financial statements. However, which line item is more important for equity valuation is an important consideration. From a regulatory perspective, this stream of research is quite relevant because standard setters will have evidence from an investor viewpoint about whether certain line items, subtotals, and totals should be defined in standards and required to be displayed in financial statements.

The paper adds to the existing capital market research in Australia by documenting differential persistence of alternative performance measures.

The purpose of this paper is to investigate whether deferred revenue changes can serve as a leading indicator for firms listed on China’s stock markets, and whether China’s market participants can appropriately incorporate future performance implications of deferred revenue changes.

Empirical/archival/regression analysis.

The authors find that deferred revenue changes are positively associated with the next two years’ sales growth, gross profit margin, profit margin, and return on assets, suggesting that deferred revenue changes can serve as a valid leading indicator for future financial performance. The authors also find that Chinese investors tend to underweight future performance implications of deferred revenue changes.

To the authors’ knowledge, this study is among the first research to examine deferred revenue changes as a leading fundamental indicator and market underreaction to reported accounting information for firms listed on China’s stock markets.

The purpose of this study is to examine the association between revenue-based earnings management in the periods immediately before and after firms’ initial public offerings (IPOs) and regulatory scrutiny by the United States Securities and Exchange Commission (SEC) during review of IPO firms’ registration statements.

This paper uses conditional discretionary revenues (Stubben, 2010) as its measure of earnings management, and revenue recognition comments delivered by the SEC as its measure of regulatory scrutiny. The authors use ordinary least squares regression (OLS) models, as well as a supplemental count model, to assess the association between conditional discretionary revenues and revenue recognition comments delivered by the SEC.

This study finds evidence of a positive association between earnings management measures in the pre-IPO period and the number of revenue recognition comments received by those firms during the SEC’s review. Furthermore, this study provides evidence that greater numbers of comments are associated with declining earnings management measures in the post-IPO period. However, the evidence suggests that these associations apply only to income-decreasing earnings management.

This paper extends the IPO earnings management literature by using conditional discretionary revenues as the measure of earnings management, and contributes to a nascent research stream in the accounting literature by investigating the SEC’s comment letter process and its association with, and impact upon, earnings management in the IPO process.

This paper aims to shed some light on the role of video games within the media industry and IT sector, on its contribution to the production and distribution of digital content in emerging economies. It offers a case study on the role of mobile devices as a factor of transformation and shows how under changing socio–economic conditions, the transformations enabled the creation of digital ecosystems and innovative business models.

The paper is based on desk research, a review of literature and trade press and comments from experts and industry players.

The paper argues that as the internet is going mobile, driven by data – mostly video – the new mobile platforms are becoming the key for the distribution of content and mobile games. Whether it is the history of browser games in China, mobile games in India or PC games in Russia, each national gaming industry has required a unique strategy for making money, building on some prominent cultural factors and adapting to the local economic conditions. The paper reveals that video games are now clearly a vital part of digital content production in these countries, while stressing upon the role of public policies.

The paper relies mostly on industry and consultancy data, as in such a fast-changing environment official data even when accessible are in most cases too old to remain relevant to identify the trends and the fast changing stakes. This calls for some caution about the data. Therefore, the data used should be treated as just signals of potential trends, sufficient to provide an appropriate overview of the evolution of the global mobile ecosystem.

This paper shows that the video games industry can serve as a pivot for the ICT industry. Besides, this prompts upstream and downstream industries of the entire digital entertainment market to thrive.

The paper shows that companies from emerging markets companies have been betting on a combination of factors: the development of the economies, the growth of the mobile market, emerging middle-classes and young customers. It provides a growth model that appears to be close to a “regular” industrial growth model.

Although there is a growing academic literature on the video games industry, few research have been devoted to specific issues of emerging economies and to the role of video games within the media industry and IT sector.

The authors aim at investigating different forms of classification shifting (CS). CS is a novel form of earnings management under which managers misclassify income statement line items and cash flow statement line items with an intent to report favorable operating performance of firms. In particular, the authors check the existence of revenue misclassification, expense misclassification and cash flows misclassification among Indian firms by taking the uniform sample of firms over a single period.

Operating revenue model (Malikov et al., 2018), core earnings expectation model (McVay, 2006) and operating cash flows model (Roychowdhury, 2006) are employed for measuring revenue misclassification, expense misclassification and cash flows misclassification, respectively. The panel data regression models are used to analyze the data for this study.

Based on the sample of 12,870 Bombay Stock Exchange (BSE) listed firm-years observations between 2010 and 2018, we find that, on average, Indian firms are engaged in revenue misclassification rather than expense misclassification to report inflated core earnings. Firms are found to be engaged in cash flows misclassification too. Besides, we find that magnitude of shifting is greater among larger firms. Results also establish that adoption of Ind AS increases the scope of shifting practices. These results are based on several robustness checks.

The results suggest that investors conduct a comprehensive review of the items of financial statements before using them in their portfolio valuation. It suggests auditors check the basis of revenue classification and standard-setting authorities, like ICAI in India, to make more mandatory disclosure requirements for classification of revenues and cash flows. It suggests lenders not to make lending decisions by looking at the operating performance metrics, as CS is the most preferred tool to positively influence the perception of lenders toward operating performance.

It is the first study that investigates different forms of classification shifting jointly for a sample of firms. Most of the earlier studies have examined one kind of classification shifting at a time. This study adds to the existing literature on earnings management by documenting that some firm-specific factors pressurize firms to prefer one form of shifting over another to report inflated core earnings.

The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the Agricultural Act of 2014.

The certainty equivalent of wealth is used to rank farm choices and assess the effects of supplemental revenue options on the crop insurance plan and coverage level chosen by the producer under a range of farm attributes. The risk-reducing effectiveness of the select programs is also examined through their impact on the farm revenue distribution. The dependence structure of yield and prices is modeled by applying copula techniques on historical data.

Farm program supplemental revenue programs generally have no effect on crop insurance choices. Crop insurance supplemental revenue programs typically reduce crop insurance coverage at high coverage levels. An individual plan of crop insurance combined with a supplemental revenue insurance plan may substitute for incumbent area crop insurance plans.

The analysis provides insights into farmers’ possible choices by focussing on alternative crops and farm attributes and extensive scenarios, using current data, crop insurance plans and programs contained in the 2014 Farm Bill and related bills. The results should be of value to policy officials and producers in regards to the design and use of risk management tools.