Predictive view of the value relevance of earnings in India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hajam Abid Bashir ◽  
Manish Bansal ◽  
Dilip Kumar
Keyword(s):  
Capital Investment ◽  
Stock Return ◽  
Value Relevance ◽  
Stock Exchange ◽  
Predictive Ability ◽  
Cash Flows ◽  
Data Set ◽  
Content Type ◽  
Uniform Sample ◽  
Reported Earnings

Purpose This study aims to examine the value relevance of earnings in terms of predicting the value variables such as cash flow, capital investment (CI), dividend and stock return under the Indian institutional settings. Design/methodology/approach The study used panel Granger causality tests to examine causality relationships among variables and panel data regression models to check the statistical associations between earnings and value variables. Findings Based on a data set of 7,280 Bombay Stock Exchange-listed firm-years spanning over ten years from March 2009 to March 2018, the results show higher sensitivity of earnings toward cash flows, CI, divided and stock return and vice-versa. Further, the findings deduced from the empirical results demonstrate that earnings are positively related to value variables. Overall, the results established that earnings are value-relevant and have predictive ability to forecast the value variables that facilitate investors in portfolio valuation. The results are consistent with the predictive view of the value relevance of earnings. Several robustness checks confirm these results. Originality/value This study brings new empirical evidence from a distinct capital market, India, and provides a new facet to the value relevance debate in terms of its prediction view. The study is among earlier attempts that jointly measure the ability of earnings in forecasting different value variables by taking a uniform sample of firms at the same period. Hence, the study provides a comprehensive view of the predictive ability of reported earnings.

Beyond earnings: do EBITDA reporting and governance matter for market participants?

2017 ◽  
Vol 43 (2) ◽  
pp. 193-211 ◽  
Author(s):  
Denis Cormier ◽  
Samira Demaria ◽  
Michel Magnan
Keyword(s):  
Corporate Governance ◽  
Information Asymmetry ◽  
Stock Price ◽  
Value Relevance ◽  
Earnings Quality ◽  
Predictive Ability ◽  
Cash Flows ◽  
Content Type ◽  
Market Participants ◽  
The Impact

Purpose The purpose of this paper is to investigate whether formally disclosing an earnings before interests, taxes, depreciation, and amortization (EBITDA) number reduces the information asymmetry between managers and investors beyond the release of GAAP earnings. The paper also assess if EBITDA disclosure enhances the value relevance and the predictive ability of earnings. Design/methodology/approach The authors explore the interface between GAAP and non-GAAP reporting as well as the impact of corporate governance on the quality of non-GAAP measures. Findings Results suggest that EBITDA reporting is associated with greater analyst following and with less information asymmetry. The authors also document that EBITDA reporting enhances the positive relationship between earnings and stock pricing as well as future cash flows. Moreover, it appears that corporate governance substitutes for EBITDA reporting for stock markets. Hence, EBITDA helps market participants to better assess earnings valuation when a firm’s governance is weak. Inversely, when governance is strong, releasing EBITDA information has a much smaller impact on the earnings-stock price relation. Originality/value The authors revisit the issue of how corporate governance relates with earnings quality by considering the potentially confounding effect of EBITDA reporting; it appears that such reporting substitutes for governance in moderating the relation between governance and earnings quality.

Efficiency evaluation of Indian oil and gas sector: data envelopment analysis

2019 ◽  
Vol 14 (2) ◽  
pp. 362-378 ◽  
Author(s):  
Vikas Vikas ◽  
Rohit Bansal
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Capital Investment ◽  
Oil And Gas ◽  
Stock Exchange ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Content Type ◽  
Indian Economy ◽  
Oil And Gas Sector

Purpose Data envelopment analysis (DEA), a non-parametric technique is used to assess the efficiency of decision-making units which are producing identical set of outputs using identical set of inputs. The purpose of this paper is to find the technical efficiency (TE), pure technical efficiency and scale efficiency (SE) levels of Indian oil and gas sector companies and to provide benchmark targets to the inefficient companies in order to achieve efficiency level. Design/methodology/approach In the present study, a group of 22 oil and gas companies which are listed on the National Stock Exchange for which the data were available for the period 2013–2017 has been considered. DEA has been performed to compare the efficiency levels of all companies. To measure efficiency, three input variables, namely, combined materials consumed and manufacturing expenses, employee benefit expenses and capital investment and two output variables – operating revenues and profit after tax (PAT) have been considered. On the basis of performance for the financial year ending 2017, benchmark targets based on DEA–CCR (Charnes, Cooper and Rhodes) model have been provided to the inefficient companies that should be focused upon by them to attain the efficiency level. The performance of the companies for the past five years has been examined to check the fluctuations in the various efficiency scores of the companies considered in the study over the years. Findings From the results obtained, it is observed that 59 percent, i.e. 13 out of 22 companies are technically efficient. By considering DEA BCC (Banker, Charnes and Cooper) model, 16 companies are observed to be pure technically efficient. In terms of SE, there are 14 such companies. The inefficient units need to improve in terms of input and output variables and for this motive, specified targets are assigned to them. Some of these companies need to upgrade significantly and the managers must take the concern earnestly. The study has also thrown light on the performance of the companies over last five years which shows Oil India Ltd, Gujarat State Petronet Ltd, Petronet LNG Ltd, IGL Ltd, Mahanagar Gas, Chennai Petroleum Corporation Ltd and BPCL Ltd as consistently efficient companies. Research limitations/implications The present study has made an attempt to evaluate the efficiency of Indian oil and gas sector. The results of the study have significant inferences for the policy makers and managers of the companies operating in the sector. The results of the study provide benchmark target level to the companies of Oil and Gas sector which can help the managers of the relatively less efficient companies to focus on the ways to improve efficiency. The improvement in efficiency of a company would not only benefit the shareholders, but also the investors and other stakeholders of the company. Originality/value In the context of Indian economy, very limited number of studies have focused to measure the efficiency of oil and gas sector in the context of Indian economy. The present study aims to provide the latest insight to the efficiency of the companies especially operating in the Indian oil and gas sector. Further, as per our knowledge, this study is distinctive in terms of analyzing the efficiency of Indian oil and gas sector for a period of five years. The longitudinal study of the sector efficiency provides a bird eye view of the average efficiency level and changes in the efficiency levels of the companies over the years.

scholarly journals The ability of cash flows to predict the earning: Evidence from Jordan

2021 ◽  
Vol 18 (4) ◽  
pp. 36-44
Author(s):  
Mohammad Fawzi Shubita
Keyword(s):  
Stock Exchange ◽  
Predictive Ability ◽  
Cash Flows ◽  
Operating Cycle ◽  
Prediction Ability ◽  
Future Earnings ◽  
Industrial Companies ◽  
Amman Stock Exchange ◽  
Great Support ◽  
The Relationship

This study aims to investigate the ability of cash flows components to predict the earning and to know the extent of the relationship between accounting profits and cash flow measures. The study sample consisted of 77 industrial companies listed on the Amman Stock Exchange in Jordan for the period from 2006 to 2019. This study relied on the regression method to test the relationship between the study variables. The study findings showed that the cash flows from operating, investing, and financial activities have a statistically significant impact on predicting future earnings. The study also examined the effect of length of operating cycle and company’s size on the predictive ability of cash flows regarding future earnings. The main results for this aspect are that large companies and short operating cycle companies have higher prediction ability for future earnings than small and long operating cycle companies. This paper provides evidence of the information content of cash flows for future earnings in emerging markets like Jordan and is important for Jordanian shareholders by enabling them to evaluate company’s performance. AcknowledgmentsI would like to thank Amman Arab University for its great support, and for funding this study.

scholarly journals Foreign Monitoring and Predictability of Future Cash Flow

2019 ◽  
Vol 11 (18) ◽  
pp. 4832
Author(s):  
Jaehong Lee ◽  
Eunsoo Kim
Keyword(s):  
Cash Flow ◽  
Stock Exchange ◽  
Predictive Ability ◽  
Financial Statements ◽  
Cash Flows ◽  
Foreign Investors ◽  
Future Cash Flow ◽  
Flow Components ◽  
Future Cash Flows

A company’s sustainability is generally determined by whether it is able to create a positive long-term cash flow. This paper investigates whether the predictive ability of cash flows and earnings in forecasting future cash flows differs depending on the foreign investors’ ownership. Based on firms listed in the Korea Stock Exchange market from 2000 to 2017, we find that earnings and cash flow components of financial statements enhance the predictability of future cash flow in the Korean stock market. Conversely, foreign investors showed a tendency to decide on investments based on operating cash flow instead of earnings when predicting future cash flow. These findings indicate that reliability towards earnings may fall since foreign investors’ concerns are on the prospects of earnings management. These results were strengthened by the addition of several more analyses including cluster analyses, consideration of information asymmetry and the chaebol governance.

Early prediction of chronic disease using an efficient machine learning algorithm through adaptive probabilistic divergence based feature selection approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sandeepkumar Hegde ◽  
Monica R. Mundada
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Chronic Disease ◽  
Learning Algorithm ◽  
Predictive Ability ◽  
Experimental Result ◽  
Data Set ◽  
Content Type ◽  
Learning Classifier ◽  
Feature Selection Approach

Purpose According to the World Health Organization, by 2025, the contribution of chronic disease is expected to rise by 73% compared to all deaths and it is considered as global burden of disease with a rate of 60%. These diseases persist for a longer duration of time, which are almost incurable and can only be controlled. Cardiovascular disease, chronic kidney disease (CKD) and diabetes mellitus are considered as three major chronic diseases that will increase the risk among the adults, as they get older. CKD is considered a major disease among all these chronic diseases, which will increase the risk among the adults as they get older. Overall 10% of the population of the world is affected by CKD and it is likely to double in the year 2030. The paper aims to propose novel feature selection approach in combination with the machine-learning algorithm which can early predict the chronic disease with utmost accuracy. Hence, a novel feature selection adaptive probabilistic divergence-based feature selection (APDFS) algorithm is proposed in combination with the hyper-parameterized logistic regression model (HLRM) for the early prediction of chronic disease. Design/methodology/approach A novel feature selection APDFS algorithm is proposed which explicitly handles the feature associated with the class label by relevance and redundancy analysis. The algorithm applies the statistical divergence-based information theory to identify the relationship between the distant features of the chronic disease data set. The data set required to experiment is obtained from several medical labs and hospitals in India. The HLRM is used as a machine-learning classifier. The predictive ability of the framework is compared with the various algorithm and also with the various chronic disease data set. The experimental result illustrates that the proposed framework is efficient and achieved competitive results compared to the existing work in most of the cases. Findings The performance of the proposed framework is validated by using the metric such as recall, precision, F1 measure and ROC. The predictive performance of the proposed framework is analyzed by passing the data set belongs to various chronic disease such as CKD, diabetes and heart disease. The diagnostic ability of the proposed approach is demonstrated by comparing its result with existing algorithms. The experimental figures illustrated that the proposed framework performed exceptionally well in prior prediction of CKD disease with an accuracy of 91.6. Originality/value The capability of the machine learning algorithms depends on feature selection (FS) algorithms in identifying the relevant traits from the data set, which impact the predictive result. It is considered as a process of choosing the relevant features from the data set by removing redundant and irrelevant features. Although there are many approaches that have been already proposed toward this objective, they are computationally complex because of the strategy of following a one-step scheme in selecting the features. In this paper, a novel feature selection APDFS algorithm is proposed which explicitly handles the feature associated with the class label by relevance and redundancy analysis. The proposed algorithm handles the process of feature selection in two separate indices. Hence, the computational complexity of the algorithm is reduced to O(nk+1). The algorithm applies the statistical divergence-based information theory to identify the relationship between the distant features of the chronic disease data set. The data set required to experiment is obtained from several medical labs and hospitals of karkala taluk ,India. The HLRM is used as a machine learning classifier. The predictive ability of the framework is compared with the various algorithm and also with the various chronic disease data set. The experimental result illustrates that the proposed framework is efficient and achieved competitive results are compared to the existing work in most of the cases.

High leverage and variance of SMEs performance

2019 ◽  
Vol 20 (2) ◽  
pp. 155-175 ◽  
Author(s):  
Mazen Gharsalli
Keyword(s):  
Firm Performance ◽  
Small Business ◽  
Firm Growth ◽  
Family Firms ◽  
Global Financial Crisis ◽  
Cash Flows ◽  
Data Set ◽  
Content Type ◽  
Good Investment ◽  
The Relationship

Purpose The purpose of this paper is to examine the relationship between leverage and firm performance using small business data from France by estimating the effects of leverage on both average firm performance and the variance of firm performance. Design/methodology/approach Focusing on French small- and medium-sized enterprises (SMEs), which tend to be dependent on bank loans, the authors examine the relationship between leverage and firm performance. This study was based on a unique panel data set of more than 2,157 manufacturing SMEs covering the years 2007-2015. The authors estimate the effects of leverage on both average firm performance and the variance of firm performance. Findings Focusing on the average effects of leverage, the authors find that highly leveraged firms suffer from poor performance. In addition, the variance in firm performance is higher if firms are highly leveraged. Results also underline that leveraged firms are better performers when they have sufficient collateral assets. Research limitations/implications The study, however, has also some limitations. The first one is that the findings were obtained for only one industry sector, so attempts should be made to study the issue, as it applies to other sectors as well. Second is the context where the study was conducted. This study has been conducted based on data gathered from SMEs in France within a specific socioeconomic context (2007-2008 global financial crisis), which may also limit the generalizability of the results for different contexts with different socioeconomic situations. It would also be useful, to have a better explanation for the performance of SMEs, to add to the model more financial variables or other types of variables such as those related to managerial skills or to the macro-economic environment. Finally, further research could examine the joint impact of both leverage and ownership structure on firm’s performance as a large number of French firms are family firms. The limitations of this study, however, can in fact be an opportunity for future researchers to conduct studies addressing those limitations. Practical implications This research has some implications for small business lending. SME owners and managers may, on the one hand, be encouraged by the fact that collateral assets can reduce agency costs, thereby positively affecting firm performance. On the other hand, high leverage can facilitate firm growth if firms have collateral assets. This implies that policymakers interested in stimulating SMEs should develop more suitable collaterals for high-risk SMEs with low asset tangibility. Social implications The results also have implications for financial institutions. To prevent unexpected and extensive bankruptcies, banks might classify firms with negative cash flows as borrower in danger of bankruptcy. However, the results show that highly leveraged firms with good investment opportunities and high collateral assets reduce the probability of bankruptcy. This implies that banks need to evaluate the credit risk of very highly leveraged small businesses more carefully. Originality/value It should be noted that the case of France remains marginal in terms of the conducted studies.

scholarly journals Stock return and financial performance as moderation variable in influence of good corporate governance towards corporate value

2019 ◽  
Vol 4 (1) ◽  
pp. 18-34 ◽  
Author(s):  
Suhadak Suhadak ◽  
Kurniaty Kurniaty ◽  
Siti Ragil Handayani ◽  
Sri Mangesti Rahayu
Keyword(s):  
Corporate Governance ◽  
Financial Performance ◽  
Stock Price ◽  
Stock Return ◽  
Stock Exchange ◽  
Complete Information ◽  
Company Performance ◽  
Corporate Value ◽  
Content Type ◽  
Good Corporate Governance

Purpose The purpose of this paper is to evaluate how much influence good corporate governance (GCG) has on corporate value, as well as moderating effect of stock return and financial performance on the influence of GCG on corporate value. Design/methodology/approach This study was an explanatory study. The unit of analysis was the companies listed in LQ45 in Indonesian Stock Exchange and the sources of data were ICMD, annual report and financial reports of the companies. Indonesian Stock Exchange was selected as the setting of the study since Indonesian Stock Exchange is one of trading places for various types of companies in Indonesia, and it provides complete information on company’s financial data and stock price. The population was 84 companies listed in LQ45 in Indonesian Stock Exchange between 2010 and 2016. Findings The higher GCG, independent commissioners proportion, institutional managerial and public ownerships resulted in higher corporate value. MBE and PER stock return is a moderating variable in the influence of GCG on corporate value. Financial performance is moderating variable in the influence of GCG on corporate value. Originality/value Based on the previous studies, it may be concluded that there is a gap between the influence of GCG on corporate value and the influence of stock return on financial performance, and moderating variable is needed to evaluate the influence of GCG on company performance, more particularly stock return and financial performance. This discrepancy creates opportunity for conducting an in-depth study on those variables. Its novelty is correlation between stock return and financial performance as moderation. Previous studies used these as mediating variables. This study is going to generate different finding as it is conducted in different setting (country where this study is conducted), type of industry, research period and using different method of analysis.

scholarly journals The day-of-the-week effect: South African stock market indices

2018 ◽  
Vol 9 (2) ◽  
pp. 197-212 ◽  
Author(s):  
Elda du Toit ◽  
John Henry Hall ◽  
Rudra Prakash Pradhan
Keyword(s):  
South African ◽  
Stock Exchange ◽  
Garch Model ◽  
Statistical Technique ◽  
Data Set ◽  
Content Type ◽  
Johannesburg Stock Exchange ◽  
Time Period ◽  
Day Of The Week ◽  
Micro Level

Purpose The presence of a day-of-the-week effect has been investigated by many researchers over many years, using a variety of financial data and methods. However, differences in methodology between studies could have led to conflicting results. The purpose of this paper is to expand on an existing study to observe whether an analysis of the same data set with some added years and using a different statistical technique provide the same results. Design/methodology/approach The study examines the presence of a day-of-the-week effect on the Johannesburg Stock Exchange (JSE) indices for the period March 1995-2016, using a GARCH model. Findings The findings show that, contrary to the original study, the day-of-the week effect is present in both volatility and return equations. The highest and lowest returns are observed on Monday and Friday, respectively, while volatility is observed on all five days from Monday to Friday. Originality/value This study adds to the existing literature on day-of-the-week effect of JSE indices, where different patterns or, in some cases, no pattern have been noted. Few previous studies on the day-of-the-week effect observed the effect at micro-level for separate industries or made use of a GARCH model. The present study thus expands on the study of Mbululu and Chipeta (2012), by adding four additional observation years and using a different statistical technique, to observe differences that arise from a different time period and statistical technique. The results indicate that a day-of-the-week effect is mostly a function of the statistical technique applied.

Corporate governance and dividend policy in Sri Lankan firms: a data triangulation approach

2020 ◽  
Vol 12 (4) ◽  
pp. 543-560
Author(s):  
H. Kent Baker ◽  
Narayanage Jayantha Dewasiri ◽  
Sandaram P. Premaratne ◽  
Weerakoon Yatiwelle Koralalage
Keyword(s):  
Corporate Governance ◽  
Dividend Policy ◽  
Stock Exchange ◽  
Agency Cost ◽  
Free Cash Flow ◽  
Sri Lankan ◽  
Survey Analysis ◽  
Data Set ◽  
Market Data ◽  
Content Type

Purpose This paper aims to investigate the relation between corporate governance and dividend policy in Sri Lankan firms. Design/methodology/approach The data set consists of market data using 1,608 firm-year observations from 201 firms listed on the Colombo Stock Exchange and survey-based data from 151 respondents from the same 201 firms. The authors use data triangulation to examine the two approaches. Findings The analysis of the market data reveals that a significantly positive relation between corporate governance on both the propensity to pay dividends and dividend payout. Survey analysis confirms these findings. Triangulated evidence supports the outcome model of dividends, free cash flow and agency cost theories. Practical implications The findings are useful not only for management in developing suitable corporate governance practices and dividend policies for their firms but also for shareholders in evaluating both existing and new investments. Future researchers should investigate the same phenomenon in other contexts using triangulation approaches to confirm their findings. Originality/value This study is the first to use governance indices both in terms of survey and market-based data to examine the relation between corporate governance and dividend policy.

Relationship between earnings management, CEO compensation, and stock return on Tehran Stock Exchange

2019 ◽  
Vol 23 (1) ◽  
pp. 1-22
Author(s):  
Mahdi Moardi ◽  
Mahdi Salehi ◽  
Simin Poursasan ◽  
Homa Molavi
Keyword(s):  
Earnings Management ◽  
Cash Flow ◽  
Significant Relationship ◽  
Stock Return ◽  
Stock Exchange ◽  
Discretionary Accruals ◽  
Content Type ◽  
Future Cash Flow ◽  
Accruals Quality ◽  
The Relationship

Purpose The purpose of this paper is to investigate the relationship between earnings management and chief executive officers’ (CEOs) compensation. Owing to the fact that earnings management does not have only opportunistic effects, but signaling effects, this study focuses on accruals quality to examine earnings management incentives. Thus, accruals quality is described against future cash flow. The empirical evidences suggest that a positive relationship between discretionary accruals and future cash flow provides predictive elements for earnings management, whereas a negative relationship between discretionary accruals and future cash implies to opportunistic elements for earnings management. Should there is no significant relationship between discretionary accruals and future cash flow, there will be no earnings management, and such a result suggests that incentives and managers’ performance in these firms differ. Design/methodology/approach The statistical population of this research consists of all listed companies on the Tehran Stock Exchange during 2009–2016. Panel data method is applied in order to estimate the research model. Findings Findings of the study show that there is no significant relationship between discretionary accruals and future cash flow in pharmaceutical and food industries, thus they have neither predictive nor opportunist earnings management, while the results evidence a negative significant relationship between discretionary accruals and future cash flow in machineries, automobile, mineral and chemical industries. Furthermore, it can be alleged that there is no significant difference between CEOs’ compensation in firms with opportunistic earnings management (OEM) and other types of earnings management. It shows that firms do not have appropriate plans for CEOs’ compensation. Moreover, the relationship between earnings management and stock return has been investigated in this study. We document that stock return is influenced by accruals quality and its components. In other words, stock return significantly differs in firms with OEM and firms without any kind of earnings management. Research limitations/implications The authors’ findings provide contributions; for managers, it is noticeable that stock markets have sufficient comprehension about financial statements and the undertaken procedures on them, resulting in a higher return base on fair information. For investors and regulators, using the findings, may have deeper understanding to distinguish between industries that are recognized as opportunistic and non-opportunistic, which, in turn, results in better decision and regulation. Originality/value Previous studies have been mostly investigated OEM, while the current study examines both signaling and opportunistic aspects of earnings management.

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