Annual Accounting Data Research Articles

МАТЕМАТИЧЕСКИЕ МЕТОДЫ МАКСИМИЗАЦИИ ПРОИЗВОДСТВА РАКЕТ КОСМИЧЕСКОГО НАЗНАЧЕНИЯ В РОССИИ

The possibility of applying of economic-mathematical methods to industrial process simulation in rocket and space sector is investigated in this work. The classical Cobb-Douglas function, whose parameters are calculated econometrically on the basis of the annual accounting data, is used as a production function. The emerging task of non-linear programming allows to find the optimum values of productive resources. The comparison of the received results with actual data allows to offer ways to enhance the effectiveness of financial resources management in space industry.

Risk measures and the risk-return paradox: an analysis in the context of the economic crisis

Purpose – The purpose of this study is to analyze, in the context of the last economic crisis, the prediction capacity of the different risk measures and the relationship between risk and return. Design/methodology/approach – We selected three risk measures constructed using annual accounting data obtained from Spanish companies. A logistic regression was then developed to verify whether the companies’ predictions were eventually correct, considering those companies that were able to survive the crisis. A multiple linear regression was subsequently employed in order to review Bowman’s paradox, that is, in the risk-return relationship. Findings – The research results support the two hypotheses formulated: 1) variability measures of risk have a greater predictive power than that of downside risk measures; 2) the risk-return paradox is more likely to exist in the more uncertain environment of a pre-crisis period of time. Originality/value – Managers could employ the frameworks developed in this study as important diagnostic tools in order to attain advance warning of whether an organization may be close to failure. An analysis of this nature would then allow a firm to take appropriate action to arrest the process.

Environmental Innovation and Firm Performance: How Firm Size and Motives Matter

There is limited understanding of the precise circumstances under which environmental actions—such as environmental innovation—contribute to firm performance. Building on the resource-based view and on stakeholder theory, this study argues that the general positive effect of environmental innovation on financial performance varies significantly with firm size and the motives underlying a firm’s engagement in environmental innovation. Integrating survey data and lagged annual account data on 1761 Flemish companies, we find that larger firms benefit financially from environmental innovation driven by regulation or industry codes of conduct, while smaller firms benefit from environmental innovation introduced in response to customer demand. While it is increasingly accepted that environmental innovation relates positively with firm performance, the current study highlights important boundary conditions of this relationship.

Deep Learning and the Cross-Section of Stock Returns: Neural Networks Combining Price and Fundamental Information

Traditional empirical finance research uses hand-engineering and trial-and-error to look for the anomalies in the cross-section of stock returns. In this paper, we take advantage of deep learning and utilize both the price and fundamental information to separate stocks’ winners from losers. For the first model, we used a 2-layer Long Short-Term Memory (LSTM) neural network with past 80 days’ return information as inputs to predict the next day’s return and find a before-trading-cost monthly return of 29.58% with a t-statistic of 26.81. The return of the stocks shows a strong short-term reversal pattern. For the second model, we design a novel 2-layer LSTM and Multi-layer Perceptron (MLP) hybrid neural network and utilize the monthly return and annual accounting data to predict the returns in the next month. We achieve a monthly return of 2.37% with a t-statistic of 8.97 before trading cost from 1993 through 2017. We use TAQ intraday data to explicitly estimate the trading cost and find that profits of the daily trading strategy in the first model turn negative. However, the trading strategy utilizing both the price and fundamental information in the second model keeps significantly positive with a monthly return of 1.57% and t-statistic of 6.03 after the trading cost. We show that the 2-layer LSTM and MLP hybrid model performs better than the MLP-only and the hand-engineering momentum and short-term reversal double sort trading strategy.

Forecasting the level of earnings management of Russian and Chinese companies

The purpose of the current paper is to elaborate a model to forecast a particular type of earnings management by companies: upward earnings management, downward earnings management or the absence of significant manipulation. The sample analyzed in the current paper comprises 664 Russian and 2,380 Chinese public companies for the period 2009-2014. The forecast was made for 2014 based on annual accounting data for 2009-2013. Regression analysis, as well as Classification and Regression Tree modelling (CART), were used. The data forecast for 2014 was compared with actual data for that year, and the accuracy of the forecasting model was assessed. The paper outlines the main conditions under which a particular type of earnings manipulation is expected to take place in a company in the accounting period following the current one. It is shown that the main factor influencing the company’s level of earnings manipulation of the next accounting period for both Russian and Chinese companies is the debt ratio calculated as the ratio of total liabilities to total assets. The other important factors are: the company size, return on equity, earnings persistence, the level of earnings manipulation in the current period and stock emission.

Economic and Financial Flow Generation in Tomato Industry in Italy

In many Italian regions, firms operating in tomato industry have made significant investments in plants and machinery and often sell products to large food retail chains that require large stocks of inventory and have an average time of over 150 days for the payment of receivables. These management characteristics amplify capital requirements, in large part financed, increasing debt levels. Also, because of the increasing costs of raw materials in recent years, many firms in the tomato processing sector in Italy have suffered a corporate crisis and even bankruptcy. Therefore, tomato processing firms need to properly control management, particularly in applying indicators that express the sustainability of the financial cycle. To achieve this goal, the article analyzes the annual account data of a sample of 54 tomato processing firms in Italy across a five-year period, showing that economic margins traditionally applied to assess the sustainability of the management cycle differ significantly from financial margins. Moreover, the annual account data of the sample firms highlight the difficulties in credit access, expressed by applying a multiple regression model to analyze return on equity and flow on equity generation. To deepen the analysis, the considered methods could be applied to other agri-food firms, particularly if characterized by high capital intensity.

TOMATO PROCESSING FIRMS’ MANAGEMENT: A COMPARATIVE APPLICATION OF ECONOMIC AND FINANCIAL ANALYSES

In Italy, the territory that includes the Emilia-Ro magna region, the southern areas of Lombardia and some of Piemonte’s territory is a center of nationa l importance for tomato production and transformation. The processing firms operating in t his area are characterized by significant investmen ts in fixed assets and working capital. The article an alyzes the annual account data of a sample of firms , showing that economic margins traditionally applied to assess the sustainability of the business cycle differ significantly from financial margins; also, the Interest Coverage Ratios (ICRs) differ if calculated by applying an economic or a financial a pproach. Moreover, the annual account data highlight difficult credit access, expressed by app lying a multiple regression model to analyze Free Cash Flow to Equity (FCFE) generation. The article suggests a useful metric to measure more correctly the sustainability of a firm’s management that coul d be applied to others in the agri-food sector, particularly if characterized by a capital-intensiv e processing cycle.

Economic Importance of the Flemish Maritime Ports - Report 2003

The Flemish maritime ports play a major role in the Belgian economy, not only in terms of the industries they encompass but also as intermodal centres where transhipment activities are concentrated. This update1 paper provides an extensive overview of the economic importance and development of the Flemish maritime ports, through revised results for the period 1997 - 2003. Focusing on the three major variables of value added, employment and investment, it also provides some information about the financial situation of a few vital sectors in each port. A global indication concerning the financial health of the companies studied is also provided, using the NBB bankruptcy prediction model. In addition, it includes figures with respect to the ongoing growth of several cargo traffic segments and provides an overall picture of social developments in the Flemish maritime ports. The indirect effects of these port activities are estimated in terms of value added and employment. Annual account data from the Central Balance Sheet Office were used for the calculation of direct effects, the study of financial ratios and the analysis of the social balance sheet. The indirect effects were estimated on the basis of data from the National Accounts Institute. In the Flemish maritime ports, direct VA came to almost 11.5 billion euro and total VA - the sum of direct and indirect VA - to 22 billion euro in 2003. In the same year direct and total employment reached respectively 105,000 and 239,000 full-time equivalents, while direct investment reached 2.5 billion euro. The ongoing developments in the maritime ports sector in the Hamburg - Le Havre range continue to affect the port operations: concentration of capital, privatisation of port logistic services, expansion and dispersion of foreign trade, internationalisation of production and consumption patterns, increase in containerised shipments, etc. Production, trade and transport are no longer considered as individual and isolated activities, but are integrated within a single system, while economies of scale continue. Therefore, ports are becoming real logistic centres: ports able to add value to the goods passing through the port area have a major advantage in a climate of increasing international competition. Flemish ports are following this trend, and that is also reflected in the analysis presented in this report.

Evolution and Sources of Manufacturing Productivity Growth: Evidence from a Panel of European Countries

The study aims at describing productivity growth in the manufacturing sector for a selected panel of five European countries using firm-level data. The paper explores the empirical regularities of firm productivity distribution across countries. In particular, we assess the degree of persistence of firm relative productivity and consider its effect on aggregate productivity improvements. Moreover, the paper analyses the impact of the competitive forces on aggregate productivity growth by disentangling the role of firm learning and market selection. Finally, we estimate the relationship between labour productivity growth and firm-specific factors such as size, age and capital intensity across countries. The paper uses annual account data over the period 1993-2003 from Amadeus dataset (Bureau van Dijk) for a balanced panel of manufacturing firms. In line with previous evidence, our analysis shows that firm relative productivity levels are both highly heterogeneous across firms and very persistent over time in all the countries in the sample. With reference to aggregate productivity growth, we find that both labour productivity and total factor productivity changes are mostly driven by firm learning, i.e. within-firm productivity improvements, in most European countries. Conversely, the reallocation of resources spurred by the competitive selection process is found to play a minor role in fostering aggregate productivity growth. Finally, in line with macroeconomic trends, gains in productivity seem to be associated with capital deepening, but also with employment losses. JEL Classification: D24, L11, L60

Emerging Market Multinationals: An Analysis of Performance and Risk Characteristics

ABSTRACT This study explores the risk and performance characteristics of emerging market multinationals (EMNCs). We use a sample composed of 79 EMNCs from 15 countries located in Africa, Asia, Eastern Europe-Russia, and Latin America. Our risk and performance analyses are based on monthly share price returns collected over 1996–2003 period and annual accounting data. We find that EMNCs on average perform better than their respective country market indices, a widely used EM benchmark, S&P500 and, global market index (MSCI-World) during the period of analysis. Our sample firms on average earn 13.21% return on assets, 8.97% return on equity, and 11.96% return on invested capital. We also find that EMNC returns are highly volatile, and despite some level of diversification achieved by EMNCs, their returns remain highly sensitive to local market shocks. The cross-sectional analysis of the determinants of the performance of the EMNCs reveals that leverage and systematic risk are the most important factors, followed by size. Our analysis indicates that performance is not affected by the degree of internationalization and EMNC investments in developed markets have a positive impact on the value. Finally, our results indicate that EMNCs in less risky emerging markets enjoy higher firm value.

Calculating a potential increase in hospital margin for elective surgery by changing operating room time allocations or increasing nursing staffing to permit completion of more cases: a case study.

Administrators routinely seek to increase contribution margin (revenue minus variable costs) to better cover fixed costs, provide indigent care, and meet other community service responsibilities. Hospitals with high operating room (OR) utilizations can allocate OR time for elective surgery to surgeons based partly on their contribution margins per hour of OR time. This applies particularly when OR caseload is limited by nursing recruitment. From a hospital's annual accounting data for elective cases, we calculated the following for each surgeon's patients: variable costs for the entire hospitalization or outpatient visit, revenues, hours of OR time, hours of regular ward time, and hours of intensive care unit (ICU) time. The contribution margin per hour of OR time varied more than 1000% among surgeons. Linear programming showed that reallocating OR time among surgeons could increase the overall hospital contribution margin for elective surgery by 7.1%. This was not achieved simply by taking OR time from surgeons with the smallest contribution margins per OR hour and giving it to the surgeons with the largest contribution margins per OR hour because different surgeons used differing amounts of hospital ward and ICU time. We conclude that to achieve substantive improvement in a hospital's perioperative financial performance despite restrictions on available OR, hospital ward, or ICU time, contribution margin per OR hour should be considered (perhaps along with OR utilization) when OR time is allocated. For hospitals where elective surgery caseload is limited by nursing recruitment, to increase one surgeon's operating room time either another surgeon's time must be decreased, nurses need to be paid a premium for working longer hours, or higher-priced "traveling" nurses can be contracted. Linear programming was performed using Microsoft Excel to estimate the effect of each of these interventions on hospital contribution margin.

Reliability in Income Numbers for Investment Decision: The Case of the Istanbul Stock Market

This paper uses annual accounting data to show that the frequency of occurrence of the first and second digits contained in the income numbers of companies, listed in the Istanbul Stock Exchange, does not deviate significantly from expectations.

Anomalies in Annual Accounting Numbers

Annual accounting numbers are used in different ways by researchers and investors. Besides the obvious regulatory uses of accounting numbers in financial institutions and public utilities, researchers and investors uses annual accounting data in forming their expectations about the future prospects of enterprises. Watts and Zimmerman [1990] stated that researchers also uses financial accounting data to investigate differences in investment opportunity sets, accounting policies, contracting costs, organisational structures, and financial polices.

The Effects of Annual Accounting Data on Stock Returns and Trading Activity: A Causal Model Study

Abstract This study develops a structural equation model linking both abnormal stock returns and abnormal trading volume to unexpected changes in accounting ratios that result from the issuance of annual accounting data. The three contributions of this study are as follows: (a) a simultaneous investigation of both the price and the trading activity stock market reactions to the issuance of annual financial statements; (b) the application of a measurement model to depict the changes in a firm's financial characteristics, which result from the issuance of financial statements; and (c) a causal model structure is developed, estimated, and tested. Through overidentification of the model, the hypothesized model structure is evaluated. Instead of investigating the price and trading activity reactions separately, as was done in previous studies, the two reactions are modeled simultaneously and are linked. A measurement model is hypothesized to aggregate the unexpected changes in 13 financial ratios into the unexpected changes in 4 latent financial dimensions: liquidity, leverage, profitability, and activity. The structural model then links the unexpected changes in the financial dimensions to abnormal stock market returns and trading volume. The 13 equations of the measurement model and the 2 structural equations are estimated simultaneously using LISREL, a full information maximum likelihood estimation procedure. The model is estimated, and the hypothesized model configuration recreates 82% of the generalized variance in the observed data. The individual parameter estimates show that the major source of variation in abnormal returns is the unexpected changes in profitability. None of the unexpected changes in the financial dimensions are found to be significantly linked directly to abnormal trading volume. Instead, the link is indirect through the relationship between abnormal returns and abnormal volume.

The Effects of Annual Accounting Data on Stock Returns and Trading Activity: A Causal Model Study

Abstract This study develops a structural equation model linking both abnormal stock returns and abnormal trading volume to unexpected changes in accounting ratios that result from the issuance of annual accounting data. The three contributions of this study are as follows: (a) a simultaneous investigation of both the price and the trading activity stock market reactions to the issuance of annual financial statements; (b) the application of a measurement model to depict the changes in a firm's financial characteristics, which result from the issuance of financial statements; and (c) a causal model structure is developed, estimated, and tested. Through overidentification of the model, the hypothesized model structure is evaluated. Instead of investigating the price and trading activity reactions separately, as was done in previous studies, the two reactions are modeled simultaneously and are linked. A measurement model is hypothesized to aggregate the unexpected changes in 13 financial ratios into the unex...

Discussion of The Influence of Quarterly Earnings Announcements on Investor Decisions As Reflected in Common Stock Price Changes

The thrust of my remarks can probably best be analyzed after a brief delineation of some of the important areas of general agreement between Professor May and myself. The first major finding which was discussed in his paper was that the magnitude of common stock price-change responses in weeks of all types of quarterly earnings announcements was, in general, significantly greater than the average price change for nonannouncement weeks. This finding led to the conclusion that a significant demand exists for quarterly accounting data to be used by investors in actual decisions. I agree that in general there seems to exist in the financial community a significant demand for quarterly accounting data to be used in investment decision making. May also found that the relative price-change response to quarterly earnings announcements was less than responses to annual earnings announcements, but, with one exception, not significantly less. He then concluded from this finding that investors may be unaware of, or unable to take account of differences in the reliability of quarterly and annual accounting data. I also agree that some important investors are definitely unaware of potential differences in the reliability of quarterly and annual accounting data, and that there are some investors who are aware of them but unable to take account of such differences. It is also likely that there are some investors who are in the unenviable position of being both unaware of the differences, and, if they were aware, unable to take account of differences in reliability. Although there may be some slight levity in that last remark, it was partially intended to point to the difficulties in-