Number Of Financial Indicators Research Articles

Assessment of financial sustainability and risk of bankruptcy of agricultural enterprises in Bulgaria

The diagnostics of financial sustainability of economic subjects and the risk of bankruptcy constantly attract the attention of economists. For these purposes, a number of financial indicators have been studied and threshold values were set, above and below which the probability of bankruptcy is considered significant. The agricultural sector is an invariable field for the realization of such studies, because it is seen as highly risky due to the action of many external and internal critical factors whose influence may lead to insolvency. The present research aims to evaluate the applicability of some of the most commonly used models for analyzing financial sustainability in the agricultural sector by using financial reports over a five-year period of a representative excerpt of large and middle-sized Bulgarian firms in the agricultural sector. Crop and livestock farms have been analyzed as separate subsectors in order to determine whether the applied methods for analysis of the financial sustainability show their specifics depending on the character of their particular activity. In parallel, the authors have studied the dependency between financial health and innovative activity and proved that the higher level of digitalization presupposes better financial sustainability and reduces the risk of bankruptcy.

Number of Financial Indicators as a Factor of Multi-Criteria Analysis via the TOPSIS Technique: A Municipal Case Study

Multi-criteria analysis is a decision-making and efficiency assessment tool for application in both the private and public sectors. Its application is preceded by the selection of suitable indicators and a homogenous set of variants, as well as suitable methods based on the nature of the input data. The goal of the submitted research is to highlight the importance of selecting suitable indicators using a case study assessment of the financial health of a municipality—more precisely, the efficiency of management of this municipality. Four key indicators, thirty-two homogenous subjects, and one multi-criteria analysis method were identified in this study based on the theoretical foundations of the specific issue. These elements were processed into a total of 14 variants depending on the number of assessed indicators. Then, these results were subjected to statistical verification alongside verification using the Jaccard index. Based on the acquired results, we highlight the need for correct and expert identification of the relevant sets of alternatives (the criteria matrix) and expert discussion, which should precede the selection of the assessed indicators and objectify this selection process as much as possible. Assessment based on a low number of indicators was shown to be insufficient, highly variable, and diverse, and these differences were partially eliminated as the number of assessed indicators increased.

The role of capital in bank failures across EU-15 countries: backward LR approach

Resolving the puzzle which financial indicators persistently indicate severe disruptions in the business of banking, is of the utmost importance for prudential authorities. Thus, the intent of this paper is to outline microeconomic determinants of bankruptcies within the banking sectors of the EU-15 countries and to clarify the role of bank capital in it. Namely, the bank capital regulation is designed as both, ex-ante (bankruptcy prevention) and ex-post (bankruptcy costs reducer) regulatory instrument. Backward stepwise logistic regression was applied on the Bankscope data sample of around 60 commercial banks in the period that preceded the global financial crisis. Estimations were obtained for the year in which a certain bank bankrupted as well as for each year over the five-year period prior to the bankruptcy. Research findings confirm that a number of financial indicators, such as asset quality and liquidity indicators could serve as early warning signals of bank failures even five years before the bankruptcy. The results for bank capital ratios were non-persistent regarding their sign and significance in the year preceding the bankruptcy and several years prior to bankruptcy. Finally, the most convincing results speak in favor of the too-big-to-fail phenomenon, as bank size explains the most of its survival odds.

CNN-based multivariate data analysis for bitcoin trend prediction

Bitcoin is the most widely known blockchain, a distributed ledger that records an increasing number of transactions based on the bitcoin cryptocurrency. New bitcoins are created at a predictable and decreasing rate, which means that the demand must follow this level of inflation to keep the price stable. Actually, the price is highly volatile, because it is affected by many factors including the supply of bitcoin, its market demand, the cost of the mining process, as well as economic and political world-class news.In this work, we illustrate a novel approach for bitcoin trend prediction, based on the One-Dimensional Convolutional Neural Network (1D CNN). First, we propose a methodology for building useful datasets that take into account social media data, the full blockchain transaction history, and a number of financial indicators. Moreover, we present a cloud-based system characterized by a highly efficient distributed architecture, which allowed us to collect a huge amount of data in order to build thousands of different datasets, using the aforementioned methodology. To the best of our knowledge, this is the first work that uses 1D CNN for bitcoin trend prediction. Remarkably, an efficient and low-cost implementation is feasible due to the simple and compact configuration of 1D CNN models that perform one-dimensional convolutions (i.e., scalar multiplications and additions). We show that the 1D CNN model we implemented, trained, validated and tested using the aforementioned datasets, allow one to predict the bitcoin trend with higher accuracy compared to LSTM models. Last but not least, we introduce and simulate a trading strategy based on the proposed 1D CNN model, which increases the profit when the bitcoin trend is bullish and reduces the loss when the trend is bearish.

Econometric Model for Readjusting Significance Threshold Levels through Quick Audit Tests Used on Sustainable Companies

Given the present-day economic situation, which is characterized by economic destabilization as a result of the pandemic crisis, auditors are facing the issue of establishing materiality, which is partly based on the fact that a certain level of financial misstatement influences the decisions of the involved parties. The aim of the present study is to suggest an econometric model for readjusting significance threshold levels through quick audit tests used on sustainable companies. The main objectives of the study are to emphasize the causal relationship between the manifestation of constant errors in financial reports and the inconsistency of audit opinions, as well as to put into practice the causal relationship that exists between the improvement of the audit function and sustainability itself, given companies’ crisis situation. In this particular context—based on the entire sample of companies listed in the Bucharest Stock Exchange (BVB), Bucharest Exchange Trading Plus category (BET Plus)—we estimated a number of financial indicators between 2009 and 2018 so that we could determine the materiality of accounting errors identified by auditors in order to express an opinion regarding the reliability and accuracy of financial reporting. The study’s key findings show that, given the economic crisis, the significance threshold level is a volatile test and it needs to be reconsidered taking into account the decline in the quality of reporting and, indirectly, the disclosure of financial information. From a holistic point of view, we believe that our study will have a significant impact on both practitioners and regulatory entities by shifting the qualitative approaches of analysis itself towards key prudential regulations stipulated by International Standard on Auditing (ISA) 320, ISA 450 and ISA 700. The study also highlights the process of refining information sources that can impact the significance, understanding and materiality of business decisions.

Financial Indicators of Selected Service-Provider Companies of Telecommunication Sector in India: An Empirical Study

Purpose: The aim of this article is to measure profitability of selected services provider companies of telecommunication sector in India. The study also aims to identify liquidity and solvency of the selected services provider companies of telecommunication, and how these indicators determine their management efficiency. 
 Approach/Methodology/Design: In this study, three service-provider telecommunication companies operating in India were selected. The study period is from 2013-14 to 2017-18. The criterion for selection of samples is market capitalization in which higher capitalized companies are selected like Bharti Airtel, Tata Communication and Reliance Communication. In this study ratio analysis is used as accounting tool, and One-way Anova technique is used as statistical tool for the identification of difference between the sample means.
 Findings: The major findings of the study indicate that Bharti Airtel and Tata Communication are in a better financial soundness as compared to Reliance Communication. In addition, the results of the study reveal that Reliance Communication suffered huge losses during the study period.
 Practical Implications: The study examines the status of the telecommunication sector with the current rules and regulations provided by government. It also assess the financial condition of the selected telecommunication companies, providing a systematic evaluation based on certain financial indicators that can help investors make relevant decisions.
 Originality/value: The financial indicators are important figures which give an overview about the financial health of any particular organization. There are number of financial indicators which are employed to identify the fair and true picture of organization. Profitability, liquidity and solvency ratios are one method for the identification of financial strength or weakness out of number of methods.

A cost–benefit analysis of hospital diagnostic imaging services in public hospital units in Greece

This study involved a financial analysis of five Greek public hospital units in the sixth health region from 2012–15. Geographical information systems can be used for the rational management of diagnostic imaging examinations as they allow users to exchange large volumes of financial data very quickly and their statistics allow users to estimate a number of financial indicators. The data include the cost of radiology departments, total cost, revenue, number of magnetic resonance imaging exams and number of hospital beds. Statistical Package for the Social Sciences analysis shows a strong linear correlation between the number of magnetic resonance imaging exams and hospital beds. The majority of hospital units display an overtime revenue increase of magnetic resonance imaging exams in 2012–14. In 2013–15 the cost of radiology departments (a major part of the total cost for the majority of hospital units) decreased by 2–76%.

MECHANISMS OF ANALYSIS OF AGGREGATE FINANCIAL FLOWS FOR GROUPS AND INDIVIDUAL OF ECONOMIC ENTERPRISES

The article examines the mechanisms of analysis of aggregate financial flows of economic entities. Analysis of the formation and movement of financial flows showed that, despite the widespread use of financial indicators in the analysis, today there is no integrated assessment of the state of financial flows of a group of economic entities that form the commodity-production subsystem (СPS). The authors propose to analyze the formation of financial flows using the structuring of financial flows and reflect their state within the СPS. This approach, as well as a number of financial indicators, takes into account data that assess flows by type of activity in their ratio. At the stage of formation of the financial system of СPS, the relationship between the change in the results of the functioning of СPS-forming business entity and the efficiency of financial flows is established through a block of indicators. First, absolute, then relative, and then get integrated indicators. The calculation of relative indicators is based on the comparison of the obtained values with the normative ones, which are determined by a vector that reflects the directions (positive or negative) of changes in financial flows, based on a specific stage of development. The assessment of the formation of financial flows of СPS-forming economic entities is able to show the main sources of funding and identify the centres of consumption of finance within the СPS. An autocorrelation model and an adaptive Brown model were used for prediction. In the first step, the characteristic regression method determines the best regression function - the most appropriate for the available values of financial flows for certain periods of time. The second step calculates the regression parameters using the least squares method. It is concluded that the constructed model is consistent with the experimental data. The presented developments reflect the developed and proposed algorithm for analyzing the formation of financial flows of СPS-forming economic entities, which differs from existing approaches using not only financial indicators but also a block of indicators that characterize the ratio of financial flows. This allows to increase the objectivity of the assessment of financial flows in the process of economic system development

The Financial Cycle Indexes for Early Warning Exercise

This paper introduces financial cycle indexes and uses them in an early warning exercise. The indexes are based on the traditional theory of business cycles. Juglar cycles are deduced from a number of financial indicators, categorized as leading and lagging indicators, and aggregated into leading and lagging indexes. We constructed Japanese financial cycle indexes and found that they warn of the current global financial crisis about a year in advance. However, the result should be interpreted with caution, since the indexes fail to take into consideration the uncertainty surrounding real‐time problems and the potential delays that may be caused by policy judgment. As a solution, we propose a scheme to forecast financial cycle indexes. According to the test results based on the Japanese data, our scheme gives advance warning of the ongoing global financial crisis.

“Stock‐touting” through spam e‐mails: a data mining case study

PurposeAlthough the financial markets are regulated by robust systems and rules that control their efficiency and try to protect investors from various manipulation schemes, markets still suffer from frequent attempts to mislead or misinform investors in order to generate illegal profits. The impetus to effectively and systematically address such schemes presents many challenges to academia, industry and relevant authorities. This paper aims to discuss these issues.Design/methodology/approachThe paper describes a case study on fraud detection using data mining techniques that help analysts to identify possible instances of touting based on spam e‐mails. Different data mining techniques such as decision trees, neural networks and linear regression are shown to offer great potential for this emerging domain. The application of these techniques is demonstrated using data from the Pink Sheets market.FindingsResults strongly suggest the cumulative effect of “stock touting” spam e‐mails is key to understanding the patterns of manipulations associated with touting e‐mail campaigns, and that data mining techniques can be used to facilitate fraud investigations of spam e‐mails.Practical implicationsThe approach proposed and the paper's findings could be used retroactively to help the relevant authorities and organisations identify abnormal behaviours in the stock market. It could also be used proactively to warn analysts and stockbrokers of possible cases of market abuse.Originality/valueThis research studies the relationships between the cumulative volume of spam touts and a number of financial indicators using different supervised classification techniques. The paper aims to contribute to a better understanding of the market manipulation problem and provide part of a unified framework for the design and analysis of market manipulation systems.

Methods of Measuring the Efficiency of Commercial Banks: an Example of Polish Banks

Efficiency analysis is essential for the evaluation of banks’ performance. To estimate banks’ efficiency, we can apply different methods. Analysis of financial indicators is the most popular efficiency analysis method in banks, but the number of financial indicators can be really big and make the interpretation of the results more difficult. Another way to estimate efficiency measures is the nonparametric frontier method - Data Envelopment Analysis (DEA). This method has become increasingly popular in measuring bank efficiency in the countries with developed banking systems.The main aim of this article is to present the results of efficiency analysis, computed by means of both methods, i. e. the classical index of balance sheet characteristics and the non-parametric DEA method.The analysis was carried out in the biggest banks operating in Poland in 2000-2007. The empirical results show that the efficiency measures give a similar although not identical picture of Polish commercial banks’ performance. These results (yielded by both methods) are complementary to each other and suggest that the non-parametric DEA method is really valuable and worth applying in bank practice.The work presents also the reasons that would explain the achieved results. It also compares both methods, their potentials and limitations in applying them to banking.

Multiattribute Data Presentation and Human Judgment: A Cognitive Fit Perspective*

AbstractWe assessed the ability of the cognitive fit theory to explain the performance of certain display formats on multiattribute judgment tasks. This theory suggests that for most effective and efficient problem solving to occur, the problem representation and any tools or aids employed should all support the strategies (methods or processes) required to perform that task. The theory was tested by assessing performance with schematic faces, graphs, and tables on a bankruptcy prediction task. Bankruptcy prediction involves integrating a large amount of data (a number of financial indicators over a number of years), as well as referring to ranges and/or levels of financial indicators. Schematic faces provide a cognitive fit with such tasks since the information in a face can be processed holistically; however, they do not permit decision makers to refer to the underlying data. Graphs facilitate a different integrating process; further, they preserve characteristics of the underlying data. Tables, on the other hand, do not aid the decision maker in integrating information; they provide only the underlying data values. It was hypothesized that graphs would provide the best cognitive fit for the bankruptcy prediction task since they permit processing both integrated and discrete data. Participants made judgments with two of the three display formats, at two levels of information load, in a fractional factorial design. The information load manipulation was designed to provide meaningful and meaningful plus redundant information to the decision maker in a test of information load “per se.” The research findings provided substantial support for the theory of cognitive fit. The findings also have implications for the study of information load.

Corporate Acquisitions and Shareholder Wealth: A Review and Exploratory Analysis

This exploratory study examined the effect of corporate acquisitions on shareholder wealth by reviewing the current literature and then analyzing a selected group of recent takeovers. In order to determine whether or not any effect did in fact exist, six "acquiring " corporations were compared with similar "non-acquirors"from the same industries on a number offinancial indicators readily available to the average investor Analyses of these data indicated that, contrary to what would be expectedfrom classical economic theory, the acquisitions studied had essentially negative impacts on shareholder wealth. These results lead to discussion of alternative rationales for initiating merger activities and possible long term effects of the recent merger trend.