International Journal of Finance and Managerial Accounting
Volume:4 Issue: 16, Winter 2020

In the last decade, high profile financial frauds committed by large companies in both developed and developing countries were discovered and reported. This study compares the performance of five popular statistical and machine learning models in detecting financial statement fraud. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements between the years 2011 and 2016. The results show, that artificial neural network perform well relative to a Bayesian network, Discriminant Analysis, logistic regression and Support vector machine. The results also reveal some diversity in predictors used across the classification algorithms. Out of 19 predictors examined, only nine are consistently selected and used by different classification algorithms: Employee Productivity, Accounts Receivable to Sales, Debt-to-Equity, Inventory to Sales, Sales to Total Assets, Return On Equity, Return on Sales, Liabilities to Interest Expenses, and Assets to Liabilities. These findings extend financial statement fraud research and can be used by practitioners and regulators to improve fraud risk models.

A firm is called to have stock price crash risk if the firm has a tendency to experience a sudden drop in its stock price. In this study, the relation between the firm-level of business strategy and future stock price crash risk Is examined, as well as the effect of stock overvaluation on the relationship between business strategy and crash risk investigated. Using the strategy index and crash risk indicators the question that whether innovative business strategies (prospectors) are more prone to future crash risk than defenders is investigated. In so doing, we identify two main hypotheses and the data of 111 listed companies of Tehran Stock Exchange for the period between 2009 and 2017 were analyzed and a panel data approach has been used to test of research hypotheses. We develop a measure of business strategy based on Miles and Snow and test the association between this business strategy measure, overvaluation and stock price crash risk. Our investigations show that overvalued firms on average have higher price crash risk.

This study is about the exploration of accounting system and annual report review process in the context of new public management initiative in Australia. A Government Department in the Australian Capital Territory has been adopted as the field for investigation. Qualitative research methodology was chosen to obtain a better understanding of the phenomena. Case based research method was used in developing a fuller understanding of the relative role of accounting system in the management of organisational performance. In this study, data collection involved a triangulation approach and the sources were organisational documents, interviews and observation. As accounting system is socially constructed Giddens’ Structuration Theory was used in this research to obtain a better understanding of human actions and to explore how this system is implicated in the wider social context through time. Empirical evidence from the field supported that in the researched organization the new elements of interpretive schemes are the accrual accounting and annual report review. It appears that these interpretive schemes are the direct outcome of the new public management ideals and was implemented to establish the principle- value for money.

In today's competitive world, reduction of production costs has become one of the corporates priorities. Survival triangle (cost, quality and time) is the solution that helps companies focus on these three dimensions and have the ability to compete with other companies. Cost management is the first step in this way that providing solutions and advice to managers who need help to have a precise estimate of the costs and enable them to control costs in the anticipated budget framework. The main objective of this research is the evaluation of relationship between information technology and project cost management from viewpoint of Soufian Cement Co executives. According to statistical population of research encompasses all company managers (n= 35), the sampling method that used is census-type and depending on the nature of the topic, a researcher-made questionnaire method (Cronbach's alpha coefficient was 88% for IT questionnaire and 81% for project cost management questionnaire) used for data collection. Preliminary results showed that the level of usage of information technology and project cost management in the company is moderate. Due to normality of all the data, Pearson correlation coefficient test was used for data analysis. The overall results showed that there is a significant relationship between information technology and project cost management, but there is no possibility to control costs by using information technology.

This study wants to investigate the rating of the actual customers of banks based on credit risk using multiple criteria decision making and artificial intelligence hyperbolic regression. This is an applied research. The statistical population of the study includes the credit customers of Agriculture Bank in west branches of Mazandaran province, Iran in 2012-2016. A total of 100 cases have been evaluated. AHP method has been used in the case of elites' comments on the prioritized seven key factors using the corresponding weighting matrix. To model the classes of creditworthy and non-creditworthy customers and to predict the appropriate model based on the evidence in the customer's credit file, artificial intelligence hyperbolic regression has been employed. Using AHP method, the rating include customer revenue, credit in the market, customers' job, the duration of the relationship with the bank, the type of collateral, the value of collateral, average account balance to facilitate the credit risk of the actual customers, respectively. Using artificial intelligence hyperbolic regression, prioritization is based on the amount of credit in the market, customer revenue, the value of collateral, the duration of the relationship with the bank, the type of collateral and customers' job.

Competitive and skilled management accountants are needed for the companies' survival in an ever-changing world and also a world without borders. Therefore, the problem is what components in a decision maker brings out the best decision. Since learning is continuous and continuous learning is essential in an ever changing world in order for the company to survive. The aim of this study is to determine the effect of metacognition on management accounting students' decision. To reach this aim 83 graduate students of Islamic Azad University of Tehran have been studied in 2017 using three questionnaires. Path analysis and factor analysis have been conducted simultaneously in PLS software. The results show that the correlation between metacognition and management accounting students' decision (what it is) is negative. And also the relationship between metacognition and management accounting students' decision in practice (what it should be) is negative. The study concludes that although metacognitions' aim is to bring out competitive learners, it does not necessarily make innovative decision-makers. Also centralized management in low-privatized countries could affect innovation in decision making

The main purpose of this research is to evaluate the role of the company life cycle in providing an appropriate model in predicting the quality of discretionary accruals (Abnormal) using the Dickinson Cash Flow Model approach. The statistical population of the research consisted of 180 company observations that were divided into three stages of life cycle using Dickinson's model variables (2011). Multivariate regression technique was used to test the hypotheses based on the cross-sectional data. Then, using initial models for measuring the quality of discretionary accruals (Abnormal), the error values ​​of each model were compared with the error values ​​obtained from the life cycle adjusted models. The results show that the coefficients of determination in the Kasznik adjusted model are not significantly increased compared to the initial model, but in the other models, the coefficient of determination increases significantly compared to the initial model, indicating that the values ​​estimated by the adjusted models are an appropriate approximation of the real values. ​​They predict and identify more exactly up to a few percent of accruals quality or the operational cash flow difference and net profit compared to the initial models; so, except for the Kasznik model, in the other models an increase in the life cycle increases the predictive power of the Models.

Regarding the fact that each country might be a net oil seller or net buyer, and considering its large share in the whole economy, the price of this commodity as well as its volatility could affect all economies around the world.  The impact of oil price volatility on the economy is seemed to be more dominant in Iran rather than any other developed or emerging economies, especially in recent years. The purpose of this study is to investigate the effect of direct and indirect oil shocks on the stock returns in the selected energy companies listed in Tehran Stock Exchange. The reason behind choosing such industries is that energy prices play an important role in the production cost. For this reason, we used monthly basis data spanning the period starting from April 2009 to July 2019. Appling three-stage least squares (3SLS) and Panel data, the direct effect of oil shocks on stock returns found to be negative even though those for indirect effect were positive

Investors behavior is one of the most important discussion of the financial science in the financial market. Individual investors consider various factors when they buy and sell securities and show different behavior (Rational, Herding, Reaction and Heuristic). The main purpose of this research is to identify and categorize factors which impact individual investors behavior that are known as behavioral biases in behavioral finance literature. This research is practical as objective and implies a descriptive-survey research method. At the first phase of the research for the purpose of identifying those factors that impact the investors behavior, 30 behavioral finance experts participated. In the second phase of the research (examining the proposed model), statistical population consists of all investors in Tehran stock market of which 384 samples were selected randomly.. Questionnaires were made by researchers. Cronbach’s alpha Coefficient is 0.79 and 0.82 Respectively that indicates suitable reliability. The SPSS software and Smartpls.2 software was used for analyzing the data. The result of statistical analysis revealed that, financial ratios, status market, market total index trend, and rumors, etc were identified as influential factors. Finally,  factors was classified in four group(Company Internal, Transactional information, Environmental and Psychological). Research proposal model was confirmed by confirmatory factor analysis

The survival and growth of the banking industry, on the one hand, requires the trust and satisfaction of individuals in the community, on the other hand, requires financial health. In this research, we seek to evaluate the impact of activity-based management on indices of banking health in the banking system of IR Iran. The activity-based management tools examined in this study are activity-based budgeting and activity-based costing. The population of this study consisted of banks approved by the Central Bank of the Islamic Republic of Iran; however, as not all the banks provided the required information and due to the need to obtain reliable data, 19 banks, which had submitted financial statements for the year ending in 2017, were chosen as study samples. Structural equation modeling and correlation analysis were used to investigate and answer the research questions. The results of this study showed that activity-based management techniques have a significant impact on banking health, and more precisely, activity-based costing is the most effective. In terms of prioritizing the components of ABC and ABB techniques, ABC training and ABB training have the first and second priorities, respectively. Next to these two components, "understanding, supporting, and engaging in strategy" as well as "acceptance and implementation by units" of ABC components bear more significance.