INTERNATIONAL JOURNAL OF FINANCE AND MANAGERIAL ACCOUNTING
Year:2023 | Volume:8 | Issue:31|Papers Count:14

Globalization and, consequently, intensifying the competition between banks and financial institutions in domestic and foreign financial markets increase significantly the importance and requirement of strengthening and modifying systems in financial enterprises. Banks are no exception. Credit risk assessment is one of the most significant components of the granted facilities process. Small and medium enterprises are the majority of customers of commercial banks; hence, it is possible that designing a credit risk system considerably helps banks to manage credit risk.This study aims to introduce a new approach to predict and assess the credit risk of small and medium-sized enterprises. To this end, we identified the indices effective on the credit risk of medium and small-sized enterprises and determined significant indices by selecting the feature. We selected 98 cases of medium and small-sized legal clients in the industrial sector for research data from one of the commercial banks during the years 2018-2020. We then implemented the logit regression models, artificial neural network, and hybrid model (fuzzy expert system, logit, and artificial neural network) in order to predict and assess customers' credit risk and also calculated the accuracy of the models. Ultimately, we have designed the program applying visual studio software. We calculated the customer using logit regression models, artificial neural network, and hybrid model according to the designed program by inserting each customer's information and we also determined credit rating and type of collateral of each customer based on customer risk.

This study used the Copula-ARIMA-GARCH approach to calculate the VAR of a portfolio of four investment companies and daily data (from March/April 2009 to February/March 2017) to calculate risk more accurately and develop methods of the performance evaluation of value at risk (VaR ) models by a combination of a copula function and ARIMA/GARCH models. In this study, a novel method was proposed to evaluate the performance of VaR models using the fuzzy multicriteria decision-making models. For this purpose, ranks attained by the VaR estimation models were employed considering the unconditional coverage test procedure, Dowd’s loss function procedure, and the rank given the prediction accuracy. The results indicated that risk-taking and risk-indifferent investors assume that the VaR calculated from the Copula-ARIMA-GARCH model is the most accurate model, while risk-averse investors take the generalized extreme value (GEV ) model as the most accurate model considering the high importance of the loss function.

Development and Assessment of a Business Intelligence-based Management Accounting Information System Model: A Structural Equation Modeling ApproachAbstractNon-academic models have been used to examine the importance of business intelligence (BI) and business analysis in supporting business decisions, as well as their links with management accounting (MA). The structural equation modeling approach was used in this study to evaluate a conceptual business intelligence-based management accounting information system model.The qualitative section of the study included qualitative content analysis and grounded theory to create a business intelligence-based management accounting information system model comprised of causal conditions, strategies, underlying conditions, intervening conditions, and outcomes. The quantitative section employed structural equation modeling to evaluate the effects of the identified parameters on the effectiveness of the management accounting information system. According to the findings, the identified factors had a substantial impact on the research variables.Keywords: Management Accounting Information System, Business Intelligence, Grounded Theory, Structural Equation Modeling, Causal Conditions, Intervening Conditions, Underlying Conditions, Outcomes

AbstractThe aim of this study was to investigate the professional and organizational identity of auditors and commercialization in auditing firms. In order to achieve the research goal, about 384 questionnaires were distributed and collected among the auditors of auditing firms in Iran as a statistical sample. The data collected by the questionnaires were analyzed by SPSS24 and Smart PLS3 software using structural equation modeling. The results of the analysis of research hypotheses is using structural equation modeling at 99% confidence level indicated that the professional identity and organizational identity of auditors have a positive and significant the effect on the market orientation of auditing firms. The professional identity and organizational identity of auditors have a positive and significant effect on the customer orientation of auditing firms. The professional identity and organizational identity of auditors have a positive and significant effect on the direction of the processes of auditing firms.

The present research develops and examines an indigenized model for understanding the determinants and consequences of social capital among Iranian audits. This is a mixed exploratory paper and the thematic method was used for qualitative analysis. The statistical population of the research includes professional audits including trustable audits of the Tehran Stock Exchange and managers of the Iran Auditing Organization. Purposeful sampling was used to pick sample members for the qualitative phase. Data reached saturation in the 18th interview but 20 interviews were conducted for a higher validity. Using a qualitative method, research model constructs were identified namely organizational management, moral principles and professional rules, human capital, cognitive factors, strategic considerations, organizational environment, and social capital. Then, the created model was tested among the certified public accountants of Iran using simple random sampling. The structural equations modeling with partial least squares (PLS) was used to analyze data. The results show that all research hypotheses were supported. At the end of the paper, practical implications and future research are discussed.

Our goal in this paper analysis the dynamics of national saving investment relationships between 1978 and 2017 in the economy of Iran to determine the degree of capital mobility. For this purpose, the validity of the Feldstein-Horioka hypothesis was tested by relying on the ARDL Bounds testing approach to co-integration and vector error correction model. The authors interpret the close relationship between national saving and investment in the long run as a reflection of a lack of capital mobility. These results suggest that the Feldstein-Horioka Hypothesis is applicable for the Iran economy in the period analyzed. The analysis of the time series characteristics of the current account balance shows that the current account balance does not have a unit root and the link between Iran's economy and international capital markets is not significant. We observed that trade openness, can't help explain the investment. Our findings for Iran suggest that home bias in the allocation of domestic savings significantly declines when domestic investment is financed by domestic savings alone. Furthermore, the empirical results indicate that the Feldstein-Horioka puzzle does not hold for the Iran economy.

This research examining the relationship between political connections in board, family ownership and earnings quality with an emphasis on political economy perspective and agency theory at the firms listed in Tehran stock exchange (TSE) from the years 2012 to 2018. To achieve this Purpose, this study uses a sample (805 firm-years observations) including the firms listed to examine research hypothesis. Also, the multivariate panel data regression is used for testing the relationship between variables. To enhance the robustness of the empirical results, this study uses other proxies of earnings quality and it has seen the effect of inflation. The present study finds are consistent with the resulting of the studies on the theory of political economy and agency theory previous literature. The results of the study indicate that firms with politically connected in board, have a lower earnings quality than politically non-connected. Also, the results show that family-owned firms have a higher quality of earnings than non-family companies. Furthermore, the negative effect of political connections on earnings quality moderating by family ownership. This means that mitigates the costs of political connection and improves the quality of firm's earnings when existing family ownership.

The study of profit information content has a wide range of theoretical and practical foundations for the academics and professionals in the field of accounting and management, to conduct scientific research to fill the gaps. Consequently, in the present study, the information content was examined for the profitability of companies listed on the Tehran Stock Exchange as the research population, during a time period of 5 years from 1393 to 1397. Using a systematic elimination method, among all listed companies on the Tehran Stock Exchange at the beginning of 1398, 128 companies having the desired conditions were selected to be explored as the research sample. Using a Quantile Regression Model, the results showed different indicators: A) The quarters analyzed, showed a significant relationship between changes in Stock Return and future Profitability, but it was negative only in the first quarter, and positive, in the sub-sequent quarters studied. B) All analyzed quarters, showed a significant relationship between the economic variable of Liquidity Growth and future Profitability, but it was positive in the 1st quarter, and negative in the sub-sequent quarters.

The ultimate goal of investments in stock markets is to earn a satisfactory return on investment, but this is difficult to achieve without enough information to predict stock returns. Information asymmetry refers to a situation where some investors have access to private information that is not reflected in the prices and is yet to be revealed to others. Information asymmetry as a market failure can lead to adverse effects such as poor investor decisions, increased corporate investment risk, and finally reduced stock returns. The issue is important in capital market of developing countries particularly due to the incomplete voluntary disclosure of information as well as its low quality and defective regulatory system. Therefore, in this study, effect of information asymmetry on stock returns has been investigated in a select group of companies listed in Tehran Stock Exchange. The analysis of this relationship was conducted dynamically for the short-term and long-term using Westerlund and Dumitrescu-Hurlin tests and Generalized Method of Moments to achieve articulated results. Using the tests is suitable with cross-sectional dependence of variables and error terms. Also, using the method is appropriate for measuring lagged effect of dependent variable and removing the bias caused by the endogeneity of explanatory variables. The Results demonstrate a significant relationship between information asymmetry and stock return dynamically in short- and long-run. The results show that there is a negative systemic effect of information asymmetry on stock return. Also, debt to asset, profit to sales, firm size and lagged stock return effects are significant.

One of the most important favorite topics for economists and financial analysts is to explain the reason and trend of price fluctuations because a large number of factors affecting profitability in this market are associated with risk.Due to the changes in the industry index in recent years and the complexity of the economic environment of construction in Iran, one of the most important issues for capital market participants and shareholders of the mentioned group is the possibility of forecasting stock prices. Therefore, the purpose of this study is to design and explain the stock price forecasting model in real estate mass construction companies on Tehran Stock Exchange using the data panel regression model. The research is quantitative in terms of the data type and practical in terms of the result and descriptive and exploratory in terms of the purpose.The statistical population of the study consists of all companies listed in the group "Mass Construction and Real Estate" on Tehran Stock Exchange. The results showed that for the overall stock index, both moving average and autoregressive factors have a positive and significant effect with more than 99% certainty and the retrospective trend of the stock index is predictable.

A cursory look at the formation of corruption and financial fraud cases shows that fraud is always disclosed after a considerable period of time from the date of the fraud, often through reports of intelligence agencies, informed staff and managers, and the media; only a small percentage has been revealed by corporate accountants. In this regard, the purpose of this study is to provide a model for disclosing fraudulent actions for accountants with an emphasis on effective factors. During the implementation stages of the present study, the most important indices were obtained by studying the theoretical foundations. Based on these indices, interviews were conducted with experts and some codes were extracted relying on the results of these interviews. Finally, based on the results of these interviews with experts and extracting keywords and key answers, a model was presented with a factor analysis approach. It is worth mentioning that after conducting several studies, we conducted 12 semi-structured interviews. Open-ended questions were used in these interviews. In summary, the results of the present study showed that personal responsibility, sense of importance, philosophical attitude, risk-taking, cultural characteristic of distance from power, cultural characteristic of corporate citizen, organizational commitment and experience of similar cases have a positive and increasing effect on the extra-organizational disclosure of the frauds.

This study investigated the effect of auditors’ identity on the commercialization of auditing firms with a focus on the mediating role of auditors' creativity. This study is an applied study in terms of its objectives and a descriptive survey in terms of the method of data collection. The research population included certified public accountants and professional managers in auditing firms (n = 1300) as members of the Iranian Society of Certified Public Accountants. The sample size was estimated at 297 persons using Cochran's formula. The data were collected using questionnaires. The validity of the questionnaire was assessed using convergent validity and divergent validity. Moreover, the reliability of the variables was assessed using Cronbach's alpha coefficient and the composite reliability, and the corresponding values were greater than 0.7 for all variables. The collected data were analyzed using SPSS and Smart PLS3 software. The results of the study indicated that auditor identity has a positive and significant effect on auditor creativity as well as the commercialization of auditing firms. It was also shown that auditor creativity has a positive and significant effect on the commercialization of auditing firms. Thus, it can be concluded that auditor creativity plays a mediating role in the impact of auditors' identity on the commercialization of auditing firms.

The purpose of this research is to identify and analyze the importance-performance of factors affecting the development of green financing based on the role of the banking industry in Iran for the transition to a circular economy. The current research has been conducted using the mixed exploratory research method in two parts: qualitative (theme analysis) and quantitative (importance-performance analysis). In the qualitative part, by using the non-random judgmental method, the opinions of 14 managers and experts of the banking industry as well as university professors were used. Also, in order to determine the random sample size in the quantitative part of the research to complete the questionnaires, the power analysis method presented by Cohen (1992) was used. Based on this, the required sample size was determined to be at least 113. According to the research findings in the qualitative part, during the data first stage, 52 cases of evidence identified from the text of the interviews were labeled in the form of 26 primary codes. Next, the primary codes were categorized into five sub-themes and then a main theme. The results of the importance-performance analysis also showed that financial factors as well as infrastructure and technology have a higher than average importance in providing green financing based on the role of Iran's banking industry for the transition to a circular economy, and their performance is also higher than average, and this is due to The meaning of the special status of these variables.

The main purpose of this study is to measure the value of quality improvements in one of the two greatest steelmaking factories in middle east during the six months period since June to December,2020 and has used a new method (introduced by dahlgaard & setijono) for transforming quality cost measurements into value of quality improvements(ROQI). The two used models in this paper have been theorically developed and examined in a Swedish wood-flooring manufacturer. The data analysis results in present study suggest that quality improvement efforts do affect on quality improvement indicators, and model validation is reconfirmed.By converting quality costs measurements into value, a better explanation concerning the effect of prevention and appraisal activities on the quality improvement indicators would be provided. Thus, the value of quality improvements is a measure of return on quality improvements (ROQI), which reveals whether the quality improvement efforts gave higher, fair, or lower return.