Seyed Mohammad Soleymani; Farhad Dehdar; Mohammadreza Abdoli
Abstract
The growth and complexity of society justify the need for relevant economic information, information systems, and information-generating processes, and the need for auditing as part of the information reporting process increases. This has affected the professional functions of auditors. The purpose of ...
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The growth and complexity of society justify the need for relevant economic information, information systems, and information-generating processes, and the need for auditing as part of the information reporting process increases. This has affected the professional functions of auditors. The purpose of this research is to choose the influential dimension of mindfulness of auditors' professional judgments based on social pressure analysis based on Rough Theory. The methodology of this research is mixed and it has been used by Meta-synthesis, Delphi and Rough Theory. The target population was the qualitative, similar research and academic experts in the field of accounting. However, the target population in a small number of 19 audit partners had more than 5 years of work experience, which is acceptable from the statistical population due to the requirement of Ruff theory analysis. In this study, based on the Meta-synthesis analysis of selected researches, 4 propositions of pressures based on social compliance and 3 components of auditors' professional judgment were determined. The results in this section show that the most effective proposition of social compliance pressures was the market pressure proposition, which affects the inferential consciousness of auditors in their professional judgment and violates the auditors' mental functions such as skepticism and objectivity.
Javad Ghaznavi Doozandeh; Mansour Garkaz; Ali Khozein; Alireza Maetoofi
Abstract
The present study aimed to identify the most effective causes of conflict of interest by examination of accounting literature and expert consensus. Understanding these factors, using cognitive psychology theories, can lead to a model for reducing conflict of interests. The dignity of the audit profession ...
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The present study aimed to identify the most effective causes of conflict of interest by examination of accounting literature and expert consensus. Understanding these factors, using cognitive psychology theories, can lead to a model for reducing conflict of interests. The dignity of the audit profession depends on fair and proper professional judgment by auditors, and achieving this requires identification and controlling of the key factors affecting judgment and decision-making. When auditors intentionally or unintentionally accredit financial statements in line with the opinion of their employers, public interests and the auditing profession are at serious risk. Several factors that can categorize into seven categories of structure, community, culture, environment, personality, audit firm characteristic, and ethics and behavior are rooted in a conflict of interests. However, no comprehensive research examining all the above factors and identifying the most effective ones has been done so far. By reviewing the research literature, major and minor factors were identified in domestic and foreign sources. Ten expert auditors were selected by the snowball method and interviewed. The considered major and minor factors were selected from among the introduced factors, and a questionnaire was sent to the experts using the Fuzzy Delphi (Screening) method. The results of the above statistical analysis identified eighteen of the most prominent sub-criteria of the factors affecting conflict of interests and identified structural factors the highest rank in this classification, which was agreed by the experts.
Babak Sohrabi; Ahmad Khalili Jafarabad; Saba Orfi
Abstract
The impact of personal judgment on the assessment of an individual’s financial situation has been drastically reduced through the development of credit scoring. The systems are capable of deciding based on an applicant’s total score which is a combination of several factors and indicators. ...
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The impact of personal judgment on the assessment of an individual’s financial situation has been drastically reduced through the development of credit scoring. The systems are capable of deciding based on an applicant’s total score which is a combination of several factors and indicators. Over the past few decades, credit scoring has been considered an essential tool for evaluation in various institutions and has also been able to transform the industry as a whole.
Most of the research conducted in the field has taken into account traditional credit scoring, but considering the ever-evolving technological world that we live in and the increasing emergence of new social media networks, such research has now become obsolete. Such technological advancements have not only paved the way for far more sophisticated credit scoring systems but also essentially rendered the previous generations useless. It should be noted that credit scoring and its features have widely been discussed across the globe but, considering the various aspects and models that have to be taken into account, no one best method has been designed or suggested for it so far. This study shows that social media channels tend to perform relatively well in predicting stock market trends when the overall index is growing positively. The research also illustrates that a higher number of days of activity and a large number of signals released do not necessarily mean that the channels can or have credited their offered stock return on a one-month time frame.
The methodology used is "CRISP-DM," which consists of six steps. The main variables include social and financial variables that are examined for six months. In the research, we seek to identify, analyze and categorize active telegram channels in stock signals using the data mining model and the RFM method. The k-means algorithm is selected for this category. Then, in each cluster, the importance of social variables and the performance of the channels are extracted by the EXTRATREECLASSIFIER algorithm, and channel performance is measured by considering the changes in the total index.
Leila Nateghian; Saeid Jabbarzadeh Kangarlouei; Jamal Bahri Sales; Parviz Piri
Abstract
Today, choosing the suitable model for determining the portfolio of investment in financial assets is one of the critical issues of the attention of analysts and capital market activists, and investing in a portfolio consisting of mutual investment funds is the same. With this statement, the purpose ...
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Today, choosing the suitable model for determining the portfolio of investment in financial assets is one of the critical issues of the attention of analysts and capital market activists, and investing in a portfolio consisting of mutual investment funds is the same. With this statement, the purpose of the article is to evaluate and compare the net assets value (return) of the Federation of Asian and European Stock Exchanges (FEAS) member countries by using support machine models in comparison with statistical models. The statistical and sample population included the data of 39 selected traded funds and FEAS members from 12 selected countries (including Iran) between 2014 and 2021.
The data related to the mentioned funds were classified and analyzed using spss-modeler, rapid miner, and Weka software. They were tested with 24 support machine methods and 11 statistical methods, and the results showed that the prediction accuracy of statistical models is lower than that of support machine models. The Mann-Whitney test was used to determine the significance of this difference. Also, the results show that at the 95% confidence level, it can be claimed that the prediction accuracy of machine learning models is higher than statistical models. The average rating of machine learning models was (20.86) much higher than statistical models (10.85).
Shahram Molavi Bisetoni; Kiamars Fathi Hafshejani; Aboutorab Alirezaei; Ghanbar Abbaspour Esfadan
Abstract
The primary purpose of this study is twofold: Firstly, using the Markov Regime Switching model throughout December 2008 to February 2020, it investigates and compares the nonlinear impacts of exchange rate movements and monetary policies on Petroleum Stock Index, PSI, in Iran. Accordingly, some control ...
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The primary purpose of this study is twofold: Firstly, using the Markov Regime Switching model throughout December 2008 to February 2020, it investigates and compares the nonlinear impacts of exchange rate movements and monetary policies on Petroleum Stock Index, PSI, in Iran. Accordingly, some control variables, such as OPEC oil price, inflation rate, and international sanctions, have also been used to model these relationships more accurately. Secondly, it is an empirical attempt to trace the historical changes in the PSI behavior through distinguishing the precise regime numbers, and the relationships between the exogenous variables and the PSI. Our results confirm that the effects of both exchange rate movements and monetary policies on the petroleum stock market return are direct and significant. More interestingly, the more we move from regime one to regime three, the greater the effects of the research variables on the index, except for the impact of OPEC oil prices. Our empirical findings further suggest as the effects of sanctions intensify, the influences of monetary policy and exchange rate movements would have a more significant impact on the petroleum stock index returns.
Mostafa Hashemi Tilehnouei; Javad Nikkar
Abstract
The ability to produce future cash flows is an important part of the decision-making mechanism of the various shareholders. If cash flows can be predicted appropriately, a significant part of the informational needs associated with cash flows will be provided. Some analysts and investors argue that cash ...
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The ability to produce future cash flows is an important part of the decision-making mechanism of the various shareholders. If cash flows can be predicted appropriately, a significant part of the informational needs associated with cash flows will be provided. Some analysts and investors argue that cash flows are the main criterion for valuation. In this regard, the objective of this study is to examine the impact of firm characteristics in predictable future cash flows from operating activities by employing present operating cash flow and profitability. For this reason, eight hypotheses were developed and information was analyzed for 127 firms listed in Tehran Stock Exchange for the period of between 2011 and 2020. The regression model was tested with fixed effect model using panel data. The findings of the study showed that the firm characteristics like size, level of competition and level of supervision have a positive impact on the predicting power of present operating cash flow and present profitability in anticipating future operating cash flow. By contrast, the outcomes disclose that characteristics such as company’s life will not have a significant effect on the predicting strength of present operating cash flow and present profitability to forecast future cash flow from operating activities.
Mohsen Rahmani; majid ashrafi; Parviz Saeidi; Jamadori Gorganli Doji
Abstract
The flow of information in the capital market is of strategic importance because it determines the path of investors' decisions. In this decision-making process, the managers of the companies can disclose timely and reliable information based on their cognitive and perceptual characteristics of capital ...
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The flow of information in the capital market is of strategic importance because it determines the path of investors' decisions. In this decision-making process, the managers of the companies can disclose timely and reliable information based on their cognitive and perceptual characteristics of capital market situations. This article aims to contribute to the capital market knowledge literature by presenting the framework of managers' inertia drivers in response to reliable disclosure of information. This study adopted mixed, both inductive and deductive approaches to develop an integrated framework, validate its practicability and verify its effectiveness in selected firms listed on Tehran Stock Exchange respectively. In developing the framework and implementation procedure, the study employed a systematic screening data collection (qualitative) approach to review the managers' inertia drivers. Then, in this study's second phase, the Interpretive Rating Process (IRP) and Fuzzy Reference System are used to develop the framework of managers' inertia drivers in response to reliable disclosure of information. The results of the study in the qualitative part indicate the determination of 8 driving areas of managers' inertia in the reliable disclosure of information. On the other hand, the results in the quantitative section showed that the most effective field in stimulating managers' inertia in the timely disclosure of information is managers' overconfidence excitability. Based on the results, it was determined that the excitability of managers' overconfidence in creating inertia causes managers' subjective estimates to cause exclusivity in information disclosure.