محمدرضا عبدلی

Choosing the proper investment mechanism is one of the main tasks of any investor that requires careful analysis and research on all available information. Since no investor exactly knows whether his or her expectations for a particular stock return will be met, they need to build their strategy in such a way as to eliminate as much damage as possible in the event of an adverse outcome. This study aims to predict the optimal portfolio using Algorithm Analysis Systems. In this regard, 98 firms listed on the Tehran Stock Exchange were examined in 2015-2019. Then, random portfolios were selected to test the research hypotheses by separating value stocks and growth stocks. For analysis, two algorithms of Support Vector Machines and an Adaptive Neuro-Fuzzy Inference System were used to select the most desirable portfolio. According to the support vector machine algorithm analysis, the results confirm the difference between the Sortino and Marquitz portfolios. To build their portfolios, decision-makers often rely on growth stocks which can boost their expected returns. Therefore, recognizing the analytical nature of portfolio formation in specialized areas can help improve investment analysis and pave the way for higher returns.

The financial anomalies, which have brought about challenges for the nature of efficient-market hypothesis, provide ample experimental evidence on the deviation of market from rationality. According to the efficient-market hy-pothesis, investors avail themselves of all the information available in the market, and then attempt a thorough and painstaking interpretation of it. The empirical evidence, however, reveals that most investors fail to imple-ment rigorous information processing, thereby rendering to a number of behavioral theories concerning market inefficiency and biased information processing. The current research sets out to identify and scrutinize the im-pact of the CEO’s perceptual biases in judgment and economic decision-making on the reporting quality of the firms listed on the Tehran Stock Ex-change. The Purpose of this study CEO Overconfidence and Overinvestment by Role of Economic moderators Tehran Stock Exchange (TSE). One hun-dred five companies were selected as the sample size by systematic removal sampling reviewed in 2012-2019. Due to its dichotomous dependent variable, this study uses probit regression to test the research hypotheses. The results indicated the significant positive effect of CEO overconfidence on overin-vestment. It was also noted that Exchange Rate strengthens the positive effect of CEO overconfidence on overinvestment. Based on these results, the CEO's decisions as a decision-maker in charge of any company, especially under inflationary conditions, can play a substantial role in future corporate investment levels. The findings reveal that the indices of the CEO’s percep-tual biases in judgment and economic decision-making exert a significantly negative effect on financial reporting reliability and competitiveness.

The purpose of the research Decline of Auditors' Financial Bias in Decision making by Professionalism in Auditing: Rough Set Analysis. The research approach is of inductive-deductive type in terms of the data collection meth-od, because it was first determined based on the content analysis of the com-ponents and propositions related to the professional characteristics, then it was tried to confirm or delete the propositions based on the Delphi analysis. This research by participating 14 individuals of the audit partners with the academic degrees over a one-year period, 2018-2019. The results According to the formation of decision making matrix, the results showed that both propositions, the perceptual error of failure to separate the context from con-tent as the Halo bias and the perceptual error of the experience of fraud de-tection in the financial statement as memory bias were determined as the most influential perceptual errors in the audit profession in Iran. In addition, according to gray vikor theory analysis, it was found that the component of the audit's professional maturity was selected as the most important priority and the most effective feature for reducing the audit perceptual bias.

The purpose of this study is to analyze the most effective basis for assessing the intellectual capital maturity based on the themes of the ambidextrous learning link. In terms of purpose, this research is part of developmental research. Because of the lack of a basis for assessing the intellectual capital maturity under ambidextrous learning in previous research, based on meta-synthesis in the first step, an attempt was made to identify components as the analytical basis of the research and propositions as reference variables. Then, in order to explain the identified components and propositions, in a small part, intuitive fuzzy sets (IFSs) was used to determine the most effective basis for evaluating the intellectual capital maturity based on the themes of the ambidextrous learning link. In this study, the target population consisted of two parts: qualitative and quantitative. In the qualitative section, with the help of 16 management specialists and experts, an attempt was made at the university level to identify research components and propositions in the form of score forms. In the small section, 50 managers, officials and experts at various levels of knowledge-based companies participated. The results showed that the proposition of strategic tendencies in learning is considered as the most influential themes of the ambidextrous learning link in the studied companies, which strengthens the sustainability of knowledge creation as an effective component in the intellectual capital maturity.