Advances in Mathematical Finance and Application (AMFA)

Investigating the performance of companies is one of the most important issues for the users of accounting information. The purpose of this study was to provide evidence about the effect of asymmetric appropriateness on investors' expectations. The results of the research on accepted companies In the Tehran Stock Exchange during the period from 2012 to 2016. To collect data, a library method was used and referring to financial statements, explanatory notes and monthly stock exchange of the Stock Exchange. Using Cochran sampling method, 120 firms were selected as the statistical sample. To analyze the data, multivariate regression analysis was used to confirm the rejection and research hypotheses (ivyz software). The results showed that asymmetric accountability leads to different expectations of investors about the company's outlook, and the negative relationship between asymmetric verification (conservatism) and investors' controversy is weaker with the release of good news and gets worse by the publication of bad news. The results are consistent with the documentation referred to in the theoretical framework of financial research and literature, such as the theory of vision and the concepts of behavioral and financial behavior, and the publication of good and bad news has a significant role.

One of the most important effective factors in the economic growth is the increased efficiency of manufacturing sectors. Thus, it is necessary to review and measure the efficiency of business units from a variety of dimensions to plan the increase of efficiency in future courses. One of these dimensions is the economics to scale (ES) referring to the concept of enhanced earnings due to the increased manufacturing unit, which may be of an increasing, fixed or decreasing trend. ES can be measured through economic production functions. This paper has applied Translog production function to measure corporates' ES. Therefore, data of 105 manufacturing corporates have been collected during 2008-2017. With regard to linearity between independent variables, the elastic net regression method has been used. Results indicate that some industries are of increasing economics to scale trend and some have a decreasing ES. Results can be applied in order to plan and determine the appropriate production level in the management accounting of corporates.

Banks are the financial institutions that collect assets from various sources and allocate them to the sectors that require liquidity. Therefore, banks are an inherent element in the system of every country. As private banks enter financial markets, the demand for diverse banking services increases dramatically. Banks seek to use various techniques to improve their performance in attracting customers to increase their market share and profitability. In this regard, assessing the performance of banks is of utmost importance and has become a major activity of bank managers. With the constant changes in the modern world and incessant attempts of competitors to increase their market share by gaining competitive advantage, special attention should be paid to ambidexterity as a key strategy to increase competitive advantage and achieve high performance in dynamic business environments. The present study aimed to identify the ambidextrous factors affecting the performance of banks and present a model to assess the performance of an ambidextrous bank using an agent-based modeling approach. The main objective of the research is to achieve an applied model for managing the performance of the banking industry. The simulation model is processed using the agent-based modeling approach in AnyLogic software environment.

Today, in large projects such as constructing oil, gas and petrochemical refineries, it is inevitable to use modern management methods and project timing. On the other hand, in classic scheduling case, the focus is on balance between time and cost of carrying out projects, which in such a situation, one of possible solutions to shorten time of implementing project is to accelerate activities. This acceleration can affect the quality of conducting projects and environmental impacts, in addition to impose more costs. Hence, in such studies, environmental impacts and quality of activities were also considered as new indicators in case of project time-cost balance. There has been proposed a new mathematical model with four indicators: cost, time, quali-ty and environmental impacts. The provided model is a multi-objective mathematical model of zero-and-one programming type that despite traditional models, in which there is only considered an implementation mode for carrying out activities and a pre-conditional relationship between activities, modes of implementing activities are as multi-form and the dependence relationship between the activities is a generalized pre-requisite. Including the relationships brings the problem closer to the real world. Because of NP-hard of the problem in large dimensions and the necessity of using meta-heuristic Algorithms, we used MOBEE algorithm to solve the model.

The purpose of this research is to design a sustainable supply chain model with an emphasis on behavioral factors for foodstuff in Kermanshah province. This is an applied research. The literature review was the outcome of a library study such as books, journals, dissertations, articles, and so on, and the data were collected through a questionnaire which was analyzed by statistical methods. Regarding the subject of this research, the study population consists of managers and staff associated with the supply chain in Kermanshah food companies, involving 100 people. Having analyzed the data using the structural equation modeling and PLS software, it was turned out that the training environment, innovation, motivation, staff empowering, mutual trust and respect, as well as teamwork had a positive and significant effect on the sustainable supply chain with three environmental, social and economic indicators.

Investment decision making is one of the key issues in financial management. Selecting the appropriate tools and techniques that can make optimal portfolio is one of the main objectives of the investment world. This study tries to optimize the decision making in stock selection or the optimization of the portfolio by means of the artificial colony of honey bee algorithm. To determine the effectiveness of the algorithm, its sharp criteria was calculated and compared with the portfolio made up of genes and ant colony algorithms. The sample consisted of active firms listed on the Tehran Stock Exchange from 2005 to 2015. The sample selected by the systematic removal method. The findings show that artificial bee colony algorithm functions better than the genetic and ant colony algorithms in terms of portfolio formation

The current research sets out to identify and scrutinize the impact of the CEO’s perceptual biases in judgment and economic decision-making on the reporting quality of the firms listed on the Tehran Stock Exchange. Adopting a mixed method, the present study first seeks to detect the components and indices of CEO’s perceptual biases via critical appraisal and with the special participation of 10 accounting experts. Afterwards, the rec-ognized indices are set to undergo a Delphi analysis given the mean and the coefficient of agreement. The verified indices are then adapted to the ac-counting models and analyzed in the form of research hypotheses. The re-sults of qualitative analysis using Delphi method verify the reliability of 16 indices out of 22 ones. Regarding the quantitative analysis, the association between the indices of the CEO’s perceptual biases in judgment and econom-ic decision-making, and the primary proxies of financial reporting, namely reliability and competitiveness is tested. The findings reveal that the indices of the CEO’s perceptual biases in judgment and economic decision-making exert a significantly negative effect on financial reporting reliability and competitiveness.

The purpose of this study is to investigate and identify the periods of formation and bursting of speculative bubbles in Iran's capital market by creating a state space model and two-mode switching regime (mode 1 is bubble growth and burst stage and mode 2 is the time of bubble loss) during the period from April 2011 to March 2018. The Oxmetrics 7 software is used to investigate the existence of multiple bubbles and research objective. The results of the study of the state space switches confirm the bubble of the capital market in Iran during four periods in the research domain. The life span of the first speculative bubble is 2 months from October to November 2011, the second is 8 months from March to October 2013, the third is 3 months from December 2015 to February 2016, and the fourth period of bubble is 5 months from August to December 2017. Therefore, the result of the research stipulates that the stock index of the Iranian capital market in the realm of research time period has had 18 months of bubbles and has spent 66 months in balance.