فریماه مخاطب رفیعی

Making decisions regarding capital structure is among the most challenging issues ahead for firms and the most critical decisions for their survival. On the other hand, several significant aspects, such as behavioral factors, have been overlooked in this field. Thus, the present study mainly seeks to identify the factors affecting capital structure in Iranian firms, emphasizing the role of behavioral factors. The present study employs mixed qualitative and quantitative research methods. From the qualitative point of view, capital market experts were inquired, and theoretical saturation was achieved using the snowball method. After the interviews, research components were extracted through coding. The opinions of a group of experts and managers of firms listed on the Tehran Stock Exchange were used in the quantitative section, and a structural equation form was used to perform confirmatory factor analysis on the research model. A total of 63 concepts in the form of six categories were identified at the first stage, which was reduced to 58 in the form of six categories and was confirmed after the concepts were sent back to the experts. The principal components included behavioral factors, macroeconomic factors, political factors, socio-cultural factors, firm features, and corporate governance. Results were validated through factor analysis in the quantitative portion of the study. The present study can be considered among the comprehensive studies at the construct level with an integrated approach to firms' capital structure. The emergence of behavioral finance resulted from understanding the importance of measuring human behavior as a factor with transcendent consequences for financial decisions. Hence, most behavioral finance studies are focused on observable behaviors. However, the item response theory presents an integrated method for disciplines that work with cognitive variables. Accepting opportunities for new knowledge is essential for firm decisions to respond to the mental views of financial managers. The present study sought to identify the factors influencing firms' capital structure in Iran. The tool used in the present study reflected the elements making up the capital structure. In this regard, the notable point is how the classic criterion of structural capital components can explain financial managers' perception of decision-making. The research results in this area are interesting since we have confirmed a capital structure theory at the construct level. The conformity of the results and the obtained reliability levels indicate that this theory fits the given dimensions well. Moreover, relevant evidence indicates that senior financial managers adopt various states considering internal and external factors at the structural level, which can cause cognitive bias in decision-making.

Managing a single portfolio is a basic assumption in the most of research. However, in reality, an advisor manages many accounts at the same time; therefore, there is a significant dependency among portfolios and correlation between decisions on one portfolio with the performance of others, so the results of multi portfolio is different with classic models (single portfolio management, that portfolios are optimized independently) due to market impact and the trade dependency of one account to the other accounts. We propose a structural model to optimize accounts simultaneously, considering interdependences, decision’s correlation and mutual behavioral effects of managed portfolios. Moreover, to compare and analyze both single portfolio and multi portfolio approaches, real data from Tehran Stock Exchange in 1398 are used and model is solved with GAMS. Results indicate that multi portfolio optimization excel other approach and consequence notable improvement on the perspective of customer and advisor. Also, for the validation of the proposed model, the selected stocks are considered in pairs to solve the model and the results show the proper performance of the model with different stocks, thus indicating the validity of the model.