درخت حوزه‌های تخصصی

Behavioral financial knowledge deals with the behavior of investors and other users in the capital market. According to the financial knowledge, it is no longer expected that only factors such as accounting information and macroeconomic variables will affect decision-making but also a variety of behavioral variables including manager’s optimism, information influence management, patience of major shareholders and other investors' biases can have an impact on the prices and stock returns. The purpose of this study was to investigate the impact of managers' optimism on the relationship between the patience of major shareholder and information influence management. This study attempts to investigate the relationship between these behaviors and information influence management by measuring the degree of major shareholders patience and managers’ optimism. This is a descriptive post-event research. The study population consisted of the companies listed on Tehran Stock Exchange (n = 87) between the years 2008 and 2017. Multivariate regression was used to test the hypotheses. The findings showed no significant relationship between the major shareholders patience and the information influence management (high, low, balanced). Further, it was found that managers’ optimism has a significant effect on the relationship between the major shareholders' patience and the information influence management (balanced level) and no significant relationship was observed between two other levels.

The main goal of this paper is to propose a new approach for efficiency measurement and ranking of stocks. Data envelopment analysis (DEA) is one of the popular and applicable techniques that can be used to reach this goal. However, there are always concerns about negative data and uncertainty in financial markets. Since the classical DEA models cannot deal with negative and imprecise values, in this paper, possibilistic range directional measure (PRDM) model is proposed to measure the efficiencies of stocks in the presence of negative data and uncertainty with input/output parameters. Using the data from insurance industry, this model is also implemented for a real case study of Tehran stock exchange (TSE) in order to analyse the performance of the proposed method.