درخت حوزه‌های تخصصی

According to the study of Fang and his colleagues in 2021, in order to reduce the fall of the stock market, companies pay attention to trading strategies and behavioral financial perspective, which have evaluated the assumptions and goals set in this regard; But there may be a gap in this path that prevents the connection or effect between the above variables, which is discussed in this study. This study aims to determine the effect of quantitative trading strategies on the fall of the stock market according to the perspective of behavioral finance (case study: companies admitted to the Tehran Stock Exchange). In order to analyze the research hypotheses, the statistical population was selected from 2016 to 2021 and for 6 years and included listed companies; the statistical sample was selected by elimination method and 90 companies. The research method used is a descriptive-analytical method and historical research data was collected and classified by referring to the financial statements and financial reports of the companies admitted to the Tehran Stock Exchange. The panel data method was used to analyze the statistical data; And in the analysis section, descriptive statistics, inferential statistics and various relevant tests were performed and data analysis was done using Eviews version 9 software. According to the analysis of the regression model, the findings of the research show that the main hypothesis has been confirmed and it was found that quantitative trading strategies have a negative and significant effect on the fall of the stock market according to the behavioral financial perspective of the companies admitted to the Tehran Stock Exchange. So that in this research, based on the t-statistics, the effectiveness of both special hypotheses (fall-timing and movement-reverse) was determined, and according to the mediating variable of behavioral financial perspective, they can also play a positive and significant role in reducing the fall of the stock market to be.

The purpose of this research is to investigate the non-linear effect of size and capital structure of companies on profitability in the framework of threshold panel regression in companies listed on Tehran Stock Exchange. For this purpose, 105 companies from different industries were selected as a statistical sample between 2010 and 2021. Hypotheses testing were analyzed under two scenarios: linear multivariate regression and non-linear multivariate regression (threshold panel regression method). Profitability as a dependent variable, capital structure and company size as independent variables and equity, sales growth and company life as control variables were examined. The results of statistical analysis showed that there is no significant relationship between company size and profitability in a non-linear mode. In the case of a threshold panel, the size of the company is known as the threshold variable and the capital structure is known as the dependent variable of the regime. The threshold value was estimated at 15.89, since the model has a threshold limit, so two different regimes were obtained for the capital structure variable. In both regimes, the relationship between capital structure and non-linear profitability is negative and significant. In this way, in the first regime, the capital structure up to the threshold value of the company's size reduces the profitability, and in the second regime, when the capital structure value exceeds the threshold value, the capital structure has less effect on the profitability and increases the profitability. It reduces less than before. According to the obtained results, the companies that are in the second regime have a more favorable capital structure and profitability than the companies in the first regime.