quantile regression

The purpose of this research is to statistically investigate the effect of trading volume on daily returns obtained in exchange traded fund as one of the new achievements of the capital market and the results obtained with the relationship between volume - returns are compared in the capital market. In order to investigate the subject of the study, information on the financial statements of tradable investment funds was extracted by Eviews and Stata statistical software during the year 2022. The results show that the trading volume (in terms of value of rials transactions and quantity) in Exchange Traded Fund has not significant impact on returns earned by them. Also, the trading volume carried out on the units of these funds had a negative and meaningless effect on the daily returns obtained by them. Regarding the relationship between volume and return in the capital market, the findings show that trading volume had a positive and significant effect on the daily return of the market. Also, with the increasing volume of transactions, the amount of daily return has been increased and more prosperity and efficiency have been observed in the capital market. In addition the use of quantile regression compared to normal regression, gives a better view of the effect of the independent variable on the dependent variable because the normal regression presents the result of the effect of the independent variable on the dependent in the form of an average while Quantile regression shows this effect in different quantiles.

Improving financial performance will not be possible by maximizing profits and benefits alone. Based on social contract theory, society allows the company to operate and they expects the company to serve the interests of all stakeholders. One of the expected benefits of all stakeholders is social responsibility. The special value of a brand and trademark as a brand name also is one of the achievements of social responsibility that leads to improving the financial performance of the company. Therefore, the purpose of this paper is to investigate the effect of social responsibility on the financial performance of the company by considering the moderating role of the value of brand name and trademark. This study uses quantile regression and structural equation modeling to explore the causal linkages among these factors in firms listed on the Tehran Stock Exchange over the period 2011–2015. The results of quantile regression analysis show that the economic dimension of corporate social responsibility and the special value of a brand and trademark are a positive significant effect on all of the quantiles. The brand extension driver provides a significant positive effect on the higher quantiles of firm performance. However, the findings indicate a significant negative effect on firm performance considering the brand loyalty driver.

According to Prospect Theory, Investors have different behaviors in the profit and loss situations and indeed their trading behavior is different in bull and bear markets. This study uses quantile regression model (in different quartiles) and OLS model to estimate beta of 180 firms. Results showed that first, equity total risk (standard deviation) increase in Upper quartile and second, stocks beta changes in different quartiles and by moving from quartile 0.25 to quartile 0.75, systematic risk (beta) increases significantly. Linear regression model and Quantile regression model show also that unexpected variance can explain excess return at least similar to expected variance. The results can also be interpreted with both Insight of standard finance and insight of behavioral finance. In standard finance area, riskreturn positive relation that exists in upper quintiles is consistent with long run growth of economy. Moreover, negative relation between return and risk in lower quintiles imply more uncertainty and as a result causing stock returns to fall. In behavioral finance area, regime-dependent behavior of slope coefficients is consistent with prediction of Prospect theory of investor’s behaviors around the reference point.