stock trading volume

Since the first research on Earning Response Coefficient, one of the most important directions of studies conducted in financial accounting is explaining and identifying different factors affecting the Earning Response Coefficient for companies. Also it can be shown that the financial characteristics are not the same in different periods of a firm's life cycle and changes depending on period and the situation it is placed. In other words, the financial characteristics are influenced by the stage of the life cycle, therefore, the firm life cycle can be used as a key for stronger forecasting as well as making more logically decisions. Therefore, the purpose of this research is to investigate the effect of the firm's life cycle on the relationship between stock trading volume and the Earning Response Coefficient of listed companies in Tehran Stock Exchange.This research is a type of applied research in which the financial data of 151 companies during the period of 2013 to 2022, including 1510 observations, were examined. The results show that the effect of the trading volume on the Earning Response Coefficient is different in different stages of the life cycle, and it is more in the Stagnation Stage than in other stages. The results show that the life cycle is an influential factor in the relationship between the trading volume and the Earning Response Coefficient, so that the adjusted determination coefficient changes with the entry of each of the life cycle variables into the regression equation.

The aim of this study was to compare the valuation models accounting from the perspective of market trading and price-making in companies listed on the Tehran Stock Exchange. The study sample consisted of 104 active company stock during the period 1388-1394. In this study the effect of different pricing valuation models Ohlson (1995), Zhang (2000) and traditional models earnings per share were determined using Wong. The results showed no significant difference between the explanatory power of these models and the models created on the basis of earnings per share, higher than the explanatory power of residual income. The results showed that by increasing the ratio of price to earnings valuation models increased explanatory power, while increasing the volume of stock trading, the explanatory power of the Ohlson model and the traditional model increases. These findings indicate that the ratio of price to earnings and stock trading volume has been adequately reflect reflection of market liquidity. Understanding these factors can help to improve pricing and to determine the intrinsic value of company stock and will be effective.